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Category: robotics/AI – Page 236

Liquid neural networks, spiking neural networks, neuromorphic chips. The next generation of AI will be very different.
#ainews #ai #agi #singularity #neuralnetworks #machinelearning.

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Newsletter: https://aisearch.substack.com/

Continue reading “The future of AI looks like THIS (& it can learn infinitely)” | >

The exoskeleton is being developed for older adults and people with conditions like cerebral palsy:

A new method developed by researchers uses AI and computer simulations to train robotic exoskeletons to autonomously help users save energy.

Researchers from North Carolina State University, in their new study, showed the technologically advanced instrument as an achievement in reinforcement learning, a technique that trains software to make decisions.

Continue reading “AI improves human locomotion in robotic exoskeletons, saves 25% energy” | >

👉 Researchers at the Shanghai Artificial Intelligence Laboratory are combining the Monte Carlo Tree Search (MCTS) algorithm with large language models to improve its ability to solve complex mathematical problems.

Integrating the Monte Carlo Tree Search (MCTS) algorithm into large language models could significantly enhance their ability to solve complex mathematical problems. Initial experiments show promising results.

While large language models like GPT-4 have made remarkable progress in language processing, they still struggle with tasks requiring strategic and logical thinking. Particularly in mathematics, the models tend to produce plausible-sounding but factually incorrect answers.

In a new paper, researchers from the Shanghai Artificial Intelligence Laboratory propose combining language models with the Monte Carlo Tree Search (MCTS) algorithm. MCTS is a decision-making tool used in artificial intelligence for scenarios that require strategic planning, such as games and complex problem-solving. One of the most well-known applications is AlphaGo and its successor systems like AlphaZero, which have consistently beaten humans in board games. The combination of language models and MCTS has long been considered promising and is being studied by many labs — likely including OpenAI with Q*.

Continue reading “AI that defeated humans at Go could now help language models master mathematics” | >

Science and Technology: Some robots could be “eaten” so they could walk around inside the body and perform tests or surgeries from the inside out; or administer medications.

Robots made of several nanorobots joined together could assemble and reassemble themselves inside the body even after being…

Robots and food have long been distant worlds: Robots are inorganic, bulky, and non-disposable; food is organic, soft, and biodegradable. Yet, research that develops edible robots has progressed recently and promises positive impacts: Robotic food could reduce , help deliver nutrition and medicines to people and animals in need, monitor health, and even pave the way to novel gastronomical experiences.

But how far are we from having a fully edible robot for lunch or dessert? And what are the challenges? Scientists from the RoboFood project, based at EPFL, address these and other questions in a perspective article in the journal Nature Reviews Materials.

Continue reading “A fully edible robot could soon end up on our plate, say scientists” | >

https://youtu.be/Op3zYytUDDs.

Using generative AI, this time lapse sequence shows how melanoma skin cancer develops over 10 years. Starting with normal skin, slow progression to stage 4 melanoma is shown.

Obviously, such a time lapse can not be realistically accomplished as there is no way to know if any given area of skin will turn into cancer. Obviously, somebody with such future knowledge would have to start taking such photos now in the same spot over next 10 years to watch it slowly turn into cancer.

Watch time lapse video of basal cell carcinoma: https://youtube.com/shorts/d_O5zHgKnP8

Continue reading “Melanoma Skin Cancer Development Time Lapse (Normal to Stage 4 Melanoma Over 10 Years)” | >

The efforts of Jeff Hawkins and Numenta to understand how the brain works started over 30 years ago and culminated in the last two years with the publication of the Thousand Brains Theory of Intelligence. Since then, we’ve been thinking about how to apply our insights about the neocortex to artificial intelligence. As described in this theory, it is clear that the brain works on principles fundamentally different from current AI systems. To build the kind of efficient and robust intelligence that we know humans are capable of, we need to design a new type of artificial intelligence. This is what the Thousand Brains Project is about.

In the past Numenta has been very open with their research, posting meeting recordings, making code open-source and building a large community around our algorithms. We are happy to announce that we are returning to this practice with the Thousand Brains Project. With funding from the Gates Foundation, among others, we are significantly expanding our internal research efforts and also calling for researchers around the world to follow, or even join this exciting project.

Today we are releasing a short technical document describing the core principles of the platform we are building. To be notified when the code and other resources are released, please sign up for the newsletter below. If you have a specific inquiry please send us an email to [email protected].

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