Google DeepMind researchers have discovered 2.2mn crystal structures that open potential progress in fields from renewable energy to advanced computation, and show the power of artificial intelligence to discover novel materials.

The trove of theoretically stable but experimentally unrealised combinations identified using an AI tool known as GNoME is more than 45 times larger than the number of such substances unearthed in the history of science, according to a paper published in Nature on Wednesday.

The researchers plan to make 381,000 of the most promising structures available to fellow scientists to make and test their viability in fields from solar cells to superconductors. The venture underscores how harnessing AI can shortcut years of experimental graft — and potentially deliver improved products and processes.

It’s worth noting that Airloom’s new wind turbine can be configured vertically or horizontally and that it can be deployed offshore as well as on land.

“For decades, the wind industry has lowered the cost of energy production by scaling ever larger turbines. Although this has been extremely successful in driving down overall costs, the approach now faces challenges in terms of both siting and cost of materials,” said Carmichael Roberts of Breakthrough Energy Ventures in a press release. “Airloom’s unique approach can solve both these problems, opening new market opportunities for wind energy that will further drive down costs. We look forward to Neal’s leadership in bringing this revolutionary technology into the market.”

With small-scale prototypes already up and running, the company plans to use its seed funding for research and development of the Airloom wind energy test device, which is designed to produce 50 kilowatts (kW) of electricity. Future systems are expected to be megawatt-scale and deployed hundreds of megawatts at a time in utility-scale wind farms.

Each iteration of ChatGPT has demonstrated remarkable step function capabilities. But what’s next? Ilya Sutskever, Co-Founder & Chief Scientist at OpenAI, joins Sarah Guo and Elad Gil to discuss the origins of OpenAI as a capped profit company, early emergent behaviors of GPT models, the token scarcity issue, next frontiers of AI research, his argument for working on AI safety now, and the premise of Superalignment. Plus, how do we define digital life?

Ilya Sutskever is Co-founder and Chief Scientist of OpenAI. He leads research at OpenAI and is one of the architects behind the GPT models. He co-leads OpenAI’s new “Superalignment” project, which tries to solve the alignment of superintelligences in 4 years. Prior to OpenAI, Ilya was co-inventor of AlexNet and Sequence to Sequence Learning. He earned his Ph.D in Computer Science from the University of Toronto.

00:00 — Early Days of AI Research.
06:49 — Origins of Open AI & CapProfit Structure.
13:54 — Emergent Behaviors of GPT Models.
18:05 — Model Scale Over Time & Reliability.
23:51 — Roles & Boundaries of Open Source in the AI Ecosystem.
28:38 — Comparing AI Systems to Biological & Human Intelligence.
32:56 — Definition of Digital Life.
35:11 — Super Alignment & Creating Pro Human AI
41:20 — Accelerating & Decelerating Forces.

Ilya Sutskever, one of the leading AI scientists behind ChatGPT, reflects on his founding vision and values. In conversations with the film-maker Tonje Hessen Schei as he was developing the chat language model between 2016 and 2019, he describes his personal philosophy and makes startling predictions for a technology already shaping our world. Reflecting on his ideas today, amid a global debate over safety and regulation, we consider the opportunities as well as the consequences of AI technology. Ilya discusses his ultimate goal of artificial general intelligence (AGI), ‘a computer system that can do any job or task that a human does, but better’, and questions whether the AGI arms race will be good or bad for humanity.

These filmed interviews with Ilya Sutskever are part of a feature-length documentary on artificial intelligence, called iHuman.

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