Lifeboat Foundation

Neural networks have a remarkable ability to learn specific tasks, such as identifying handwritten digits. However, these models often experience “catastrophic forgetting” when taught additional tasks: They can successfully learn the new assignments, but “forget” how to complete the original. For many artificial neural networks, like those that guide self-driving cars, learning additional tasks thus requires being fully reprogrammed.

Biological brains, on the other hand, are remarkably flexible. Humans and animals can easily learn how to play a new game, for instance, without having to re-learn how to walk and talk.

Inspired by the flexibility of human and animal brains, Caltech researchers have now developed a new type of algorithm that enables neural networks to be continuously updated with new data that they are able to learn from without having to start from scratch. The algorithm, called a functionally invariant path (FIP) algorithm, has wide-ranging applications from improving recommendations on online stores to fine-tuning self-driving cars.

Sometimes, the LLMs have the internal knowledge to self-correct their responses. They just need the right training technique to use it.

China’s state-backed JFS Laboratory has unveiled the country’s first silicon photonics chip, a significant advancement that could revolutionize AI and high-performance computing. This novel technology uses lasers instead of traditional copper wires, offering increased bandwidth, reduced latency, and improved energy efficiency.

Engineers at King’s College London created a fluid pressure circuit that enables robots to operate independently of electricity.

Summary: Researchers have developed an AI-powered “electronic tongue” capable of distinguishing subtle differences in liquids, such as milk freshness, soda types, and coffee blends. By analyzing sensor data through a neural network, the device achieved over 95% accuracy in identifying liquid quality, authenticity, and potential safety issues. Interestingly, when the AI was allowed to select its own analysis parameters, it outperformed human-defined settings, showing how it holistically assessed subtle data.

This technology, which uses graphene-based sensors, could revolutionize food safety assessments and potentially extend to medical diagnostics. The device’s AI insights also provide a unique view into the neural network’s decision-making process. This innovation promises practical applications across industries where quality and safety are paramount.

Two researchers whose work has led to the AI revolution won the 2024 Nobel Prize in physics. A materials physicist explains statistical mechanics, the physics field behind their discoveries.

University of Toronto professor Geoffrey Hinton has been awarded the Nobel Prize in Physics for his work in AI. Adrian Ghobrial has more.

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Continue reading “Meet Geoffrey Hinton: Winner of the 2024 Nobel Prize in Physics” »

The US Department of Justice (DoJ) has submitted a new “Proposed Remedy Framework” to correct Google’s violation of antitrust antitrust laws in the country (h/t Mishaal Rahman). This framework seeks to remedy the harm caused by Google’s search distribution and revenue sharing, generation and display for search results, advertising scale and monetization, and accumulation and use of data.

The most drastic of the proposed solutions includes preventing Google from using its products, such as Chrome, Play, and Android, to advantage Google Search and related products. Other solutions include allowing websites to opt-out of training or appearing in Google-owned AI products, such as in AI Overviews in Google Search.

Google responded to this by asserting that “DOJ’s radical and sweeping proposals risk hurting consumers, businesses, and developers.” While the company intends to respond in detail to DoJ’s final proposals, it says that the DoJ is “already signaling requests that go far beyond the specific legal issues in this case.”

Research that eliminates the guesswork in developing advanced 3D printed materials could help accelerate the development of new forms of “self-sensing” airplanes, robots, bridges and more.