System can look through research and propose new hypotheses – which appear to be correct.
Category: robotics/AI – Page 85
Imagine being able to speed up evolution – hypothetically – to learn which genes might have a harmful or beneficial effect on human health. Imagine, further, being able to rapidly generate new genetic sequences that could help cure disease or solve environmental challenges.
Now, scientists have developed a generative AI tool that can predict the form and function of proteins coded in the DNA of all domains of life, identify molecules that could be useful for bioengineering and medicine, and allow labs to run dozens of other standard experiments with a virtual query – in minutes or hours instead of years (or millennia).
Trained on a dataset that includes all known living species – and a few extinct ones – Evo 2 can predict the form and function of proteins in the DNA of all domains of life.
Plastic that conducts electricity might sound impossible. But there is a special class of materials known as “electronic polymers” that combines the flexibility of plastic with the functionality of metal. This type of material opens the door for breakthroughs in wearable devices, printable electronics and advanced energy storage systems.
Yet, making thin films from electronic polymers has always been a difficult task. It takes a lot of fine-tuning to achieve the right balance of physical and electronic properties. Researchers at the U.S. Department of Energy’s (DOE) Argonne National Laboratory have created an innovative solution to this challenge with artificial intelligence (AI).
They used an AI-driven, automated materials laboratory, a tool called Polybot, to explore processing methods and produce high-quality films. Polybot is located at the Center for Nanoscale Materials, a DOE Office of Science user facility at Argonne.
Last video: Why Tesla Energy Will Take Over in 2025
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Welcome to the Tesla Space, where we share the latest news, rumors, and insights into all things Tesla, Space X, Elon Musk, and the future! We’ll be showing you all of the new details around the Tesla Model 3 2023, Tesla Model Y 2023, along with the Tesla Cybertruck when it finally arrives, it’s already ordered!
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In today’s AI news, Codeium, an AI-powered coding startup, is raising a new round of funding at a $2.85 billion valuation. The round is being led by returning investor Kleiner Perkins, the people said. The new round comes just six months after Silicon Valley-based Codeium announced that it had closed a $150 million Series C at a $1.25 billion post-money valuation.
In other advancements, a couple of weeks after the initial release of Mistral’s AI assistant, Le Chat, the company told Le Parisien that it has reached one million downloads. “Go and download Le Chat, which is made by Mistral, rather than ChatGPT by OpenAI — or something else,” French president Emmanuel Macron said in a TV interview ahead of the recent AI Action Summit in Paris.
And, Google is launching a new experiment that uses AI to help people explore more career possibilities. The company announced in a blog post on Wednesday that a new “Career Dreamer” tool can find patterns between your experiences, educational background, skills, and interests to connect you with careers that might be a good fit.
Meanwhile, Forbes’ Lance Eliot analyzes a popular mantra right now. The recent AI-industry groupthink that says we merely need to increase the so-called “thinking time” of generative AI and LLMs to get better responses. AI makers are allowing users to stipulate that the AI can expend more time and effort doing various processing before displaying a generated answer.
In videos, Microsoft’s Satya Nadella sits down with Dwarkesh Patel to talk about their new Majorana Quantum chip breakthrough, plans for artificial general intelligence, topological qubits, gaming world models, and whether Microsoft Office commoditizes LLMs, or the other way around.
Then, dive into the world of Model Context Protocol and learn how to seamlessly connect AI agents to databases, APIs, and more. IBM’s Roy Derks breaks down its components, from hosts to servers, and showcases real-world applications. Gain the knowledge to revolutionize your AI projects.
Are Biological Systems More Intelligent Than Artificial Intelligence?. Are Biological Systems More Intelligent Than Artificial Intelligence?
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W/ michael timothy bennett australian national university.
Speakers: Michael Timothy Bennett, Cecile Tamura
A study led by Professor Ginestra Bianconi from Queen Mary University of London, in collaboration with international researchers, has unveiled a transformative framework for understanding complex systems.
Published in Nature Physics, this paper establishes the new field of higher-order topological dynamics, revealing how the hidden geometry of networks shapes everything from brain activity to artificial intelligence.
“Complex systems like the brain, climate, and next-generation artificial intelligence rely on interactions that extend beyond simple pairwise relationships. Our study reveals the critical role of higher-order networks, structures that capture multi-body interactions, in shaping the dynamics of such systems,” said Professor Bianconi.
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Future Day is coming up — no fees — just pure uncut futurology — spanning timezones — Feb 28th-March 1st.
We have: * Hugo de Garis on AI, Humanity & the Longterm * Linda MacDonald Glenn on Imbuing AI with Wisdom * James Barrat discussing new book ‘The Intelligence Explosion’ * Kristian Rönn on The Darwinian Trap * Phan, Xuan Tan on AI Safety in Education * Robin Hanson on Cultural Drift * James Hughes & James Newton-Thomas discussing Human Wage Crash & UBI * James Hughes on The Future Virtual You * Ben Goertzel & Hugo de Garis doing a Singularity Salon * Susan Schneider, Ben Goertzel & Robin Hanson discussing Ghosts in the Machine: Can AI Ever Wake Up? * Shun Yoshizawa (& Ken Mogi?) on LLM Metacognition.
Why not celebrate the amazing future we are collectively creating?
Have you ever questioned the true nature of time? Some physicists claim that time is just an illusion, but our lived experience suggests otherwise. In his latest work, Temporal Mechanics: D-Theory as a Critical Upgrade to Our Understanding of the Nature of Time, cyberneticist Alex M. Vikoulov explores how time is deeply rooted in information processing by conscious systems. From species-specific time perception to the implications of Quantum AI’s accelerated mentation, this video presents some mind-bending ideas in the physics of time. Could an advanced superintelligence manipulate its own past states? Could time itself be an editable construct? Could an AI with advanced temporal modeling actually see every possible future simultaneously?
*Preview TEMPORAL MECHANICS eBook/Audiobook on Amazon:
*Preview Audiobook on Audible:
https://www.audible.com/pd/Audiobook/B0CY9HXWXX
#TemporalMechanics #PhysicsofTime #TimeTravel