Despite the energy innovations of artificial intelligence newcomer DeepSeek’s models, AI power requirements as a whole are predicted to rise.
Researchers have developed a new material that could help to remove unwanted pollutants — including leftover medicines and synthetic chemicals — from our waterways.
Ben Lamm of ‘de-extinction’ specialist Colossal Biosciences not only has plans to bring back prehistoric creatures, but also preserve those on the verge of vanishing.
In today’s AI news, a consortium of investors led by Elon Musk is offering $97.4 billion to buy the nonprofit that controls OpenAI. The unsolicited offer adds a complication to Altman’s carefully laid plans for OpenAI’s future, including converting it to a for-profit company and spending up to $500 billion on AI infrastructure through a JV called Stargate.
In other advancements, all eyes were on French President Emmanuel Macron Sunday at the end of the first day of the AI Action Summit in Paris after he announced a €109 billion investment package. “For me, this summit is not just the announcement of a lot of investment in France. It’s a wake-up call for a European strategy,” he said.
And, Current AI, a “public interest” initiative focused on fostering and steering development of artificial intelligence in societally beneficial directions, was announced at the French AI Action summit on Monday. It’s kicking off with an initial $400 million in pledges from backers and a plan to pull in $2.5 billion more over the next five years.
Then, ZDNET contributor Jack Wallen reports his local AI of choice is the open-source Ollama. He recently wrote a piece on how to make using this local LLM easier with the help of a browser extension, which he uses on Linux. But on MacOS devices, Jack turns to an easy-to-use, free app called Msty.
In videos, At the AI Action Summit in Paris, Yann LeCun underscored a fundamental shift in artificial intelligence—one that moves beyond the brute-force approach of large language models in his presentation, “The Next AI Revolution”. The future of AI hinges on *world models*—structured, adaptive representations that can infer, reason, and plan.
The transformative power of artificial intelligence (AI) is bringing about major changes in the worlds of business and cybersecurity.
Source: Forbes.
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Human brain organoids (“mini-brains”) are being grown in labs around the world. They’re being fed neurotransmitters, competing with AI to solve non-linear equations, and going to space to study the effects of microgravity. This video reviews three preprints, preliminary reports of new scientific studies. (My AI voice caught a cold this week.)
Support the channel: https://www.patreon.com/ihmcurious.
Preprints:
Humans and certain animals appear to have an innate capacity to learn relationships between different objects or events in the world. This ability, known as “relational learning,” is widely regarded as critical for cognition and intelligence, as learned relationships are thought to allow humans and animals to navigate new situations.
Researchers at ML Collective in San Francisco and Columbia University have conducted a study aimed at understanding the biological basis of relational learning by using a particular type of brain-inspired artificial neural network. Their work, published in Nature Neuroscience, sheds new light on the processes in the brain that could underpin relational learning in humans and other organisms.
“While I was visiting Columbia University, I met my co-author Kenneth Kay and we talked about his research,” Thomas Miconi, co-author of the paper, told Medical Xpress.
This hybrid system allows precise manipulation of quantum states while naturally modeling real-world physics, enabling breakthroughs in fields like magnetism, superconductors, and even astrophysics.
Breakthrough in Quantum Simulation
Physicists working in Google’s laboratory have developed a new type of digital-analog quantum simulator, capable of studying complex physical processes with unprecedented precision and adaptability. Two researchers from PSI’s Center for Scientific Computing, Theory, and Data played a crucial role in this breakthrough.
A theoretical particle that travels faster than light, the tachyon has long intrigued physicists and fueled decades of speculation. Initially conceived as a possible solution to quantum and relativity paradoxes, tachyons remain purely hypothetical. Despite the lack of experimental evidence, they continue to serve as a thought-provoking concept in modern physics.
A recent study by an international team of researchers has reignited interest in tachyons, suggesting they might be possible within the framework of Einstein’s special theory of relativity. This bold claim challenges conventional understandings of causality and time, raising fundamental questions about the structure of reality. If confirmed, it could lead to a radical shift in how scientists perceive the limits of physical laws.
Physicist Gerald Feinberg introduced the idea of tachyons in 1962, proposing that such particles could always travel faster than light without ever slowing down to subluminal speeds. His argument was based on the concept of imaginary mass, a theoretical construct involving the square root of a negative number. This allowed for the mathematical possibility of faster-than-light motion without explicitly violating relativity.
A recent study published in Science investigates the underlying mechanisms of endothelial insulin resistance involved in obesity-associated diabetes.
What causes insulin resistance?
Diabetes is a chronic disease that occurs when the body cannot adequately produce or use insulin, a hormone that facilitates the transportation of glucose from the blood into cells for energy. The activation of insulin receptors, which are highly expressed on the luminal side of endothelial cells, induces endothelial nitric oxide (NO)-synthase (eNOS) activity. Subsequently, NO-mediated vasodilation allows insulin to reach metabolic target cells including adipocytes, skeletal muscle cells, and hepatocytes.