Basetwo

basetwo

Boosting Product Discovery With UX Research: Lessons From Retail and Banking

How Etherspot Redefines The Way We Build Ethereum Smart Contracts (Account Abstraction)

ইথারস্পট কীভাবে আমরা ইথেরিয়াম স্মার্ট চুক্তি তৈরি করি তা পুনরায় সংজ্ঞায়িত করে (অ্যাকাউন্ট বিমূর্ততা)

Wie Etherspot die Art und Weise neu definiert, wie wir Ethereum-Smart-Contracts erstellen (Kontoabstraktion)

Cómo Etherspot redefine la forma en que construimos contratos inteligentes de Ethereum (abstracción de cuenta)

Comment Etherspot redéfinit la façon dont nous construisons les contrats intelligents Ethereum (abstraction de compte)

इथरस्पॉट किस तरह से एथेरियम स्मार्ट कॉन्ट्रैक्ट बनाने के तरीके को फिर से परिभाषित करता है (खाता सार)

Etherspot が Ethereum スマート コントラクトの構築方法をどのように再定義するか (アカウントの抽象化)

Etherspot이 Ethereum 스마트 계약 구축 방식을 재정의하는 방법(계정 추상화)

Como o Etherspot redefine a maneira como construímos contratos inteligentes Ethereum (abstração de conta)

Как Etherspot меняет подход к созданию смарт-контрактов Ethereum (абстракция аккаунта)

Etherspot, Ethereum Akıllı Sözleşmeleri Oluşturma Yöntemimizi Nasıl Yeniden Tanımlıyor (Hesap Soyutlaması)

Cách Etherspot xác định lại cách chúng tôi xây dựng hợp đồng thông minh Ethereum (Tóm tắt tài khoản)

Etherspot 如何重新定义我们构建以太坊智能合约的方式（账户抽象）

Authors: (1) Ruohan Zhang, Department of Computer Science, Stanford University, Institute for Human-Centered AI (HAI), Stanford University & Equally contributed; zharu@stanford.edu; (2) Sharon Lee, Department of Computer Science, Stanford University & Equally contributed; zharu@stanford.edu; (3) Minjune Hwang, Department of Computer Science, Stanford University & Equally contributed; zharu@stanford.edu; (4) Ayano Hiranaka, Department of Mechanical Engineering, Stanford University & Equally contributed; zharu@stanford.edu; (5) Chen Wang, Department of Computer Science, Stanford University; (6) Wensi Ai, Department of Computer Science, Stanford University; (7) Jin Jie Ryan Tan, Department of Computer Science, Stanford University; (8) Shreya Gupta, Department of Computer Science, Stanford University; (9) Yilun Hao, Department of Computer Science, Stanford University; (10) Ruohan Gao, Department of Computer Science, Stanford University; (11) Anthony Norcia, Department of Psychology, Stanford University (12) Li Fei-Fei, 1Department of Computer Science, Stanford University & Institute for Human-Centered AI (HAI), Stanford University; (13) Jiajun Wu, Department of Computer Science, Stanford University & Institute for Human-Centered AI (HAI), Stanford University. Table of Links Abstract & Introduction Brain-Robot Interface (BRI): Background The NOIR System Experiments Results Conclusion, Limitations, and Ethical Concerns Acknowledgments & References Appendix 1: Questions and Answers about NOIR Appendix 2: Comparison between Different Brain Recording Devices Appendix 3: System Setup Appendix 4: Task Definitions Appendix 5: Experimental Procedure Appendix 6: Decoding Algorithms Details Appendix 7: Robot Learning Algorithm Details Appendix 3: System Setup The robot we use in our tabletop manipulation task is a standard Franka Emika robot arm with three RealSense cameras. For mobile manipulation, we use a Tiago++ model from PAL Robotics, with an omnidirectional base, two 7-degrees-of-freedom arms with parallel-yaw grippers, a 1-degree-of-freedom prismatic torso, two SICK LiDAR sensors (back and front of the base), and an ASUS Xtion RGB-D camera mounted on the robot’s head, which can be controlled in yaw and pitch. All sensors and actuators are connected through the Robot Operating System, ROS [74]. The code runs on a laptop with an Nvidia GTX 1070 that sends the commands to the onboard robot computer to be executed. Robot platform. A list of primitive skills along with their parameters can be found in Table 6, eight for Franka (16 tasks) and five for Tiago (four tasks). Human users can accomplish all 20 tasks, which are long-horizon and challenging, using these skills. Primitive skills list. This paper is under CC 4.0 license. available on arxiv

NOIR: Neural Signal Operated Intelligent Robots for Everyday Activities: Appendix 3

THE FIRST VISION

A BIT OF A BACKGROUND Many of you know of my first post on this topic that was back in 2018/2019 when I had just started with my journey which still continues but I have more to share in this update (and I hope you will like it). At that time we had a good number of resources and the divide between and non- related resources were not so to have discussions about — since then things have changed, let’s see what the landscape looks like. Two years in the life of AI, ML, DL and Java Java Java I’m hoping that I’m able to share richer aspects of my journey, views, opinions, observations and learnings this time around as compared to . my previous summary post I do admit that this is only a summary post and I intend to write more specific and focussed posts like the ones I did in 2019 (see the following section) — I have earmarked a couple of topics and I will flesh them out as soon as I’m happy with my selections. 2019: YEAR OF BLOGS Looking at my activities in 2019 towards 2020, I can say I was more focussed on writing blogs and creating a lot of hands-on solution which I shared via my projects on GitHub and blogs on Medium. Here is a list of all of them: August 2019: How to build Graal-enabled JDK8 on CircleCI? August 2019: How to do Deep Learning for Java? September 2019: Running your JuPyTeR notebooks on the cloud October 2019: Running Apache Zeppelin on the cloud November 2019: Applying NLP in Java, all from the command-line November 2019: Exploring NLP concepts using Apache OpenNLP December 2019: Exploring NLP concepts using Apache OpenNLP inside a Java-enabled Jupyter notebook 2020: YEAR OF PRESENTATIONS Similarly in 2020, from a blogging point-of-view I didn’t write much, this officially my first proper post of the year  (with the exception of one in August 2020, which you will find below) — I was quite busy with preparing for talks and presentations and online meetings and discussions. I kicked off the year with my talk at the conference in London, UK. So let me list them here so you can take a look at them in your own time: Grakn Cosmos 2020 February 2020: at conference Naturally, getting productive, my journey with Grakn and Graql Grakn Cosmos 2020 July 2020: at conference “nn” things every Java Developer should know about AI/ML/DL JOnConf 2020 August 2020: on meet up From backend development to machine learning Abhishek Talks(YouTube channel) August 2020: An Interview by Neural Magic: Machine Learning Engineer Spotlight (blog post) October 2020: at the NLP Zurich meet up Profiling Text Data October 2020: at conference Tribuo: an introduction to a Java ML Library MakeITWeek 2020 October 2020: at conference “nn” things every Java Developer should know about AI/ML/DL Oracle Groundbreakers Tour – APAC 2020 You can find slides (and videos of some) of the above presentations under the links provided. OTHER ACHIEVEMENTS AND ACTIVITIES THIS YEAR As to my journey, I have also been involved a good part of this year learning by online AI/ML competitions, see and post shared to learn more. You can also find all of my and for further study. Also the launch of an -based NLP Library called was another important feat for me this year. this this datasets notebooks Python NLP Profiler WHAT’S HAPPENING IN THIS SPACE? There is a lot of hype happening in the space and as rightly said during a conversation sometime back: And I think you will agree with me that we can relate to this situation. Also many of the things we are seeing look nice, and shiny but may NOT be fully ready for the real-world yet, I did cover similar arguments in a . There are few entities who are openly claiming various things about the not-so-bright-sides of AI, they are things like: Suyash Joshi “It’s easy to get sucked into hype and shiny new stuff I fell a lot for that and then get overwhelmed“. post in August (similar to the previous point) the statistical methods used are from the last century and may not be suited to modern day data(led by Nassim Taleb’ s school of thought)many modern-day open-source tools and industry methods to derive at solutions are broken or inadequatewe are not able to explain our predictions and findings(blackbox issue: explainability and interpretability)our AI solutions lack causality, intent and reasoning These come from individuals, groups and companies who are building their own solutions (mostly closed-source) as they have noticed the above drawbacks and doing things to overcome them but also making the rest of the world aware of it. WHERE IS JAVA ON THE MAP? Java has been contributing to the AI force since sometime now, all the way when there was a lot of talk during the Big Data buzz, which then transformed to the new buzz about AI, Machine Learning and Deep Learning. If we closely look at the categories and sub-categories of resources here: Apache Spark [1] | [2] Apache Hadoop and Deeplearning4J many other such tools, libraries, frameworks, and products and now more recently and (from the folks at behind all the ) grCuda graalPython Oracle Labs GraalVM magic DeepNetts Tribuo and more under these resources Java: AI/ML/DL NLP Java Tools and libraries (Java/JVM) some intriguing resources: or | or | or | or | or GitHub AI Artificial Intelligence ML Machine Learning DL Deep Learning RL Reinforcement Learning NLP Natural Language Processing [1] Nvidia and Apache Spark [2] Oracle Labs and Apache Spark You can already see various implementations using Java and other JVM languages — they have just not been noticed by us, unless we made an attempt to look for them. If you have been following the progress of (see ) in this space boosting server-side, desktop and cloud-base systems in terms of performance, ergonomic footprint and language interop — then you will, just like me also see that ’s presence and position is growing from strength-to-strength in this space. GraalVM and Truffle GitHub Java ( grCuda and graalPython are two such examples: see AI/ML/DL related resources on Awesome Graal and also at the appendix sections of  the talk slides for more resources — see section above for talks) SOME HIGHLIGHTS IN PICTURES RECOMMENDED RESOURCES If I had to go through many of the resources I have shared in this post so far, of all of them I would look at these topics (in no particular order and also not an exhaustive list, it’s still a lot of topics to learn and know about): | | | | | | | | | | | | | | | | | | | | | Bayesian Performance in Python Made With ML Virgilio Visualisation TVM: Compiler stack for CPUs, GPUs, etc… Hyperparameter tuning Normalising (and Standardising) a distribution Things to Know grCuda Running compiled and optimised AI Models in the Cloud Neural Magic: Model Pruning and Sparsification Train and Infer models via a native-image Genetic Algorithms by Eyal DeepNetts: Deep Learning in Java by Zoran NLP NLP with Java Graphs ML on Code/Program/Source Code Tribuo: A java-base ML library Chatbots talking to each other Testing My apologies as — I’m working on these topics and slowly gaining knowledge and experience and hence my urge to immediately share them with the rest of the community. I’ll admit few of these may be still — but I hope we can all learn these together. I’ll share more as I make more progress with them during the course of the days, weeks and months into 2021. YMMV Work in Progress CONCLUSIONS We are in a heterogenous space and AI/ML/DL ideas and innovations from creation to deployment go through various forms and shapes and depending on the comfort-zones and end-use cases of the ideas and innovations get implemented using multitudes of technologies. It won’t be correct or fair to say only one technology is being used. We are seeing R&D, rapid prototyping, MVP, PoC and the likes are being done using languages like , , , and the likes while when it comes to robust, reliable, scalable, production-ready solutions more serious contenders are chosen for encapsulating the original work. And and other languages, and the likes that can provide such stability are often being considered both for desktop and cloud implementations. Python R Matlab Julia Java JVM W earing my Oracle Groundbreaker Ambassador hat : I recommend taking advantage of the Free cloud credits from Oracle (also see this post )— the VMs are super fast and easy to setup(see my posts above). WHAT NEXT? The journey continues, the road may be long, but it’s full of learnings — that certainly helps us grow. Many times we learn at the turning points while the milestones keep changing. Let’s continue learning and improving ourselves. Please do feedback if you are curious to explore deeper aspects of what you read above, as you may understand the topic is wide and deep and one post cannot do full justice to such rich topics (plus many of them are moving targets). Previously published at https://www.javaadvent.com/2020/12/another-two-years-in-the-life-of-ai-ml-dl-and-java.html

2 Years In The Life Of AI, ML, DL And Java - Part II

The Essence of The Zoho vs. Freshworks [Deep Dive]

Exploration of Black Rock City, Burning Man 2017. Photo: Camille Betinyani 7 principles I wish I knew before quitting my job, about marketing, productivity, and self-awareness. ℹ️️ This article is a quick translation of “ ” ( ), and can be seen as complementary to “ ”. Feel free to read it non-linearly. Ce que j’ai appris en travaillant à mon compte pendant 2 ans 🇫🇷 12 months to become an Indie Hacker Two years ago, . I had an awesome job Eating out with Whyd’s team, a few months before quitting. As the of an ambitious startup company: . I was developing a B2C product blending two of my passions: music and technology. Every day, a 15-minute bike ride would take me back to my team, my friends. With them, I was never bored, and we laughed a lot! lead developer Whyd On top of that, I was paid well to do something I loved: . coding Nevertheless, I became envious of other developers who got rid of their bosses to do their own thing: indie hackers. I wanted to . After 4.5 years, I had gained enough confidence to quit and start my own business. So I did. work my own way and take my own decisions Two years later, I realise that . My understanding of work, of the value of what we produce, of their “users,” and about life and relationships in general. my understanding of the world has evolved Back then, I was self-confident, but also very . Now, I’m not that confident about anything at all — including myself — but I believe that the experience I’ve had during the last few months made me stronger and . naive wiser This is the kind of I would have loved to be given, back in 2015. advice Users are not unthankful. They are desperate. We’ve received hundreds of emails and tweets from people while using our product: “Whyd.” Because it was the result of hard work, and it was provided to users at no cost, I could not help thinking that these users were unthankful. complaining about bugs One of the principles from the excellent book “How to win friends and influence people,” by Dale Carnegie. After reading “ ,” I measured how naive I was. Rather than “unthankful”, Dale Carnegie advocates that people are simply . How to win friends and influence people self-centered Let’s put ourselves in a Whyd user’s shoes: everything they want is to . Whyd is just a solution among thousands. The user probably found Whyd thanks to our efforts towards growth. They got convinced by Whyd as a good solution for their need: to listen to music. So, when this solution does not work as promised, we can understand that the user is upset. By complaining, they don’t mean any harm against the team that developed Whyd, they manifest the of not being able to solve their need fully yet, despite their efforts and trust. listen to music marketing The user did not choose Whyd. deception Give before expecting to cash in. When I started as a consultant, towards clients. I feared to fail. To not make enough money. I feared that my clients would . I was insecure abuse my time and services without paying One of the I applied to secure my income was to brand myself as a “10x developer.” A super busy software engineer that works super fast by optimising his focus. With that , I strived to make my communication with clients and prospects more concise, pragmatic, and uncompromising. I do believe that I’m a good software engineer. But, in retrospect, I was mostly showing that I was a . Besides the risk of earning a bad reputation, adopting this posture can lead to picking opportunities for the wrong reasons. For instance, letting exciting missions go, in favour to missions proposed by clients that tolerated to play my game. It happened to me once: I accepted a mission that wasn’t really a good fit with my interests, just to stick to my values and . Was that a smart way to take decisions? strategies posture cold, unreassuring person to not lose face I that, in order to create quality relationships and build a better future for myself, I had to first, without expecting anything in return. By giving, I mean: to listen, to give advice, to suggest, to show, to share, or more generally, to help people. Besides making the world a better place, giving is a one’s quality, skills, and benevolence. The fact that I’m writing this article and publishing it publicly is a good example. The idea of publishing useful information is also the basis of “ .” learned give more great way to demonstrate content marketing A few months after having given strategic advice to young startup creators, I had the surprise of receiving an email from one of them. He was telling me that he had launched his startup, that it was developing well, and that my advice had helped him a lot in that process. I was so to read from him, and to read that my advice was useful, that it cleared every trace of guilt I was feeling for not having found a way to charge him and/or other creators I had met at that time. In retrospect, I had just offered him some advice (that was obvious for me), while drinking a few beers. But, for him, this meeting apparently had a lot of value. Thinking about it, I’m glad I indirectly to the birth of a new startup, and I’m flattered that its creator remembers and values the help I gave him. Anecdote: happy contributed It works the other way round, as well: people like to be helpful. The secret is to call a favour “a favour.” I’ve seen too many people (including myself) awkwardly saying “ ” Most times, they were expecting a favour without actually asking it as a favour. Try being more clear and direct when asking favours: pick fewer people, choose them mindfully, and don’t forget to explain how their help will help you. You’ll see that people will be delighted to help! Pro tip: feel free to… Monetising a product takes more than visibility. When I started working on my own products, I was convinced that was not going to be too painful, thanks to my experience developing B2C web apps , and the of my product ideas. Leveraging ProductHunt and my social network, I succeeded in getting on my first product, within 10 months after launch. making a profit efficiently pragmatism 10000 users My first product, installed by 10,000 users: Next Step for Trello I was very proud of what I had built. The of usefulness, product quality, design simplicity and efficient engineering. A developer’s wet dream. perfect balance But I realised that asking people to was not as easy as I had thought. Probably because I had relied too much on my own vision and intuitions to develop this product. I had pushed my vision to a crowd, instead of (or a need) of a pack of users. pay for premium features solving a problem By reading Justin Jackson’s articles, I understood that I was . Justin often insists on the idea that, in order to make dollars, a product must be designed to to its users. For instance: in order to reduce carbon footprint, Telsa do not market their cars as ecological cars. Rather, they sell “high tech”, high performance cars. Cars that people . Buyers are not looking for an ecological car, they want to of drivers who live on the edge of technology. This explains why Tesla integrated the “Insane Mode,” making their cars accelerate from 0 to 60 mph in just 3 seconds. lacking basic marketing knowledge give “super powers” desire to buy be part of a minority It’s become clear that my first product does not give super powers to anybody. So the best I can do is to get to know its users, to better , then to help them fulfill them. understand their needs : A few weeks after launch, I sent a survey to my users. I asked them what would make my product really indispensable for their everyday use, and how much they would be happy to pay for this. The results convinced me to launch a crowdfunding campaign to develop a second version of my product, based on the most popular feature requests. At the end, only three users agreed to participate, and the campaign failed. My advice: survey results are overly optimistic. The decision is not fully made until the user sent their payment. I tested for you Marketing: “everybody” is not a target. Too many startups hope for press coverage on Techcrunch or spam their contacts to get more . Yes, it does feel good to have your product loved by thousands of people, right after launching it! But is early fame a good thing for your business? votes on ProductHunt Being an advocate of the philosophy, I know that it’s important to increase a product’s retention (i.e. reach a level of quality that makes their users keep using it over time) before trying to optimise acquisition (i.e. growing the user base). I did apply these principles while developing my first product. But I had underestimated the importance of . I had no idea who my users were, and what kind of value they were running after. So how could I ever sell anything to them? Lean Startup talking to my users individually In retrospect, I had better pick a more specific target. Yes, targeting a “niche” means having fewer potential users. But, by getting to know them better, I would have built a product that was for them. So, this would have hopefully resulted in . better tailored more sales Sure, this kind of communication is not scalable. But doing this manually would have made users trust me more, thus increase . And loyal users are more likely to recommend my product to their colleagues, resulting in a better, more organic . retention growth Multilingual creators, this reflection also applies to the language you decide to use when communicating online. When I share stuff in English, I can reach a global audience. When I share in French, my audience is way smaller, but it results in more opportunities, at least in the short term, because most of my network is more attentive to communications in French, and people from my network trust me more than random people from my global audience. Note: Wording: use keywords that your target searches for. On my first product’s landing page, I did my best to pick precise keywords. I wanted to explain my vision clearly, and its features concisely. My objective was to make a of my project, for visitors. “high fidelity” description I had forgotten something important: how would visitor find my page? What would they type on Google in order to find it, while looking for solutions to their problems? keywords A famous quote from Henry Ford about what people need VS how people express their need. After reading Clifford Oravec and Justin Jackson, I understood that there were at least two kinds of behaviours to expect from potential users: Simple case: a potential user that searches for a solution by picking keywords that . Example: “ ” best describe their problem fix broken windshield Complex case: a potential user imagines a solution to their problem — to the best of their knowledge — and searches for it by picking keywords that to the problem. Example: “ ” best describes their imaginary solution adhesive patch for windshield In order to increase the odds of both kinds of users to find my product, I need to build (a) landing page(s) that contain keywords corresponding to the — as expressed by “simple case” potential users — and to as they could be expressed by “complex case” potential users. problem solutions To reach and convert more potential users, it is important to put ourselves , and determine what keywords they may use to find our landing page(s). well is essential. (as seen in the previous part) in their shoes Knowing your target When in doubt: avoid regret, take risks. Now that we’ve talked about product users and marketing, I’d like to share what I learned at a more personal level . As a very rational person, I tend to list pros and cons before deciding anything. My level of indecision is so high that even the thought of having to choose what to buy in a clothing store makes me sweat! Risk aversion probably made me miss many to evolve professionally and personally. Especially during my entrepreneurial period. Bummer! opportunities It’s back from the trip at the end of my entrepreneurial period that I took the : I accepted to hold an 8-hour workshop in a school I had never taught at, with just a 24-hour notice! Why was this ? I had never physically given a course about “Lean Management” before, and I had got no course material to rely on. Over the last 18 months, this experience ended up being one of the ones! biggest risk of the last 18 months risky most exciting and rewarding : It’s important to keep reflecting, learn and be curious, but it’s even more important to not wait “ ” before going ahead with an exciting project. Challenges allow us to push our limits forward, or at least, to be able to discover what are our real limits. Following your gut feeling makes you feel alive, and evolve. Take-away to be ready Perfection does not exist. But regret definitely does. Between pleasure and efforts: the quest of Flow Let’s end this article with an experience that was a success and a failure at the same time: . the optimisation of my productivity routine Web products usually take months before showing any sign of success. Because my time was limited by my financial savings, I had decided to . For that, I had developed a task planning and tracking system relying on a Trello board + a list of measurable objectives + a well-filled calendar every week + frequent retrospectives. My goal was to work as as possible. develop multiple projects simultaneously efficiently This screenshot shows the level of I was reaching every week: planning A typical week during my entrepreneurial period. Each 4-letter prefix refers to one of my projects. After of use of this productivity system, I can confirm that it is effective. I developed a dozen of projects, published my results regularly and efficiently. Even my friends were asking me for productivity advice! one year That being said, this routine ended up turning me into some kind of . Now that I let go from my objectives and strict time management rules, I feel like I’m breathing again after a long suffocation. mechanical zombie I did probably not leave enough space to serendipity. Enough time for my brain to process. And enough listening to the moods and desires I was feeling at all times. I would not recommend anyone to apply such a strict time management routine for more than 6 months in a row. Moreover, while I was having a lot of fun working on some of my tasks, others were me: tasks that relied on knowledge or experience I did not have (e.g. .) draining Marketing A representation of “Flow” If I was to create a business again, I would spend less than 20% of my time on this kind of tasks, in order to spend more time in “ ”: this state of immersion and pleasure that we feel when we’re working on something that is . In my case: programming and writing. flow challenging and mastered at the same time : I’m glad I was able to achieve that much is that little time. I’m also relieved to turn this page, in which I was too concerned about being efficient, and not enough about being connected to the real world, and to myself. As Sean McCabe advises: working on a too broad range of topics causes confusion for oneself and their network. Clarity and focus enable more relevant and exciting opportunities. In retrospect Conclusion and perspectives Writing this article helps me to : a period during which I had challenged myself to develop and commercialise my own products, by myself. It’s also of what I’ve learned during this period. turn an important page of my life a trace I also wanted to testify that following the “ ” route does . The many success stories I had read gave me the . It’s definitely not. Indie Hacker not necessarily lead to success impression of an easy path You may feel sorry for me. Please don’t. I take the end of that entrepreneurial experience as an to start a new life, with fewer dead-ends to explore and a more solid mindset. I’m grateful for having been able to live this experience. And I’m excited about the next chapter of my life, now that about business, and about myself. exciting occasion I’ve become more knowledgeable Thanks for reading! 😊

What I learned while working as an indie developer for 2 years

How I Built an AI Programmer to Automate GitHub Issue Fixes 🤯

গিটহাব ইস্যু ফিক্সগুলি স্বয়ংক্রিয় করার জন্য আমি কীভাবে একটি এআই প্রোগ্রামার তৈরি করেছি 🤯

Wie ich einen KI-Programmierer zur Automatisierung der Behebung von GitHub-Problemen entwickelt habe 🤯

Cómo construí un programador de inteligencia artificial para automatizar la solución de problemas de GitHub 🤯

Comment j'ai construit un programmeur d'IA pour automatiser les résolutions de problèmes GitHub 🤯

मैंने GitHub समस्या समाधान को स्वचालित करने के लिए एक AI प्रोग्रामर कैसे बनाया 🤯

GitHub の問題修正を自動化する AI プログラマーの構築方法 🤯

GitHub 문제 수정을 자동화하기 위해 AI 프로그래머를 구축한 방법 🤯

Como desenvolvi um programador de IA para automatizar correções de problemas do GitHub 🤯

Как я создал программатор искусственного интеллекта для автоматизации исправления проблем на GitHub 🤯

GitHub Sorun Düzeltmelerini Otomatikleştirmek için Nasıl Bir Yapay Zeka Programcısı Oluşturdum 🤯

Cách tôi xây dựng một lập trình viên AI để tự động sửa lỗi GitHub 🤯

我如何构建 AI 程序员来自动修复 GitHub 问题

Machine Learning: Your Ultimate Feature Selection Guide Part 2 - Select the Real Best

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 Frost Plant of Russia. here The Frost Plant of Russia. To the Editor of the Scientific American: Mr. Charles Williams, of Winoa, Ohio, has written a letter to that veteran botanist, Humphrey Marshall, of Chester county, Pa., on the subject of the abovenamed plant, and my opinion concerning it has been asked for. Seeds of this plant were obtained by citizens of Boston, who had snow brought from the White Mountains and from the coast of Labrador, and who stated that they have "now the most unbounded satisfaction and pleasure of announcing that all signs are favorable to the realization of their fondest hopes." This wonderful plant, it seems, was found amid the perpetual snows of the northern boundaries of Siberia, in 1863, by Count Swinoskoff, the eminent Russian botanist, and it was by him cultivated at St. Petersburgh. The account sent me is very vague, and is evidently not from the pen of a botanist. It is stated that it comes forth on the first day of the year, grows to the height of three feet, and flowers on the third day. It continues in bloom for twenty-four hours, then dissolves itself, being of the finest snow; it has a stalk one inch in diameter, and leaves, three in number, 1½ inches wide, covered with infinitesimal frost or snow cones. The flower is of the shape of a star, with petals 3 inches long and ½ inch wide at the broadest part, forming a basketwork of frost. The seeds are like a pin's head. This is about all that can be gleaned from the description, and is by no means satisfactory. Allow me to present my humble views of an analogous discovery of frostwork on December 6, 1856, in a sandy loam in Chester county, Pa., near the Paoli monument. In the of Philadelphia, then edited by J. Jay Smith (New Series, volume vii., page 73, 1857), an account was published of my observations then. These I have since more fully confirmed. The common dittany (cunila Mariana) is frequently met with in December, with the base of the stem surrounded with shellwork of ice, of a pearly whiteness. Dr. Darlington, in his "Flora Cestrica" published in 1853, page 199, under the article cunila, observes: "In the beginning of winter, after a rain, very curious ribbons of ice may be observed, attached to the base of the stems, produced, I presume, by the moisture of the earth rising in the dead stems by capillary attraction, and then being gradually forced out horizontally, through a slit, by the process of freezing. The same phenomenon has been observed in other plants. See observations on , page 27." Had the doctor given a more extended investigation, I fancy he would have agreed with me as to the cause. I found hundreds of diversified specimens. I am not aware that it was after a rain, but I took up a number of the plants, and always found a vigorous scaly root bud, undergoing development at this early season under ground, to produce a new stem the following spring. I came to the conclusion that, as the temperature was below freezing and snow was on the ground, the expanding bud, in close proximity to the surface, gave out sufficient caloric or warmth to generate vapor from the moist soil. This vapor rising around the stem of the plant, and attracted by it, becomes congealed into what we term hoar-frost, in numerous forms; some like shellwork, others like tulips, with radiated petals, variously contorted, and often as symmetrical as snowflake crystals. Horticultural Journal helianthemum That plants in germinating have the power of generating heat was proved by Mr. Hunter and by Lamarck. Experiments of Hales and Du Hamel show that vegetation is not wholly suspended, however cold it may be; and that there is a regular and gradual progress till the returning warmth of spring gives a greater degree of velocity to the juices, rendering their development more vigorous and apparent. If the crystallization takes place when the air is calm, the crystals will be regularly formed; otherwise, when windy, I have seen them like a shell within a shell, very thin, of a pearly whiteness. Professor Tyndall has shown in a very beautiful manner that ice is but an agglomeration of snow crystals: the transparency of the former being due to the expulsion of the air, entrapped in and causing the whiteness and opacity of the latter. There is a formation called the snow plant of California, which arises to some height, and has been compared to various things, a fountain convoluted and enlarged above, a crystallized small bushy shrub, etc.; but on closer inquiry, I have failed as yet to get any definite ideas to its true character. Some bulbs in the soil might cause such formations by the congelation of vapor deposited successively upon itself, or the stems of the previous year's growth yet remaining, and thus give them a sheathing of frosting. The shape of a star is common in snow crystals, which we all know assume the most beautiful forms, and which are illustrated in various publications. The eminent botanist Count Swinoskoff should give us some clue as to the genus or character of the plant, the flower of which, we are told, melted away on being touched, and as to the stamens, the diamond seeds like a pin's head, etc. The whole needs further explanation. I trust those Bostonians who are in such hope will edify the public as to the final result of their experiment. What has that veteran in botany, Dr. Asa Gray, to say about it? Let some one well qualified tell us more about this frost flower of Russia. J. Stauffer. Lancaster, Pa. 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 Frost Plant of Russia

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