If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
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Graphics processing units from Nvidia are too hard to program, including with Nvidia's own programming tool, CUDA, according to artificial intelligence research firm OpenAI. The San Francisco-based AI startup, which is backed by Microsoft and VC firm Khosla ventures, on Wednesday introduced the 1.0 version a new programming language specially crafted to ease that burden, called Triton, detailed in a blog post, with the link to GitHub source code. OpenAI claims Triton can deliver substantial ease-of-use benefits over coding in CUDA for some neural network tasks at the heart of machine learning forms of AI such as matrix multiplies. "Our goal is for it to become a viable alternative to CUDA for Deep Learning," the leader of the effort, OpenAI scientist Philippe Tillet, told ZDNet via email. Triton "is for machine learning researchers and engineers who are unfamiliar with GPU programming despite having good software engineering skills," said Tillet.
This post is sponsored by NVIDIA. AI is enabling digital transformation across the financial services industry, from fintech and investment firms to commercial and retail banks. With AI, banks can better protect their customers' accounts, secure payments, improve return on investments, and personalize content, investments, and next-action recommendations for their customers. These AI-enabled services were also the top use cases for AI found in the NVIDIA "State of AI in Financial Services" survey of C-suite leaders, managers, developers and IT architects in the global financial industry: fraud detection, portfolio optimization, and sales and marketing enablement. The growing capabilities of AI and increase in available data mean that financial firms need to execute an AI strategy, or risk being left behind their competitors.
Contentsquare, which has developed a digital experience analytics platform that enables businesses to track online customer behavior, has acquired Upstride, a French startup specializing in improving machine-learning performance. Terms of the deal were not released. With the acquisition, Contentsquare gains Upstride's deep-learning experts to help it further drive innovation in ML and artificial intelligence. Fourteen Upstride engineers will join Contentsquare, bringing their experience of working for leading tech companies such as Facebook, Samsung, GoPro, and Nvidia. Meanwhile, Upstride CEO Gary Roth will fill a strategic role on Contentsquare's operations team.
Like Dogecoin devotees, the mayor of Reno, and the leaders of El Salvador, Aldo Baoicchi is convinced cryptocurrency is the future. The CEO and founder of Canadian scooter maker Daymak believes this so strongly that when he unveiled the company's first autonomous car last month, the 2023 Spiritus, he touted a bonus feature: the ability to mine cryptocurrency when the car is parked. Baiocchi told WIRED the company is still developing software for this purpose, but designers want cryptomining for car owners to be as simple as pressing a button. He says solar power on the roof of the three-wheeled electric car should help offset the energy consumption of mining Bitcoin. "We have the equipment in the car. We figure we might as well mine and make some money for the rider," he said.
AI could be the 21st century's biggest new industry. Long a focal point of science fiction, AI is no longer a curious theme to ponder for the distant future -- it's here. The best artificial intelligence stocks to buy already use processes like machine learning and neural networks on a daily basis. In fact, if you took away AI capabilities from the following companies, their profitability would instantly plummet -- and five of them are trillion-dollar businesses, underscoring the new technology's importance to 2021's economy. The growth of artificial intelligence is also enviable.
Nvidia is launching the $100 million Cambridge-1, the most powerful supercomputer in the United Kingdom, and it is making it available to external researchers in the U.K. health care industry. The machine will be used for AI research in health care, and it's one of the world's fastest supercomputers. Nvidia will make it available to accelerate research in digital biology, genomics, and quantum computing. Nvidia is collaborating with AstraZeneca, maker of one of the COVID-19 vaccines, to fuel faster drug discoveries and creating a transformer-based generative AI model for chemical structures. Transformer-based neural network architectures, which have become available only in the last several years, allow researchers to leverage massive datasets using self-supervised training methods, avoiding the need for manually labeled examples during pre-training.
Artificial intelligence is now helping to design computer chips--including the very ones needed to run the most powerful AI code. Sketching out a computer chip is both complex and intricate, requiring designers to arrange billions of components on a surface smaller than a fingernail. Decisions at each step can affect a chip's eventual performance and reliability, so the best chip designers rely on years of experience and hard-won know-how to lay out circuits that squeeze the best performance and power efficiency from nanoscopic devices. Previous efforts to automate chip design over several decades have come to little. But recent advances in AI have made it possible for algorithms to learn some of the dark arts involved in chip design.
From information arrangement and preparing to show sending and past, these organizations offer best in class stages for dealing with the whole AI lifecycle. Alongside the enormous and expanding interest in AI applications, there's a correlative yearn for framework and supporting programming that makes AI applications conceivable. From information arrangement and preparation to organization and past, various new companies have shown up on the scene to direct you through the early universe of MLops. Here's a glance at a portion of the additional fascinating ones that will make your AI drives more fruitful. Loads and Biases is turning into a heavyweight presence in the AI space, particularly among information researchers who need a far-reaching and very much planned investigation following assistance.
This is the web version of Eye on A.I., Fortune's weekly newsletter covering artificial intelligence and business. To get it delivered weekly to your in-box, sign up here. Everyone can become a data scientist. That's the somewhat radical view of Alan Jacobson, the chief data and analytic officer at Alteryx, a company that sells data analytics software to many of the Fortune 500. Jacobson says that while he frequently hears executives complain about being unable to hire people with data science experience, let alone machine-learning skills, these executives are ignoring the amazing human resource already sitting inside their own organizations.