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Everything regarding Artificial Intelligence

  1. What's new in this club
  2. A CryptoKitties' ownership is tracked via a smart contract on the Ethereum blockchain. CryptoKitties are distributed automatically, via smart contract, at the rate of one every 15 minutes (672 per week) for one year. Each CryptoKitty is represented in the form of a non-fungible ERC-721 token, which allows for each entity to have specific cattributes. Based on the limited number of cats going into circulation and their limited genomes, there is a limit of 4 billion total cats that can be bred. Each cat will have a distinct visual appearance ("phenotype") determined by its immutable genes ("genotype") stored in the smart contract. Because cats are tokens on a blockchain, they can be bought, sold, or transferred digitally, with strong guarantees of ownership. A CryptoKitty does not have a permanently assigned gender. While they can only engage in one breeding session at one time, each cat is able to act as either matron or sire. The owner chooses with each breeding interaction. A group known as Axiom Zen innovation studio developed the game. Until November 2018, Axiom Zen intends to continually release a new CryptoKitty every 15 minutes, with the rest of supply determined by breeding of CryptoKitties. CryptoKitty owners may put them up for sale via an auction for a price set in Ether (ETH).
  3. The virtual cats are breedable and carry a unique number and 256 bit distinct genome with DNA and different attributes (cattributes) that can be passed to offspring. Several traits can be passed down from the parents to the offspring. These include pattern, mouth (shape), fur, eye shape, base color, accent color, highlight color, eye color, and optional wild and environment characteristics. Other features like cool down times are not passed down but are instead a function of the 'generation' of the offspring, which is one higher than the maximum generation between the two parents. In December 2017 a CryptoKitty sold for $100,000. On March 20, 2018, it was announced that CryptoKitties would be spun off into its own company and raised $12 million from several top venture capital firms and angel investors. The investment round was led by New York based Union Square Ventures and San Francisco based Andreessen Horowitz. In May 2018, CryptoKitties launched their first celebrity-branded CryptoKitty with Stephen Curry, an American professional basketball player. As part of the partnership, Curry was given three CryptoKitties with special imagery, the first of which he put up for auction.The company later suspended the auction, claiming that Stephen Curry wasn't as involved as they initially thought. The company was later sued for trade secret theft over the Stephen Curry collectibles. In October 2018, CryptoKitties reached the milestone of 1 million cats being bred with a volume of 3.2 million transactions on its smart contracts. In November 2018, Dapper Labs, which was spun out of Axiom Zen as the developer of CryptoKitties, raised an additional $15 million in a venture round led by Venrock. The company doubled its valuation in this round. In 2018, CryptoKitties was used by the German museum ZKM Center for Art and Media Karlsruhe to showcase blockchain technology.
  4. CryptoKitties cannot be replicated and cannot be transferred without the user's permission even by the game developers. Users can interact with their CryptoKitties, having the ability to buy, sell, and sire (breed) them. A test version of CryptoKitties was unveiled at ETH Waterloo on October 19, 2017, the largest Ethereum hackathon in the world.[citation needed] As of December 2, 2017, Genesis, the first and highest selling cat was sold for 246.9255 ETH (~$117,712 USD) on that day.
  5. CryptoKitties is a blockchain based video game developed by Axiom Zen that allows players to purchase, collect, breed and sell various types of virtual cats. It represents one of the earliest attempts to deploy blockchain technology for recreational and leisurely purposes. The game's popularity in December 2017 congested the Ethereum network, causing it to reach an all-time high in transactions and slow down significantly it completely changes the way you look at digital copies because now a days everything digital is a copy and not the original thing.
  6. Give mind to the machines and at that rate you won't be able to compete with them. Tables would turn before you can even blink an eye.
  7. Researchers at the non-profit AI research group OpenAI just wanted to train their new text generation software to predict the next word in a sentence. It blew away all of their expectations and was so good at mimicking writing by humans they’ve decided to pump the brakes on the research while they explore the damage it could do. Elon Musk has been clear that he believes artificial intelligence is the “biggest existential threat” to humanity. Musk is one of the primary funders of OpenAI and though he has taken a backseat role at the organization, its researchers appear to share his concerns about opening a Pandora’s box of trouble. This week, OpenAI shared a paper covering their latest work on text generation technology but they’re deviating from their standard practice of releasing the full research to the public out of fear that it could be abused by bad actors. Rather than releasing the fully trained model, it’s releasing a smaller model for researchers to experiment with. The researchers used 40GB of data pulled from 8 million web pages to train the GPT-2 software. That’s ten times the amount of data they used for the first iteration of GPT. The dataset was pulled together by trolling through Reddit and selecting links to articles that had more than three upvotes. When the training process was complete, they found that the software could be fed a small amount of text and convincingly continue writing at length based on the prompt. It has trouble with “highly technical or esoteric types of content” but when it comes to more conversational writing it generated “reasonable samples” 50 percent of the time. In one example, the software was fed this paragraph: Based on those two sentences, it was able to continue writing this whimsical news story for another nine paragraphs in a fashion that could have believably been written by a human being. Here are the next few machine-paragraphs that were produced by the machine: GPT-2 is remarkably good at adapting to the style and content of the prompts it’s given. The Guardian was able to take the software for a spin and tried out the first line of George Orwell’s Nineteen Eighty-Four: “It was a bright cold day in April, and the clocks were striking thirteen.” The program picked up on the tone of the selection and proceeded with some dystopian science fiction of its own: The OpenAI researchers found that GPT-2 performed very well when it was given tasks that it wasn’t necessarily designed for, like translation and summarization. In their report, the researchers wrote that they simply had to prompt the trained model in the right way for it to perform these tasks at a level that was comparable to other models that are specialized. After analyzing a short story about an Olympic race, the software was able to correctly answer basic questions like “What was the length of the race?” and “Where did the race begin?” These excellent results have freaked the researchers out. One concern they have is that the technology would be used to turbo-charge fake news operations. The Guardian published a fake news article written by the software along with its coverage of the research. The article is readable and contains fake quotes that are on topic and realistic. The grammar is better than a lot what you’d see from fake news content mills. And according to The Guardian’s Alex Hern, it only took 15 seconds for the bot to write the article. Other concerns that the researchers listed as potentially abusive included automating phishing emails, impersonating others online, and self-generating harassment. But they also believe that there are plenty of beneficial applications to be discovered. For instance, it could be a powerful tool for developing better speech recognition programs or dialogue agents. OpenAI plans to engage the AI community in a dialogue about their release strategy and hopes to explore potential ethical guidelines to direct this type of research in the future. They said they will have more to discuss in public in six months. [OpenAI via The Guardian]
  8. something doesn’t “feel” right about this. 🙂
  9. 1507940147251-drlcss.mp4 Learn more at
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  10. Talk about inciting the mobs!!! This video is very scary.
  11. We're building an artificial intelligence-powered dystopia, one click at a time, says techno-sociologist Zeynep Tufekci. In an eye-opening talk, she details how the same algorithms companies like Facebook, Google and Amazon use to get you to click on ads are also used to organize your access to political and social information. And the machines aren't even the real threat. What we need to understand is how the powerful might use AI to control us -- and what we can do in response.
  12. Having had many eye surgeries, which were painless, but I was still awake and somewhat awake ..... I hate it when they have that military powered searchlight shining directly in your eye, and you hear the doctor say " ... oops ...".
  13. Doctors across the world are beginning to rely on artificial intelligence algorithms to help accelerate diagnostics and treatment plans, with the goal of making more time to see more patients, with greater precision. We all can understand—at least conceptually—what it takes to be a doctor: years of medical school lectures attended, stacks of textbooks and journals read, countless hours of on-the-job residencies. But the way AI has learned the medical arts is less intuitive. In order to get more clarity on how algorithms learn these patterns, and what pitfalls might still lurk within the technology, Quartz partnered with Leon Chen, co-founder of medical AI startup MD.ai, and radiologist Luke Oakden-Rayner, to train two algorithms and understand how it matches with a medical professional as it learns. One detects the presence of tumorous nodules, and the second gauges the potential of it being malignant.
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