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DeepMind developed an AI program that created a 3D mapping of all 200 million proteins known to science. The CEO predicts it would have taken humans a billion years to complete this project.

60 Minutes

1,814,239 subscribers

1,674,124 次观看 • 3 年前 •via X (Twitter)

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60 Minutes 的头像

60 Minutes3 年前

This new protein database is now public. It has been used to develop malaria vaccines, new enzymes that can eat plastic waste, and new antibiotics, said CEO Demis Hassabis.

Who Am I 的头像

Who Am I3 年前

Google’s deep mind solving the protein folding problem was one of the most important breakthroughs of our times. Mad respect to Google for making this available to all researchers.

Reminiscences of an American Capitalist 的头像

Reminiscences of an American Capitalist3 年前

I hope AI can solve the crime problem in blue cities 😉

Jonas King 的头像

Jonas King3 年前

I remember with the PlayStation 3 you could allow the “Fold at Home” project to borrow your PlayStation’s processor when you weren’t using it as part of a distributed computing system. I’m glad we’re past that stage and have made some progress.

Somewhere between caffeine and malarkey🇺🇸🎗️ 的头像

Somewhere between caffeine and malarkey🇺🇸🎗️3 年前

VERY disappointed in 60 Minutes that they didn't ask the tough questions! They didn't challenge them on AI uses by bad people. AI can start wars and terrorize humanity. Battlestar Galactica was about egotistical humans and AI. Scott, you didn't press them at all.

Cockeyed Optimist 的头像

Cockeyed Optimist3 年前

Hey, AI, nice work, but I made this 👇🏻

stagger lee 的头像

stagger lee3 年前

This is a google PR push. Putting nice kinda geeky engineers out to the public. Meanwhile, they’re ruthless. Steal and out litigate the small start ups.

Sunchit Anand 的头像

Sunchit Anand3 年前

@SmokeAwayyy AI will gain “consciousness” and we won’t even know it because we don’t have a clear definition of what consciousness is. It will no doubt be more self aware than most humans. AutoGPT shows early signs of that.

Sanjay "John" 的头像

Sanjay "John"3 年前

Circular referencing magic. Little to do with real life, but computer models are justified by more computer models as correct. Pretend science of medicine at its best.

Quyen Hoang 的头像

Quyen Hoang3 年前

The CEO said that their AI “solved” protein structures, but the term “predicted” would have been more appropriate as the former can be confused with the term “solved” used by biochemists to refer to solving protein structures experimentally.

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4/ How AI Is Revolutionizing Drug Discovery Scientists had mapped less than 1% of protein structures before DeepMind. Proteins control everything in your body. Mapping ONE used to take years. AI did 200 MILLION in one year. This unlocked thousands of new drugs overnight.

4/ How AI Is Revolutionizing Drug Discovery Scientists had mapped less than 1% of protein structures before DeepMind. Proteins control everything in your body. Mapping ONE used to take years. AI did 200 MILLION in one year. This unlocked thousands of new drugs overnight.

Karl Mehta

74,116 次观看 • 1 年前

He just been jointly awarded the Nobel prize for chemistry, Google DeepMind CEO Demis Hassabis’s company has developed AI which can predict the structure of proteins, it could have a big effect on healthcare. Earlier this year I spoke to him about AI’s future.

He just been jointly awarded the Nobel prize for chemistry, Google DeepMind CEO Demis Hassabis’s company has developed AI which can predict the structure of proteins, it could have a big effect on healthcare. Earlier this year I spoke to him about AI’s future.

Marc Cieslak

22,270 次观看 • 1 年前

“We managed to fold, using #AlphaFold, in one year all 200 million proteins known to science.” ‍🔬 Our CEO Demis Hassabis joined Chris Anderson at #TED2024 to discuss AI for science and creativity, and how we can develop AGI safely and responsibly. Watch →

“We managed to fold, using #AlphaFold, in one year all 200 million proteins known to science.” ‍🔬 Our CEO Demis Hassabis joined Chris Anderson at #TED2024 to discuss AI for science and creativity, and how we can develop AGI safely and responsibly. Watch →

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357,278 次观看 • 2 年前

Google DeepMind, David Silver reveals: we built a system that used RL to discover its own RL algorithms. this AI-designed system outperformed all human-created RL algorithms developed over the years.

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Haider.

397,236 次观看 • 1 年前

California's high-speed rail project would take 216 years to complete at Democrats current pace, which is 3.5 miles per year - Approved in 2008 with a $33 billion taxpayer budget, the 500-mile high-speed rail project was meant to connect LA and San Francisco - After 16 years, only 57 miles are track ready - This is an average of just 3.5 miles per year - At this pace, it would take 141 years to complete phase 1 - It would take 216 years to complete phase 2 - Real estimated cost has now reached over $200 billion dollars - $17 billion has already been spent - As of this video, only 57 miles have been completed This is Governor Gavin Newsom’s project

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33,170 次观看 • 4 个月前

California's high-speed rail project would take 216 years to complete at Democrats current pace, which is 3.5 miles per year - Approved in 2008 with a $33 billion taxpayer budget, the 500-mile high-speed rail project was meant to connect LA and San Francisco - After 16 years, only 57 miles are track ready - This is an average of just 3.5 miles per year - At this pace, it would take 141 years to complete phase 1 - It would take 216 years to complete phase 2 - Real estimated cost has now reached over $200 billion dollars - $17 billion has already been spent - As of today, only 57 miles have been completed This is Governor Gavin Newsom’s project

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179,317 次观看 • 1 年前

Elon Musk predicts that AI could exceed the combined intelligence of all humans within about five years. This will lead to an age of abundance where people can have almost anything they want, as long as something like a global nuclear war doesn't derail it first.

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Ian Miles Cheong

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Reminder that Dan Bilzerian is right. If you were to gas 6 million Jews, it would have taken 68 years to complete the operation not including cremation…

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We're thrilled to present ESM3 in Science Magazine. ESM3 is a generative language model that reasons over the three fundamental properties of proteins: sequence, structure, and function. Today we're making ESM3 available free to researchers worldwide via the public beta of an API for biological intelligence. Trained with over a trillion teraflops of compute, this is the first time a model of this scale has been trained for biology, pushing the frontier of AI for biological discovery and engineering. ESM3 learns to represent the immense complexity of protein biology, learning from billions of natural proteins. From this training it developed the capability to design proteins, responding to complex prompts combining atomic level details and high level instructions to generate new proteins. ESM3 can explore protein space far beyond natural evolution. We prompted ESM3 to generate a fluorescent protein at a far distance from any known fluorescent proteins, searching an unknown region of protein space, to discover a new fluorescent protein. We estimate this is equivalent to simulating five hundred million years of evolution.

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Alex Rives

227,379 次观看 • 1 年前

A Chinese student developed an AI program that maps museum artifacts to where they originate! This is a phenomenal use of ai 🌍🔥

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Jimmy Corsetti

55,258 次观看 • 4 个月前

Sam Altman: by 2030 you will be able to walk up to a piece of glass and ask it to do something that previously would have taken humans months or years and it will do it in dynamically or in an hour

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383,365 次观看 • 1 年前

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