Energy-friendly chip can perform powerful artificial-intelligence tasks

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In recent years, some of the most exciting advances in artificial intelligence have come courtesy of convolutional neural networks, large virtual networks of simple information-processing units, which are loosely modeled on the anatomy of the human brain. Neural networks are typically implemented using graphics processing units (GPUs), special-purpose graphics chips found in all computing devices with screens. A mobile GPU, of the type found in a cell phone, might have almost 200 cores, or processing units, making it well suited to simulating a network of distributed processors. At the International Solid State Circuits Conference in San Francisco this week, MIT researchers presented a new chip designed specifically to implement neural networks. It is 10 times as efficient as a mobile GPU, so it could enable mobile devices to run powerful artificial-intelligence algorithms locally, rather than uploading data to the Internet for processing.


Watch a Sci-Fi Film short Written by #ArtificialIntelligence #ai

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Filmmaker Oscar Sharp and AI expert Ross Goodwin created a neural network named Benjamin (its own choice!) over the course of a year. Once the network was up and running, Benjamin wrote the script based on just a few prompts. Then, they made it into a movie. And yes, that is the guy from Silicon Valley.


Artificial Intelligence Influencers Nathaniel C Schooler

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But I write about all sorts of important business related topics and reguarly interview thoughtleaders around this and other crucial topics. If you are interested then please contact me nat@natschooler.com


AI 100: The Artificial Intelligence Startups Redefining Industries

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The 100 startups on our list have raised $11.7B in aggregate funding across 367 deals. Today, CB Insights unveiled the second annual AI 100 -- a list of 100 of the most promising private companies applying artificial intelligence algorithms across 25 industries, from healthcare to cybersecurity -- at the A-Ha! conference in San Francisco. The companies were selected from a pool of 2,000 startups based on several criteria, including investor profile, tech innovation, team strength, patent activity, mosaic score, funding history, valuation, and business model. The market map below categorizes the AI 100 companies based on their industry focus. Please click on the image to enlarge.


How advanced industrial companies should approach artificial-intelligence strategy McKinsey & Company

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Artificial intelligence (AI) has reached a commercialization tipping point. As a result of several technology advancements that are now converging, major investments by technology companies and start-ups, and demand from businesses, AI is starting to have a major impact across markets. Advanced industries such as automotive, semiconductors, and industrial manufacturing could harness AI over the next decade to discover entirely new ways to make things better, cheaper, and faster. While popular reporting on the topic often tends to focus only on generating new business ideas, companies can directly apply AI to their current core business processes and operations. However, many companies have yet to think through how they could embed AI in their strategies and businesses.