Bolt6

bolt6

A Brief Introduction to The Boltzmann Brain Theory

বোল্টজম্যান ব্রেন থিওরির একটি সংক্ষিপ্ত ভূমিকা

Eine kurze Einführung in die Boltzmann-Gehirntheorie

Una breve introducción a la teoría del cerebro de Boltzmann

Une brève introduction à la théorie du cerveau de Boltzmann

बोल्ट्ज़मैन मस्तिष्क सिद्धांत का संक्षिप्त परिचय

ボルツマン脳理論の簡単な紹介

볼츠만 뇌 이론에 대한 간략한 소개

Uma breve introdução à teoria do cérebro de Boltzmann

Краткое введение в теорию мозга Больцмана

Boltzmann Beyin Teorisine Kısa Bir Giriş

Giới thiệu tóm tắt về Lý thuyết bộ não của Boltzmann

玻尔兹曼脑理论简介

Today we will be creating a SlackBot that reacts to every message sent by a specific user. Useful, right? 😄 Creating a New Slack App The first thing we have to do is create a new app. We do this by navigating to and navigating to . Slack api.slack.com Your Apps -> Create New App We’ll call our app . Next up, we have to set up , a , and . reacting-bot event subscriptions bot user permissions Socket Mode The first thing we have to do is enable Socket Mode. Turning on Socket Mode will route your app’s interactions and events over a WebSockets connection instead of sending these payloads to different Request URLs. To enable Socket Mode, navigate to and hit . You will be prompted to add scopes and generate an app-level token. Give the token a name, e.g., “token”, and add the following scopes: Settings -> Socket Mode Enable Socket Mode & connections:write authorizations:read As the names suggest, these will give our app permission to read and write messages. Event Subscriptions Next up, we need to enable Event Subscriptions, which can be found beneath in the left-side menu. After enabling Event Subscriptions, you will need to add the following Event Subscriptions. Features Subscribe to bot events: message.groups Subscribe to event on behalf of users: message.channels Bot User If a Bot User has not yet been created, it can be set up on the tab. Here we can set a display name and its username. App Home Permissions Lastly, we need to ensure that the SlackBot has all the correct permissions needed. Head over to and add the permission to the . OAuth & Permissions reactions.write Bot Token Scopes We have now set up the SlackBot, and we are ready to start coding! Writing The Bot We will be using the library as an interface to the Slack API. It comes with many useful features that make creating SlackBots a breeze. bolt-js While in a new directory , we can initialize the project using . This will create a file that looks like the following: reacting-bot npm init -y package.json {
  "name": "reacting-bot",
  "version": "1.0.0",
  "description": "",
  "main": "index.js",
  "scripts": {
    "test": "echo \"Error: no test specified\" && exit 1"
  },
  "author": "",
  "license": "ISC"
} For this project, we are going to need two packages. and . is an interface that we use to communicate with the Slack API, and is used to access environment variables. We can install the packages with the following command: @slack/bolt dotenv Bolt dotenv npm install @slack/bolt dotenv Next up, we need to create the file which should store our environment variables for when we are running this project locally. The file should contain the following: .env SIGNING_SECRET=5c24e...
TOKEN=xoxb-...
APP_TOKEN=xapp-...
USER_ID=UCF8... can be found on the page SIGNING_SECRET Basic Information (xoxb) can be found on the page TOKEN OAuth & Permissions (xapp) can be found on the page under APP_TOKEN Basic Information App-level tokens can be found when viewing a slack profile under USER_ID More In , we start by importing and , and we initialize a bolt application in socket mode in the constant : index.js @slack/bolt dotenv app const { App } = require("@slack/bolt");
require("dotenv").config();

const app = new App({
  signingSecret: process.env.SIGNING_SECRET,
  token: process.env.TOKEN,
  socketMode: true,
  appToken: process.env.APP_TOKEN,
}); We then write the logic that uses the method to attach a listener for messages. message() app.message(async ({ message, context }) => {
  if (message.user === process.env.USER_ID) {
    try {
      const result = await app.client.reactions.add({
        token: context.botToken,
        name: "heavy_plus_sign",
        channel: message.channel,
        timestamp: message.ts,
      });
    } catch (error) {
      console.error(error);
    }
  }
}); We check any given message is sent by the user with the . If we find a match, we use the function to add a reaction to the message. ID USER_ID app.client.reactions.add() Lastly, we add a function that runs when the application starts. This function will start up the Slack App: (async () => {
  const port = process.env.PORT || 3000;
  await app.start(port);
  console.log(`⚡️ reacting-bot is running on port ${port}`);
})(); And that’s it! You can now run the app using the command, and the bot will start reacting to messages once it has been added to the correct channels. npm start This is what the final code looks like: const { App } = require("@slack/bolt");
require("dotenv").config();

const app = new App({
  signingSecret: process.env.SIGNING_SECRET,
  token: process.env.TOKEN,
  socketMode: true,
  appToken: process.env.APP_TOKEN,
});

app.message(async ({ message, context }) => {
  if (message.user === process.env.USER_ID) {
    try {
      const result = await app.client.reactions.add({
        token: context.botToken,
        name: "heavy_plus_sign",
        channel: message.channel,
        timestamp: message.ts,
      });
    } catch (error) {
      console.error(error);
    }
  }
});

(async () => {
  const port = process.env.PORT || 3000;

  await app.start(port);

  console.log(`⚡️ reacting-app is running on port ${port}`);
})(); Thanks for checking out this guide! You can view the code for this project on my . GitHub Also published here.

How to Create a Slackbot With JavaScript Bolt

The Nuts and Bolts of Crafting Quality Content

Photo by on Christopher Campbell Unsplash Hey Hackers! I’m and I’m the Mike Todd CEO and Founder of . Near-Life First of all, I’d like to say a huge thank you to the community for recognizing as the winner of: HackerNoon us The Top Startup in Bolton Reporter: What does it mean for you to win this title? HackerNoon There’s been huge development and development and change in the Greater Manchester region over the last two decades - but Bolton, specifically, has faced its own set of challenges. This town has a history of creativity and innovation that we’re proud to be part of and we want to play our part in the revitalization of the area. How do you or your company intend to embrace the responsibility of this title in 2022? Continuing to do what we’re doing. We want to push on with the work we’ve started to make a leading player in the world of interactive and immersive content. We stand by our founding ambition to be the first interactive video and VR authoring tool for everyone. Near-Life What are some of the goals you’re looking forward to accomplishing in 2022 (whether it be through company initiatives or your personal journey)? We’re looking to raise investment this year to take us to the next level of our journey. We have already have users all over the world but we want more people to understand who we are and how we can improve the way content is created and shared. We are still only at the foothills of what interactive video and interactive VR can offer. After participating in this journey, is there anything that you would like the team to know? HackerNoon Being an entrepreneur isn’t easy. You’re constantly trying to communicate your belief to others. Not everything is plain sailing. But it is a rewarding struggle to try and create and build something that you feel can make a difference in the world. What is something special about you or your company that you’ve rarely had the chance to properly share but really wanted to? (Give this one a proper think, I’ll know if you didn’t!) We’re very much rooted in the idea of democratising creativity - empowering our users on their own journey of innovation and creativity. We came from a creative content background and were always inspired by the idea that creativity is part of the human condition, something that we all benefit from. We think our interactive authoring tool has the potential to make the world better at communicating. Ambitious, I know. What are some concepts you wish people knew more about? Interactive video and immersive content is still an emergent space. We spend a lot of time trying to share an understanding of the value it can bring. If people already knew more about that, we’d spend less time making the case of the concept - and be able to fast forward to helping explain why our solution is the best and how it can save time, money, effort - and improve results! Is there anything else you’d like me to know? It can be anything. If you, or anyone, is interested to find out more about what we do at Near-Life…you can sign up for a at any time! demo or free trial For more information: Read the FAQs about or . To see all of the winners you may visit , pick any city and view the name that appears at the top. Or follow for posts with the list of names released over the course of the week of February 14, 2022. Startups here here this site this account Thank you to all of our sponsors! We truly appreciate your contribution to the tech world and thus the future! : Startups , , , , , , , , , , Blockster Brex FreeCodeCamp LaunchDarkly Coil Udacity Udemy Vercel Asia Pacific Transgender Network Bybit Everscale Network

Near-Life is Bolton's Top Startup of 2021

The rise of the internet and social media created a significant impact on our purchasing behavior. A found that there has been a shift in the effectiveness of advertisements in the favor of peer recommendations. Nielsen survey The survey shows that the trust customers place in conventional ads has been on a steady decline. At the time the study was published, only 33 percent of people trusted general advertisements while 90 percent have faith in ‘earned’ advertisements such as peer recommendations, such as . influencer marketing Keeping in mind the study was published in 2011, those numbers may be even more inflated at this point. The initial release of Instagram for iOS happened in 2010, with the Android release following two years later. Seeing how Instagram changed the way online marketing has evolved, it’s currently a no-brainer for companies to use this effective and targeted marketing strategy. Instagram influencers offer access to a huge pool of potential customers. Because every influencer has a certain audience, it makes it cheaper to advertise effectively to your target group. In this article, we’ll discuss tips to find reliable and good influencers that will give you the highest return of investment. Now, how can you start getting a piece of the action? Types of Influencers Celebrities Macro influencers Micro influencers We will mainly focus on the second and third categories. The choice between them depends mostly on the budget. The first category, celebrities, are not a good choice as an effective marketing strategy. A concluded that celebrities are not a good choice as only 3 percent of buyers are influenced by celebrity endorsements. 2016 Collective Bias survey Further, you may be wondering where the difference between macro and micro influencers lies. The difference is based on the following they have: A ‘Macro’ influencer is someone who has managed to build up a following of more than 10,000 followers A ‘Micro’ influencer is someone who has built up a more modest, but still significant number of followers (1000 - 10,000) (Source: Screenshot from SocialBakers about types of influencers) The reason why your business should focus on micro influencers and macro influencers is because the 2016 study we mentioned above demonstrates that 30 percent of customers were more likely to purchase a product by a non-celebrity influencer. A brings forth another important aspect to keep in mind. We are talking about the balance of engagement and reach. Macro influencers may have a greater reach, but micro influencers have much greater engagement from their nice audience. survey by Markerley Macro influencers may have a greater reach, but micro influencers have much greater engagement. If you are selling a specialized product, it may prove to be more effective to opt for a greater number of different micro influencers instead of one single macro influencer. On the other hand, it takes more time to find the different micro influencers in the required niche. But the engagement of the audience of micro influencers means more people will actively come into contact with your product. Another factor that adds to the advantages micro influencers have over celebrities or even macro influencers is their authenticity. Often micro influencers have a narrow scope, but you can be sure they are effectively involved in their niche. This brings authenticity to the table, which is arguably one of the most important aspects of marketing. However, many companies face a challenge when trying to find authentic influencers with an engaged audience. How to Identify the Right Influencers? Picking the wrong influencers can be a costly mistake. Determining whether an influencer is a fit choice for your campaign takes time. There are several metrics to keep in mind when you are targeting influencers. The of their audience: This is probably the most important metric for a business trying to sell a product. Try to aim for influencers who have an for their posts. By engaging we mean, liking, commenting and sharing. engagement engagement rate of at least 2-4% Another important metric is the of the influencer. The overlap between their niche and the as possible. niche niche of your business should be as big The is also an important metric. Does the part of the audience that actively engages with the posts reflect the target audience you are going for? follower quality This is also a metric that shouldn’t be overlooked. If the cost is too high in relation to the possible reach it’ll get, you should probably look further. Post costs. To make your search easier it’s a good idea to use different tools to find suitable influencers. You could use tools like an Instagram influencer platform to quickly search through lists of influencers. A lot of platforms display useful information about the influencers and often offer the possibility to directly reach out to them. Next read? 14 Advanced Techniques for Getting More Instagram Followers Pro Tip: Use an Instagram Audit Tool to Avoid Fake Influencers (Source: Unsplash by Carlos Muza ) Another tool to ease your search for a fitting influencer is an . Using such a tool allows for quickly scanning accounts, discovering the hashtags they focus on, quickly calculating engagement rates across multiple posts. This saves you a lot of time reviewing each account manually. An audit tool can quickly give you a list of the most promising influencers you should further investigate and perhaps contact. Instagram Audit tool An audit tool can quickly give you a list of the most promising influencers you should further investigate. Furthermore, fake Instagram influencers are on the rise. An audit tool can quickly tell you if the engagement rate is normal or whether it is subpar. An account with a lot of fake followers will often have very low engagement. Real Instagram users tend to be able to evaluate accurately which accounts seem not genuine or have a lot of fake followers. Real users will unfollow, leaving the account behind with a majority of fake followers. Another way an Instagram Audit tool can detect fake influencers is by looking at the followers liking and commenting on the posts. If the influencer has an engagement rate of 2-4%, but has a low variety in the followers who comment and like posts, it may be a fake influencer. If it’s always the same people commenting, chances are they’re actually bots. Which Type of Influencer Campaign Should You Choose? There are several types of influencer campaigns you could choose from. Your type of campaign depends on your goals: brand awareness, promote a product, or gain more Instagram followers? Below we’ll discuss several campaigns you could choose from and which benefits they offer. Sponsored Posts This one is probably the most widespread due to its simplicity. The influencer creates a post highlighting your product and you pay them for it. Contests A contest is also a really good idea because it immediately ensures followers are engaged with the post because they can win a product. Branded Content Branded content means the influencer uses your product in an informative way that is engaging to their followers. Branded content is great because it allows the influencer the freedom to be authentic while displaying your product. Reviews Reviews are an optimal choice if you’re bringing a new product to the market. The influencer can then do an in-depth review demonstrating the advantages your product has. Brand Representative Program Sending your product to an influencer is also a great idea because it shows you are confident about your product. It may also be a relatively cheap option because you can use your own product. Influencer Takeover This is when an influencer takes over your Instagram page for a day. This is great when there is a significant overlap between your niche and the niche of the influencer. It can result in a mutual increase in followers. Track the Success of Your Instagram Influencer Campaign Depending on your campaign type, you can monitor different metrics to keep track of the performance of your campaign. For example, when you want to increase your follower count, you can simply track your daily follower growth starting on the day of your campaign. However, if you want to track more advanced metrics such as engagement levels or branded hashtag usage, you should consider using an Instagram analytics tool. Many Instagram analytics tools allow you to track your engagement levels. This correlates directly with the Instagram algorithm and is therefore important to track. If you’ve used branded content, you can also track your brand awareness. Has there been an increase in the number of times your branded hashtags have been used on Instagram since the start of the campaign? The key takeaways of this post include using influencers to do the heavy lifting of your marketing campaign. Finding the best influencers for your business or product can be made easier by using an Instagram influencer platform. And, an Instagram audit tool can help you predict the success of your campaign because it helps you weed out fake influencers. Good luck with your Instagram influencer journey!

Instagram Influencer Marketing: The Nuts and Bolts Of It

The Lightning Network was built around the idea of financial inclusivity. Anyone can make a purchase and should be able to do so pseudonymously. What if conferences and hackathons were structured around these same core principles? As the world’s first online Lightning Network conference and hackathon, that’s exactly what the was designed to be. By hosting the event online, Bolt-A-Thon reaches a world-wide community, sets incredibly affordable ticket prices, and process all payments into Lightning Bitcoin. Bolt-A-Thon Hackathon The first part of the Bolt-A-Thon is for our hackers. They hackathon will start on April 5 with the kick off at 6pm PST and runs through April 7 at 2pm PST. Hackers will be provided a suggested theme and will have two and a half days to build their projects to then present in front of their peers and our judges. First, second, and third place winners will receive respectively. Blockstack PBC will also be offering an additional bounty of for the best project built with Blockstack. 0.3 BTC, 0.2 BTC, and 0.1 BTC $1000 Conference www.boltathon.com The second part of the Bolt-A-Thon is the conference. Our fantastic lineup includes representatives from all three major Lightning Network implementations: from Blockstream, from Lightning Labs, and Fabrice Drouin from ACINQ. This ensures diverse client coverage that will be available for current and future developers. Rusty Russell Conner Fromknecht Not a coder? Not to worry. The Bolt-A-Thon also offers alternative topics such as the Node Launching session with , Lightning Network games with , and even a sobering talk about the limitations of the Lightning Network with . Pierre Rochard Lightning Koala Alex Bosworth Voting One of the unique features of our website is that it allows people to submit posts to become a potential speaker for the Bolt-A-Thon. It also allows people from the community to vote on their favorite topic proposal with satoshis. The top posts will earn a spot to speak at the conference. Ticket Prices So join the Lightning revolution that is taking Bitcoin by storm. are (~$10) per session and to register for the hackathon. And if you don’t have a Lightning wallet, you can always pay on-chain with Bitcoin or Litecoin through submarine swaps. Tickets 250,000 satoshis 100 satoshis Buy Your Tickets Today!

Bolt-A-Thon: World’s First Online Lightning Network Conference and Hackathon

The internet is filled with tutorials to get started with Deep Learning. You can choose to get started with the superb Stanford courses or , or Deep Learning AI if you are an absolute beginner. All except Deep Learning AI are free and accessible from the comfort of your home. All you need is a good computer (preferably with a Nvidia GPU) and you are good to take your first steps into Deep Learning. CS221 CS224 Fast AI courses courses This blog is however not addressing the absolute beginner. Once you have a bit of intuition about how Deep Learning algorithms work, you might want to understand how things work below the hood. While most work in Deep Learning (the 10% apart from Data Munging viz 90% of total work) is adding layers like Conv2d, changing hyperparameters in different types of optimization strategies like ADAM or using batchnorm and other techniques just by writing one line commands in Python (thanks to the awesome frameworks available), a lot of the people might feel a deep desire to know what happens behind the scenes. This is the list of resources which might help you get to know what happens inside the hood when you (say) put a conv2d layer or call T.grad in Theano. General Treatise Deep Learning Book is of course the most famous and well-known . Other good resources are Professor Charniak’s and which is a technical introduction to Deep Learning. There are other resources too which you might want to take up if you want to understand things from a particular perspective. For example, the was written from point of applied mathematicians and if you just want to start coding without going into any theory then read . One more recommended resource is Deep Learning course in PyTorch . This course talks about things bottom up and help you grab a bigger perspective. resource course paper tutorial here here Issues about Backpropogation There are many a time, when people are not sure about “how is gradient descent and backpropogation the same thing ?” or “what exactly is the chain rule and backpropogation?”. To understand the basics, we might choose to read the original paper by Rumelhart, Hinton, and Williams where it all started. The paper is located and is a very simple to understand document. here Some other very useful resources one can read on top of this are Karpathy’s blog on backward and explaining backprop’s derivation. prop derivation this video Linear Algebra and other Maths Anyone would redirect someone aspiring to learn Linear Algebra to goto Prof. Strang’s . This is probably the best resource on Linear Algebra on the planet. Similar is the case with Optimization course of Prof. Boyd or Calculus on Manifolds book for vector calculus (You can find a pdf when you Google “Calculus on Manifolds”). However, one doesn’t need to go through the depth at which these resources look at their subjects to jump into Deep learning. A very quick way to get started is to take the quick refresher on all prerequisite Calculus for Deep Learning which is available . There is also this very good set of to just look at convex optimization used in Deep Learning. Another good resource is Sebastian Reuder’s paper . I also like these lecture notes to understand derivatives on . course here here lecture notes here tensors Automatic Differentiation and Deep learning libraries Automatic Differentiation isn’t something that you absolutely need to know when you are doing Deep Learning. Most frameworks like Torch, Theano or tensorflow do it for you automatically. In most cases, you don’t even have to know how the differentiation is being done. That said, if you are determined to understand how Deep Learning frameworks work, you might want to understand how automatic differentiation works . Other good resources to understand how Deep Learning libraries function are can be found in this and . here blog video Convolutional Neural Networks: The most useful things you might need after you have done some courses which enable you to use basic convents is to understand how convolutions work on images. “What is output shape after you apply a certain type of convolutions on an input ?” , “How does stride affect convolutions ?”, “What is Batch Normalization ?” and stuff like that. The two best resources I have seen for these type of applied questions are the tutorial and Ian Goodfellow’s talk . A more thorough on Convnets is here if you want to get an idea. This is a very good resource in the topic. here here review review on object detection Deep Learning in NLP The Stanford 224 course I pointed out earlier in the blog is a very good starting point and you should be good enough for almost everything. There is also a course on youtube by Graham Neubig (which uses dynet) . There is also an by Yoav Goldberg which you might like. (Newer) advances of NLP after this book was written are reviewed . There is also a very common question about whether to use convnets or RNNs (LSTMs/GRUs) on text. A good overview is . here NLP book here here Reinforcement Learning Sutton and Barto is the bible to get started with these methods. The book is free and is available . A very good review of recent Deep Reinforcement Learning methods is available . There is this very interesting tutorial on Reinforcement Learning . here here here A good review of Monte Carlo Tree Search (which is a part of AlphaGo algorithm by Deepmind apart from Deep Reinforcement Learning techniques) is . I, however, used quick tutorial to learn about them. here this Some other good reviews/tutorials A good tutorial about GANs (Generative Adversarial Networks) and generative models in general is what Goodfellow gave in ICLR 2016. It can be found . Neural Networks have been used to transfer art (for example in Prisma app), a detailed survey of methods to do that can be found . Another good survey on Multi Task Learning (combining multiple tasks by same neural network) by Reuder is here here here . Criticisms Although Deep Learning works amazingly well on multiple problems, we know there will always be some places where they have not reached yet. Some good criticisms to read are Failures of gradient-based learning by , this talk by Hinton which lists some difficulties for and how convnets cannot decipher negatives of images . Another criticism here went viral/controversial few days back is . There is also on the malicious use of Deep Learning. Shalev-Shwartz et al. convnets they train on this this extensive report Adversarial Examples This is a huge field of making artificial/real data points that can fool Convnets. I could have put it in in criticism sections but didn’t as they are not a technical challenge for all applications and I am not very well read on them. One very cool case to get started and interested is where they generate “adversarial objects” to fool neural networks. here You can also read about Machine Learning algorithms you should know to become a Data Scientist . here We hope you liked the article. Please for a free ParallelDots account to start your AI journey. You can also check demo’s of PrallelDots AI APIs . Sign Up here You can read the original article . here _Read writing about Deep Learning in Hacker Noon. how hackers start their afternoons._hackernoon.com Deep Learning - Hacker Noon

Best (and Free!!) Resources to understand Nuts and Bolts of Deep learning

A look at 3rd-party AI tools and services, uncovering easy wins, and where to invest in an automated world Artificial Intelligence has become a bit of a divisive topic. While some industries have oriented their entire business around the technology, others are struggling to develop a strategy. The good news is that adopting AI doesn’t need to be this . dramatic An entire ecosystem of applications and services have cropped up to bridge the gap between the business processes of today and the intelligent ones of tomorrow. Adopting AI-enabled solutions can help companies streamline operations and eliminate repetitive tasks. From growing sales with intelligent customer engagement to reducing opex with automated IT operations, there are new tools available to support every department within a business. Here are some tools you can integrate today, at whatever stage or opinion you have on AI. Cross-Functional Solutions Where there is data, there is an opportunity for intelligent systems (AI) — to do something. A number of companies have built cross-functional solutions to meet the data opportunity across the board. The drawback is that these solutions do require collaboration (not plug and play) to develop models that are best suited for your use case, but the impact can be dramatic. : API for human automation. Apres : Builds augmented intelligence software for healthcare, commerce and financial markets. CognitiveScale : Cloud software that transforms handwritten paper forms into digital data. Captricity : Simplifies and accelerates your ability to use AI to unlock the value in your data. Machinify Natural Language Processing (NLP) technology for Splunk enables you to ask “plain English” queries of your machine data. Insight Engines : Maximizing the impact of data through advanced natural language generation (Advanced NLG) for the enterprise. Narrative Science : Human Resources HR is operationally intensive, rigidly structured and often slow to adopt new technologies. Recruiters alone spend over 60% of their time reading through resumes — time better spent with candidates. HR presents a clear opportunity for AI to improve the efficiency of the role: Actively pursue all credible candidates in the market at any given time, all the time — matched against fit criteria tailored toward your business. Optimized Recruiting: The opportunity to deal with employees as people, rather than functions and creating tailored milestones and objectives. Personalized Career Development: The ability to analyze messaging, both in the market and internally, and adjusting accordingly. Employee Sentiment Analysis: Packages tailored to the implicit needs of your employees, such as fitness trackers and programs for health insurance. Tailored Benefits: Uses machine learning to help organizations hire smarter by analyzing a person’s publicly available online presence. FAMA : Your team’s A.I. recruiter. Mya : AI-based anonymous career development platform allowing users to both know their worth and get concrete offers in real time (previously Workey). Gloat : AI powered employee retention tool. UnderstandBetter : Reduce corporate travel spend by rewarding employees for saving. Rocketrip : Cloud HR service that provides an integrated and video enabled digital platform for all recruitment needs. Peoplise : Talent Relationship Marketing (TRM) cloud platform connecting people to their ideal job. Phenom People : Predictive hiring platform that informs you who to hire before you meet them Koru : Helps businesses better understand their employees. Humanyze : Customer Service Advances in Natural Language Processing (NLP) have created new opportunities for companies to engage with customers. From chatbots to voice assistants, AI can now simulate human interaction, triage the required service and route the solution accordingly. This has streamlined customer service centers to personalize customer service and enable more efficient interactions between vendors and consumers. Service personalized to the tune of all available data on the client and intelligent virtual assistants as an interface layer. Differentiated customer experience: Streamline inquiry capture and resolution process, proactive support, and account/client management. Smarter operations: Data analysis on a continuous basis — uncovering new revenue streams and decrease churn. Intelligent insights: Brings practical applications of deep learning & artificial intelligence to customer service operations of large companies. Digital Genius : Supplies artificial intelligence to augment and replace live chat customer support agents at eCommerce companies. Eloquent Labs : Automates customer care conversations. Kylie.ai : Virtual assistant solutions. Interactions : Offers artificial intelligence powered customer service. AlphaBlues : utomated customer support. True AI : A Advanced AI customer service across multiple channels including chat, email, SMS, Facebook Messenger and Twitter. Hello Vera : AI for customer service. HelpScout : Social media customer service. Sparkcentral : AI voice platform for connected devices. Snips : Sales & Marketing SAAS has entrenched the value of sales and marketing data over the last decade, making historic records commonplace and an ideal for applying AI. Conversion-focused tools promise to make a significant impact on the top and bottom line: Automated outbound strategy targeting highest value leads, and delivering qualified prospects at the right time. Optimized account development: AI systems to support the salesforce with relevant insights, market movement and continuous training/coaching. Improved salesforce productivity: Personalized customer engagement, predictive marketing and messaging. Intelligent customer engagement: AI generated content and distribution, predictive marketing to increase retention, real-time competitive intelligence. Automated marketing: People-based intelligence through reorganizing the information on the web based on the people who use it. Node : AI powered sales intelligence to build relationships with your buyers and grow your sales. Nudge : AI software for marketing and sales enablement. Conversica : Records, transcribes, and analyzes sales conversations in real-time, highlighting important moments and revealing why you win and lose deals. Chorus : Provides users with a platform to maximize sales leads with analytics programs and innovative organization tools. FunnelBeam : Helps inside sales reps win more with an AI that learns from how your best reps communicate effectively with their customers. Nitrio : AI-powered analyst for marketers. Aiden : Automatically capture all sales activity to drive intelligent sales management and marketing accountability. People.ai : Predictive Marketing Platform for enterprise enables insight-driven customer engagement to win and retain customers. Mintigo : shows you the best way to communicate with any prospect, customer, or coworker based on their unique personality. Crystal : Virtual assistant that schedules your meetings. Clara : Marketing automation AI that delivers a personalized experience to each customer. Retention Science : AI generated language that resonates the most with any audience, segment or individual. Persado : AI powered marketing insights to create compelling content. Unmetric : Social strategy and analytics firm that provides Convey.AI semantic machine learning technology and Conversus App. Converseon : Legal Legal departments commit the majority of their resources to operational overhead — document parsing, research and discovery. Various AI tools have been developed to support these time-consuming tasks, often more effectively than their human counterparts. Augmenting existing legal teams with AI can provide an enormous benefit/ boost to productivity. AI assistant that provides rapid analysis and summarization of legal briefs. Legal research: AI able to identify relevant briefs and automatically generate next steps and other research tasks. Contract diligence: Documentation review and prioritization, automated story builder, instant translation. Discovery: Artificially intelligent attorney to help power through legal research. ROSS : Casetext’s CARA, automates key legal research tasks to analyze litigation documents, and uses that information to algorithmically query the law. Casetext : Platform for legal search, analytics and visualization. Ravel: Legal legal document review and discovery platform. Everlaw: Legal technology company providing research and analytics tools to turn unstructured case law into structured data. Judicata : Makes in-depth contract reviews accessible to everyone. LawGeex : IT Operations Increasingly complex IT operations are changing infrastructure attack surface area, continuously exposing organizations to new threat vectors. There is a real need for tools that offer the necessary intelligence and speed to keep up with the growing security threats companies face today. Beyond being able to take over manual tasks prone to human error, AI will be enable real-time threat detection and most importantly, prevent threats before they cause damage. Anomaly detection and prevention, real-time monitoring, autonomous remediation. Security: AI system that mimics how a user investigates, monitors, and troubleshoots events. Cognitive Insights: RPA tools to replace manual tasks and provide a real-time view of process workflows, and self-learning topology analysis. Streamlined Operations: Enable NLP bots that talk to a system to identify and resolve performance issues, monitor digital performance of IT infrastructure. Improved Customer Experience: : Root cause analysis software company acquired by Splunk. Rocana : Advanced monitoring platform for modern applications. SignalFx : Human-centered that helps people and machines work together to find clarity in chaos, and accelerate innovation. Moogsoft technology : AI-powered log analysis solution that monitors all your IT stack in real-time to predict issues before they affect the business and help you solve them faster. LoomSystems : Teaching machines to think, reason and communicate, acquired by Microsoft. Maluuba : Multi-turn, easy-to-use, and easy-to-author chatbot. Kitt.AI : AI-driven threat detection and prevention solution. Mistnet security : Enterprise immune system technology for cyber security. DarkTrace : Combines humans and machines into an AI system that detects cyber threats at scale and in real time. PatternEx Conclusion Building an AI muscle in-house is not the right strategy for every company (more here). That said, taking advantage of AI is necessary for all companies to keep up in any market. If the competition is running more efficiently, you are already a step behind. AI will affect every industry, everywhere. Whether or not you see this change happening today, it is important to start planning for it. Being ahead of the curve here is worth it. Disclosure: Juniper Networks is an investor in one of these companies.

Bolt-on AI: Is this the AI shortcut we’ve been looking for?

I should start off by saying that I am not a car guy. If you know me, you’ve probably never heard me talk about a car, and you likely will never hear me talk about one again. My dad is a car guy. He rebuilt Porches before I was born. At some point, he sort of tried to teach me how to change belts and brake pads and things that you could do on cars before they were 95% electronics, though little of that stuck. For all my car-guy pedigree, I could just never really care less about cars. In fact, I would really rather not own one at all. When we lived in Paris, we never needed one. You can walk most places and there’s public transit for the rest. We lived for a year with no car and no real need of one and it would be amazing if we could do that in America, but it’s sadly not very practical here. So, own a car we must. This post is my simple love letter to the first car I’ve ever really liked owning, the Chevy Bolt. The story starts when we bought our first house recently. When we moved into the house, we decided that we should try getting an electric car. We live in Berkeley, we now have a driveway and a place we could easily install a charger, it seemed like a good call. We owned a Tacoma, but it’s big and gas-guzzling and impossible to park in Berkeley and San Francisco, and overall just not a very good . car We researched everything out there and decided that the only two electric cars that currently get anywhere near the range we wanted were the Telsa and the Chevy Bolt. Now, I do love the . Tesla For our 14th wedding anniversary, we rented a Tesla Model S for the weekend and drove it to Napa. It’s a great car. The simplicity is amazing, it’s super safe and the acceleration is totally insane. Ludicrous, one might say. However, there are two problems with the Telsa. The first is that it’s really wide — as in, the same width as our Tacoma. The other is that it’s really expensive. Which itself presents another problem, which is that even if I wanted to spend $90k on a car, which I absolutely do not, I still don’t really want to be the guy driving around in a Tesla. With apologies to any of my Telsa owning friends, if I have any. So we took a chance on the Bolt and . It has all of the important advantages of the Tesla and none of the downsides. Let’s quickly go over the main things that are great about this car. it’s the best car I’ve ever owned There are exactly two versions of the car, one that costs $37k and slightly nicer version that costs $41k. After federal and state incentives, which I believe end up around $10k, it costs less than $30k. It’s inexpensive. Not only does it cost about the same as a Honda CRV, but it’s cheap to drive. PG&E has a EV plan where you can get cheaper electric rates after 11pm, and the Bolt has a setting where it won’t draw power until then, which means you can charge it only when your electric rate is $0.12 per kilowatt hour. This means you can drive it’s entire 240 mile range for less than $9. If your car gets 30 miles per gallon on average, that’s the equivalent of about for fuel. Put another way, for $1 in fuel costs you can drive 30 miles in this car. Unless of course you install solar panels, in which case your “gas” is essentially free for life. $1 per gallon Like nearly all electric cars, it has constant torque. Like the Tesla, when you step on the gas, all of its torque is instantly available and it accelerates linearly. It never switches gears. This little sub-$30k car goes from 0–60 in 6.3 seconds, . Faster than an ‘84 Chevy Corvette. This is not as quick as a Tesla, but it’s still amazing and really fun to experience. It’s quick. faster than a 2006 Audi TT Roadster In my opinion, it’s nicer to drive overall than the Tesla. It’s possible that nobody will agree with me on this, but there probably also aren’t that many people who have driven both. For me, the smaller size and width of the car makes it more fun to drive around town. Plus, if you’ve ever actually tried to floor a Tesla, it’s too much — I nearly made my wife throw up twice when we rented it. Flooring the Bolt off the line makes the passenger ‘oomph’, but not vomit. (It literally made me make an ‘oomph’ sound yesterday when my wife floored it without warning me) Also like most electric cars, I imagine, it makes almost no noise. This is pretty weird if you’ve never driven in a totally quiet car. There is no external sound when it turns on, no acceleration sound, no real moving parts to hear revving or grinding. It’s insanely quiet. This point cannot be stressed enough. When you drive an electric car, you do not ever spend a minute at a gas station ever again. Every night you plug in your car and every morning you have a full tank. It’s like free tiny gas fairies come and service your car every night whilst you slumber. No fucking gas stations. If you’re into it, it’s pretty cool that this thing isn’t burning gas. If you install solar panels and a wall battery, it’s possible to have an almost totally eco-friendly method of transportation. However, even if you don’t care about that stuff, you can get a white sticker in California, meaning you can drive in the carpool lanes. More importantly if you’re living in the Bay Area, you can go through the bus lane of the maze. That’s maybe worth $30k right there, environment-enschmironment. Hippie environment stuff. . It is the best designed user interface in any car I’ve ever driven. I travel a lot, I’ve rented a lot of cars and I can say without a doubt that car UX designers are maybe the dumbest people on the planet, on average. Unless of course you happen to know one, that person is probably super smart but just stuck under horrible management, it’s hard to say. The internal software UI is amazing I can’t tell you how many times I’ve found myself yelling at the center console of a car, madly trying to get something to work, in vain. They are constantly and without exception just plain thoughtless. I drove a car once where every 45 minutes or so, if you were listening to music on Bluetooth, would randomly switch to the first FM channel in it’s memory for no reason. When listening to news about Asia on NPR in our Toyota, it shows a picture of the band Asia. Have you ever used the little circle input device on an Audi to type in an address? Have you ever used any of the awful integrated GPS systems instead of just resorting to Google Maps on your iPhone? Car software is just the worst. My god. This all actually makes sense. However, every single thing I’ve tried to do in the Bolt was easy to find, straightforward to understand or simple to get working. It’s mind blowing. Like I just can’t imagine how it happened. What’s even more amazing is that the screens are better than the Tesla’s in my opinion. The Tesla screen is enormous, which is kind of cool, but ultimately not very additionally helpful, and the interface looks like it was designed by someone who made WinAmp skins in the 90s. It’s not horrible, but it’s a strange juxtaposition to the slickness of the rest of the Tesla. . This is a debatable point, but there is no self-driving stuff or auto-parking stuff. There is an amazing generated top-down view when you’re parking the car that makes it look like a crazy video game, but it doesn’t do any of the actual parking for you. I actually like this and prefer it for now over the idea of the car being partially sentient and possibly plotting my demise. The Bolt is not magic The top-down view is composited from multiple cameras, but it makes parking the car like some ridiculous video game. It’s impossible not to park perfectly between the lines. The range is essentially the same as normal car. We’ve never come close to being low on it. On a full charge, you can drive the two hours from San Francisco to Monterey, then turn around and drive all the way back without a problem and without needing to plug it in once. It drives over 230 miles on a charge. The entire car is like someone took a Tesla, removed all the insane from it, kept everything great and sold it for the price of a normal car. If you’re waiting for a Tesla 3, I think you’re better off going out and buying a Bolt right now. I’m a real picky person when it comes to user experience and there is almost nothing on this car I would improve. I just can’t imagine anything that would make the Tesla 3 better than a Bolt. My wife and I were just this week talking about getting rid of the pick-up truck we have and getting something smaller we could replace it with, and it’s hard to not land on simply getting a second Bolt. It seems weird to own two of exactly the same car, but there aren’t any really good reasons we can think of to choose something else. So, why am I writing this? I suppose that I just really appreciate good design and good product. I complain about everything, I’m easily frustrated. It’s rare that there’s a product I use, even very simple things, where I’m so impressed with the thought put into it and the execution of it that there’s nothing practical that I can think of to improve. When it happens, especially if nobody else seems to be noticing it for whatever reason, I feel like it’s important to point out. Truly amazing job, everyone who worked on the Bolt.

My Love Letter to the Chevy Bolt

If you follow the social media sites like and , you’ll have noticed that rather than use the full URL we use a nice friendly shortened one like . Twitter Google+ t.co/EvDSyOOPTH Wouldn’t be great to have your own shortened URLs inside your own domain? Let’s review the basics first. The Tools Programming Languages are just tools for us, but we need a safe, fast and “cross-platform” programming language to power our service. is a open source programming language designed for building simple, fast, and reliable software. Take a look which great companies use Go to power their services. Go rapidly growing here Install the Go Programming Language Extensive information about downloading & installing Go can be found . here Maybe or user? Windows Mac OS X The article does not contain an introduction to the language itself, if you’re a newcomer I recommend you to bookmark this article, the language’s fundamentals and come back later on. learn The Dependencies Many articles have been written, in the past, that lead users not to use a web framework because they’re “bad”. I have to tell you that there is no such a thing, it always depends on the (web) framework that you’re going to use.In production level, usually, we don’t have the time to code everything that we wanna use in the big company’s applications. In short terms: . good frameworks are helpful tools for any developer, company or startup and bad are waste of time, clear and simple You’ll need only two required dependencies and one optional: , our web framework Iris , an embedded key/value database Bolt (now bbolt) library, will help us to generate the short urls UUID Installing using go packages is a simple task, just open your terminal and execute the following commands: $ go get -u github.com/kataras/iris$ go get -u github.com/etcd-io/bbolt$ go get -u github.com/satori/go.uuid The Best Part Good, if we’re all in the same page, it’s time to learn how we can create a URL Shortener server that will be easy to deploy and can be extended even more! To create a short link, we generate a random string and use Bolt to store the original URL with our random string as the key. When a “GET ” request is issued to the shortened URL , we retrieve the original URL from Bolt. If such a value exists, we redirect, otherwise we respond with a corresponding message. For the sake of simplicity let’s say that the project is located at directory and the package name is . $GOPATH/src/you/shortener main Our is ridiculous simple, it contains just an index page and its “style”, templates are located to folder and the style at folder. front-end ./templates ./resources/css Moving straight to the level, we will create a simple implementation which will be able to a shortened URL(key) and its original/full URL(value), a full URL based on the key and return the total number of all registered URLs to the database. database save retrieve Let’s create our which will the shortened URLs for us! factory generate We should create a which will connect and combine all the components to run an http server which will serve our small URL Shortener service. main file And…. let’s build and run our application! $ cd $GOPATH/src/github.com/myname/url-shortener$ go build # build$ ./url-shortener # run section BONUS our apps is always a useful thing to do, therefore I’ll give you the first idea on how you can test these type of web applications with Iris, straight to the code below. Testing Running the test… $ cd $GOPATH/src/github.com/myname/url-shortener$ go test -v # test That’s all, pretty simple. Right? Share your thoughts about this post and let me know what awesome apps you’re planing to build with Go + Iris! Thanks for taking the time to read the whole article, I admire you for your patience :) The full source code is located .If you have any further questions please feel free to leave a comment below or ask ! here here Update I have updated the source code and the article’s links at in order to replace the ( archived) “ ” with the new from CoreOS based on the (released at 29 August of 2018) 31 August of 2018 https://github.com/boltdb/bolt https://github.com/etcd-io/bbolt https://github.com/etcd-io/bbolt/releases/tag/v1.3.1-etcd.7

A URL Shortener Service using Go, Iris and Bolt

COPA v. Wright, Court Filing, retrieved on January 29, 2024, is part of HackerNoon’s Legal PDF Series. You can jump to any part of this filing here. This part is 7 of 42. 5. “Project BlackNet” paper (Reliance Document) {ID_001379} / {L1/79/1} 100. This document purports to be a copy of a “Project BlackNet” research paper dated on its face to 3 October 2002. The document contains references to a “Stage 4 – Release Phase” and other textual amendments, referring to “Digital Cash”, as well as other features of purported relevance to Bitcoin. 101. This document includes the text of the BlackNet Abstract (see the section above) pleaded as a forgery in COPA’s Particulars of Claim [26-27], and dealt with in the preceding section. (a) COPA’s Reasons for Alleging Forgery 102. The document has been backdated [PM8 [60-61]. The document is dated on its face to 3 October 2002. However, the internal metadata for the document indicate that it was actually created on 17 February 2014. [PM8 [15]]. 103. The document is an edited version of an earlier document, into which passages of text have been inserted using text from the Bitcoin White Paper. [PM8 [23-33, 60.b.]]. 104. The document is apparently part of a series of documents, all of which carry similar content on their face, but which have been edited or are converted versions of the same file [PM8 [3]]. Some of those documents are consistent with a pattern of editing beginning with an earlier precursor document, and ending with a document which would be deployed as if it was original and authentic, in connection with Dr Wright’s claim to be Satoshi Nakamoto. See in particular Mr Madden’s discussion of {ID_001016} as another backdated document in the sequence [PM8 [34-50]]. 105. The metadata indicates that the file was created using Microsoft Word 2013 as the PDF Producer. Microsoft Word 2013 was not yet published in 2002 (the date on the face of the document) but is contemporaneous for 2014. [PM8 [15]]. 106. The document was created in PDF form by printing to PDF from an underlying precursor DOC or .DOCX document on 17 February 2014 [PM8 [16]]. No such underlying precursor document has been disclosed by Dr Wright. (b) COPA’s Reasons for Inferring Dr Wright’s Knowledge / Responsibility 107. Dr Wright is listed in the metadata as the author of the document. 108. Dr Wright is listed on the face of the document as its first author. 109. Dr Wright is listed as the sole author in the ‘version control’ section of the document on page 2. 110. The document contains Dr Wright’s address and telephone number. 111. Dr Wright has positively asserted in these proceedings that this is a document on which he primarily relies as supporting his claim to be Satoshi Nakamoto. 112. The effect of the tampering is to make the document appear to be supportive of Dr Wright’s claim to be Satoshi Nakamoto (suggesting work done by him in 2002, elements of which then appeared in the Bitcoin White Paper), contrary to fact. 113. Dr Wright has posted screenshots of this document or a very similar document on Twitter, apparently in support of his claim to be Satoshi Nakamoto. 114. In his evidence in these proceedings, Dr Wright has claimed this to be a document related to the later Bitcoin White Paper and that it is original to the purported date on its face, contrary to fact. [Exhibit CSW 14]. 115. Dr Wright has relied on this document, or documents with similar content, in previous proceedings and in public in support of his claim to be Satoshi Nakamoto. 116. The metadata records “DeMorgan” as the company from which the document was created. In his evidence in these proceedings, Dr Wright relies on his work on various projects from his time at DeMorgan, as part of his claim to have been working on the concepts behind the Bitcoin White Paper. [Wright1 [32-47]]. 117. The document was created in the time zone UTC+11, consistent with Dr Wright’s location in Australia in February 2014, being the date of creation of the document. [PM8 [18]]. 118. In his Defence in these proceedings, in public social media posts, and elsewhere, Dr Wright has repeatedly stated that the series of research papers (to which this document belongs) are related to the Bitcoin White Paper, and that later applications (submitted in 2009/2010) contained the abstract of the Bitcoin White Paper. (c) Dr Wright’s Explanations and COPA’s Rebuttal 119. In Appendix B to Wright11, Dr Wright accepted that this document was created by conversion of a document to PDF format in 2014. He claimed that this document was obtained from the computer of a former employee who had achieved unauthorised access to Dr Wright’s current wife’s email account, although he did not explain why that claim was relevant. He gave no coherent explanation for why a project paper supposedly prepared for an ITOL application in 2002 would be converted to PDF by an employee of one of his companies in 2014. See: {CSW/2/59} to {CSW/2/60}. 120. In his oral evidence, Dr Wright tried to explain away the fact that (a) authentic versions of this document describe an IT security project (involving an encrypted network), with no reference to any digital transaction system and (b) this version (among others) includes the content of the authentic versions but adds incongruous sections referring to a peer-to-peer digital transaction system involving transactions being structured into “an ongoing chain of hash-based proof-of-work” to preclude double-spending or replay attacks. See {Day2/56:22} to {Day2/77:18}. Key aspects of his explanations and their deficiencies are addressed below. 121. This document is a forgery. Its content is not authentic to 2002, as Dr Wright claims it is. His attempts to explain away the indications of forgery should be rejected for the following reasons: 121.1. A version of this document in disclosure which Mr Madden has established as apparently authentic to 2002 ({ID000013}) is an internally coherent plan for an IT security system with three stages, in which the Stage 3 is described as the Final Phase and the budget covers three stages. It includes nothing about a digital transaction system, still less one involving a chain of hash-based proof-of-work. 121.2. Similarly, a project plan for this IT project which Dr Wright actually submitted to AusIndustry in 2003 has the same content as that apparently authentic document: {L1/113/1} [p8ff. Both the application form {L/113/3} and the project plan {L/113/8} were consistent in their description of the project. Neither says anything about a digital transaction system, still less one involving a chain of hash-based proof-of-work. 121.3. Even an apparently authentic version of the project plan in disclosure which dates to March 2009 {ID_001016} shows the project in the same terms, concluding with Stage 3 and including nothing about a digital currency system. 121.4. In this reliance document {ID_001379}, as in some other (similarly inauthentic) versions of the project plan in disclosure, Dr Wright has added an Abstract (at p4) which describes a digital transaction system similar to Bitcoin. The Abstract bears no obvious relation to the various other parts of the document, which are survivals of the authentic version, such as the Overall Objective section at p6 and the Assessment Against the Selection Criteria section at p8. Dr Wright has also added a few references to a Stage 4 involving the development of the supposed digital transaction system. However, he has forgotten to modify the budget on p11-12, which makes no financial provision for the supposed Stage 4 and still describes Stage 3 as the Final Phase. 121.5. In the Kleiman trial, Dr Wright said that parts of the Bitcoin White Paper went back to his “2002 AusIndustry filings for research and development”: see {L17/327/93}. When that evidence was put to him in this trial, he insisted that the document including the supposed Stage 4 elements of the project (involving a digital transaction system) “would have been filed [with AusIndustry] in 2002 and then in 2003”: {Day2/72:24}. That evidence was flatly contradicted by the actual AusIndustry filing from July 2003 (summarised above). 121.6. Dr Wright has attempted to account for these documents by a confused narrative of different versions of the document being in existence in 2002 and 2009 and used for different purposes, while the version control was in a state of chaos (see transcript reference above). The documents tell their own clear story: that Dr Wright produced an IT security project plan in 2002, which he used for tax concession applications, but he later (from 2014) doctored that plan to bolt on sections reflecting features of the Bitcoin system in order to promote his false claim to have been involved in creating that system. (d) Conclusion 122. I am entirely satisfied that the Project BlackNet paper was forged by Dr Wright. Continue Reading Here. About HackerNoon Legal PDF Series: We bring you the most important technical and insightful public domain court case filings.

This court case retrieved on January 29, 2024, judiciary.uk is part of the public domain. The court-created documents are works of the federal government, and under copyright law, are automatically placed in the public domain and may be shared without legal restriction. COPA v. Wright, Court Filing, retrieved on January 29, 2024, is part of HackerNoon’s Legal PDF Series. You can jump to any part of this filing here. This part is 7 of 42. COPA v. Wright, Court Filing, retrieved on January 29, 2024, is part of HackerNoon’s Legal PDF Series . You can jump to any part of this filing here . This part is 7 of 42. HackerNoon’s Legal PDF Series HackerNoon’s Legal PDF Series here here 5. “Project BlackNet” paper (Reliance Document) {ID_001379} / {L1/79/1} 100. This document purports to be a copy of a “Project BlackNet” research paper dated on its face to 3 October 2002. The document contains references to a “Stage 4 – Release Phase” and other textual amendments, referring to “Digital Cash”, as well as other features of purported relevance to Bitcoin. 101. This document includes the text of the BlackNet Abstract (see the section above) pleaded as a forgery in COPA’s Particulars of Claim [26-27], and dealt with in the preceding section. (a) COPA’s Reasons for Alleging Forgery (a) COPA’s Reasons for Alleging Forgery 102. The document has been backdated [PM8 [60-61]. The document is dated on its face to 3 October 2002. However, the internal metadata for the document indicate that it was actually created on 17 February 2014. [PM8 [15]]. 103. The document is an edited version of an earlier document, into which passages of text have been inserted using text from the Bitcoin White Paper. [PM8 [23-33, 60.b.]]. 104. The document is apparently part of a series of documents, all of which carry similar content on their face, but which have been edited or are converted versions of the same file [PM8 [3]]. Some of those documents are consistent with a pattern of editing beginning with an earlier precursor document, and ending with a document which would be deployed as if it was original and authentic, in connection with Dr Wright’s claim to be Satoshi Nakamoto. See in particular Mr Madden’s discussion of {ID_001016} as another backdated document in the sequence [PM8 [34-50]]. 105. The metadata indicates that the file was created using Microsoft Word 2013 as the PDF Producer. Microsoft Word 2013 was not yet published in 2002 (the date on the face of the document) but is contemporaneous for 2014. [PM8 [15]]. 106. The document was created in PDF form by printing to PDF from an underlying precursor DOC or .DOCX document on 17 February 2014 [PM8 [16]]. No such underlying precursor document has been disclosed by Dr Wright. (b) COPA’s Reasons for Inferring Dr Wright’s Knowledge / Responsibility (b) COPA’s Reasons for Inferring Dr Wright’s Knowledge / Responsibility 107. Dr Wright is listed in the metadata as the author of the document. 108. Dr Wright is listed on the face of the document as its first author. 109. Dr Wright is listed as the sole author in the ‘version control’ section of the document on page 2. 110. The document contains Dr Wright’s address and telephone number. 111. Dr Wright has positively asserted in these proceedings that this is a document on which he primarily relies as supporting his claim to be Satoshi Nakamoto. 112. The effect of the tampering is to make the document appear to be supportive of Dr Wright’s claim to be Satoshi Nakamoto (suggesting work done by him in 2002, elements of which then appeared in the Bitcoin White Paper), contrary to fact. 113. Dr Wright has posted screenshots of this document or a very similar document on Twitter, apparently in support of his claim to be Satoshi Nakamoto. 114. In his evidence in these proceedings, Dr Wright has claimed this to be a document related to the later Bitcoin White Paper and that it is original to the purported date on its face, contrary to fact. [Exhibit CSW 14]. 115. Dr Wright has relied on this document, or documents with similar content, in previous proceedings and in public in support of his claim to be Satoshi Nakamoto. 116. The metadata records “DeMorgan” as the company from which the document was created. In his evidence in these proceedings, Dr Wright relies on his work on various projects from his time at DeMorgan, as part of his claim to have been working on the concepts behind the Bitcoin White Paper. [Wright1 [32-47]]. 117. The document was created in the time zone UTC+11, consistent with Dr Wright’s location in Australia in February 2014, being the date of creation of the document. [PM8 [18]]. 118. In his Defence in these proceedings, in public social media posts, and elsewhere, Dr Wright has repeatedly stated that the series of research papers (to which this document belongs) are related to the Bitcoin White Paper, and that later applications (submitted in 2009/2010) contained the abstract of the Bitcoin White Paper. (c) Dr Wright’s Explanations and COPA’s Rebuttal (c) Dr Wright’s Explanations and COPA’s Rebuttal 119. In Appendix B to Wright11, Dr Wright accepted that this document was created by conversion of a document to PDF format in 2014. He claimed that this document was obtained from the computer of a former employee who had achieved unauthorised access to Dr Wright’s current wife’s email account, although he did not explain why that claim was relevant. He gave no coherent explanation for why a project paper supposedly prepared for an ITOL application in 2002 would be converted to PDF by an employee of one of his companies in 2014. See: {CSW/2/59} to {CSW/2/60}. 120. In his oral evidence, Dr Wright tried to explain away the fact that (a) authentic versions of this document describe an IT security project (involving an encrypted network), with no reference to any digital transaction system and (b) this version (among others) includes the content of the authentic versions but adds incongruous sections referring to a peer-to-peer digital transaction system involving transactions being structured into “an ongoing chain of hash-based proof-of-work” to preclude double-spending or replay attacks. See {Day2/56:22} to {Day2/77:18}. Key aspects of his explanations and their deficiencies are addressed below. 121. This document is a forgery. Its content is not authentic to 2002, as Dr Wright claims it is. His attempts to explain away the indications of forgery should be rejected for the following reasons: 121.1. A version of this document in disclosure which Mr Madden has established as apparently authentic to 2002 ({ID000013}) is an internally coherent plan for an IT security system with three stages, in which the Stage 3 is described as the Final Phase and the budget covers three stages. It includes nothing about a digital transaction system, still less one involving a chain of hash-based proof-of-work. 121.2. Similarly, a project plan for this IT project which Dr Wright actually submitted to AusIndustry in 2003 has the same content as that apparently authentic document: {L1/113/1} [p8ff. Both the application form {L/113/3} and the project plan {L/113/8} were consistent in their description of the project. Neither says anything about a digital transaction system, still less one involving a chain of hash-based proof-of-work. 121.3. Even an apparently authentic version of the project plan in disclosure which dates to March 2009 {ID_001016} shows the project in the same terms, concluding with Stage 3 and including nothing about a digital currency system. 121.4. In this reliance document {ID_001379}, as in some other (similarly inauthentic) versions of the project plan in disclosure, Dr Wright has added an Abstract (at p4) which describes a digital transaction system similar to Bitcoin. The Abstract bears no obvious relation to the various other parts of the document, which are survivals of the authentic version, such as the Overall Objective section at p6 and the Assessment Against the Selection Criteria section at p8. Dr Wright has also added a few references to a Stage 4 involving the development of the supposed digital transaction system. However, he has forgotten to modify the budget on p11-12, which makes no financial provision for the supposed Stage 4 and still describes Stage 3 as the Final Phase. 121.5. In the Kleiman trial, Dr Wright said that parts of the Bitcoin White Paper went back to his “2002 AusIndustry filings for research and development”: see {L17/327/93}. When that evidence was put to him in this trial, he insisted that the document including the supposed Stage 4 elements of the project (involving a digital transaction system) “would have been filed [with AusIndustry] in 2002 and then in 2003”: {Day2/72:24}. That evidence was flatly contradicted by the actual AusIndustry filing from July 2003 (summarised above). 121.6. Dr Wright has attempted to account for these documents by a confused narrative of different versions of the document being in existence in 2002 and 2009 and used for different purposes, while the version control was in a state of chaos (see transcript reference above). The documents tell their own clear story: that Dr Wright produced an IT security project plan in 2002, which he used for tax concession applications, but he later (from 2014) doctored that plan to bolt on sections reflecting features of the Bitcoin system in order to promote his false claim to have been involved in creating that system. (d) Conclusion (d) Conclusion 122. I am entirely satisfied that the Project BlackNet paper was forged by Dr Wright. Continue Reading Here. Continue Reading Here . Here About HackerNoon Legal PDF Series: We bring you the most important technical and insightful public domain court case filings. This court case retrieved on January 29, 2024, judiciary.uk is part of the public domain. The court-created documents are works of the federal government, and under copyright law, are automatically placed in the public domain and may be shared without legal restriction. About HackerNoon Legal PDF Series: We bring you the most important technical and insightful public domain court case filings. This court case retrieved on January 29, 2024, judiciary.uk is part of the public domain. The court-created documents are works of the federal government, and under copyright law, are automatically placed in the public domain and may be shared without legal restriction. judiciary.uk judiciary.uk

So, About That BlackNet Paper... Looks Like It’s Not from 2002 After All

Sidechains are independent blockchains that connect to their parent chains via a two-way bridge. This bridge allows the transfer of assets between the two. These sidechains have some sovereignty, operating using their consensus mechanism. This means even if the sidechain has a security  breach, the mainnet will remain secure. The primary purpose of the sidechain is simple — to help scale the parent blockchain. Although that  can sound a lot like Layer 2 blockchains, sidechains have some fundamental differences. Just like Rootstock is a side chain of Bitcoin, there are many side chains for other crypto networks, Ex: Ethereum has Polygon, Skale. Fundamentals of Sidechains Sidechains are integral to enhancing blockchain functionality and efficiency. Understanding what sidechains are and their role is fundamental to grasping how blockchain technology can evolve to meet growing demand. A  sidechain is an independent blockchain that connects to a parent  blockchain (main chain) using a two-way peg mechanism. The primary  purpose of sidechains is to alleviate scalability issues, increase  throughput, and foster innovation without overburdening the main chain.  Sidechains enable you to conduct transactions and smart contracts off  the main chain, resulting in faster processing times and potentially  lower transaction costs. When  you transfer assets from the main blockchain to a sidechain, the assets  are locked on the main chain, and an equivalent number of tokens are  minted on the sidechain. This process ensures that asset quantities are  conserved across both chains. Structurally,  sidechains are equipped with consensus mechanisms that can be similar  to or different from the parent chain. This flexibility in choosing a  consensus model allows sidechains to experiment with various governance  models and security protocols, customizing them for specific use cases. Now, transactions on older networks such as Ethereum or Bitcoin are notoriously slow and expensive for users, problems that accelerate  as more people use those networks. This makes them impossible to use on a  mainstream basis. So how can the utility of blockchain be brought to  bear on a larger scale? Well, improving a blockchain’s scalability also impacts its security  and decentralization. As such, layer 2 blockchains employ different  methods in order to scale their parent networks. But before we dive into  the details, let’s learn the basics: What Is A Layer 2 Blockchain? A layer 2 blockchain is a network that aims to scale its parent  network by handling part of the blockchain’s capabilities with a  secondary chain. There are a few different layer 2 scaling solutions and  each of them has its advantages and disadvantages. But what is the  point of a layer 2 blockchain anyway? What Is a Layer 2 Blockchain For? The Problem With Layer 1 Blockchains The two most obvious examples of a Layer 1 network are Bitcoin and  Ethereum. These blockchains are base networks – they handle every aspect  of every blockchain transaction on-chain and without assistance from any other network. But this makes transactions on those blockchains extremely heavy and slow. Every single new blockchain transaction must be validated by the network. Then, before a new block is added to  the chain, it must be checked against the entire history of the network.  There are no shortcuts in layer 1 blockchains. Scalability is the ability of a system to handle increased load or  traffic. In the context of blockchains, it is the ability to process  more transactions per second (TPS) in order to meet the growing demands  of users, something that layer 1 networks really struggle with. A good analogy would be to imagine adding bricks to a pile – only,  instead of adding each new brick to the top of the pile, you’re adding  it to the bottom. To add a new brick, you have to pick up all of the  existing bricks. Plus, that pile is constantly growing and becoming  heavier, and there is also more demand than ever for new bricks to be  added. So each new addition becomes a heavier, slower job. On the other hand, the  sheer computational power required to complete this process is what  keeps the network – and your crypto – secure. But on the other hand, it  renders the system totally impractical for day-to-day use. Essentially, that’s exactly how blockchains work, and how they can become slow and congested. How Layer 2s Scale Blockchains Layer 2 blockchains are so-called because they sit as a second layer on top of a base mainnet. Layer 2 has one main purpose: to allow the network to process more  transactions per second. Accordingly, they move transactions off of the heavy mainnet. Different layer 2 solutions achieve this in slightly  different ways, but the objective is always the same: streamlining the  amount of information that needs to be validated by cumbersome  underlying blockchain. There are a multitude of layer 2 blockchain solutions and each of them have their advantages and disadvantages. Types of Layer 2 Blockchain Sidechains Sidechains are independent blockchains that have their own consensus mechanisms and then connect to their parent chains via a two-way bridge. This blockchain bridge allows the transfer of assets between the two. In short, the layer 2 network can execute transactions cheaper and faster, but they also have a connection to the parent chain. This allows the user to bridge their assets back and forth and benefit from the transaction speed a separate chain can offer. While that’s a simplification, make sure you check out our article on what a sidechain is to find out the details. Rollups Blockchain rollups are another type of layer 2 solution that involves pushing multiple crypto transactions together in one block. This means they are processed in a single transaction, which reduces fees for the user, but also saves data space on the blockchain, which can otherwise cause network congestion. There are two main types; Optimistic and ZK Rollups. Both rollup types consolidate transactions, but some methods are more decentralized than others. Optimism is a great example of a chain that uses optimistic rollups to scale Ethereum. Why Are Layer 2 Blockchains So Important? Lower Cost and More Efficient for Users For users, these blockchains are dramatically faster and cheaper to  use. Keeping the nuts and bolts of low-value transactions off-chain  means users can transfer assets quickly and with minimal network costs. Broader Blockchain Utility By facilitating transfers of value that are fast and efficient, layer  2 solutions open up broader possibilities for blockchain application. A  great example of its possible impact includes El Salvador, where  Bitcoin is legal tender. To illustrate, this would not have been  possible without the speed and efficiency of the Lightning Network. Relieves the Mainnet Layer 2 solutions don’t just benefit their users, but also the crypto  ecosystem as a whole. With large segments of the network activity  handled off-chain, congested mainnets are relieved of much of their  traffic. This means a faster, more efficient system for transactions on  the parent network. Plus, users pay lower transaction fees than they  would on the parent chain too. Opinion/Thoughts As web3.0 grows and the  inflow of users increases  blockchain technology will be improving  exponentially manner and we need to adopt various different forms of solutions, Side chains and layer 2 are such examples of it without worrying about the future one can only work in the present So on that said Have a nice day! Sidechains are independent blockchains that connect to their parent chains via a two-way bridge. This bridge allows the transfer of assets between the two. These sidechains have some sovereignty, operating using their consensus mechanism. This means even if the sidechain has a security  breach, the mainnet will remain secure. The primary purpose of the sidechain is simple — to help scale the parent blockchain. Although that  can sound a lot like Layer 2 blockchains , sidechains have some fundamental differences. Layer 2 blockchains Just like Rootstock is a side chain of Bitcoin, there are many side chains for other crypto networks, Ex: Ethereum has Polygon , Skale . Polygon Skale Fundamentals of Sidechains Fundamentals of Sidechains Sidechains are integral to enhancing blockchain functionality and efficiency. Understanding what sidechains are and their role is fundamental to grasping how blockchain technology can evolve to meet growing demand. A  sidechain is an independent blockchain that connects to a parent  blockchain (main chain) using a two-way peg mechanism. The primary  purpose of sidechains is to alleviate scalability issues, increase  throughput, and foster innovation without overburdening the main chain.  Sidechains enable you to conduct transactions and smart contracts off  the main chain, resulting in faster processing times and potentially  lower transaction costs. When  you transfer assets from the main blockchain to a sidechain, the assets  are locked on the main chain, and an equivalent number of tokens are  minted on the sidechain. This process ensures that asset quantities are  conserved across both chains. Structurally,  sidechains are equipped with consensus mechanisms that can be similar  to or different from the parent chain. This flexibility in choosing a  consensus model allows sidechains to experiment with various governance  models and security protocols, customizing them for specific use cases. Now, transactions on older networks such as Ethereum or Bitcoin are notoriously slow and expensive for users, problems that accelerate  as more people use those networks. This makes them impossible to use on a  mainstream basis. So how can the utility of blockchain be brought to  bear on a larger scale? Well, improving a blockchain’s scalability also impacts its security  and decentralization. As such, layer 2 blockchains employ different  methods in order to scale their parent networks. But before we dive into  the details, let’s learn the basics: What Is A Layer 2 Blockchain? What Is A Layer 2 Blockchain? A layer 2 blockchain is a network that aims to scale its parent  network by handling part of the blockchain’s capabilities with a  secondary chain. There are a few different layer 2 scaling solutions and  each of them has its advantages and disadvantages. But what is the  point of a layer 2 blockchain anyway? What Is a Layer 2 Blockchain For? What Is a Layer 2 Blockchain For? The Problem With Layer 1 Blockchains The Problem With Layer 1 Blockchains The two most obvious examples of a Layer 1 network are Bitcoin and  Ethereum. These blockchains are base networks – they handle every aspect  of every blockchain transaction on-chain and without assistance from any other network. But this makes transactions on those blockchains extremely heavy and slow. Every single new blockchain transaction must be validated by the network. Then, before a new block is added to  the chain, it must be checked against the entire history of the network.  There are no shortcuts in layer 1 blockchains. Scalability is the ability of a system to handle increased load or  traffic. In the context of blockchains, it is the ability to process  more transactions per second (TPS) in order to meet the growing demands  of users, something that layer 1 networks really struggle with. A good analogy would be to imagine adding bricks to a pile – only,  instead of adding each new brick to the top of the pile, you’re adding  it to the bottom. To add a new brick, you have to pick up all of the  existing bricks. Plus, that pile is constantly growing and becoming  heavier, and there is also more demand than ever for new bricks to be  added. So each new addition becomes a heavier, slower job. On the other hand, the  sheer computational power required to complete this process is what  keeps the network – and your crypto – secure. But on the other hand, it  renders the system totally impractical for day-to-day use. Essentially, that’s exactly how blockchains work, and how they can become slow and congested. How Layer 2s Scale Blockchains How Layer 2s Scale Blockchains Layer 2 blockchains are so-called because they sit as a second layer on top of a base mainnet. Layer 2 has one main purpose: to allow the network to process more  transactions per second. Accordingly, they move transactions off of the heavy mainnet. Different layer 2 solutions achieve this in slightly  different ways, but the objective is always the same: streamlining the  amount of information that needs to be validated by cumbersome  underlying blockchain. There are a multitude of layer 2 blockchain solutions and each of them have their advantages and disadvantages. Types of Layer 2 Blockchain Sidechains Sidechains Sidechains are independent blockchains that have their own consensus mechanisms and then connect to their parent chains via a two-way bridge. This blockchain bridge allows the transfer of assets between the two. In short, the layer 2 network can execute transactions cheaper and faster, but they also have a connection to the parent chain. This allows the user to bridge their assets back and forth and benefit from the transaction speed a separate chain can offer. While that’s a simplification, make sure you check out our article on what a sidechain is to find out the details. Rollups Rollups Blockchain rollups are another type of layer 2 solution that involves pushing multiple crypto transactions together in one block. This means they are processed in a single transaction, which reduces fees for the user, but also saves data space on the blockchain, which can otherwise cause network congestion. There are two main types; Optimistic and ZK Rollups. Both rollup types consolidate transactions, but some methods are more decentralized than others. Optimism is a great example of a chain that uses optimistic rollups to scale Ethereum. Why Are Layer 2 Blockchains So Important? Why Are Layer 2 Blockchains So Important? Lower Cost and More Efficient for Users For users, these blockchains are dramatically faster and cheaper to  use. Keeping the nuts and bolts of low-value transactions off-chain  means users can transfer assets quickly and with minimal network costs. Broader Blockchain Utility By facilitating transfers of value that are fast and efficient, layer  2 solutions open up broader possibilities for blockchain application. A  great example of its possible impact includes El Salvador, where  Bitcoin is legal tender. To illustrate, this would not have been  possible without the speed and efficiency of the Lightning Network. Relieves the Mainnet Layer 2 solutions don’t just benefit their users, but also the crypto  ecosystem as a whole. With large segments of the network activity  handled off-chain, congested mainnets are relieved of much of their  traffic. This means a faster, more efficient system for transactions on  the parent network. Plus, users pay lower transaction fees than they  would on the parent chain too. Opinion/Thoughts As web3.0 grows and the  inflow of users increases  blockchain technology will be improving  exponentially manner and we need to adopt various different forms of solutions, Side chains and layer 2 are such examples of it without worrying about the future one can only work in the present So on that said Have a nice day!

What Are Side Chains?     

Trump v. United States Court Filing, retrieved on July 1, 2024, is part of HackerNoon’s Legal PDF Series. You can jump to any part in this filing here. This part is 18 of 21. JUSTICE JACKSON, dissenting. JUSTICE SOTOMAYOR has thoroughly addressed the Court’s flawed reasoning and conclusion as a matter of history, tradition, law, and logic. I agree with every word of her powerful dissent. I write separately to explain, as succinctly as I can, the theoretical nuts and bolts of what, exactly, the majority has done today to alter the paradigm of accountability for Presidents of the United States. I also address what that paradigm shift means for our Nation moving forward. I To fully appreciate the profound change the majority has wrought, one must first acknowledge what it means to have immunity from criminal prosecution. Put simply, immunity is “exemption” from the duties and liabilities imposed by law. Black’s Law Dictionary 898 (11th ed. 2019); see Hopkins v. Clemson, 221 U. S. 636, 643 (1911) (explaining that immunity is “exemption from legal process”). In its purest form, the concept of immunity boils down to a maxim— “‘[t]he King can do no wrong’”—a notion that was firmly “rejected at the birth of [our] Republic.” Clinton v. Jones, 520 U. S. 681, 697, n. 24 (1997) (quoting 1 W. Blackstone, Commentaries *246 (Blackstone)); see United States v. Burr, 25 F. Cas. 30, 34 (No. 14,692d) (CC Va. 1807). To say that someone is immune from criminal prosecution is to say that, like a King, he “is not under the coercive power of the law,” which “will not suppose him capable of committing a folly, much less a crime.” 4 Blackstone *33. Thus, being immune is not like having a defense under the law. Rather, it means that the law does not apply to the immunized person in the first place. Conferring immunity therefore “create[s] a privileged class free from liability for wrongs inflicted or injuries threatened.” Hopkins, 221 U. S., at 643. It is indisputable that immunity from liability for wrongdoing is the exception rather than the rule in the American criminal justice system. That is entirely unsurprising, for the very idea of immunity stands in tension with foundational principles of our system of Government. It is a core tenet of our democracy that the People are the sovereign, and the Rule of Law is our first and final security. “[F]rom their own experience and their deep reading in history, the Founders knew that Law alone saves a society from being rent by internecine strife or ruled by mere brute power however disguised.” United States v. Mine Workers, 330 U. S. 258, 308 (1947) (Frankfurter, J., concurring in judgment). A corollary to that principle sets the terms for this case: “No man in this country is so high that he is above the law. No officer of the law may set that law at defiance with impunity. All the officers of the government, from the highest to the lowest, are creatures of the law, and are bound to obey it.” United States v. Lee, 106 U. S. 196, 220 (1882). We have long lived with the collective understanding that “[d]ecency, security and liberty alike demand that government officials shall be subjected to the same rules of conduct that are commands to the citizen,” for “[i]n a government of laws, existence of the government will be imperilled if it fails to observe the law scrupulously.” Olmstead v. United States, 277 U. S. 438, 485 (1928) (Brandeis, J., dissenting). Continue Reading Here. About HackerNoon Legal PDF Series: We bring you the most important technical and insightful public domain court case filings.
This court case retrieved on July 1, 2024, supremecourt.gov is part of the public domain. The court-created documents are works of the federal government, and under copyright law, are automatically placed in the public domain and may be shared without legal restriction. Trump v. United States Court Filing, retrieved on July 1, 2024, is part of HackerNoon’s Legal PDF Series. You can jump to any part in this filing here. This part is 18 of 21. Trump v. United States Court Filing, retrieved on July 1, 2024, is part of HackerNoon’s Legal PDF Series . You can jump to any part in this filing here . This part is 18 of 21. HackerNoon’s Legal PDF Series here JUSTICE JACKSON, dissenting. JUSTICE JACKSON, dissenting. JUSTICE SOTOMAYOR has thoroughly addressed the Court’s flawed reasoning and conclusion as a matter of history, tradition, law, and logic. I agree with every word of her powerful dissent. I write separately to explain, as succinctly as I can, the theoretical nuts and bolts of what, exactly, the majority has done today to alter the paradigm of accountability for Presidents of the United States. I also address what that paradigm shift means for our Nation moving forward. I To fully appreciate the profound change the majority has wrought, one must first acknowledge what it means to have immunity from criminal prosecution. Put simply, immunity is “exemption” from the duties and liabilities imposed by law. Black’s Law Dictionary 898 (11th ed. 2019); see Hopkins v. Clemson, 221 U. S. 636, 643 (1911) (explaining that immunity is “exemption from legal process”). In its purest form, the concept of immunity boils down to a maxim— “‘[t]he King can do no wrong’”—a notion that was firmly “rejected at the birth of [our] Republic.” Clinton v. Jones, 520 U. S. 681, 697, n. 24 (1997) (quoting 1 W. Blackstone, Commentaries *246 (Blackstone)); see United States v. Burr, 25 F. Cas. 30, 34 (No. 14,692d) (CC Va. 1807). To say that someone is immune from criminal prosecution is to say that, like a King, he “is not under the coercive power of the law,” which “will not suppose him capable of committing a folly, much less a crime.” 4 Blackstone *33. Thus, being immune is not like having a defense under the law. Rather, it means that the law does not apply to the immunized person in the first place. Conferring immunity therefore “create[s] a privileged class free from liability for wrongs inflicted or injuries threatened.” Hopkins, 221 U. S., at 643. It is indisputable that immunity from liability for wrongdoing is the exception rather than the rule in the American criminal justice system. That is entirely unsurprising, for the very idea of immunity stands in tension with foundational principles of our system of Government. It is a core tenet of our democracy that the People are the sovereign, and the Rule of Law is our first and final security. “[F]rom their own experience and their deep reading in history, the Founders knew that Law alone saves a society from being rent by internecine strife or ruled by mere brute power however disguised.” United States v. Mine Workers, 330 U. S. 258, 308 (1947) (Frankfurter, J., concurring in judgment). A corollary to that principle sets the terms for this case: “No man in this country is so high that he is above the law. No officer of the law may set that law at defiance with impunity. All the officers of the government, from the highest to the lowest, are creatures of the law, and are bound to obey it.” United States v. Lee, 106 U. S. 196, 220 (1882). We have long lived with the collective understanding that “[d]ecency, security and liberty alike demand that government officials shall be subjected to the same rules of conduct that are commands to the citizen,” for “[i]n a government of laws, existence of the government will be imperilled if it fails to observe the law scrupulously.” Olmstead v. United States, 277 U. S. 438, 485 (1928) (Brandeis, J., dissenting). Continue Reading Here. Continue Reading Here . Here About HackerNoon Legal PDF Series: We bring you the most important technical and insightful public domain court case filings. This court case retrieved on July 1, 2024, supremecourt.gov is part of the public domain. The court-created documents are works of the federal government, and under copyright law, are automatically placed in the public domain and may be shared without legal restriction. About HackerNoon Legal PDF Series: We bring you the most important technical and insightful public domain court case filings. This court case retrieved on July 1, 2024, supremecourt.gov is part of the public domain. The court-created documents are works of the federal government, and under copyright law, are automatically placed in the public domain and may be shared without legal restriction. supremecourt.gov

Justice Jackson Breaks Down What Trump v United States Means

AI Regulations and Standards - ISO/IEC 42001

Med-Flamingo: a Multimodal Medical Few-shot Learner - Discussion, Acknowledgments, and References

Authors:
(1) Michael Moor, Department of Computer Science, Stanford University, Stanford, USA and these authors contributed equally to this work;
(2) Qian Huang, Department of Computer Science, Stanford University, Stanford, USA and these authors contributed equally to this work;
(3) Shirley Wu, Department of Computer Science, Stanford University, Stanford, USA;
(4) Michihiro Yasunaga, Department of Computer Science, Stanford University, Stanford, USA;
(5) Cyril Zakka, Department of Cardiothoracic Surgery, Stanford Medicine, Stanford, USA;
(6) Yash Dalmia, Department of Computer Science, Stanford University, Stanford, USA;
(7) Eduardo Pontes Reis, Hospital Israelita Albert Einstein, Sao Paulo, Brazil;
(8) Pranav Rajpurkar, Department of Biomedical Informatics, Harvard Medical School, Boston, USA;
(9) Jure Leskovec, Department of Computer Science, Stanford University, Stanford, USA. Table of Links Abstract and 1 Introduction 2 Related Works 3 Med-Flamingo 4 Evaluation 5 Results 6 Discussion, Acknowledgments, and References A Appendix 2 RELATED WORKS The success of large language models (LLMs) Brown et al.; Liang et al. (2022); Qin et al. (2023) has led to significant advancements in training specialized models for the medical domain. This has resulted in the emergence of various models, including BioBERT Lee et al. (2020), ClinicalBERT Huang et al. (2019), PubMedBERT Gu et al. (2021), BioLinkBERT Yasunaga et al. (b), DRAGON Yasunaga et al. (a), BioMedLM Bolton et al., BioGPT Luo et al. (2022), and Med-PaLM Singhal et al.. Although these medical language models are typically smaller than general-purpose LLMs like GPT-3 Brown et al., they can match or even surpass their performance on medical tasks, such as medical question answering. Recently, there has been a growing interest in extending language models to handle vision-language multimodal data and tasks Su et al. (2019); Ramesh et al.; Alayrac et al. (2022); Aghajanyan et al.; Yasunaga et al. (2023). Furthermore, many medical applications involve multimodal information, such as radiology tasks that require the analysis of both X-ray images and radiology reports Tiu et al. (2022). Motivated by these factors, we present a medical vision-language model (VLM). Existing medical VLMs include BiomedCLIP Zhang et al. (2023a), MedVINT Zhang et al. (2023b). While BiomedCLIP is an encoder-only model, our focus lies in developing a generative VLM, demonstrating superior performance compared to MedVINT. Finally, Llava-Med is another recent medical generative VLM Li et al. (2023), however the model was not yet available for benchmarking. This paper is available on arxiv under CC BY-NC-SA 4.0 DEED license. Authors: (1) Michael Moor, Department of Computer Science, Stanford University, Stanford, USA and these authors contributed equally to this work; (2) Qian Huang, Department of Computer Science, Stanford University, Stanford, USA and these authors contributed equally to this work; (3) Shirley Wu, Department of Computer Science, Stanford University, Stanford, USA; (4) Michihiro Yasunaga, Department of Computer Science, Stanford University, Stanford, USA; (5) Cyril Zakka, Department of Cardiothoracic Surgery, Stanford Medicine, Stanford, USA; (6) Yash Dalmia, Department of Computer Science, Stanford University, Stanford, USA; (7) Eduardo Pontes Reis, Hospital Israelita Albert Einstein, Sao Paulo, Brazil; (8) Pranav Rajpurkar, Department of Biomedical Informatics, Harvard Medical School, Boston, USA; (9) Jure Leskovec, Department of Computer Science, Stanford University, Stanford, USA. Authors: Authors: (1) Michael Moor, Department of Computer Science, Stanford University, Stanford, USA and these authors contributed equally to this work; (2) Qian Huang, Department of Computer Science, Stanford University, Stanford, USA and these authors contributed equally to this work; (3) Shirley Wu, Department of Computer Science, Stanford University, Stanford, USA; (4) Michihiro Yasunaga, Department of Computer Science, Stanford University, Stanford, USA; (5) Cyril Zakka, Department of Cardiothoracic Surgery, Stanford Medicine, Stanford, USA; (6) Yash Dalmia, Department of Computer Science, Stanford University, Stanford, USA; (7) Eduardo Pontes Reis, Hospital Israelita Albert Einstein, Sao Paulo, Brazil; (8) Pranav Rajpurkar, Department of Biomedical Informatics, Harvard Medical School, Boston, USA; (9) Jure Leskovec, Department of Computer Science, Stanford University, Stanford, USA. Table of Links Abstract and 1 Introduction Abstract and 1 Introduction 2 Related Works 2 Related Works 3 Med-Flamingo 3 Med-Flamingo 4 Evaluation 4 Evaluation 5 Results 5 Results 6 Discussion, Acknowledgments, and References 6 Discussion, Acknowledgments, and References A Appendix A Appendix 2 RELATED WORKS The success of large language models (LLMs) Brown et al.; Liang et al. (2022); Qin et al. (2023) has led to significant advancements in training specialized models for the medical domain. This has resulted in the emergence of various models, including BioBERT Lee et al. (2020), ClinicalBERT Huang et al. (2019), PubMedBERT Gu et al. (2021), BioLinkBERT Yasunaga et al. (b), DRAGON Yasunaga et al. (a), BioMedLM Bolton et al., BioGPT Luo et al. (2022), and Med-PaLM Singhal et al.. Although these medical language models are typically smaller than general-purpose LLMs like GPT-3 Brown et al., they can match or even surpass their performance on medical tasks, such as medical question answering. Recently, there has been a growing interest in extending language models to handle vision-language multimodal data and tasks Su et al. (2019); Ramesh et al.; Alayrac et al. (2022); Aghajanyan et al.; Yasunaga et al. (2023). Furthermore, many medical applications involve multimodal information, such as radiology tasks that require the analysis of both X-ray images and radiology reports Tiu et al. (2022). Motivated by these factors, we present a medical vision-language model (VLM). Existing medical VLMs include BiomedCLIP Zhang et al. (2023a), MedVINT Zhang et al. (2023b). While BiomedCLIP is an encoder-only model, our focus lies in developing a generative VLM, demonstrating superior performance compared to MedVINT. Finally, Llava-Med is another recent medical generative VLM Li et al. (2023), however the model was not yet available for benchmarking. This paper is available on arxiv under CC BY-NC-SA 4.0 DEED license. This paper is available on arxiv under CC BY-NC-SA 4.0 DEED license. available on arxiv

Med-Flamingo: a Multimodal Medical Few-shot Learner - Related Works

Warp Core of Confidence: How Blockchain Creates Trust in the Digital Frontier

Everyone has issues with some member of their family at some point in their lives. It is not an ideal situation for anyone, and it takes more away from you than the situation itself is worth. Some of us have the foresight to see the issue and are able to address them before it gets worse. Then there are others who let past situations define their future with their loved ones and it ends in regret and sadness. This Father’s Day has come and gone, and this is the first Father’s Day I have had without a father. It’s also the first Father’s Day that I have thought of others who do not have a father and the struggles that they have. There are a lot of people in the world who are missing out on the knowledge and wisdom passed down from father to son. This article is from me to you as a gift for this year’s Father’s Day. I will share with you what I was taught as a child and how it helped shape me into the man I am today. “You only have one shot, and you better make it count”. One of our family traditions is hunting. I am one of kids that went to grandma’s house with the living room full of deer head trophies. I am sure there are a lot of you out there that have the same family decorations. Most of them belonged to my grandfather. He was a WWI veteran and an expert marksman. Every time he picked up a firearm, I would stop whatever I was doing and watch in amazement. I was a kid and really didn’t know much about firearms, but I knew I wanted to be just like him. The day came that I got my “shot”. I was a teenager and was able to participate in hunting for the first time. My grandfather bought me a single shot 12 gauge to practice with and eventually hunt with. I just had to get my grandfather’s approval after proving I was going to be safe. This was also followed by going to a firearms course and getting a permit. This involved many days of target practice and black and blue shoulder pain. After finishing my class and getting my permit, my grandfather agreed to take me hunting with him in the morning. This was a big moment for me as a kid and as an adult now. I loved my grandfather and him inviting me to something was an amazing feeling. Morning came and my grandmother woke me up. I put on all my clothes and my boots. I went into the kitchen and my grandpa was sitting at the table dressed and ready. We sat for a few minutes, but he didn’t waste any time and we got ready to head out for our first hunt. We rode into the darkness of morning till we reached the tree stand. My grandfather wanted me to have his tree stand for my first hunt. His tree stand was considered to be the “Cadillac” to my family members. He watched me climb up the tree stand and get settled in. He gave me a Snickers bar if I got hungry and he gave me one bullet. I asked him if I needed more because one didn’t seem like enough. He replied, “You only need one bullet, and you better make it count”. Needless to say, I hunted for 4 years and never killed anything. I just wasn’t good at it and really didn’t like sitting in the woods when I could have been doing exciting things. The one bullet speech never left my mind. I used it later in my life when it came to jobs, life and opportunities. The jest of it is, if something great happens in your life, go for it and don’t look back. “You only have one shot, and you better make it count”. “Return it better than when you borrowed it”. I followed my grandpa everywhere he went. He owned a 91-acre farm that was passed down from the Great Depression. It was a small farm that consisted of cows, pigs, ducks, geese, rabbits and dogs. It kept him very busy, and he loved and lived the family farm. The day came that my grandpa let me work with him in his workshop. His workshop was full of all kind’s tools and retro memorabilia from the 40’s and on. He had an old metal fridge that was full of nuts and bolts and other items. He had a wood stove that would keep the place warm when the winters came. It was a sacred place to the family and being invited in was a blessing to anyone he asked. He was working on something that had broken and asked me to help. I was really excited and couldn’t wait to get started. I also did not have a clue what I was doing. He showed me all the tools and what was going to be needed to fix what was broken. I watched with amazement of every turn of a wrench and every move my grandpa would make. I also didn’t repeat any word he ever said in the shop. When we finished, he asked me to put back all the tools. He didn’t tell me where they go because he wanted me to become familiar with what tools look like and what they go with. As I placed a wrench on a shelf, he stopped me. He said, “Do you see how this wrench looks?”. I said yes, its dirty. He says, “Anytime you borrow something, return it better than when you borrowed it”. He then cleans the wrench and places it back on the shelf. He was never mean or upset when it came to lessons, and I was always wanting to learn more. Recently, a neighbor told me to borrow his zero-turn mower when it came to mowing my yard. He wanted to help me from roasting in the sun when it came time to mow. I own a lot and a half and have two children. An hour outside while my wife is watching kids can be a very long time for a person. Especially when one of them is Autistic. 😂 I took him up on his offer and mowed my yard in under 40 minutes. It made my life so much easier, and I was very thankful for him. Once I was done with the yard, I washed and dried the mower and returned it. My neighbor was shocked that I took the time to wash his mower. I replied that my grandfather taught me “Return it better than when you borrowed it”. I have never forgot this important lesson and always try to practice it when I can. When life brings you situations like this, always apply it and it will be returned to you in full. “Talk is cheap, whiskey costs money”. When I was a teenager, I was able to keep up with my grandpa. I was able to farm with him as well as walks, gardening, shooting and anything he wanted. Things were getting fun for me because he always saw me as an equal. Every once and a while, I would challenge him to a shooting contest with an old Coke can. Just like they did in the old John Wayne movies…without coke. He loved John Wayne films and anything cowboy. I placed the coke can on a post and walked away. I said you only get one shot to knock the can off the post and you win. We took a few paces back and got ready. I said I was going to win, and I was going to brag about it all day. He said, “Talk is cheap, whiskey costs money”. I didn’t know what that meant at the time. I was the first to shoot and missed. When it came to grandpas turn, it took one shot, and it was over. In life you are going to be faced with many decisions that will challenge you. Be ready to stand by your word and try your best. A man is only as good as his word. Even if you fail at trying, you at least have to show up and try. I hope that these brief memories help and guide you this Father’s Day. Know that you are loved and are needed and people like you. Always love your family through everything. Be the person that is there no matter what happens in life and pay attention to the lessons taught. You never know when your last lesson will be. All the best. Everyone has issues with some member of their family at some point in their lives. It is not an ideal situation for anyone, and it takes more away from you than the situation itself is worth. Some of us have the foresight to see the issue and are able to address them before it gets worse. Then there are others who let past situations define their future with their loved ones and it ends in regret and sadness. This Father’s Day has come and gone, and this is the first Father’s Day I have had without a father. It’s also the first Father’s Day that I have thought of others who do not have a father and the struggles that they have. There are a lot of people in the world who are missing out on the knowledge and wisdom passed down from father to son. This article is from me to you as a gift for this year’s Father’s Day. I will share with you what I was taught as a child and how it helped shape me into the man I am today. “You only have one shot, and you better make it count”. One of our family traditions is hunting. I am one of kids that went to grandma’s house with the living room full of deer head trophies. I am sure there are a lot of you out there that have the same family decorations. Most of them belonged to my grandfather. He was a WWI veteran and an expert marksman. Every time he picked up a firearm, I would stop whatever I was doing and watch in amazement. I was a kid and really didn’t know much about firearms, but I knew I wanted to be just like him. The day came that I got my “shot”. I was a teenager and was able to participate in hunting for the first time. My grandfather bought me a single shot 12 gauge to practice with and eventually hunt with. I just had to get my grandfather’s approval after proving I was going to be safe. This was also followed by going to a firearms course and getting a permit. This involved many days of target practice and black and blue shoulder pain. After finishing my class and getting my permit, my grandfather agreed to take me hunting with him in the morning. This was a big moment for me as a kid and as an adult now. I loved my grandfather and him inviting me to something was an amazing feeling. Morning came and my grandmother woke me up. I put on all my clothes and my boots. I went into the kitchen and my grandpa was sitting at the table dressed and ready. We sat for a few minutes, but he didn’t waste any time and we got ready to head out for our first hunt. We rode into the darkness of morning till we reached the tree stand. My grandfather wanted me to have his tree stand for my first hunt. His tree stand was considered to be the “Cadillac” to my family members. He watched me climb up the tree stand and get settled in. He gave me a Snickers bar if I got hungry and he gave me one bullet. I asked him if I needed more because one didn’t seem like enough. He replied, “You only need one bullet, and you better make it count”. Needless to say, I hunted for 4 years and never killed anything. I just wasn’t good at it and really didn’t like sitting in the woods when I could have been doing exciting things. The one bullet speech never left my mind. I used it later in my life when it came to jobs, life and opportunities. The jest of it is, if something great happens in your life, go for it and don’t look back. “You only have one shot, and you better make it count”. “Return it better than when you borrowed it”. I followed my grandpa everywhere he went. He owned a 91-acre farm that was passed down from the Great Depression. It was a small farm that consisted of cows, pigs, ducks, geese, rabbits and dogs. It kept him very busy, and he loved and lived the family farm. The day came that my grandpa let me work with him in his workshop. His workshop was full of all kind’s tools and retro memorabilia from the 40’s and on. He had an old metal fridge that was full of nuts and bolts and other items. He had a wood stove that would keep the place warm when the winters came. It was a sacred place to the family and being invited in was a blessing to anyone he asked. He was working on something that had broken and asked me to help. I was really excited and couldn’t wait to get started. I also did not have a clue what I was doing. He showed me all the tools and what was going to be needed to fix what was broken. I watched with amazement of every turn of a wrench and every move my grandpa would make. I also didn’t repeat any word he ever said in the shop. When we finished, he asked me to put back all the tools. He didn’t tell me where they go because he wanted me to become familiar with what tools look like and what they go with. As I placed a wrench on a shelf, he stopped me. He said, “Do you see how this wrench looks?”. I said yes, its dirty. He says, “Anytime you borrow something, return it better than when you borrowed it”. He then cleans the wrench and places it back on the shelf. He was never mean or upset when it came to lessons, and I was always wanting to learn more. Recently, a neighbor told me to borrow his zero-turn mower when it came to mowing my yard. He wanted to help me from roasting in the sun when it came time to mow. I own a lot and a half and have two children. An hour outside while my wife is watching kids can be a very long time for a person. Especially when one of them is Autistic. 😂 I took him up on his offer and mowed my yard in under 40 minutes. It made my life so much easier, and I was very thankful for him. Once I was done with the yard, I washed and dried the mower and returned it. My neighbor was shocked that I took the time to wash his mower. I replied that my grandfather taught me “Return it better than when you borrowed it”. I have never forgot this important lesson and always try to practice it when I can. When life brings you situations like this, always apply it and it will be returned to you in full. “Talk is cheap, whiskey costs money”. When I was a teenager, I was able to keep up with my grandpa. I was able to farm with him as well as walks, gardening, shooting and anything he wanted. Things were getting fun for me because he always saw me as an equal. Every once and a while, I would challenge him to a shooting contest with an old Coke can. Just like they did in the old John Wayne movies…without coke. He loved John Wayne films and anything cowboy. I placed the coke can on a post and walked away. I said you only get one shot to knock the can off the post and you win. We took a few paces back and got ready. I said I was going to win, and I was going to brag about it all day. He said, “Talk is cheap, whiskey costs money”. I didn’t know what that meant at the time. I was the first to shoot and missed. When it came to grandpas turn, it took one shot, and it was over. In life you are going to be faced with many decisions that will challenge you. Be ready to stand by your word and try your best. A man is only as good as his word. Even if you fail at trying, you at least have to show up and try. I hope that these brief memories help and guide you this Father’s Day. Know that you are loved and are needed and people like you. Always love your family through everything. Be the person that is there no matter what happens in life and pay attention to the lessons taught. You never know when your last lesson will be. All the best.

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