Woedenis in the Industrial Robotics Industry

Woeden

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Scientific American, Volume XXXVI., No. 8, February 24, 1877 by Various, is part of the HackerNoon Books Series. You can jump to any chapter in this book . The Wetli Mountain Railroad and Its Disastrous Trial Trip here THE WETLI MOUNTAIN RAILROAD AND ITS DISASTROUS TRIAL TRIP. Among the various means proposed of late years for building lines of railroad on the steep slopes of mountains, that of M. Wetli, of Zurich, Switzerland, has attracted considerable attention from European engineers. We have already laid before our readers the system of central toothed rails used on the Righi and other mountain roads in Europe. In the Wetli system, instead of this rail and the pinion on the vehicle engaging it, there is a drum having a helicoidal thread which engages with triangular rails. This drum is attached to the locomotive. The construction will be readily understood from the illustrations given herewith, which we take from . The thread on the drum is precisely that which would be formed could a rail similar to one of the central angular rails be wrapped around it; so that it always is in contact with the mid rails, and necessarily prevents any bodily sliding or rolling of the vehicles over the regular track when the drum is held motionless. The V-shaped mid rails are securely fastened to horizontal iron ties, which rest on wooden traverses. The angle of the V is 50°; the distance between any two traverses is 2.8 feet. La Nature The locomotive has three coupled axles, on the mid one of which the drum is attached so as to be raised or lowered to engage the rails at the will of the engineer: it being possible to cause it to act on the rails with a pressure of 3.7 tons. The diameter of the drum is 2.14 feet. Its spiral thread is of steel, very solidly attached, and so made as to grip the rails to a distance of 0.6 inch below the level of the track. In order to insure this contact, on the drum axle are two pulleys which run on the exterior road, and of which the diameter determines the depth of the hold of the threads. These pulleys are 34.7 inches in diameter, while the driving wheels are very slightly in excess, to provide for the use of tyres. M. Wetli's invention, as we have described it, was placed between Woedensweil and Einsiedlen, Switzerland. The difference in altitude between these points is 1,513 feet, the distance 9.6 miles. The grade is from 4 to 5 per cent over the first six miles of the way, and subsequently decreases to 1 per cent. The Wetli railroad was established last October only on the heavy grade, that is, the first six miles. Early in November, trial trips were made which did not prove satisfactory. Sometimes the drum thread gripped the triangular rails properly and acted well; again it would wedge itself upon them, and often would simply roll over their tops without engaging at all. After the first trials, during which very many of the rails were broken, M. Welti re-adjusted the drum thread. Finally, he concluded that he had overcome all difficulties in his apparatus; and accordingly a formal trial was arranged on November 30. For about four and a half miles of the ascent the drum worked well; and the hoarfrost, with which the rails were thickly covered, showed good contact. Afterward it worked irregularly; but the station of Schindelleghi, a distance of five miles, was reached without accident, the locomotive dragging a car loaded with 20 tons of rails. It was then attempted to make the descent by the aid of the helicoidal drum; but this jumped the rails, and broke them almost immediately. By the aid of back pressure of steam and brakes, the locomotive was stopped. Then, unfortunately, the engine was started again; but hardly had the descent been resumed when it was evident that the drum was not holding, and that the speed was accelerating rapidly. Brakes and steam were both found useless, and the engine went tearing over the rails at the rate of a mile a minute. Of the fourteen persons in the vehicles, three were thrown out and killed, and the rest were more or less seriously injured. The heavily loaded car left the track, and tore up both central and side rails until its coupling broke. The engineer, with great intrepidity, clung to his engine, coolly giving signals to open switches so that the locomotive might run upon the level track and so expend its momentum; but the engine left the rails at a sharp curve, destroyed the track for about a hundred feet, and finally stopped a mass of ruins, with its brave engineer mortally wounded. Whether the Wetli system can be made to work as intended by the inventor is regarded as doubtful by the engineers who have examined into the causes of the disaster. About HackerNoon Book Series: We bring you the most important technical, scientific, and insightful public domain books. This book is part of the public domain. Various (2006). Scientific American, Volume XXXVI., No. 8, February 24, 1877. Urbana, Illinois: Project Gutenberg. Retrieved https://www.gutenberg.org/cache/epub/19406/pg19406-images.html This eBook is for the use of anyone anywhere at no cost and with almost no restrictions whatsoever. You may copy it, give it away or re-use it under the terms of the Project Gutenberg License included with this eBook or online at , located at www.gutenberg.org https://www.gutenberg.org/policy/license.html

THE WETLI MOUNTAIN RAILROAD AND ITS DISASTROUS TRIAL TRIP

Things To Make by Archibald Williams is part of the HackerNoon Books Series. You can jump to any chapter in this book . A WOODEN WORKBOX here XXXIII. A WOODEN WORKBOX. The box illustrated by Fig. 181 was copied from an article of Norwegian manufacture. Its construction is an extremely simple matter, provided that one can get a piece of easily bent wood (birch, for instance), not exceeding 3/16 inch in thickness, for the sides. [Illustration: FIG. 180.—Showing how to draw an ellipse.] [Illustration: FIG. 181.—Norwegian workbox.] The bottom of the box is made of 5/16 or 3/8 inch wood, cut to an oval or elliptical shape. To mark out an ellipse about 8 inches long and 5-1/2 inches wide—this will be a. convenient size—stick two pins into the board 5-1/8 inches apart, pass a loop of thread 14 inches in circumference round these, and run the point of a pencil round the pins in the path which it has to take when confined by the slack of the loop (Fig. 180). Fret-saw along the line. The wood strip for the side is 4-1/2 inches deep, and 1-1/2 inches longer than the circumference of the bottom. The ends are thinned off somewhat, as shown in Fig. 181, to prevent the lap having a clumsy appearance, and the surface is smoothed all over with sandpaper. Bore a number of small nail holes 3/16 inch from one edge, and then steam the wood over a big saucepan or other suitable vessel until it is quite lissom. When attaching the side piece to the bottom, begin at the middle, and work first towards what will be the inside end of the lap, and then towards the outside end. Nails are driven in through the holes already drilled. When nailing is finished, clip the top of the overlap with a hand-vice or screw spanner, to prevent the tops of the ends sliding over one another, and bore a line of holes l/4 inch apart, and at the same distance from the outer end. Fine copper wire drawn to and fro through alternate holes from one end of the row to the other and back again, will secure the joint. The lid overlaps the side 1/4 inch in all directions and has a square notch cut in it at one end to pass under the piece A, and at the other a deeper, circular-ended nick to enable it to pass over the key B when that is turned into the position shown in the illustration. A is cut out of 1/4-inch wood; B, in one piece, out of 1/2-inch. Their length under the heads exceeds the inside depth of the box by the thickness of the lid. A is affixed rigidly to the side by small screws or wire, while B must be attached in a manner, which will allow the head to rotate. Cut two nicks round the shank, and two horizontal slots at the same height through the end of the box. A couple of brass rings must then be procured of such a size that, when flattened into a somewhat oval shape, they will project beyond the slots sufficiently to allow a piece of wire to pass through them and prevent their being drawn back again. Quarter-inch wood will do for the lid. A handle is made out of a couple of inches of small cane bent into a semicircle, let through the lid at each end, glued, and cut off flush. The exterior may be decorated by a design in poker-work, or be stained and varnished. This is left to the maker’s discretion. About HackerNoon Book Series: We bring you the most important technical, scientific, and insightful public domain books. This book is part of the public domain. Archibald Williams (2005). Things To Make. Urbana, Illinois: Project Gutenberg. Retrieved https://www.gutenberg.org/cache/epub/14664/pg14664-images.html This eBook is for the use of anyone anywhere at no cost and with almost no restrictions whatsoever. You may copy it, give it away or re-use it under the terms of the Project Gutenberg License included with this eBook or online at , located at . www.gutenberg.org https://www.gutenberg.org/policy/license.html

A WOODEN WORKBOX

In this interview, I speak to author and engineer on the potential implication Artificial Intelligence could possibly have on Fiction Writing. We speak about his new , AI-written books, and how can potentially alter the creative process of every writer. Michael Woudenberg book AI Edem: Hey Michael, it’s incredible to have you! Could you share more about yourself, your professional qualifications, and such Hi, it’s wonderful to be part of the Tech Writer’s Stack, and I’ve loved the incredible network and collaboration that Substack is allowing us to build, which I found largely absent from other blog spaces.  My background is a menagerie of experiences across multiple domains and disciplines.  I call myself an aspiring ; a jack of all trades and master of none, but more often better than a master of one. Michael: Polymath is in systems engineering, but it’s more like systems thinking.  I like to say that is more than just engineering and consists of three things: My core background Systems Thinking First, insatiable curiosity. Second, the humility to accept we just don’t know that much. Third is intentional reframing of a problem or idea to see if we really do understand it. I’ve got a Master's Degree in Systems Engineering from Johns Hopkins and a diverse background in advanced technologies such as autonomy, artificial intelligence, blockchain, cyber, aerospace, national security, and weapon systems across a variety of companies from tech startups to Fortune 150 companies. I also recently founded , which provides Systems Innovation to unlock the full potential across multiple domains and disciplines.  As mentioned earlier, I am also the author on Substack of , which provides counterintuitive insights from technology, innovation, philosophy, psychology, and more. Polymathic Disciplines Polymathic Being Edem: You recently announced your new book titled Paradox, Could tell us about it? that explores AI and dives into what it means to be human.  The tagline is: In the battle over Advanced AI, will we lose our humanity or learn what truly makes us human? Michael: Paradox is a science fiction novel It really explores the paradox of being human and what it would take to actually achieve a sentient artificial intelligence, along with all the challenges and potential consequences. My goal is that I want people to wonder which side they’d take in the end because I’m still not sure myself. Here’s a fun video trailer that gives a nice summary. https://youtu.be/k4_Ej2B2ZV4?si=jPnTuTjpVaW490-Q&embedable=true Edem: For the sake of Completion, could you define what fiction means? Fiction is the art of narrative that is not purely grounded in fact. , though, is where science fiction meets science fact. The book idea started about five years ago when I was trying to figure out how to take the psychology, sociology, and theology of being human and make it more interesting to read. Michael: Paradox AI makes a great plot device to work with because the goal, or the worry, is if we achieve artificial general intelligence (AGI), humanity as we know it is in trouble. AGI simply means that AI is as good or better than humans.  But to do that, you need to learn a lot about what it means to be human, and we are a lot more complex than we fully understand.  AI can only handle the logical right now, and humans are built on top of an emotional brain, which is also connected to a hormonal or gut brain.  Let’s just say there’s a lot to explore there. Edem: I’m sure you get asked this a lot, but did you make use of AI to write it? I did use AI to help write it.  But then again, any author who is using a computer with a word processor and a search engine is using AI to write.  What is slightly different is that ChatGPT 4.0 helped me to kick it off.  I had already crafted the entire outline, the ideas, and everything.  I just asked GPT to put together a narrative on a few topics. Michael: But the truth is that AI is a terrible author! It takes so much time and effort to craft the prompts right for any results.  Anything it created, I ripped apart and rewrote completely.  But, it helped me get off the blank page problem that so many authors are blocked by. It was a terrible writer, but it got started. me I used AI with Grammarly and WordTune, as well as Bing with GPT, to help me do editing and research. It was useful for coming up with names for characters and organizations.  For example, Hyperion Defense, one of the key organizations defending humanity, was recommended by ChatGPT due to the connection to the Greek myth of the Titan Hyperion, known for his watchfulness and protection. Edem: Let’s talk about the potential of AI in fiction. How do you envision AI could change the fiction writing landscape? Right now, AI is a terrible author.  It’s okay with simple descriptions, research, character definition, etc. It really can’t do longer form narrative well. It’s something that is explored in , which is titled Almost Intelligent.  What the characters find is that AI is good at mimicry; it just isn’t very good at creativity. Michael: Paradox in Chapter 3 A more painful conversation is that those who are worried about AI replacing them probably have a point.  The key to not being replaceable is to have a skillset or, more specifically, an understanding of what makes humans unique that can’t be algorithmized away.\ I do worry that a lot of weak writers will to crank out bad content.  We saw this recently with a book someone published literally two days after the Maui fire about how the fire was indicative of climate change.  When you got into the text, it was not just bad; it was horrible. I’m not even sure the fellow took the time to read it before he pushed it to Amazon. start using the LLMs Edem: If you were to rewrite your book, how would you use Text models to facilitate your creative process? Well, I wouldn’t rewrite this book, but I am about to kick off book two.  It’s titled Integration and explores the AI arc after the calamity of . It’s going to be exploring a lot of concepts more broadly, like race, gender, and nationality, among others, but back to your question, I don’t think I’m going to change much. Michael: Paradox I’ll use AIs like ChatGPT, WordTune, and Bing to help me with my research, scene descriptions, and similar, but these tools are just not at a place where they can write to the level I need them to. Edem: Is it possible for Large Language Models to ever be capable of creating Literary masterpieces like Harry Potter and Irobot? LLMs will be able to mimic those masterpieces.  But it will clearly be a mimic. I can’t see them being able to create something new and unique. Not without pretty heavy human involvement. Michael: Another thing to consider is that, right now, AI can’t learn. It can be trained, but once the training is done, it’s static again. Humans never stop learning though and social learning is one of our superpowers where we build off of one another. Humans learn and create through social connections. Moreso, what I found in the book that limited AI was that it was purely logical and could only fake emotion. Humans are smart because we are emotional, not so much that we are logical. That’s the piece that had to fall into place in to actually achieve AGI, but that’s just not something we are anywhere close to. So, no, AI is nowhere near capable of creating masterpieces. At least not to the trained eye Paradox Edem: Let’s take a look at ethics. If hypothetically, a book is co-authored with the aid of AI, who should take credit for the work and why? I’ll ask the question back a different way. If I went to a library and a librarian helped me do research, edited some of my ideas, etc., how much credit should they get?  The thing with AI like ChatGPT is that they are only responding with mathematically structured algorithms returning statistically predictive textual completion. Michael: They aren’t creating per se.  They certainly aren’t being creative. I will acknowledge AI was a useful tool, among many others, but there’s a ton of human input to the book, which just goes back to the idea from earlier on how we are social learners. I can honestly say there is nothing in my book that isn’t first mine and then aided by people and tools. Edem: What are your thoughts on a future where AI systems can efficiently imitate the literary technique of popular authors and potentially extend their literary legacy? I mean, we are doing that in some ways already.  They did that with Carrie Fisher in the 9th . But I think even if they could imitate, would we, as humans, appreciate it as much? Michael: Star Wars film I think of J.R.R. Tolkien. He has hundreds of manuscripts and world-building concepts he never wrote into books.  That’s why the Silmarillion is so clunky. It was never formed and polished.  Could AI help us with a better version of that? But do we want a better version of that? Or is his true legacy that he nearly wholesale invented the fantasy literary world as we know it?  Thousands of new authors are imitating the worlds he created, using his concepts of elves, dwarves, knights, and wizards to this day.  His legacy is seen in all the authors who were moved to build on it.  AI can only copy; it could never do what those human authors did with Tolkien’s legacy. Edem: Collaboration with AI seems inevitable. How best can writers incorporate AI into their creative process without outsourcing their potential creativity? I’d say that if you outsource your creativity, you’re not really creative. But AI can be incredibly helpful, as I mentioned earlier. You can even use it to provide counter-arguments or recommend new phrasing.  In drafting my second book, I’ve been asking ChatGPT to recommend changes to dialog to make my antagonist more antagonizing in a sneering, condescending way.  That helps get my brain juices flowing and I then craft it in my own way. Michael: But this isn’t any different in some ways from bringing up a personal experience and trying to express it.  AI just helps the process flow a bit faster. It still requires me to feed very specific prompts to get focused answers that are usable.  Without my creative input, its output is rubbish. It’s good as an admin, an editor, and an idea generator in the writing process. In publishing AI, behind distributors like Amazon’s Kindle Direct Publishing, it actually gives me the ability to write, design, publish, and fulfill orders in ways that didn’t exist 15 years ago. Edem: Looking \Michael: forward to the distant future. What parts of the entire writing process (writing, publishing, editing, marketing, and publishing) do you think AI tools could be most useful? AI in marketing through places like Meta’s ad space makes writing ads and finding eyes and clicks so easy it’s incredible. AI has literally democratized publishing to where anybody can do it without the archaic and nepotistic publishers and without paying many thousands of dollars.  All in, thus far, I’ve probably invested $2,000 to write and publish my book, including some marketing and more.  Twenty years ago, that wouldn’t have been possible. Edem: What advice would you give to a budding writer looking to write and publish their work in the current state of AI? Don’t let AI replace your writing. You have to be creative, unique, and thought-provoking.  If you’re writing isn’t any better than an AI, I’d look hard at improving your craft and finding out where you can be unique. AI also offers writers a unique opportunity to step out and above the average by understanding and leveraging the unique capabilities that humans can leverage over machine AI. Michael: AI is an enabler, not a replacement, for good writing. Those who use it to do the work for them will never compete with those who use it to make their work better. Edem: Well, that’s a wrap, Michael! Do you have any closing words? A lot of people are worried about AI.  My biggest worry isn’t AI but how we react to AI. That’s the thread I pulled in Paradox that unleashed the most destruction.  I didn’t need to have AI kill people; I just had the AI in the story unlock the fears and ignorance so that it triggered a human societal auto-immune response, and the humans did all the dirty work. Michael: But that’s not how it has to be, and that’s the true underlying lesson in the book.  Because it really does come down to that tagline: In the battle over Advanced AI, will we lose our humanity or learn what truly makes us human? If you are interested in more of these topics, please subscribe at PolymathicBeing.com You can find the book on . You can also watch a short video (2-½ minutes) on AI as a co-author below on YouTube, which you can share with others. Amazon

How AI Is Impacting Fiction Writing: An Interview with Michael Woudenberg 

After completing one project, we’re often in a hurry to start a new one. But why the rush? If you complete a quality project, recycle it: iterate on it and create your own mini-projects along the way. I do this myself. The process is helping to build my skills and solidify concepts—and it can help you, too. So in this article, I’ll share my process for creating programming projects. Let’s start with an approach I’ve adopted from the famous basketball coach, John Wooden. It’s called the “whole-part method.”[1] 1. The Whole-Part Method Coach Wooden used his “whole-part method” when teaching his team a particular basketball play. First, he’d show the team the entire play from start to finish. Then, he’d break the play down and the team would work on each part.[1] It’s a simple—but extraordinarily successful—learning strategy that you can apply to programming. It’ll help you nail the core competencies of a concept or technology. It'll also help you to see how these individual parts fit into a broader context. Start with a project that you’ve already completed, much like Coach Wooden showed his team a new basketball play from start to finish. Say you just completed a React project, where a user enters todos. The todos are displayed on your screen. Let’s use this as an example of a base project. Here’s how it works. Focus on Each Part Next, break the project down into smaller projects, just as Coach Wooden’s team would break down and drill each part of a new play. These are several mini-projects you could create from this React “todo” project: Implement the project using functions. Implement the project using classes. Add CSS to one version of the project. Add functionality to remove a todo. Notice that each mini-project centers around a core concept of React, like using classes and functions. This is one way to identify mini-projects: . Alternatively, you can create a project around something specific that you want to get better at. identify core concepts and design a small project around them Drill It and Internalize It Note that you’re not re-completing the entire project each time. Instead, you’re . The aim of this practice is to . focusing on one thing take something that has multiple parts, and break it down and drill each part Recall that one mini-project focuses on classes: write some classes in order to get a few user-entered “todos” to show up. Don’t add CSS. Don’t add the functionality to remove a todo. It’s pretty bare-bones, but that’s the point: you’re concentrating solely on writing classes. Likewise, when you work on the CSS mini-project focus exclusively on CSS. Take one version of the project that you’ve already completed and add CSS to it. Isolating specific aspects of a project and drilling them is a great way to really understand and internalize core concepts and build skills. It’ll also point out areas of weakness. If you struggle with classes, then you’ve identified an area to work on. Once you’ve completed a mini-project—and this is the critical point—take time to reflect: What did you do well? Did you try something different? What’s something that could’ve gone better? Are there any stumbling blocks? The idea is to look at your work objectively and analyze it: give yourself . If you struggled with a project, then let a few days pass and repeat it. This is also a great opportunity to refer back to your base project and compare. feedback Put it Back Together Once you’ve completed your mini-projects, put everything back together again and do the entire project from scratch. You’ll probably be amazed by how smooth the process is by this point. You’ll also have a much clearer understanding of how the individual parts (the mini-projects) fit together as a whole. 2. Extend It Another suggestion for creating projects is to extend an existing one. Whereas the “whole-part” method breaks down and drills concepts that you’re already familiar with, this one has you add something . The idea is to extend your knowledge. new Say you just completed a backend project. Now extend it by adding middleware, if you've not used middleware before. Then extend it once more by creating a new React app and connecting it to the server. You can extend a project in any number of ways, these are just some examples. Each time, you’re going beyond the original project requirements by adding something new to it. In doing so, you’re pushing yourself outside of your comfort zone just a bit, which is the intent. That’s how you’ll get better. Once you start using these approaches, you’ll find yourself creating your own projects from scratch. You’ll take “x” from this mini-project and “y” from another and create a new project. The process will also get you thinking creatively of entirely new projects you can put together, and it’s a lot of fun! When you find a good project, get the most from it. Hopefully, this article gave you some ideas of how to do that. Reference: Nater, Swen. You Haven't Taught Until They Have Learned: John Wooden's Teaching Principles and Practices. Morgantown, Fitness Information Technology, 2006. Programmer and writer: amymhaddad.com | programmerspyramid.com | I tweet about programming, learning, and productivity @amymhaddad Originally published on amymhaddad.com .

Applying John Wooden's "Whole-Part Method" Approach To Programming

Imagine an industry that has seen little innovation since the Civil War. It may seem unbelievable, but the United States railroad infrastructure is still the same as it was back in the original era. Taking on the industry to improve and plan for the future is Evertrak -- ready for a railroad infrastructure revolution. The company's mission is bold: replace traditional wooden railroad ties with cutting-edge, sustainable alternatives made from recycled plastics. Evertrak is addressing environmental concerns and industry challenges head-on. \Tim Noonan, CEO of Evertrak, doesn’t mince words: “It’s 2024!” he emphasizes. “We can do better. We must do better.” His vision of “the railroads of our Nation rolling on ties made from recycled plastics” isn’t just about sustainability—it’s about transforming an industry stuck in the past and solving real problems. Evertrak's journey began with a revolutionary idea: What if the plastic waste choking our planet could become the foundation of our transportation infrastructure? The team realized the industry needed more than just a new product—it needed a paradigm shift. “Our insight was that the industry needed a tie that was as strong as wood, not as cheap as wood,” Noonan explains. “We’re not offering a band-aid. We’re providing a solution for a real problem in the industry.” Addressing Industry Challenges Safety and efficiency are paramount in the railroad industry. With the adoption of Precision Schedule Railroading (PSR), which focuses on moving individual cars rather than waiting for long trains to be built, uptime has become more critical than ever. Evertrak’s ties directly address this need and offer a redefinition of what’s possible in railroad operations. “Using our tie, railroads won't have to replace ties in high decay zones every 8-12 years,” says Noonan. “This means better uptime for PSR and lower total cost of ownership.” Sustainability Impact Experts suggest only 9% of plastic waste is effectively recycled globally. And industry estimates for North America alone suggest 20 million wooden railroad ties are replaced annually—equivalent to approximately 6 million trees. As Noonan mentioned, with an average lifespan of around a decade (reduced to just 5 years in high-rot regions), the environmental impact of current railroad practices is significant and the environmental benefits of Evertrak's ties are clear. By using recycled plastics, Evertrak not only diverts hundreds of thousands of pounds of waste from landfills but also prevents deforestation and avoids the CO2 produced when traditional ties are incinerated or landfilled at the end of their life. “This is just the beginning,” Noonan promises, explaining that the industry replaces more millions of wood ties a year. For Noonan and Evertrak, it’s about securing a livable planet for future generations. “Imagine that many trees saved. Imagine millions of pounds of plastic put to better use and removed from our landfills and oceans. Every tie we produce is a blow against deforestation and plastic pollution.” Union Pacific’s commitment to alternative railroad ties strikes Noonan as a resounding endorsement of this important industry shift, and the CEO sees it as a rallying cry: “UP is the de facto leader of the railroad industry. Their measured implementation of our ties builds trust and confidence for others. I think the message is: It’s time to get on board.” Industry Veterans Signal Transformation One of the most promising signs of Evertrak’s potential to revolutionize the railroad industry is the company’s ability to attract respected executives who have historically been on the wood tie side of the business. “Yes, it really signals disruption in the industry,” Noonan explains. “These executives understand that the Class 1 railroads do not have alternatives when it comes to ties. They understand the business practices and products that keep things going between big creosote and the railroads.” This insider knowledge is proving invaluable as Evertrak seeks to transform the industry. With the never-ending rise of single-use plastic and the detrimental impact of deforestation, Noonan believes there's room for improvement. “We can do better,” he asserts. “I've been speaking with a number of industry veterans who believe that the time is right for transformation.” The involvement of these industry veterans not only lends credibility to Evertrak’s mission but also suggests that the railroad industry as a whole might be gearing up for a significant shift towards more sustainable practices. Future of Sustainable Infrastructure in Railroads Evertrak’s highest priority is continuing to build trust with Class 1 customers, bringing awareness to one of America’s oldest industries—some of the first tracks were laid nearly 200 years ago—so they have the resources and support to join the modern era. The company’s goals are ambitious: save millions of trees, drastically reduce plastic buildup, and do it all now. Evertrak’s approach is collaborative, empowering the customer to dictate success through communication and keeping commitments. “We have 7 years of proven results,” Noonan says. “And that includes never missing a delivery timeline. To date, we’ve installed over 100,000 composite ties with zero claims.” For other companies looking to innovate with sustainable materials, Noonan offers this advice: “Identify a pain point and make that pain go away for the customer. Your customer doesn’t care that the product is made from sustainable material; they want their problem to go away. Deliver the business case, and the case for sustainability comes along to close the deal.” As the railroad industry grapples with the need for more sustainable practices, companies like Evertrak are proving that environmental responsibility and business efficiency can go hand in hand. By addressing real industry pain points with innovative, sustainable solutions, Evertrak is helping to lay the tracks for a sustainable future in transportation infrastructure. The implications of this shift are far-reaching, potentially influencing other sectors of the transportation industry. As Noonan puts it, "If a pain point in the business can be solved through a sustainable solution, I believe the industry can have the business case and the benefit of sustainability without a tradeoff." With industry leaders like Union Pacific embracing these innovations, it's clear that the future of railroad infrastructure isn’t about maintaining the status quo—it’s about revolutionizing it for a more sustainable, efficient tomorrow. In Noonan’s words, “It’s time for the railroad industry to declare its independence from wood ties and creosote. Join us in this revolution! We’re not just making ties—we’re making history.” Imagine an industry that has seen little innovation since the Civil War. It may seem unbelievable, but the United States railroad infrastructure is still the same as it was back in the original era. Taking on the industry to improve and plan for the future is Evertrak -- ready for a railroad infrastructure revolution. The company's mission is bold: replace traditional wooden railroad ties with cutting-edge, sustainable alternatives made from recycled plastics. Evertrak is addressing environmental concerns and industry challenges head-on. Evertrak Evertrak \Tim Noonan, CEO of Evertrak, doesn’t mince words: “It’s 2024!” he emphasizes. “We can do better. We must do better.” His vision of “the railroads of our Nation rolling on ties made from recycled plastics” isn’t just about sustainability—it’s about transforming an industry stuck in the past and solving real problems. “It’s 2024!” he emphasizes. “We can do better. We must do better.” His vision of “the railroads of our Nation rolling on ties made from recycled plastics” isn’t just about sustainability—it’s about transforming an industry stuck in the past and solving real problems. must sustainability—it’s about transforming an industry stuck in the past and solving real problems. Evertrak's journey began with a revolutionary idea: What if the plastic waste choking our planet could become the foundation of our transportation infrastructure? The team realized the industry needed more than just a new product—it needed a paradigm shift. “Our insight was that the industry needed a tie that was as strong as wood, not as cheap as wood,” Noonan explains. “We’re not offering a band-aid. We’re providing a solution for a real problem in the industry.” Addressing Industry Challenges Addressing Industry Challenges Safety and efficiency are paramount in the railroad industry. With the adoption of Precision Schedule Railroading (PSR), which focuses on moving individual cars rather than waiting for long trains to be built, uptime has become more critical than ever. Evertrak’s ties directly address this need and offer a redefinition of what’s possible in railroad operations. “Using our tie, railroads won't have to replace ties in high decay zones every 8-12 years,” says Noonan. “This means better uptime for PSR and lower total cost of ownership.” Sustainability Impact Sustainability Impact Experts suggest only 9% of plastic waste is effectively recycled globally. And industry estimates for North America alone suggest 20 million wooden railroad ties are replaced annually—equivalent to approximately 6 million trees. As Noonan mentioned, with an average lifespan of around a decade (reduced to just 5 years in high-rot regions), the environmental impact of current railroad practices is significant and the environmental benefits of Evertrak's ties are clear. only 9% only 9% By using recycled plastics, Evertrak not only diverts hundreds of thousands of pounds of waste from landfills but also prevents deforestation and avoids the CO2 produced when traditional ties are incinerated or landfilled at the end of their life. “This is just the beginning,” Noonan promises, explaining that the industry replaces more millions of wood ties a year. For Noonan and Evertrak, it’s about securing a livable planet for future generations. “Imagine that many trees saved. Imagine millions of pounds of plastic put to better use and removed from our landfills and oceans. Every tie we produce is a blow against deforestation and plastic pollution.” that millions Union Pacific’s commitment to alternative railroad ties strikes Noonan as a resounding endorsement of this important industry shift, and the CEO sees it as a rallying cry: “UP is the de facto leader of the railroad industry. Their measured implementation of our ties builds trust and confidence for others. I think the message is: It’s time to get on board.” Industry Veterans Signal Transformation One of the most promising signs of Evertrak’s potential to revolutionize the railroad industry is the company’s ability to attract respected executives who have historically been on the wood tie side of the business. “Yes, it really signals disruption in the industry,” Noonan explains. “These executives understand that the Class 1 railroads do not have alternatives when it comes to ties. They understand the business practices and products that keep things going between big creosote and the railroads.” “Yes, it really signals disruption in the industry,” Noonan explains. “These executives understand that the Class 1 railroads do not have alternatives when it comes to ties. They understand the business practices and products that keep things going between big creosote and the railroads.” This insider knowledge is proving invaluable as Evertrak seeks to transform the industry. With the never-ending rise of single-use plastic and the detrimental impact of deforestation, Noonan believes there's room for improvement. “We can do better,” he asserts. “I've been speaking with a number of industry veterans who believe that the time is right for transformation.” The involvement of these industry veterans not only lends credibility to Evertrak’s mission but also suggests that the railroad industry as a whole might be gearing up for a significant shift towards more sustainable practices. Future of Sustainable Infrastructure in Railroads Evertrak’s highest priority is continuing to build trust with Class 1 customers, bringing awareness to one of America’s oldest industries—some of the first tracks were laid nearly 200 years ago—so they have the resources and support to join the modern era. The company’s goals are ambitious: save millions of trees, drastically reduce plastic buildup, and do it all now. Evertrak’s approach is collaborative, empowering the customer to dictate success through communication and keeping commitments. “We have 7 years of proven results,” Noonan says. “And that includes never missing a delivery timeline. To date, we’ve installed over 100,000 composite ties with zero claims.” zero For other companies looking to innovate with sustainable materials, Noonan offers this advice: “Identify a pain point and make that pain go away for the customer. Your customer doesn’t care that the product is made from sustainable material; they want their problem to go away. Deliver the business case, and the case for sustainability comes along to close the deal.” As the railroad industry grapples with the need for more sustainable practices, companies like Evertrak are proving that environmental responsibility and business efficiency can go hand in hand. By addressing real industry pain points with innovative, sustainable solutions, Evertrak is helping to lay the tracks for a sustainable future in transportation infrastructure. The implications of this shift are far-reaching, potentially influencing other sectors of the transportation industry. As Noonan puts it, "If a pain point in the business can be solved through a sustainable solution, I believe the industry can have the business case and the benefit of sustainability without a tradeoff." With industry leaders like Union Pacific embracing these innovations, it's clear that the future of railroad infrastructure isn’t about maintaining the status quo—it’s about revolutionizing it for a more sustainable, efficient tomorrow. In Noonan’s words, “It’s time for the railroad industry to declare its independence from wood ties and creosote. Join us in this revolution! We’re not just making ties—we’re making history.”

Railroad Infrastructure: How Evertrak is Leading the Way with Sustainable Materials

When I first transitioned to remote work, I underestimated the importance of having a dedicated workspace, relying solely on my laptop and couch. However, this approach soon led to back and neck pain and a disrupted work-life balance, making me realize the need to create a tailored working environment in my apartment. Here’s what I’ve learned from organizing my home office, where I’ve been working for almost four years now. A home office should be both functional and visually pleasing. Otherwise, you risk experiencing a decline in productivity and your overall sense of well-being. Arrange your work from the home area in a minimalist style, including only the furniture and decor items necessary for physical and mental comfort and functional tasks. Excessive and unfitting stuff can mess up your workspace and make you feel overwhelmed and tense. Another big deal is keeping your home office private. Choose a location that minimizes distractions. A separate room with a door is ideal, but if your apartment planning doesn’t allow this, find a quiet corner or use room dividers. Below, I’ll share five practical tips for organizing an effective workspace and setting an advantageous atmosphere for your remote job. Prioritize Furnishing Essentials Your top priority is maintaining your body’s comfort during long workdays. Invest in an ergonomic chair with good lumbar support, adjustable height, and armrests, and a writing desk spacious enough to accommodate your computer and other work essentials you may need. I prefer shopping for furniture offline to ensure the items meet my needs. For example, I test the chair for proper spine support and confirm that the desk is tall enough to avoid knocking my knees on its edge. Placing a footrest under your desk will help promote a proper posture while sitting and help you keep a neutral position throughout the workday. For added comfort, you can put a cushion on your chair. If made from soft fabrics, it will promote relaxation and help you return to your body sensations. Create a Favorable Background Place a freestanding or wall-mounted shelving unit behind your work desk. Ideally, choose one that is vertical and matches the width of your desk to avoid taking up too much floor space. Fill the shelves with books and decorative items to create a stylish, professional background infused with your personal touch. This setup creates a visually appealing backdrop for virtual meetings and ensures that you’ll always be ready for calls, including unplanned ones, in your neat, small office, even when the rest of your apartment is messy during a busy week. Add a Nature Touch As with your living space, your workspace shouldn't be packed with artificial-only items, making it a nature-depravated zone and negatively affecting your mental state. It will also drastically drop the air quality in your room, causing stuffiness and decreasing concentration. The lifeful decor elements such as plants, wooden furniture, aquariums, imitation waterfalls, and more can fulfill your need for affinity to the natural world in your working environment, boosting your enthusiasm and productivity. Be Mindful of Colors Choosing a color scheme that resonates with your personal preferences is no less important than getting comfortable furniture. Gloomy color solutions or flashy-bright design patterns act as ultimate stressors for your mind, overloading your eyes and brain and draining your productivity without you even realizing it. Overall, a natural base of whites, grays, or beiges will bring a tranquil sounding to your work surroundings. Pastel colors promote serenity and comfort, and warm neutrals are uplifting. You can also incorporate accent colors, like blues and greens for focus and concentration, and yellows or oranges for energy and creativity. Ensure Adequate Lighting Position your desk near a window to take advantage of natural light, which is essential for maintaining the body’s healthy internal clock. Exposure to sunlight helps regulate sleep patterns and prevent chronic fatigue. In contrast, working in poorly lit environments can increase stress and anxiety, cause energy dips, and reduce productivity and motivation. If you work late in the evenings, invest in a desk lamp with adjustable brightness and ensure the room is well-lit with overhead lighting to avoid eye strain. Last but not least, you should regularly clean and declutter your home office compartment and keep your work essentials in order. A tidy environment enhances focus and productivity, while a not-properly-organized space can be disorienting and provoke procrastination. When I first transitioned to remote work, I underestimated the importance of having a dedicated workspace, relying solely on my laptop and couch. However, this approach soon led to back and neck pain and a disrupted work-life balance, making me realize the need to create a tailored working environment in my apartment. Here’s what I’ve learned from organizing my home office, where I’ve been working for almost four years now. When I first transitioned to remote work, I underestimated the importance of having a dedicated workspace, relying solely on my laptop and couch. However, this approach soon led to back and neck pain and a disrupted work-life balance, making me realize the need to create a tailored working environment in my apartment. Here’s what I’ve learned from organizing my home office, where I’ve been working for almost four years now. A home office should be both functional and visually pleasing. Otherwise, you risk experiencing a decline in productivity and your overall sense of well-being. Arrange your work from the home area in a minimalist style, including only the furniture and decor items necessary for physical and mental comfort and functional tasks. Excessive and unfitting stuff can mess up your workspace and make you feel overwhelmed and tense. Another big deal is keeping your home office private. Choose a location that minimizes distractions. A separate room with a door is ideal, but if your apartment planning doesn’t allow this, find a quiet corner or use room dividers. Below, I’ll share five practical tips for organizing an effective workspace and setting an advantageous atmosphere for your remote job. Prioritize Furnishing Essentials Your top priority is maintaining your body’s comfort during long workdays. Invest in an ergonomic chair with good lumbar support, adjustable height, and armrests, and a writing desk spacious enough to accommodate your computer and other work essentials you may need. I prefer shopping for furniture offline to ensure the items meet my needs. For example, I test the chair for proper spine support and confirm that the desk is tall enough to avoid knocking my knees on its edge. Placing a footrest under your desk will help promote a proper posture while sitting and help you keep a neutral position throughout the workday. For added comfort, you can put a cushion on your chair. If made from soft fabrics, it will promote relaxation and help you return to your body sensations. Create a Favorable Background Place a freestanding or wall-mounted shelving unit behind your work desk. Ideally, choose one that is vertical and matches the width of your desk to avoid taking up too much floor space. Fill the shelves with books and decorative items to create a stylish, professional background infused with your personal touch. This setup creates a visually appealing backdrop for virtual meetings and ensures that you’ll always be ready for calls, including unplanned ones, in your neat, small office, even when the rest of your apartment is messy during a busy week. Add a Nature Touch As with your living space, your workspace shouldn't be packed with artificial-only items, making it a nature-depravated zone and negatively affecting your mental state. It will also drastically drop the air quality in your room, causing stuffiness and decreasing concentration. The lifeful decor elements such as plants, wooden furniture, aquariums, imitation waterfalls, and more can fulfill your need for affinity to the natural world in your working environment, boosting your enthusiasm and productivity. Be Mindful of Colors Choosing a color scheme that resonates with your personal preferences is no less important than getting comfortable furniture. Gloomy color solutions or flashy-bright design patterns act as ultimate stressors for your mind, overloading your eyes and brain and draining your productivity without you even realizing it. Overall, a natural base of whites, grays, or beiges will bring a tranquil sounding to your work surroundings. Pastel colors promote serenity and comfort, and warm neutrals are uplifting. You can also incorporate accent colors, like blues and greens for focus and concentration, and yellows or oranges for energy and creativity. Ensure Adequate Lighting Position your desk near a window to take advantage of natural light, which is essential for maintaining the body’s healthy internal clock. Exposure to sunlight helps regulate sleep patterns and prevent chronic fatigue. In contrast, working in poorly lit environments can increase stress and anxiety, cause energy dips, and reduce productivity and motivation. If you work late in the evenings, invest in a desk lamp with adjustable brightness and ensure the room is well-lit with overhead lighting to avoid eye strain. Last but not least, you should regularly clean and declutter your home office compartment and keep your work essentials in order. A tidy environment enhances focus and productivity, while a not-properly-organized space can be disorienting and provoke procrastination.

5 Home Office Setup Ideas for Productivity and Work-Life Balance

Everything You Need to Know About Trump v. United States

Many organizations that we’ve spoken to are in the exploration phase of using for AI-powered personalization, recommendations, semantic search and anomaly detection. The recent and astronomical improvements in accuracy and accessibility of large language models (LLMs) including BERT and OpenAI have made companies rethink how to build relevant search and analytics experiences. vector search In this blog, we capture engineering stories from 5 early adopters of vector search- Pinterest, Spotify, eBay, Airbnb and Doordash- who have integrated AI into their applications. We hope these stories will be helpful to engineering teams who are thinking through the full lifecycle of vector search all the way from generating embeddings to production deployments. What is vector search? Vector search is a method for efficiently finding and retrieving similar items from a large dataset based on representations of the data in a high-dimensional space. In this context, items can be anything, such as documents, images, or sounds, and are represented as vector embeddings. The similarity between items is computed using distance metrics, such as or , which quantify the closeness of two vector embeddings. cosine similarity Euclidean distance The vector search process usually involves: : Where relevant features are extracted from the raw data to create vector representations using models such as , or Generating embeddings word2vec BERT Universal Sentence Encoder : The vector embeddings are organized into a data structure that enables efficient search using algorithms such as or Indexing FAISS HNSW : Where the most similar items to a given query vector are retrieved based on a chosen distance metric like cosine similarity or Euclidean distance Vector search To better visualize vector search, we can imagine a 3D space where each axis corresponds to a feature. The time and the position of a point in the space is determined by the values of these features. In this space, similar items are located closer together and dissimilar items are farther apart. GITHUB JULIE-MILLS ^
  |          x Item 1
  |         /
  |        /
  |       /x Item 2
  |      /
  |     /
  |    /x Item 3
  |   /
  |  /
  | /
  +-------------------> Given a query, we can then find the most similar items in the dataset. The query is represented as a vector embedding in the same space as the item embeddings, and the distance between the query embedding and each item embedding is computed. The item embeddings with the shortest distance to the query embedding are considered the most similar. Query item:         x
                    |
  ^                 |
  |          x Item 1|
  |         /       |
  |        /        |
  |       /x Item 2 |
  |      /          |
  |     /           |
  |    /x Item 3    |
  |   /             |
  |  /              |
  | /               |
  +-------------------> This is obviously a simplified visualization as vector search operates in high-dimensional spaces. In the next sections, we’ll summarize 5 engineering blogs on vector search and highlight key implementation considerations. The full engineering blogs can be found below: by Jinfeng Zhuang at Pinterest PinText: A Multitask Text Embedding System in Pinterest by Alexandre Tamborrino at Spotify Introducing Natural Language Search for Podcast Episodes by Senthilkumar Gopal, Shubhangi Tandon, Christopher Miller, Deepika Srinivasan, Rui Kong, Selcuk Kopru and Srinivas Bhagavathula at eBay How eBay’s New Search Feature Was Inspired By Window Shopping by Mihajlo Grbovic at AirBnb Listing Embeddings in Search Ranking by Mitchell Koch, Aamir Manasawala, Raghav Ramesh at Doordash Personalized Store Feed with Vector Embeddings Pinterest: Interest search and discovery Pinterest uses for image search and discovery across multiple areas of its platform, including recommended content on the home feed, related pins and search using a multitask learning model. vector search A multi-task model is trained to perform multiple tasks simultaneously, often sharing underlying representations or features, which can improve generalization and efficiency across related tasks. In the case of Pinterest, the team trained and used the same model to drive recommended content on the homefeed, related pins and search. Pinterest trains the model by pairing a users search query (q) with the content they clicked on or pins they saved (p). Here is how Pinterest created the (q,p) pairs for each task: : Word embeddings are derived from the selected subject (q) and the pin clicked on or saved by the user (p). Related Pins : Word embeddings are created from the search query text (q) and the pin clicked on or saved by the user (p). Search : Word embeddings are generated based on the interest of the user (q) and the pin clicked on or saved by the user (p). Homefeed To obtain an overall entity embedding, Pinterest averages the associated word embeddings for related pins, search and the homefeed. Pinterest created and evaluated its own supervised Pintext-MTL (multi-task learning) against unsupervised learning models including GloVe, word2vec as well as a single-task learning model, PinText-SR on precision. PinText-MTL had higher precision than the other embedding models, meaning that it had a higher proportion of true positive predictions among all positive predictions. Pinterest also found that multi-task learning models had a higher recall, or a higher proportion of relevant instances correctly identified by the model, making them a better fit for search and discovery. To put this all together in production, Pinterest has a multitask model trained on streaming data from the homefeed, search and related pins. Once that model is trained, vector embeddings are created in a large batch job using either Kubernetes+Docker or a map-reduce system. The platform builds a search index of vector embeddings and runs a K-nearest neighbors (KNN) search to find the most relevant content for users. Results are cached to meet the performance requirements of the Pinterest platform. Spotify: Podcast search Spotify combines keyword and to retrieve relevant podcast episode results for users. As an example, the team highlighted the limitations of keyword search for the query “electric cars climate impact”, a query which yielded 0 results even though relevant podcast episodes exist in the Spotify library. To improve recall, the Spotify team used Approximate Nearest Neighbor (ANN) for fast, relevant podcast search. semantic search The team generates vector embeddings using the as it is multilingual, supporting a global library of podcasts, and produces high-quality vector embeddings. Other models were also evaluated including , a model trained on a big corpus of text data, but found that BERT was better suited for word embeddings than sentence embeddings and was pre-trained only in English. Universal Sentence Encoder CMLM model BERT Spotify builds the vector embeddings with the query text being the input embedding and a concatenation of textual metadata fields including title and description for the podcast episode embeddings. To determine the similarity, Spotify measured the cosine distance between the query and episode embeddings. To train the base Universal Sentence Encoder CMLM model, Spotify used positive pairs of successful podcast searches and episodes. They incorporated in-batch negatives, a technique highlighted in papers including and , to generate random negative pairings. Testing was also conducted using synthetic queries and manually written queries. Dense Passage Retrieval for Open-Domain Question Answering (DPR) Que2Search: Fast and Accurate Query and Document Understanding for Search at Facebook To incorporate vector search into serving podcast recommendations in production, Spotify used the following steps and technologies: : Spotify indexes the episode vectors offline in batch using , a search engine with native support for ANN. One of the reasons that Vespa was chosen is that it can also incorporate metadata filtering post-search on features like episode popularity. Index episode vectors Vespa : Spotify uses to generate a query vector. Vertex AI was chosen for its support for GPU inference, which is more cost effective when using large transformer models to generate embeddings, and for its query cache. After the query vector embedding is generated, it is used to retrieve the top 30 podcast episodes from Vespa. Online inference Google Cloud Vertex AI Semantic search contributes to the identification of pertinent podcast episodes, yet it is unable to fully supplant keyword search. This is due to the fact that semantic search falls short of exact term matching when users search an exact episode or podcast name. Spotify employs a hybrid search approach, merging semantic search in Vespa with keyword search in , followed by a conclusive re-ranking stage to establish the episodes displayed to users. Elasticsearch eBay: Image search Traditionally, search engines have displayed results by aligning the search query text with textual descriptions of items or documents. This method relies extensively on language to infer preferences and is not as effective in capturing elements of style or aesthetics. eBay introduces to help users find relevant, similar items that meet the style they’re looking for. image search eBay uses a multi-modal model which is designed to process and integrate data from multiple modalities or input types, such as text, images, audio, or video, to make predictions or perform tasks. eBay incorporates both text and images into its model, producing image embeddings utilizing a Convolutional Neural Network (CNN) model, specifically , and title embeddings using a text-based model such as . Every listing is represented by a vector embedding that combines both the image and title embeddings. Resnet-50 BERT Once the multi-modal model is trained using a large dataset of image-title listing pairs and recently sold listings, it is time to put it into production in the site search experience. Due to the large number of listings at eBay, the data is loaded in batches to HDFS, eBay’s data warehouse. eBay uses Apache Spark to retrieve and store the image and relevant fields required for further processing of listings, including generating listing embeddings. The listing embeddings are published to a columnar store such as HBase which is good at aggregating large-scale data. From HBase, the listing embedding is indexed and served in Cassini, a search engine created at eBay. The pipeline is managed using Apache Airflow, which is capable of scaling even when there is a high quantity and complexity of tasks. It also provides support for Spark, Hadoop, and Python, making it convenient for the machine learning team to adopt and utilize. Visual search allows users to find similar styles and preferences in the categories of furniture and home decor, where style and aesthetics are key to purchase decisions. In the future, eBay plans to expand visual search across all categories and also help users discover related items so they can establish the same look and feel across their home. AirBnb: Real-time personalized listings Search and similar listings features drive 99% of bookings on the AirBnb site. AirBnb built a to improve similar listing recommendations and provide real-time personalization in search rankings. listing embedding technique AirBnb realized early on that they could expand the application of embeddings beyond just word representations, encompassing user behaviors including clicks and bookings as well. To train the embedding models, AirBnb incorporated over 4.5M active listings and 800 million search sessions to determine the similarity based on what listings a user clicks and skips in a session. Listings that were clicked by the same user in a session are pushed closer together; listings that were skipped by the user are pushed further away. The team settled on the dimensionality of a listing embedding of d=32 given the tradeoff between offline performance and memory needed for online serving. https://youtu.be/aWjsUEX7B1I?si=GREROVrWxWqtqL-m&embedable=true AirBnb found that certain listings characteristics do not require learning, as they can be directly obtained from metadata, such as price. However, attributes like architecture, style, and ambiance are considerably more challenging to derive from metadata. Before moving to production, AirBnb validated their model by testing how well the model recommended listings that a user actually booked. The team also ran an A/B test comparing the existing listings algorithm against the vector embedding-based algorithm. They found that the algorithm with vector embeddings resulted in a 21% uptick in CTR and 4.9% increase in users discovering a listing that they booked. The team also realized that vector embeddings could be used as part of the model for real-time personalization in search. For each user, they collected and maintained in real time, using Kafka, a short-term history of user clicks and skips in the last two weeks. For every search conducted by the user, they ran two similarity searches: based on the geographic markets that were recently searched and then the similarity between the candidate listings and the ones the user has clicked/skipped Embeddings were evaluated in offline and online experiments and became part of the real-time personalization features. Doordash: Personalized store feeds Doordash has a wide variety of stores that users can choose to order from and being able to surface the most relevant stores using personalized preferences improves search and discovery. Doordash wanted to apply to its store feed algorithms using vector embeddings. This would enable Doordash to uncover similarities between stores that were not well-documented including if a store has sweet items, is considered trendy or features vegetarian options. latent information Doordash used a derivative of word2vec, an embedding model used in natural language processing, called store2vec that it adapted based on existing data. The team treated each store as a word and formed sentences using the list of stores viewed during a single user session, with a maximum limit of 5 stores per sentence. To create user vector embeddings, Doordash summed the vectors of the stores from which users placed orders in the past 6 months or up to 100 orders. As an example, Doordash used vector search to find similar restaurants for a user based on their recent purchases at popular, trendy joints 4505 Burgers and New Nagano Sushi in San Francisco. Doordash generated a list of similar restaurants measuring the cosine distance from the user embedding to store embeddings in the area. You can see that the stores that were closest in cosine distance include Kezar Pub and Wooden Charcoal Korean Village BBQ. Doordash incorporated store2vec distance feature as one of the features in its larger recommendation and personalization model. With vector search, Doordash was able to see a 5% increase in click-through-rate. The team is also experimenting with new models like , model optimizations and incorporating real-time onsite activity data from users. seq2seq Key considerations for vector search Pinterest, Spotify, eBay, Airbnb and Doordash create better search and discovery experiences with vector search. Many of these teams started out using text search and found limitations with fuzzy search or searches of specific styles or aesthetics. In these scenarios, adding vector search to the experience made it easier to find relevant, and often personalized, podcasts, pillows, rentals, pins and eateries. There are a few decisions that these companies made that are worth calling out when implementing vector search: : Many started out using an off-the-shelf model and then trained it on their own data. They also recognized that language models like word2vec could be used by swapping words and their descriptions with items and similar items that were recently clicked. Teams like AirBnb found that using derivatives of language models, rather than image models, could still work well for capturing visual similarities and differences. Embedding models : Many of these companies opted to train their models on past purchase and click through data, making use of existing large-scale datasets. Training : While many companies adopted ANN search, we saw that Pinterest was able to combine metadata filtering with KNN search for efficiency at scale. Indexing : Vector search rarely replaces text search. Many times, like in Spotify’s example, a final ranking algorithm is used to determine whether vector search or text search generated the most relevant result. Hybrid search : We’re seeing many teams use batch-based systems to create the vector embeddings, given that these embeddings are rarely updated. They employ a different system, frequently Elasticsearch, to compute the query vector embedding live and incorporate real-time metadata in their search. Productionizing Rockset, a real-time search and analytics database, recently added support for . Give vector search on Rockset a try for real-time personalization, recommendations, anomaly detection and more by starting a with $300 in credits today. vector search free trial

A Look Into 5 Use Cases for Vector Search from Major Tech Companies

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Xem xét 5 trường hợp sử dụng tìm kiếm vectơ từ các công ty công nghệ lớn

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“Please tell them you made a mistake.” she pleaded. “Tell them I did not do anything wrong,” the preteen put her hands in a clasp. Bending over a little. Her lips were pressed into a “please.” Her friend, Kelly, was not so willing to ask for me to change my mind. She was standing there stiff and wooden. Her perm was always tight to her head with curls. It was a hairstyle for the early 90s. Lee Ann’s bangs were standing straight up in the fashion of that time.  So much hairspray and this was a direct contradiction to my own black hair in braids. I did not say anything. ‘She begged again.”You can tell them you made a mistake. This was a mistake” I knew she wanted to go to the big game and cheer in the game with her friends. The principal told her she was not allowed. This was the punishment she was getting for bullying me throughout the whole of 5th grade. Lee Ann was the ringleader of 2 other girls. One girl, Anne, would pretend to be my friend and I would let my guard down and talk to her. Anne would share what I had said with Lee Ann. Lee Ann and Kelly, armed with this knowledge, sat by me at lunch time every day and harassed me and then in the evening they would call my parents landline phone to harass me at home. Now it was spring and the big game was coming up. She was not going to get to participate in it or go to the game. She was miserable and I could tell. My heart relented. I felt bad about how things played out.  This time like all the other times, I was having trouble standing up for myself. I was thinking about how much she wanted to go to the game. But I was silent. I turned around. I walked away without a word. The community of small town Kentucky, USA at that time was a peaceful, quiet one. There were few threats. It was an idyllic place. This was before the opioid epidemic hit with that place being an epicenter. I went to a local elementary school and it was here I met Lee Ann and her friends who would later bully me through the whole of fifth grade. They could see I was different. I was so different from the others in the school.  I was the child of Indian immigrants and my skin was brown in contrast to the homogeneous white that most of my classmates were. So I was ending fifth grade having spoken up for myself for the first time in my life by actually not speaking up. “Here” “I pushed a letter into my teacher's hand, "Some things have been going on in class.”  I had written a letter with all the ways the 3 girls had teamed up and bullied me.  My parents let me work this out on my own. If I thought my teacher did not take my letter seriously, I would be contradicted by seeing the folded letter again on her desk with the ominous word PRIVATE marked on it in red ink.  \ Then, here I was confronted by the results of my actions.  Lee Ann had been standing in front of me groveling to be able to go to the Big Game and cheer. And I walked away.  I left Lee Ann to her problems. Whatever they were.  The problems were not my business. I didn’t care. Of the 3 fifth grade girls, I felt that Anne hurt me the most because she betrayed my trust. I had thought Anne was my friend and now I knew I was alone. I knew Kelly and Lee Ann were “bad apples” but I could not believe this about Anne, but I would have to face the truth.  \ Ultimately, this letter I wrote would be my way of dealing with not belonging to a community, but trying to find a way to be respected and treated well despite all that. And despite not fitting into any box that was made for me. Later, I would find out this was because I am neurodiverse.  \ In my career, I would face conflicts and not want to immediately speak up. I struggled with a coworker who was near retirement and who was going to probably be leaving in a year. I had a difficult time with her because she held a grudge against me and she would not do any of her job responsibilities. She was best friends with her supervisor and that person would not do anything to make her work. I was really unhappy because I had to change a lot of my workflow to accommodate her not working. I wonder if I could do this differently now. I might have been more assertive and tried to talk to her about her behaviors. Previously we did have a good relationship and there was a misunderstanding that seemed to cause a problem but I don't know what it was exactly. I would have had to be more assertive this time and be very understanding and listen to her concerns when/if we had a conversation. But instead, I remember avoiding the conflict and not dealing with it effectively.\ Now that that situation has ended and I have had a lifetime of other conflicts, I wish I had learned conflict resolution techniques and assertiveness much earlier. A friend wrote me a text message recently in which he was referring to himself and showing self compassion. I liked the comment so much I internalized it too. \ “I am taking it one day at a time and trying to acknowledge the value of acceptance. That where I am in life is exactly where I am supposed to be.” This Spring, I am voluntarily taking a class in conflict resolution and mediation. One of the first homework assignments from my mediation teachers was to write my obituary. It was an exercise to help me know what I wanted from the remaining part of my life and to help me reach that outcome. I wrote: “In her 90s, Amy Pravin Shah never retired; she was still writing and speaking throughout this decade. She found tremendous satisfaction in writing and helping others.” One of the things I would have to learn to become this elderly powerhouse would be to learn to resolve conflict with my words and to learn to speak up for myself. One conflict at a time. “Please tell them you made a mistake.” she pleaded. “Tell them I did not do anything wrong,” the preteen put her hands in a clasp. Bending over a little. Her lips were pressed into a “please.” Her friend, Kelly, was not so willing to ask for me to change my mind. She was standing there stiff and wooden. Her perm was always tight to her head with curls. It was a hairstyle for the early 90s. Lee Ann’s bangs were standing straight up in the fashion of that time.  So much hairspray and this was a direct contradiction to my own black hair in braids. “Please tell them you made a mistake.” she pleaded. “Tell them I did not do anything wrong,” the preteen put her hands in a clasp. Bending over a little. Her lips were pressed into a “please.” Her friend, Kelly, was not so willing to ask for me to change my mind. She was standing there stiff and wooden. Her perm was always tight to her head with curls. It was a hairstyle for the early 90s. Lee Ann’s bangs were standing straight up in the fashion of that time.  So much hairspray and this was a direct contradiction to my own black hair in braids. I did not say anything. ‘She begged again.”You can tell them you made a mistake. This was a mistake” I knew she wanted to go to the big game and cheer in the game with her friends. The principal told her she was not allowed. This was the punishment she was getting for bullying me throughout the whole of 5th grade. Lee Ann was the ringleader of 2 other girls. One girl, Anne, would pretend to be my friend and I would let my guard down and talk to her. Anne would share what I had said with Lee Ann. Lee Ann and Kelly, armed with this knowledge, sat by me at lunch time every day and harassed me and then in the evening they would call my parents landline phone to harass me at home. Now it was spring and the big game was coming up. She was not going to get to participate in it or go to the game. She was miserable and I could tell. My heart relented. I felt bad about how things played out.  This time like all the other times, I was having trouble standing up for myself. I was thinking about how much she wanted to go to the game. But I was silent. I turned around. I walked away without a word. The community of small town Kentucky, USA at that time was a peaceful, quiet one. There were few threats. It was an idyllic place. This was before the opioid epidemic hit with that place being an epicenter. I went to a local elementary school and it was here I met Lee Ann and her friends who would later bully me through the whole of fifth grade. They could see I was different. I was so different from the others in the school.  I was the child of Indian immigrants and my skin was brown in contrast to the homogeneous white that most of my classmates were. So I was ending fifth grade having spoken up for myself for the first time in my life by actually not speaking up. “Here” “I pushed a letter into my teacher's hand, "Some things have been going on in class.”  I had written a letter with all the ways the 3 girls had teamed up and bullied me.  My parents let me work this out on my own. If I thought my teacher did not take my letter seriously, I would be contradicted by seeing the folded letter again on her desk with the ominous word PRIVATE marked on it in red ink.  \ Then, here I was confronted by the results of my actions.  Lee Ann had been standing in front of me groveling to be able to go to the Big Game and cheer. And I walked away.  I left Lee Ann to her problems. Whatever they were.  The problems were not my business. I didn’t care. Of the 3 fifth grade girls, I felt that Anne hurt me the most because she betrayed my trust. I had thought Anne was my friend and now I knew I was alone. I knew Kelly and Lee Ann were “bad apples” but I could not believe this about Anne, but I would have to face the truth.  \ Ultimately, this letter I wrote would be my way of dealing with not belonging to a community, but trying to find a way to be respected and treated well despite all that. And despite not fitting into any box that was made for me. Later, I would find out this was because I am neurodiverse.  \ In my career, I would face conflicts and not want to immediately speak up. I struggled with a coworker who was near retirement and who was going to probably be leaving in a year. I had a difficult time with her because she held a grudge against me and she would not do any of her job responsibilities. She was best friends with her supervisor and that person would not do anything to make her work. I was really unhappy because I had to change a lot of my workflow to accommodate her not working. I wonder if I could do this differently now. I might have been more assertive and tried to talk to her about her behaviors. Previously we did have a good relationship and there was a misunderstanding that seemed to cause a problem but I don't know what it was exactly. I would have had to be more assertive this time and be very understanding and listen to her concerns when/if we had a conversation. But instead, I remember avoiding the conflict and not dealing with it effectively.\ Now that that situation has ended and I have had a lifetime of other conflicts, I wish I had learned conflict resolution techniques and assertiveness much earlier. A friend wrote me a text message recently in which he was referring to himself and showing self compassion. I liked the comment so much I internalized it too. \ “I am taking it one day at a time and trying to acknowledge the value of acceptance. That where I am in life is exactly where I am supposed to be.” This Spring, I am voluntarily taking a class in conflict resolution and mediation. One of the first homework assignments from my mediation teachers was to write my obituary. It was an exercise to help me know what I wanted from the remaining part of my life and to help me reach that outcome. I wrote: “In her 90s, Amy Pravin Shah never retired; she was still writing and speaking throughout this decade. She found tremendous satisfaction in writing and helping others.” One of the things I would have to learn to become this elderly powerhouse would be to learn to resolve conflict with my words and to learn to speak up for myself. One conflict at a time.

Learning to Deal with Conflict and Neurodiversity

How To Go From Manager to Leader

কিভাবে ম্যানেজার থেকে লিডারে যেতে হয়

So werden Sie vom Manager zur Führungskraft

Cómo pasar de gerente a líder

Comment passer de manager à leader

मैनेजर से लीडर कैसे बनें?

マネージャーからリーダーになる方法

관리자에서 리더로 가는 방법

Como passar de gerente a líder

Как пройти путь от менеджера до лидера

Yöneticilikten Liderliğe Nasıl Geçilir?

Làm thế nào để đi từ quản lý đến lãnh đạo

如何从经理转型为领导者

Moving Beyond Self-Esteem For Self-Fulfilment 

স্ব-পরিপূর্ণতার জন্য স্ব-সম্মান অতিক্রম করা

Über das Selbstwertgefühl hinausgehen und sich selbst verwirklichen

Más allá de la autoestima para la realización personal

Aller au-delà de l’estime de soi pour l’épanouissement personnel

आत्म-संतुष्टि के लिए आत्म-सम्मान से आगे बढ़ना

自己実現のために自尊心を超える

자존감을 넘어 자기 실현을 위해

Indo além da autoestima para a autorrealização

Выход за пределы самооценки ради самореализации

Kendini Gerçekleştirmek İçin Benlik Saygısının Ötesine Geçmek

Vượt lên trên lòng tự trọng để hoàn thiện bản thân

超越自尊，实现自我价值

2024’s here, and DIY LLM toys? Totally a thing now. No tech wizardry needed, just your curiosity. I took the plunge, mixing a bit of coding with heaps of fun, and bam — created my own talking toy. If you’re up for crafting an AI buddy with ease, you’re in the right spot. Let’s demystify tech together and bring your AI friend to life. In a world where technology increasingly intersects with daily life, creating your own LLM toy not only demystifies AI but also provides a personalized gateway to the wonders of interactive technology. Let’s take a look at the final effect first. https://www.youtube.com/embed/FKEYL6VgHo4?embedable=true Honestly, it’s pretty awesome. Ready to start? Let’s dive in! How Does It Work? There are three key steps: Recording: Receive real-time recording data sent by the toy through UDP, and call the STT (Sound-To-Text) API to convert the sound into text. Thinking: After receiving the previous text, the LLM (Large-Language-Model) API will be immediately called to obtain sentences generated by the LLM in a streaming manner. Then, the TTS (Text-To-Sound) API is called to convert the sentences into human speech. Play audio: Toys will receive TTS (Text-To-Sound) audio file streams generated by the FoloToy Server and play them according to the order. Preparation Before Development Before you start making your LLM toy, it is crucial to understand the necessary hardware, software, and technical knowledge. This section will guide you in preparing all the essentials to ensure a smooth start. Hardware The ChatGPT AI Voice Conversation Core Board serves as the brain of your project, enabling voice interactions with AI. Folotoy Core: Essentials like a microphone, speaker, buttons, switches, and power supply are necessary. I’m going with the for its ready-to-use setup. Toy Components: Alilo Honey Bunny G6 (any other choice): Ideal for those looking to retrofit existing toys with AI capabilities. Octopus Dev Suit Server Utilizing your own machine, like a MacBook Pro, ensures that your toy has a reliable backend to process and respond to voice interactions. Alternatively, cloud services like Google Cloud Engine (GCE) can scale your project for broader applications. Prerequisite Knowledge (required): Understanding Docker is crucial for deploying software in containers, making your project portable and scalable. I use it to start the Folo server. Docker (required): Version control is essential for managing your project’s codebase. I use it for managing the Folo server codebase. Git (optional): If you’re aiming for advanced customization, familiarity with MQTT (a lightweight messaging protocol) will be beneficial for communicating between the toy and the server. MQTT (optional): Open-source MQTT broker for IoT, IIoT, and connected vehicles. Used for managing your toys. EMQX (optional): If you want to run large language models locally, it’s a good choice. ollama Services & Registration To make your toy come to life, you’ll need access to specific AI services. For this project, I’ve chosen to utilize OpenAI’s offerings: TTS (Text-to-Speech): OpenAI’s Whisper service converts text responses from the AI into speech, making the interaction natural. LLM (Large Language Model): Utilizing OpenAI’s models for understanding and generating human-like text responses. STT (Speech-to-Text): OpenAI’s TTS service transcribes spoken words into text, allowing the AI to understand voice commands or queries. All you need do is register on the OpenAI platform and , like sk-…i7TL. create a key Assemble Your Toy Now it’s time to put all the pieces together and make your own LLM toy. https://www.youtube.com/embed/hR7V1izzeZw?si=T3cY8y4Oy2Bxkg0H&embedable=true The general steps are as follows, it is recommended to watch the above tutorial first. Check if the recording and playback of Alilo G6 are normal. Use a screwdriver to unscrew the 6 screws on the back of Alilo G6. Carefully open the casing of Alilo G6, unplug all plugs on the motherboard, and first unplug the power plug, there is glue on the plug, you can use an art knife to gently cut it open, be sure not to cut your hand. Unscrew the 4 screws on the motherboard and remove it. Replace the original motherboard with FoloToy’s motherboard and tighten 3 screws to fix it. Plug in the microphone, light, speaker, and power sockets, finally, plug in the power socket. After plugging in all sockets, do not close the casing or install screws yet. First, turn the on/off switch on the rabbit’s tail to see if the newly installed light can turn on and flash slowly in blue color. If there is no problem, install the casing and tighten the screws to complete the replacement process. Set Up the Server Strong backend support is key to making your LLM toys understand and respond to voice commands. This section will teach you how to clone the server code base, configure the server, and start Docker containers to ensure that your toys have stable backend support. First, clone the Folo server codebase from GitHub. git clone git@github.com:FoloToy/folotoy-server-self-hosting.git Then change the base server configuration in file to your own. docker-compose.yml Name Description Example OPENAI_OPENAI_KEY Your OpenAI API key. sk-...i7TL OPENAI_TTS_KEY Your OpenAI API key. sk-...i7TL OPENAI_WHISPER_KEY Your OpenAI API key. sk-...i7TL AUDIO_DOWNLOAD_URL The URL of the audio file. http://192.168.x.x:8082 SPEECH_UDP_SERVER_HOST The IP address of your server. 192.168.x.x Then configure your roles in the file, here is a minimal example, for full configuration, please refer to the . config/roles.json Folotoy documentation {
  "1": {
    "start_text": "Hello, what can I do for you?",
    "prompt": "You are a helpful assistant."
  }
} Then start the docker containers. docker compose up -d I run the Folo server in my own machine, if you want to run it in the cloud, almost the same. One thing to note is that you need to expose the port 1883, 8082, 8085, 18083 and 8083 to the public network. For more information, please refer to the . Folotoy documentation Chat with Your Toy Once everything is ready, it’s time to interact with your LLM toy. Turn on the switch on the back of the toy to power it on. The blue blinking light in the ears indicates that the toy has entered pairing mode. Turn on your phone or computer, and select the “FoloToy-xxxx” wireless network. After a moment, your phone or computer will automatically open a configuration page where you can set which WiFi network (SSID and password) to connect to, as well as the server address (like 192.168.x.x) and port number (keep the default 1883). After the network is configured and connected to the server, press the big round button in the middle to start the conversation. After you stop speaking, FoloToy will emit a beep to indicate the end of the recording. The 7 round small buttons around are role-switching buttons. After clicking, the role switch takes effect. Debugging Whether it is a server or a toy, you may encounter some technical problems. This section will provide some basic debugging tips and tools to help you diagnose and solve possible problems and ensure that your LLM toys can run smoothly. Server Debugging To check the server logs, run the following command. docker compose logs -f LOG_LEVEL can be set in the file to control the log level. docker-compose.yml Toy Debugging Folo Toy provides an easy way to debug the toy base on a USB serial port. You can use the to debug the toy. Folo Toy Web Tool Connect the toy with your computer using a USB cable. Open the Folo Toy Web Tool, and then click the “Console” button to connect to the toy. Once connected, you should be able to see real-time logs from your device in the console. Also, there is a LED on the toy, it will light up in . different colors to indicate the status of the toy MQTT Debugging Open the to check the MQTT messages. The default username is admin and the password is public. Anyways, change the password to a secure one after you log in. EMQX Dashboard Advanced Customization For advanced users who want to further explore and customize their LLM toys, this section will introduce how to locally run large language models, use tools such as CloudFlare AI Gateway, and customize the voice of characters. This will open up a broader world of DIY LLM toys for you. Run LLM Locally Running large language models locally is an interesting thing. You can run Llama 2, Gemma, and all kinds of open-source large models from around the world, even models trained by yourself. Using ollama, you can do it easily. , and then run the following command to run the Llama 2 model. Install ollama first ollama run llama2 Then, to use the local LLM model. change the role configuration {
  "1": {
    "start_text": "Hello, what can I do for you?",
    "prompt": "You are a helpful assistant.",
    "llm_type": "ollama",
    "llm_config": {
      "api_base": "http://host.docker.internal:11434",
      "model": "llama2"
    }
  }
} The api_base should be the address of your ollama server address, and don’t forget to restart the Folo server to make the changes take effect. docker compose restart folotoy That’s all, change model to Gemma or other models as you like, and enjoy it. Use CloudFlare AI Gateway Cloudflare’s AI Gateway allows you to gain visibility and control over your AI apps. By connecting your apps to AI Gateway, you can gather insights on how people are using your application with analytics and logging and then control how your application scales with features such as caching, rate limiting, as well as request retries, model fallback, and more. First, you need to . create a new AI Gateway Then edit the file to change OPENAI_OPENAI_API_BASE to the address of your AI Gateway, like this: docker-compose.yml services:
  folotoy:
    environment: OPENAI_OPENAI_API_BASE=https://gateway.ai.cloudflare.com/v1/${ACCOUNT_TAG}/${GATEWAY}/openai Then you have a dashboard to see metrics on requests, tokens, caching, errors, and cost. And a logging page to see individual requests, such as the prompt, response, provider, timestamps, and whether the request was successful, cached, or if there was an error. That’s fantastic, isn’t it? Role Voice Customization You can customize the voice of the role by changing the field in the role configuration file. voice_name {
  "1": {
    "tts_type": "openai-tts",
    "tts_config": {
      "voice_name": "alloy"
    }
  }
} Find the voice you like in the . OpenAI TTS Voice List Edge tts has many voices to choose from, enjoy it like this: {
  "1": {
    "tts_type": "edge-tts",
    "tts_config": {
      "voice_name": "en-NG-EzinneNeural"
    }
  }
} Knowledge base support ​ For higher levels of customization, such as knowledge base support. It is recommended to use Dify, which combines the concepts of Backend as Service and LLMOps, covering the core technology stack required to build generative AI native applications, including a built-in RAG engine. With Dify, you can self-deploy capabilities like Assistants API and GPTs based on any model. Let’s focus on the built-in RAG engine, which is a retrieval-based generative model that can be used for tasks such as question and answer, dialogue, and document summarization. Dify includes various RAG capabilities based on full-text indexing or vector database embedding, allowing direct upload of various text formats such as PDF and TXT. Upload your knowledge base, so you don’t have to worry about the toy-making nonsense because you don’t know the background knowledge. Dify can be deployed by itself or use the cloud version directly. The configuration on Folo is also very simple: {
  "1": {
    "llm_type": "dify",
    "llm_config": {
      "api_base": "http://192.168.52.164/v1",
      "key": "app-AAAAAAAAAAAAAAAAAAa"
    }
  }
} Custom toy shape ​ In terms of working principle, any toy can be modified. Folo Toy also offers the Octopus AI Development Kit, which can transform any ordinary toy into an intelligent talking toy. The chip is small and lightweight and can easily fit into any type of toy, whether plush, plastic, or wooden. I DIYed a Shaanxi-speaking cactus. Use your imagination, you can put it into your favorite toys, and it’s not particularly complicated to do it: open the toy Put the Octopus AI development kit into it close the toy The server still uses the same one. You can assign different roles to different toys through sn, which will not be expanded here. You can check the configuration document on the official website. Security Notes Please note, never put the key in a public place, such as GitHub, or it will be abused. If your key is leaked, delete it immediately on the OpenAI platform and generate a new one. You can also use environment variables in and pass them in when starting the container, so as to avoid exposing the key in the code. docker-compose.yml services:
  folotoy:
    environment:
      - OPENAI_OPENAI_KEY=${OPENAI_OPENAI_KEY} OPENAI_OPENAI_KEY=sk-...i7TL docker compose up -d In case you wish to make FoloToy Server publicly available on the Internet, it is strongly recommended to secure the EMQX service and allow access to EMQX only with a password. Learn more about . EMQX Security Conclusion Crafting your own LLM toy is an exciting journey into the world of AI and technology. Whether you’re a DIY enthusiast or a beginner, this guide provides the roadmap to create something truly interactive and personalized. If you encounter challenges acquiring the Folotoy Core or face any issues along the way, joining our Telegram group offers community support and expert advice. For those preferring a ready-made solution, the finished product is available for purchase . This option delivers the same interactive experience without the need for assembly. Folo toys also offer many other products which can be found . here here

DIY LLM Toys: How to Create Your Own AI Buddy with Ease

Open-source software has become the backbone of modern software development, empowering developers with a vast ecosystem of freely available libraries, frameworks, and tools. From the smallest indie projects to the mightiest tech giants, everyone is riding the open-source wave, reaping the benefits of cost savings, rapid iteration, and community-driven innovation. However, as the old saying goes, "there's no such thing as a free lunch." Despite its allure, the reliance on open-source components introduces significant security risks that can compromise the entire software supply chain. In this post, we'll delve into the dark side of open-source, exploring the hidden vulnerabilities, supply chain attacks, and the challenges of ensuring the integrity of the software we consume and build upon. Buckle up, because it's time to lift the veil on the often-overlooked dangers lurking within the open-source ecosystem. It started with a small idea The rise of open-source software (OSS) has been nothing short of a revolution, akin to a tidal wave sweeping across the tech industry. What began as a niche movement championed by idealistic developers has grown into a vast ecosystem, fueling innovation and disrupting traditional software development models. Just like a snowball rolling downhill, the adoption of OSS has gained unstoppable momentum, with even the most unlikely corporations and enterprises embracing its power. From humble beginnings as a novel concept, OSS has evolved into a cornerstone of modern software development, offering unparalleled benefits. Cost savings? Check. Rapid iteration and time-to-market? Double-check. Access to a vast pool of battle-tested code? You bet. It's like having a magical toolbox filled with pre-built components, ready to be wielded by developers worldwide. Little wonder, then, that OSS has found its way into every nook and cranny of the software world, from small passion projects to enterprise-grade applications powering global corporations. An unsuspecting threat Just like the mythical Trojan horse, the open-source world harbors an unsuspecting threat lurking within its wooden belly. While the benefits of OSS are undeniable, its very nature – the open and collaborative development model – also introduces vulnerabilities that can be exploited by malicious actors. From insecure coding practices to outdated (vulnerable) dependencies, the potential attack vectors are numerous and ever-evolving. And as recent incidents have shown, these vulnerabilities can have far-reaching consequences. Remember the SolarWinds supply chain attack of 2020? A single compromise in their software update system allowed hackers to infiltrate the networks of numerous government agencies and Fortune 500 companies. Or the more recent CodeCov breach, where malicious actors injected malware into the company's software supply chain, potentially affecting thousands of clients? These incidents serve as sobering reminders that the open-source ecosystem, for all its benefits, is not immune to the dark forces of cybercrime. Understanding the software supply chain To truly grasp the magnitude of the threat, we must first understand the intricate web that is the software supply chain. At its core, it's a complex network of interconnected components, each relying on the integrity of the others. Think of it as a sprawling factory assembly line, where a single faulty part can derail the entire production process. [Potential GIF/Meme: An assembly line with a glitch, causing chaos and disruption.] In the realm of OSS, this supply chain is further convoluted by the sheer number of dependencies and third-party libraries involved. A typical application can rely on hundreds, if not thousands, of open-source components, each with its own set of dependencies, creating a tangled mess of code origins and potential vulnerabilities. It's like a vast, intricate tapestry woven from countless threads, where a single frayed strand can unravel the entire masterpiece. [Potential GIF/Meme: A tapestry unraveling, symbolizing the potential ripple effect of a single vulnerability in the OSS supply chain.] And just like a chain is only as strong as its weakest link, the overall security of your application is only as robust as the most vulnerable component in its supply chain. SolarWinds: A Case Study Here are two paragraphs presenting a case study of a high-profile open-source software supply chain attack: To truly grasp the gravity of the situation, let's dive into a real-world example that sent shockwaves through the tech industry. Remember the SolarWinds supply chain attack of 2020? It was a masterclass in supply chain exploitation, a cyber heist that would make Ocean's Eleven look like child's play. The attackers, believed to be a sophisticated hacking group with ties to the Russian government, executed a meticulously planned operation that took months, if not years, to orchestrate. They managed to compromise SolarWinds' software update system, injecting a cleverly crafted piece of malware, dubbed "SUNBURST," into their Orion platform – a widely used network monitoring tool deployed by thousands of organizations worldwide. With each routine software update, the SUNBURST malware stealthily made its way into the networks of numerous government agencies, Fortune 500 companies, and even cybersecurity firms tasked with detecting such threats. Once inside, the malware acted as a digital Trojan horse, establishing a foothold and paving the way for further exploitation and data exfiltration. The consequences were far-reaching and severe. Sensitive data, including emails, documents, and potentially classified information, was likely stolen from victims ranging from the U.S. Department of Homeland Security to tech giants like Microsoft and Cisco. This data was spilled like Kevin’s beans onto the darknet for just few dollars per record. The fallout also included significant financial losses, as organizations scrambled to investigate and mitigate the damage, not to mention the incalculable hit to their reputation and credibility. It was a stark reminder that even the most trusted software can be a double-edged sword, capable of inflicting grievous wounds when wielded by skilled and determined adversaries. Securing the Software Supply Chain In the face of such daunting threats, it's clear that a fundamental shift in our approach to software supply chain security is necessary. No longer can we afford to treat it as an afterthought or a mere checkbox on a compliance list. Instead, we must embrace a proactive and holistic strategy that addresses vulnerabilities from the very inception of the development lifecycle. Enter DevSecOps, a paradigm that seamlessly integrates security practices into the DevOps workflow. By breaking down the silos between development, operations, and security teams, DevSecOps fosters a culture of shared responsibility and continuous collaboration. Imagine a well-oiled machine, with each component working in harmony to identify and mitigate risks at every stage of the software delivery pipeline. At the core of this approach lies the concept of "shift left" – a philosophy that emphasizes addressing security concerns as early as possible in the development process. Rather than waiting until the final stages to perform security testing and audits, vulnerabilities are proactively identified and remediated from the get-go, reducing the overall risk and cost of fixing issues later on. Government regulations to help? While the tech industry grapples with the challenges of securing the software supply chain, it's evident that government and regulatory bodies also have a crucial role to play. After all, the consequences of supply chain attacks can extend far beyond the realm of private enterprises, impacting national security, critical infrastructure, and the well-being of citizens. Currently, the policies and regulations surrounding OSS supply chain security are a patchwork quilt of varying standards and best practices. Some industries, such as healthcare and finance, have more stringent requirements, while others operate in a regulatory grey area. This lack of consistent oversight and enforcement leaves vulnerabilities ripe for exploitation by malicious actors. To address this issue, governments must take a proactive stance and implement comprehensive strategies that reinforce supply chain security. This could involve mandating the adoption of secure coding practices, enforcing the use of Software Composition Analysis (SCA) tools, and establishing industry-wide standards for software transparency and provenance tracking. Additionally, governments could incentivize and fund open-source security initiatives, fostering collaboration between public and private sectors. By leveraging the collective expertise and resources of industry leaders, academia, and government agencies, we can collectively fortify the foundations of the software supply chain and stay ahead of emerging threats. What’s next? The writing is on the wall – the open-source ecosystem, for all its benefits, is not immune to the perils of supply chain attacks. Like a double-edged sword, the very advantages that make OSS so appealing – its open nature and widespread adoption – also introduce vulnerabilities that can be exploited by malicious actors. In this digital battleground, complacency is our greatest foe. Securing the software supply chain is not a one-and-done endeavor but a continuous process that demands unwavering vigilance and a proactive mindset. It's a shared responsibility that falls on the shoulders of open-source projects, developers, organizations, and even end-users. Much like a castle under siege, we must fortify our defenses, identify weaknesses, and swiftly patch vulnerabilities before they can be exploited. Embracing a culture of security-focused collaboration, adopting DevSecOps practices, and leveraging cutting-edge tools and technologies are crucial steps in this ongoing war against supply chain threats. But above all, we must remain vigilant, ever-watchful for the slightest chink in our armor, lest the hard-earned trust in the open-source ecosystem crumbles under the weight of a single, well-executed attack.

The Dark Side of Open Source: Securing the Software Supply Chain

How can you bring your best to every situation when dealing with the pressure of high expectations? You know that you can’t screw up when doing something that matters to you or when you really care about the outcome, and yet high-pressure situations make many people react poorly and lose their calm. It leads to poor choices, bad decisions and can sometimes even lead to inaction. The higher the stake, the higher the cost of not being in control. Losing your calm and shutting people out when work gets a little bit overwhelming or feeling so paralyzed by pressure that you get stuck in an overthinking cycle hurts your productivity and performance. For example: Making a key strategy decision for your organization. Presenting your ideas to a large audience. Negotiating a big deal with a client. These are great opportunities where pressure is inevitable, and yet you need to be confident and aim high. When we aim high, pressure and stress obligingly come along for the ride. Stuff is going to happen that catches us off guard, threatens or scares us. Surprises (unpleasant ones, mostly) are almost guaranteed. The risk of being overwhelmed is always there. Regardless of how much actual danger we’re in, stress puts us at the potential whim of our baser—fearful—instinctual reactions — Ryan Holiday You may have all the expertise, skills and the knowledge in the world to do well, but if you don’t know how to handle pressure situations well—you lose control of your emotions or see the situation as a threat—pressure will make you do worse, and lead you to fail utterly. \Keeping your calm during challenging times, ability to gauge the situation with a clear head and acting deliberately instead of reacting to the situation is crucial to lead under pressure. Here are the five strategies I have used in my career to stay calm and thrive under pressure: Realistically evaluate the situation Under pressure, your mind automatically becomes hyperactive and starts racing, which makes it either exaggerate the problem or get stuck in an overthinking cycle of what-ifs. The more you let your mind take control, the worse your imagination gets—everything bad that can happen gets magnified, and every good possibility takes a back seat. Catastrophic thinking that involves exaggerating the negative consequences of a situation and imagining the worst possible outcomes takes over. To stay calm under pressure, the first thing you need to do is come in touch with reality. Decatastrophizing will shift the focus away from these catastrophic thoughts and replace them with more balanced and realistic ones. To do this, ask these questions: What exactly is the problem or situation you’re dealing with? What’s making it stressful? Are these real expectations, or is it the result of self-imposed pressure? What’s the worst that can happen? How likely is it on a scale of 1 (not at all likely) to 5 (very likely). What’s the best case scenario? How likely is it on a scale of 1 (not at all likely) to 5 (very likely). What techniques or strategies can you use to cope with the catastrophe if it does happen? If the catastrophe occurs, what are the chances you'll be okay in 1 week, 1 month and 1 year from now? You have to stay realistic about the facts of your situation—distorting it will create unrealistic pressure that’s either impossible to meet or make the situation appear so frightening that you’ll fail to act right when you need it the most. Reappraise anxiety as excitement. A by Harvard Business School researcher Alison Wood Brooks found that people who see pressure situations as opportunities and not a threat perform better—those who reappraise anxiety as excitement end up showing more enthusiasm and performing better in subsequent tasks. study Reappraisal is a cognitive change in which you don’t actually change the surroundings that are causing negative emotions but instead try to alter your understanding of the circumstances. She suggests using strategies such as self-talk by saying out loud or messages like can lead to generating more excitement and adopting an opportunity mindset as opposed to a threat mindset. Reappraisal from anxiety to excitement positively correlates with better results in a stressful situation and improves subsequent performance. “I am excited” “get excited” But aren’t we always told to act cool and have a calm and confident demeanor under pressure? Brooks’ study shows that it doesn’t work. In her experiments she found out that people who talked about being excited just before the task significantly outperformed those who talked about being nervous, or calm, or were told to try to remain calm. She says “the more often individuals reappraise their anxiety as excitement, the more likely they may be to trigger upward motivational spirals, and the happier and more successful they may become.” Instead of trying to “Keep calm and carry on,” perhaps the path to success begins by simply saying, “I am excited.” Daniel McGinn draws upon Brooks’ study and explains this further: Brooks says, “People have this really strong intuition to try to calm down in stressful situations. You hear it all the time. People either actively say, ‘Calm down,’ or they say, ‘Don’t be anxious.’ The hitch is that it seems quite difficult to find strategies to actually do that.” In a perfect world, it might be possible to reappraise one’s feelings of nervousness into an unaroused, nonchalant calm. Brooks suggests that, in reality, that’s too great a leap. “The argument is that anxiety and excitement are actually very, very close, but that anxiety and calmness are too far apart,” she says. So, instead of aiming for calm, the smarter strategy is to force yourself to make the more subtle, achievable mental shift from nervousness to excitement. Leverage your experience Pressure situations tend to heighten negative feelings while suppressing positive emotions and outcomes. They make you focus on what you can lose as opposed to what you can gain. Thinking about your past experience helps put things in perspective. It shifts your focus from worrying about things outside your control to things within your reach—your knowledge, experience, and skills. Using your past successes as a gateway to your potential future success can prevent you from feeling overwhelmed by stressful and anxiety-causing situations. When working under pressure, think about a similar problem that you solved before: What are the similarities between the two situations? What are the differences? Consciously evaluating this helps you understand that no two situations are the same, but you can always leverage knowledge and experience from one to another. What specifically did you do in those situations to perform at your best? Which behaviors were helpful? Which behaviors were damaging and prevented you from achieving your goal? How can you leverage some of that learning and adapt it to the current situation? Thinking about a similar problem that you’ve solved before makes the experience less frightening. For example: Dealing with the pressure of a job interview? Think about your past interviews where you left a positive impact on the interviewer. Worried about giving a presentation? Think about the skills you demonstrated in your previous presentations that left everyone inspired. Pressure moments are filled with uncertainty—you are uncertain that you will deliver the goods. Remembering your past successes ignites confidence—you did it before and you can do it again. As your confidence increases, uncertainty (anxiety) and pressure are diminished, freeing you to approach the task with your best effort. Nervousness becomes transformed into positive enthusiasm that is directed to the task, rather than anxious thinking that is distracting. — Hendrie Weisinger To stay calm and thrive under pressure, say it out loud: “I’ve done it before. I can do it again.” Think about the immediate next step Pressure creates a sense of urgency—you need to act quickly and get things out of the way. But thinking about the enormity of the task ahead of you can overwhelm you and prevent you from getting started. Pressure which should ignite action turns into procrastination. You keep putting things off with excuses that appear completely justified in those moments—not enough motivation, not the right time, don’t have the clarity or keeping busy with trivial tasks while ignoring important and complex tasks that must be done to accomplish your goal. \Robert Maurer states — “Radical change is like charging up a steep hill—you may run out of wind before you reach the crest, or the thought of all the work ahead makes you give up no sooner than you’ve begun.” He suggests another path altogether, “one that winds so gently up the hill that you hardly notice the climb. It is pleasant to negotiate and soft to tread. And all it requires is that you place one foot in front of the other.” This strategy of putting one foot in front of the other—taking small steps for continual improvement—is called . Lao Tzu, the Chinese philosopher captured the spirit of Kaizen in his famous saying and John Wooden, the legendary basketball coach highlighted the importance of small improvement “When you improve a little each day, eventually big things occur. When you improve conditioning a little each day, eventually, you have a big improvement in conditioning. Not tomorrow, not the next day, but eventually, a big gain is made. Don’t look for the big, quick improvement. Seek the small improvement one day at a time. That’s the only way it happens—and when it happens, it lasts.” Kaizen “A journey of a thousand miles begins with a single step” Small, consistent changes turn off your brain’s alarm system that resists and fears change. These small steps may seem trivial at first, but they soon turn into meaningful habits. Pressure moments that earlier triggered procrastination now trigger purposeful action. To stay calm and thrive under pressure, don’t think about all the steps leading to your goal; just plan the immediate next step. One foot in front of the other requires: Identify a small step and put it into action. Act, revise, and repeat step 1 till you seek the second-level challenge. Act, revise, and repeat the second-level challenge till you desire the third-level challenge. Repeat this for the third, fourth...nth level challenge. And just like that, step at a time, your effort will compound into a much bigger change. Goals that appeared too big at first will now be within your reach. There will be no resistance to pushing aside or delaying the task when working under pressure. Taking small steps to make continuous progress will become a part of your identity. It’s what you’ll do. To stay calm and thrive under pressure, ask yourself, “What’s the first small step you can take?” Always be prepared Despite your best efforts and planning, some things may not go as expected. When you aren’t mentally prepared to handle the unexpected, any deviation from the normal or even a slight change in your circumstance can throw you off balance by taking away your sense of control over the situation, making you highly anxious, and distorting your ability to think clearly. When dealing with high pressure, unwelcome events are not only dreadful, they appear devastating. You end up making bad choices and regretful decisions. In life, there will be times when we do everything right, perhaps even perfectly. Yet the results will somehow be negative: failure, disrespect, jealousy, or even a resounding yawn from the world. — Ryan Holiday To be less startled by the unexpected, train your brain to expect the unexpected. To stay calm under pressure, be prepared to face the worst using the premortem technique: Place yourself into the future and look back. Visualize the project, task, or whatever you intend to do has gone horribly wrong. Create a mental picture in your mind using “what-if” scenarios. Work backward to identify what mistakes might cause it to fail. Create a plan to solve these issues—address the risks and obstacles, thereby making it easy to deal with them when they arise. Nothing can surprise you when you’re mentally prepared to deal with the unexpected. Consciously thinking about uncomfortable and unwanted situations has another advantage—it builds the mental muscle to embrace discomfort instead of running away from it. You cannot predict the future, but you can plan for it. You cannot control the uncertain outcomes, but you can be better prepared to focus on the controllable results. When performing under pressure, knowing the worst that can happen can lift the pressure off by being less dependent on the outcomes and putting more focus on the effort. Summary Pressure is inevitable when you’re trying to do worthwhile work. Reacting to pressure can put you at a disadvantage as you end up making poor choices and terrible decisions. Leading under pressure requires the ability to keep your calm and think with a clear head—being purposeful in the way you behave and act. Pressure leads to exaggeration—you imagine the worst possibility and consider it your best case. Seeing the situation for what it is without distorting facts or reality is critical to thriving under pressure. Anxiety and stress tag along when pressure shows up. However, research shows that reappraising anxiety as excitement makes you view pressure situations as opportunities and not a threat, which leads to more enthusiasm and better performance in subsequent tasks. Pressure situations can make your knowledge, skills, and experience irrelevant if you don’t know how to deal with them. Recalling past experience and leveraging it to deal with the current situation can diffuse pressure by reminding you that you’ve done it before and you can do it again. Pressure makes it hard to visualize the end goal and all the steps you need to take to get there. In some cases, pressure can make you feel so overwhelmed that you stop even before you’ve started. To prevent this from happening, take consistent small steps towards your goal. Putting one foot in front of the other is a powerful strategy to make progress without fear or self-doubt. Finally, remember that failures and mistakes are inevitable even with the best strategies and plans in place. Train your brain to expect the unexpected. This story was previously published . Follow me on or here for more stories. here LinkedIn

Thriving Under Pressure: Tips for Staying Calm Amid High Expectations

268 Stories To Learn About Project Management

A Roadmap for User Empowerment in the Dark Pattern Landscape

Intelligent DevOps: 8 Lessons Learned from Nature

ইন্টেলিজেন্ট ডিওঅপস: প্রকৃতি থেকে শেখা ৮টি পাঠ

Intelligentes DevOps: 8 Lektionen aus der Natur

DevOps inteligente: 8 lecciones aprendidas de la naturaleza

DevOps intelligent : 8 leçons tirées de la nature

इंटेलिजेंट DevOps: प्रकृति से सीखे गए 8 सबक

インテリジェントな DevOps: 自然から学んだ 8 つの教訓

지능형 DevOps: 자연에서 배운 8가지 교훈

DevOps Inteligente: 8 Lições Aprendidas com a Natureza

Интеллектуальный DevOps: 8 уроков, извлеченных из природы

Akıllı DevOps: Doğadan Öğrenilen 8 Ders

DevOps thông minh: 8 bài học rút ra từ thiên nhiên

智能 DevOps：从大自然中汲取的 8 个教训

Scientific American, Volume XXIV., No. 12, March 18, 1871 by Various, is part of the HackerNoon Books Series. You can jump to any chapter in this book . Official lists of patents here Official lists of patents ISSUED BY THE U. S. PATENT OFFICE. FOR THE WEEK ENDING MARCH 7, 1871. Reported Officially for the Scientific American. SCHEDULE OF PATENT FEES On each Caveat $10 On each Trade-Mark $25 On filing each application for a Patent, (seventeen years) $15 On issuing each original Patent $20 On appeal to Examiners-in-Chief $10 On appeal to Commissioner of Patents $20 On application for Reissue $30 On application for Extension of Patent $50 On granting the Extension $50 On filing a Disclaimer $10 On an application for Design (three and a half years) $10 On an application for Design (seven years) $15 On an application for Design (fourteen years) $30 For Copy of Claim of any Patent issued within 30 years $1 A sketch from the model or drawing, relating to such portion of a machine as the Claim covers, from upward, but usually at the price above-named. $1 The full Specification of any patent issued since Nov. 20, 1866 at which time the Patent Office commenced printing them $1.25 Official Copies of Drawings of any patent issued since 1836, we can supply at a reasonable cost, the price depending upon the amount of labor involved and the number of views. Full information, as to price of drawings, in each case, may be had by addressing MUNN & CO., Patent Solicitors, 37 Park Row, New York. 112,309.—Hose Sprinkler.—William Anderson, San Francisco, Cal. 112,310.—Locomotive Spark Arrester.—J. G. Armstrong, New Brunswick, N. J. 112,311.—Tool for Carriage Makers' Use.—George Atkinson, San Francisco, Cal. 112,312.—Potato Probe.—John A. Beal, Waterford, N. Y. 112,313.—Hinge for Carriage Doors.—George W. Beers, Bridgeport, Conn. 112,314.—Stove Leg.—James Birckhead, Jr., Baltimore, Md. 112,315.—Clothes Pin.—Orris A. Bishop, Chicago, Ill. 112,316.—Manufacture of Rochelle Salts and Borax.—V. G. Bloede, Brooklyn, N. Y. 112,317.—Beehive.—Felix Brewer, Waynesville, Mo. 112,318.—Thill Coupling.—Theodore Burr (assignor to Allen Muir and Henry Muir), Battle Creek, Mich. 112,319.—Evaporating Pan for Saccharine Liquids.—F. C. Butler, Bellows Falls, Vt., assignor to himself and James B. Williams, Glastonbury, Conn. 112,320.—Door Securer.—William H. Caldwell, Wheeling, W. Va. 112,321.—Toe-calk Bar.—R. B. Caswell, Springfield, Mass. Antedated March 2, 1871. 112,322.—Glass Flattening Furnace and Leer.—James Clabby, Lenox, Mass. 112,323.—Spring Bed Bottom.—Alex. Cole, Manamuskin, N. J. 112,324.—Water Wheel.—E. E. Coleman, West Cummington, Mass. 112,325.—Toy Horse and Carriage.—John B. Cuzner, Bridgeport, Conn. 112,326.—Mackerel-line Holder.—E. L. Decker, Southport, Me. 112,327.—Sewing Machine.—J. William Dufour, Stratford, Conn. 112,328.—Steam Boiler.—Edwards Evans, North Tonawanda, N. Y. 112,329.—Medical Compound for Cure of Catarrh and Asthma.—Erastus Field, Ostrander, Ohio. 112,330.—Machine for Grinding the Cutters of Mowers, etc.—H. C. Fisk, Wellsville, N. Y. 112,331.—Machine for Making Hooks and Eyes.—Jeremy T. Ford, San Francisco, Cal. 112,332.—Churn.—Thompson Freeman, Westfield, Ill. 112,333.—Attachment for Revolving Mold Boards for Plows.—J. S. Godfrey, Leslie, Mich., assignor to himself and S. M. Loveridge, Pittsburgh, Pa. 112,334.—Grain Cleaner and Fertilizer Sifter.—J. A. Green, Mill Dale, Va. 112,335.—Screw Propulsion.—E. C. Gregg (assignor to A. H. Gregg and C. P. Gregg), Trumansburg, N. Y. 112,336.—Seeding Machine.—P. M. Gundlach, Belleville, Ill. 112,337.—Compound for Kindling Fires.—J. L. Hannum and S. H. Stebbins, Berea, Ohio. 112,338.—Lawn Mower.—Benjamin Harnish, Lancaster, and D. H. Harnish, Pequea, Pa. 112,339.—Composition for Pavements.—C. B. Harris, New York city. Antedated February 25, 1870. 112,340.—Spring for Vehicles.—John R. Hiller, Woodland, Cal. 112,341.—Harvester Rake.—S. T. Holly, (assignor to John P. Manny), Rockford, Ill. 112,342.—Door Clamp.—Henry O. Hooper, Diamond Springs, Cal. 112,343.—Taper Holder.—Thomas W. Houchin, Morrisania, N. Y. 112,344.—Metallic Garter.—Henry A. House, Bridgeport, Conn. 112,345.—Bobbin Winder.—Henry A. House, Bridgeport, Conn. 112,346.—Method of Knitting Stockings, etc.—Henry A. House, Bridgeport, Conn. 112,347.—Apparatus for Evaporating and concentrating Liquids.—John Howarth, Salem, Mass. Antedated March 1, 1871. 112,348.—Apparatus for Evaporating and Concentrating Liquids.—John Howarth, Salem, Mass. Antedated March 1, 1871. 112,349.—Apparatus for Removing Oil from Vegetable and other Matters.—Elias S. Hutchinson, Baltimore, Md. 112,350.—Apparatus and Process for Removing Oil from Grain, Seeds, etc.—Elias S. Hutchinson, Baltimore, Md. 112,351.—Chandelier.—Charles F. Jacobsen, New York city. 112,352.—Culinary Vessel.—Carrie Jessup, New Haven, Conn. 112,353.—Machine for Cutting Leather.—Aberdeen Keith, North Bridgewater, Mass. 112,354.—Attaching Knobs to their Spindles.—John F. Keller and Nathaniel Sehner, Hagerstown, Md. 112,355.—Miter Machine.—T. E. King, Boston, Mass. 112,356.—Take-up for Corset Looms.—Julius Kuttner, New York city. 112,357.—Elevator and Carrier.—T. W. Lackore, Worth, Ill. 112,358.—Apparatus for Burning Hydrocarbon Oils.—James R. Lee, Grass Valley, Cal. 112,359.—Burglar Alarm.—Robert Lee, Cincinnati, Ohio. 112,360.—Telegraph Apparatus.—L. T. Lindsey, Jackson, Tenn. 112,361.—Harvester.—J. P. Manny, Rockford, Ill. 112,362.—Harvester.—J. P. Manny, Rockford, Ill. 112,363.—Harvester Rake.—J. P. Manny, Rockford, Ill. 112,364.—Cheese Curd Sink.—H. C. Markham, Collinsville, N. Y. 112,365.—Mowing Machine.—H. C. Markham and Dewitt C. Markham, Collinsville, N. Y. 112,366.—Propeller.—Alex. J. Marshall, Warrenton, Va. Antedated March 3, 1871. 112,367.—Oiler.—Edward McDuff and E. D. Forrow, Warwick, R. I. 112,368.—Wash Boiler.—John McInnes, Oxford, Pa. 112,369.—Propelling Canal Boats.—H. B. Meech, Fort Edward, N. Y. Antedated February 25, 1871. 112,370.—Water-proof Compound for Coating Cloth Wood, Metals, etc.—Peter E. Minor, Schenectady, N. Y. 112,371.—Cooking Stove.—W. N. Moore, Neenah, Wis. 112,372.—Boring Machine.—J. H. Pardieck (assignor to himself and S. M. Brown), Acton, Ind. 112,373.—Vapor Burner.—R. W. Park, Philadelphia, Pa. 112,374.—Machine for Pointing Blanks for Cultivator Teeth.—John Pedder and George Abel, West Pittsburgh, Pa. 112,375.—Bale Tie.—J. E. Perkins, San Francisco, Cal. 112,376.—Lining Walls with Felt, etc.—James Phillips, Chicago, Ill. 112,377.—Cooking Stove.—Samuel Pierce, Boston, Mass. 112,378.—Tack.—A. A. Porter, New Haven, Conn. Antedated Feb. 25, 1871. 112,379.—Machine for Shaping and Cutting Gear Cutters.—F. A. Pratt (assignor to the Pratt & Whitney Company), Hartford, Conn. 112,380.—Combination Camera and Developing Box.—E. C. Ratzell, Philadelphia, Pa. 112,381.—Punching Machine.—J. C. Rhodes, South Abington, Mass. 112,382.—Washing Machine.—J. W. Ricker, Chelsea, Mass. 112,383.—Curtain Fixture.—Charles Robin. Chester, Conn. 112,384.—Machine for Making Printers' Leads.—Isaac Schoenberg, New York city. 112,385.—Slide Valve for Steam Riveting Machines.—Coleman Sellers (assignor to William Sellers & Co.), Philadelphia, Pa. 112,386.—Machine for Polishing Thread.—Samuel Semple, Sr., John Semple, Samuel Semple, Jr., and R. A. Semple, Mount Holly, N. J. 112,387.—Paint Brush.—F. S. Shearer, Washington, Ill. 112,388.—Bee Hive.—S. A. Short, F. J. Short, J. B. Short, and Jasper Kile, Decatur, Ala. 112,389.—Apparatus for Removing Oil from Vegetable and other Matter.—Thomas Sim, Baltimore, Md. 112,390.—Retort for Producing Bisulphide of Carbon.—Thomas Sim, Baltimore, Md. 112,391.—Utilizing the Silky Down of the Wild Cotton. —M. H. Simpson, Boston, Mass. 112,392.—Pruning Shears.—Frank Smiley, Batavia, N. Y. 112,393.—Water-closet Valve.—A. J. Smith, San Francisco, Cal. 112,394.—Gang Plow.—J. W. Sursa, San Leandro, Cal. 112,395.—Grinding Pan and Amalgamator.—W. H. Thoss, West Point, Cal. 112,396.—Street Lantern.—Augustus Tufts, Malden, Mass. 112,397.—Cooking Stove.—Alvin Warren, Swanton, Ohio. 112,398.—Safety Bridle.—James Weatherhead, San José, Cal. 112,399.—Fire Grate.—George Wellhouse, Akron, Ohio. 112,400.—Hay Knife.—G. F. Weymouth, Dresden, Me. 112,401.—Claw Bar.—Charles Winter, Chillicothe, Ohio. 112,402.—Steam Generator.—J. C. Woodhead, Pittsburgh, Pa. 112,403.—Animal Trap.—W. D. Wrightson, Queenstown England. 112,404.—Brush.—John Ames, Lansingburg, N. Y. 112,405.—Clod Fender.—F. L. Bailey, Freeport, Ind. 112,406.—Ruler.—H. S. Ball, Spartanburg, S. C. 112,407.—Fanning Mill.—Benjamin Barney, Time, Ill. 112,408.—Ice-cutting Machine.—Lafayett Barnum (assignor to himself and A. R. Hale), Bridgeport, Conn. 112,409.—Manufacture of Ice.—T. J. Bigger, Kansas City, Mo. 112,410.—Machine for Heading Bolts and Spikes.—Reinhold Boeklen, Brooklyn, N. Y., assignor to himself and Henry Torstrick New York city. Antedated Feb. 28, 1871. 112,411.—Washing Machine.—Joseph Boswell, L. M. Boswell, Jonathan Palmer, and J. H. James (assignors to themselves and Thomas Starbuck), Wilmington, Ohio. 112,412.—Water Wheel.—E. C. Boyles, New York city. 112,413.—Cotton Press.—R. M. Brooks, Pike county, Ga. 112,414.—Paper-cutting Machine.—Samuel Brown (assignor to himself and C. R. Carver), Philadelphia, Pa. 112,415.—Governor for Direct-acting Engines.—A. S. Cameron, New York city. 112,416.—Governor for Direct-acting Engines.—A. S. Cameron, New York city. 112,417.—Butt Hinge.—J. W. Carleton (assignor to the Union Manufacturing Co.), New Britain, Conn. 112,418.—Machine for Cutting Sheet Metal.—C. R. Choate, East Saginaw, Mich. 112,419.—Bit Brace.—William Cleveland, Lawrence, Mass., assignor to himself and James Swan, Seymour, Conn. 112,420.—Steam Engine Governor.—C. A. Condé, Indianapolis, Ind. 112,421.—Carpet-cleaning Machine.—J. C. Craft (assignor to himself and Antonio Rosello), Baltimore, Md. 112,422.—Steam Regulator for Paper Dryers.—Daniel Crosby, Hampden, Me. 112 423.—Metallic Piston and Valve Rod Packing.—G. M. Cruickshank, Providence, R. I. 112,424.—Grain-thrashing and Separating Machine.—John Culham, Grand Rapids, Mich. Antedated Feb. 25, 1871. 112,425.—Cooking Stove.—David Curtis, Mishawaka, assignor to himself and C. B. Graham, South Bend, Ind. 112,426.—Lightning Rod.—S. D. Cushman, New Lisbon, Ohio. 112,427.—Hose Bridge.—Patrick Daily (assignor to himself and J. J. Kehoe), New York city. 112,428.—Cover for Openings in Sidewalks.—William Dale, New York city. 112,429.—Rotary Pump.—F. O. Deschamps, Philadelphia, Pa. 112,430.—Machine for Cutting Files.—James Dodge, Manchester, England, assignor to David Blake, Spencertown, N. Y. 112,431.—Coupling for Railway Cars.—Henry Dubs and S. G. Goodall-Copestake, Glasgow, Great Britain. 112,432.—Tobacco Pipe.—P. J. Dwyer, Elizabethport, N. J. 112,433.—Basket for House Plants.—Albert P. Eastman, Washington, D. C. 112,434.—Sulky Plow.—Milo A. Elliott, Stratford Hollow, N. H. 112,435.—Stretcher for Paintings.—James Fairman, New York city. 112,436.—Body Lantern Holder.—Samuel C. Fessenden, Stamford, Conn. 112,437.—Stove Leg.—Amon L. Finch, Sing Sing, N. Y. 112,438.—Pump Piston.—John S. Follansbee and George Doolittle (assignors to the Forrester Manufacturing Company), Bridgeport, Conn. 112,439.—Shoe.—Samuel W. Francis (assignor to himself and W. H. Newton), Newport, R. I. 112,440.—Guard-Finger for Harvesters.—George Fyfe and Chester Hard, Ottawa, Ill. 112,441.—Dining Table.—S. R. Gardner (assignor to himself and S. M. Marquette), Independence, Iowa. 112,442.—Step Ladder.—M. Boland Geary, New York City. 112,443.—Oilcloth Printing Machinery.—Ebenezer A. Goodes (assignor to Philadelphia Patent and Novelty Company), Philadelphia, Pa. 112,444.—Tenoning Machine.—Lyman Gould, Norwich, Conn. 112,445.—Printer's Case.—Wm. H. A. Gresham, Atlanta, Ga. 112,446.—Lamp Chimney.—Geo. W. Griswold, Factoryville, Pa. 112,447.—Grain Separator.—Philander Griswold, Hudson, Mich. 112,448.—Clamp for Thill Couplings.—John W. Guider (assignor to himself and John Kiefer), St. Joseph, Mo. 112,449.—Bird Cage.—Gottlob Gunther, New York city. 112,450.—Stop Cock and Valve.—William Haas, New York city. 112,451.—Valve for Steam Engines.—Joseph L. Harley, Baltimore, Md., and Xaver Fendrich, Georgetown, D. C. 112,452.—Metallic Hub.—John H. Harper, Pittsburgh, Pa. 112,453.—Composition for Lubricating Machinery.—E. Q. Henderson (assignor to John C. Burroughs and Richard A. Springs) Charlotte, N. C. 112,454.—Post-hole Digger.—Bryant B. Herrick, Decatur, Mich. 112,455.—Door Check.—Levi S. Hicks (assignor to himself, J. Perrin Johnson, and John Buell), Peoria, Ill. 112,456.—Railway-car Brake.—Luther Hill, Stoneham, and Seth D. Tripp, Lynn, Mass. 112,457.—Truss.—Adam Hinoult, Montgomery, N. Y. 112,458.—Feed Bag for Horses.—Walter A. Hough, South Butler, N. Y. 112,459.—Shade Holder for Lamps—Mark W. House, Cleveland, Ohio. 112,460.—Lamp Chimney.—Mark Wiggins House (assignor to the Cleveland Non-Explosive Lamp Company), Cleveland, Ohio. Antedated March 1, 1871. 112,461.—Horse Hay Rake.—James Howard and E. T. Bousfield, Bedford, England. 112,462.—Tongs for Rolling Barrels.—Mark W. Ingle, Indianapolis, Ind. 112,463.—Pitman.—George W. Jayson, Lodi, Ohio. 112,464.—Paste for Paper Hangings.—John Jones (assignor to himself and Henry A. Smith), New York city. 112,465.—Twine Holder.—Edward M. Judd, New Haven, Ct. 112,466.—Clothes Pin or Clasp.—Amos L. Keeports and William Yount, Littletown, Pa. 112,467.—Putting up Hams.—Samuel Edward Kelly, Philadelphia, Pa. 112,468.—Limn Kiln.—Thomas A. Kirk, Kansas City, Mo. 112,469.—Fastening for Seats for Wagons or Sleighs.—John G. Knapp and John F. Robertson (assignors of one third their right to James H. Holly), Warwick, N. Y. 112,470.—Potato Planter.—George Knowlton (assignor for one-half his right to N. Haynes), Johnstown, Pa. 112,471.—Revolving Firearm.—Edwin S. Leaycroft, Brooklyn, N. Y., assignor by mesne assignment, to "Colt's Patent Firearms Manufacturing Company," Hartford, Conn. 112,472.—Revolving Firearm.—Edwin S. Leaycroft, Brooklyn, N. Y., assignor, by mesne assignment, to "Colt's Patent Firearms Manufacturing Company," Hartford, Conn. 112,473.—Railroad Cattle-Guard Gate.—J. H. Mallory, La Porte, Ind. 112,474.—Back-reflecting Mirror.—Richard Mason (assignor to himself and Matthew Ely), Newark, N. J. 112,475.—Ventilator and Chimney Top.—James McGowan (assignor to himself and Daniel H. Waring), New York city. 112,476.—Apparatus for Rectifying and Refining Spirits.—Frederick Measey (assignor to himself and Henry D. Fling), Philadelphia, Pa. 112,477.—Tin Can.—John F. Merrill (assignor to himself and Alexander Stewart), Cincinnati, Ohio. 112,478.—Take-up Mechanism for Looms.—John Michna and Joseph Fischer, New York city. 112,479.—Combined Baker and Broiler.—Wm. H. Miller, Brandenburg, Ky. 112,480.—Shuttle for Sewing Machines.—James D. Moore, Grinnell, Iowa. 112,481.—Cotton Chopper and Grain Cultivator.—Daniel Mosely, Osark, Arkansas. 112,482.—Sad and Fluting Iron.—Frederick Myers, New York city. 112,483.—Reed for Organs and Melodeons.—Augustus Newell, Chicago, Ill. 112,484.—Straw Cutter.—Amon Park, Germanville, Iowa. 112,485.—Apparatus for Aging Whisky and Other Spirits.—Josiah Peiffer and Samuel Richards, Valonia, Pa. 112,486.—Combined Cotton and Corn Planter.—Louis A. Perrault (assignor to himself and Joseph Huber), Natchez, Miss. 112,487.—Faucet.—Solomon Pfleger, Reading, assignor to himself and J. S. Pfleger, Tamaqua, Pa. 112,488.—Treadle.—George K. Proctor, Salem, Mass. 112,489.—Lubricating Compound.—Victory Purdy, Poughkeepsie, N. Y. 112,490.—Fertilizer and Seeding Machine.—Archibald Putnam (assignor to Elizabeth Putnam), Owego, N. Y. 112,491.—Rotary Pump.—George W. Putnam, South Glens Falls, N. Y. 112,492.—Hat Brush.—Robert Dunbar Radcliffe, Palmyra, N. Y. 112,493.—Refrigerating Show Case.—Thomas L. Rankin, Lyndon, Kansas, assignor to himself and D. W. Rockwell, Elyria, Ohio. 112,494.—Device for Starting and Stopping Cars.—Philip Rhoads, Carlisle, Pa. 112,495.—Pipe-molding Machine.—George Richardson, Milwaukee, Wis. 112,496.—Sulky Cultivator.—Richard B. Robbins, Adrian, Mich. 112,497.—Hand Plow.—Nelson Rue, Harrodsburg, Ky. 112,498.—Mechanical Movement.—Edward G. Russell, Ravenna, Ohio. 112,499.—Railway Car Brake.—Lyman Alphonzo Russell, Shrewsbury, Vt. 112,500.—Stovepipe Cleaner.—David Sanford, Ashton, Ill. 112,501.—Twine Holder.—Joseph B. Sargent and Purmont Bradford (assignors to Sargent & Co.), New Haven, Conn. 112,502.—Dovetailing Machine.—James M. Seymour, Newark, N. J. 112,503.—Wooden Pavement.—Eaton Shaw, Portland, Me. 112,504.—Guard for Circular Saws.—George W. Shipman, Ischua, N. Y. 112,505.—Breech-loading Firearm.—Dexter Smith and Martin J. Chamberlin, Springfield, Mass. 112,506.—Spark Arrester.—James Smith, Altoona, Pa. 112,507.—Horse Hay Rake.—Solomon P. Smith, Waterford, N. Y. 112,508.—Plow.—S. M. Stewart, New Harrisburg, Ohio. 112,509.—Medical Compound for Treating Fever and Ague.—George E. Swan, Mount Vernon, Ohio. 112,510.—Device for Cooling Journals of Car Axles.—Henry G. Thompson, Milford, Conn. 112,511.—Cooling Journal of Car Axles.—Henry G. Thompson, Milford, Conn. 112,512.—Cooling Journal of Car-wheel Axles.—Henry G. Thompson, Milford, Conn. 112,513.—Device for Cooling Journals of Railway Cars.—Henry G. Thompson, Milford, Conn. 112,514.—Non-heating Handle for Sad Irons, etc.—William H. Towers, Boston, Mass. 112,515.—Lubricator.—John Erst Uhl, Renovo, Pa. 112,516.—Combined Corn Planter and Cultivator.—Franklin Underwood, South Rutland, N. Y. 112,517.—King Bolt.—Wendel Vondersaar, Indianapolis, Ind. 112,518.—Wheat Roaster.—George W. Waitt (assignor to himself and Robert B. Fitts), Philadelphia, Pa. 112,519.—Plaster Sower.—Thomas J. West, Alfred Center, N. Y. 112,520.—Ticket Holder.—Henry Wexel, Providence, R. I. 112,521.—Tobacco Press.—Abraham N. Zell, Lancaster, Pa. 112,522.—Combined Bag Holder and Scales.—William Zimmerman, Lebanon, Pa. Antedated February 25, 1871. 112,523.—Breech-loading Firearm.—James M. Mason, Washington, D. C. About HackerNoon Book Series: We bring you the most important technical, scientific, and insightful public domain books. This book is part of the public domain. Various (2006). Scientific American, Volume XXIV., No. 12, March 18, 1871. Urbana, Illinois: Project Gutenberg. Retrieved https://www.gutenberg.org/cache/epub/19180/pg19180-images.html This eBook is for the use of anyone anywhere at no cost and with almost no restrictions whatsoever. You may copy it, give it away or re-use it under the terms of the Project Gutenberg License included with this eBook or online at , located at . www.gutenberg.org https://www.gutenberg.org/policy/license.html

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