Chinese researchers developed a photonic chip, the OPCA, capable of processing 100 billion pixels in 6 nanoseconds, revolutionizing high-speed image processing for edge AI applications.
Category: robotics/AI – Page 249
The use of AI to streamline drug discovery is exploding. Researchers are deploying machine-learning models to help them identify molecules, among billions of options, that might have the properties they are seeking to develop new medicines.
👉 Runway has introduced Gen-3 Alpha, a new AI model that offers significant improvements in detail, consistency, and motion representation in the generated videos compared to its predecessor, Gen-2.
Runway has introduced Gen-3 Alpha, a new AI model for video generation. According to Runway, it represents a “significant improvement” over its predecessor, Gen-2, in terms of detail, consistency, and motion representation.
Gen-3 Alpha has been trained on a mix of video and images and, like its predecessor, which was launched in November 2023, supports text-to-video, image-to-video, and text-to-image functions, as well as control modes such as Motion Brush, Advanced Camera Controls, and Director Mode. Additional tools are planned for the future to provide even greater control over structure, style, and motion.
Runway Gen-3 Alpha: First model in a series with new infrastructure
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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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.
👉 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*.
A new way to teach artificial intelligence (AI) to understand human line drawings—even from non-artists—has been developed by a team from the University of Surrey and Stanford University.
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 electronic waste, 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.
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