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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.

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 .

“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.

Link in comments!


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

Everyone is talking about AI. Do you think it will surpass human intelligence? And what consequences will this have?

We need to focus primarily on how artificial intelligence will transform the workforce and job market. For instance, AI will be a key component of humanoid robots’ brains. Tesla is already producing them, and I believe that within the next 5 years, every automotive company is likely to produce their own version. This makes sense because automotive companies already have the assembly lines and engineering expertise to produce all the small components needed to build them. We’re already amazed by what AI can do today—imagine what it will do in 5 or 10 years, and then think about what it could do when integrated into a humanoid robot. It’s already confirmed through commercial orders with current manufacturers that major fast-food franchise chains and other chains, for example, in the transportation sector, will test humanoid robots within their processes. AI is already skilled in programming tasks and will soon be able to enhance itself.

Summary: Researchers analyzed human motivation from an evolutionary perspective, identifying 15 key motives that drive behavior. These motives, grouped into five categories—environmental, physiological, reproductive, psychological, and social—reflect adaptations that helped early humans survive.

The study used network analysis of survey responses to reveal how these motives interconnect and influence one another. Notably, Status and Play emerged as central to motivational structures, facilitating resource access and skill development.

Findings also showed age and gender differences in motivational priorities, with younger individuals focusing on Status and Play, while older adults prioritize Comfort and Fear. The results have broad applications in marketing, AI, and mental health, helping tailor strategies to different motivational needs.

AI-driven service robot maker Richtech Robotics has launched an accelerator program to provide U.S. universities with development frameworks and access to the Richtech robotic systems to aid robotics research.

The program would grant participating universities access to the Richtech autonomous mobile robots and robotic arm platforms powered by Nvidia technology. The technology includes machine vision and voice interaction modules.

The AI robotics technology includes the service robots Adam and Scorpion, which were featured at CES in January.