Google DeepMind AI uncovers potential for numerous novel materials
Google DeepMind Uses AI to Predict Structure of 2 Million New Materials
4:05 PM UTC – November 29, 2023
LONDON (Reuters) – In a groundbreaking development, Google DeepMind has harnessed the power of artificial intelligence (AI) to predict the structure of over 2 million new materials. This breakthrough has the potential to revolutionize real-world technologies.
In a research paper published in the prestigious science journal Nature on Wednesday, the AI firm owned by Alphabet (GOOGL.O) revealed that nearly 400,000 of its hypothetical material designs could soon be produced in laboratory conditions.
This groundbreaking research opens up a world of possibilities, including the potential for better-performing batteries, solar panels, and computer chips.
The process of discovering and synthesizing new materials has traditionally been expensive and time-consuming. For instance, it took approximately two decades of research before lithium-ion batteries, which now power everything from phones and laptops to electric vehicles, became commercially available.
However, Ekin Dogus Cubuk, a research scientist at DeepMind, expressed optimism about the future, stating, “We’re hoping that big improvements in experimentation, autonomous synthesis, and machine learning models will significantly shorten that 10 to 20-year timeline to something that’s much more manageable.”
DeepMind’s AI was trained using data from the Materials Project, an international research group founded in 2011 at the Lawrence Berkeley National Laboratory. This data consisted of information on approximately 50,000 known materials.
Excitingly, DeepMind has announced its intention to share its data with the wider research community, aiming to accelerate further breakthroughs in material discovery.
Kristin Persson, director of the Materials Project, highlighted the potential impact of this development, stating, “If we can shrink that even a bit more, it would be considered a real breakthrough.”
Having successfully predicted the stability of these new materials, DeepMind will now focus on predicting their synthesizability in laboratory settings.
Reporting by Martin Coulter; Editing by Jan Harvey
The Censorship Industrial Complex: An Origin Story
Independent Journalists Matt Taibbi, Michael Shellenberger, and Alex Gutentag provide an intriguing account of the Censorship Industrial Complex.
Expulsion Vote, Hunter Biden Testimony, and Farewell to Charlie Munger
Rep. George Santos faces another expulsion vote, Hunter Biden is set to testify before Congress, and Warren Buffet bids farewell to Charlie Munger.
Hearing on Second Amendment Rights and Safety
The Senate Judiciary Committee holds a hearing to discuss Americans’ Second Amendment Rights and their right to safety. One America’s Chloe Hauxwell provides insights.
Hunter Biden’s Attempt to Avoid Difficult Questions
Missouri Congressman Eric Burlison accuses Hunter Biden of trying to evade challenging questions in the Biden Impeachment Inquiry before the House Oversight Committee.
Germany’s Bitcoin Group Takes Measures
November 29, 2023 – 10:58 AM UTC BERLIN (Reuters) – Germany’s Bitcoin Group (ADE.DE) announces measures to…
Challenges Faced by Electric Vehicles
Electric vehicles continue to grapple with reliability issues related to charging and batteries, despite their increasing popularity among consumers.
Amazon’s New Chatbot for Businesses
Amazon aims to attract big corporate customers to its AWS cloud computing service with the introduction of a new chatbot designed for businesses.
rnrn
How has Google DeepMind used AI to predict the structure of over 2 million new materials?
Google DeepMind Uses AI to Predict Structure of 2 Million New Materials
4:05 PM UTC – November 29, 2023
LONDON (Reuters) – In a groundbreaking development, Google DeepMind has harnessed the power of artificial intelligence (AI) to predict the structure of over 2 million new materials. This breakthrough has the potential to revolutionize real-world technologies.
In a research paper published in the prestigious science journal Nature on Wednesday, the AI firm owned by Alphabet (GOOGL.O) revealed that nearly 400,000 of its hypothetical material designs could soon be produced in laboratory conditions.
This groundbreaking research opens up a world of possibilities, including the potential for better-performing batteries, solar panels, and computer chips.
The process of discovering and synthesizing new materials has traditionally been expensive and time-consuming. For instance, it took approximately two decades of research before lithium-ion batteries, which now power everything from phones and laptops to electric vehicles, became commercially available.
However, Ekin Dogus Cubuk, a research scientist at DeepMind, expressed optimism about the future, stating, “We’re hoping that big improvements in experimentation, autonomous synthesis, and machine learning models will significantly shorten that 10 to 20-year timeline to something that’s much more manageable.”
DeepMind’s AI was trained using data from the Materials Project, an international research group founded in 2011 at the Lawrence Berkeley National Laboratory. This data consisted of information on approximately 50,000 known materials.
Excitingly, DeepMind has announced its intention to share its data with the wider research community, aiming to accelerate further breakthroughs in material discovery.
Kristin Persson, director of the Materials Project, highlighted the potential impact of this development, stating, “If we can shrink that even a bit more, it would be considered a real breakthrough.”
Having successfully predicted the stability of these new materials, DeepMind will now focus on predicting their synthesizability in laboratory settings.
Reporting by Martin Coulter; Editing by Jan Harvey
" Conservative News Daily does not always share or support the views and opinions expressed here; they are just those of the writer."
*As an Amazon Associate I earn from qualifying purchases
