Lifeboat Foundation

Tesla appears to be gearing up to launch a new Performance mode for the Model 3 and Model Y, as spotted in code from recent firmware updates.

On Sunday, Tesla code sleuth green the only posted about a “soft performance limit” option for the Model 3 and Y discovered in recent firmware, which the account says are listed as 110kW and 160kW, respectively. The discovery seems to suggest that Tesla is looking to launch a paid upgrade for the software-locked mode, allowing owners to upgrade to access full battery range.

Hm, interesting, recent firmwares bring “soft performance limit” option to Model3 and ModelY, listed as 110kW and 160kW respectively.

What if a common element rather than scarce, expensive ones was a key component in electric car batteries?

A collaboration co-led by an Oregon State University chemistry researcher is hoping to spark a green battery revolution by showing that iron instead of cobalt and nickel can be used as a cathode material in lithium-ion batteries.

The findings, published today in Science Advances, are important for multiple reasons, Oregon State’s Xiulei “David” Ji notes.

Swiss company Transmutex will use particle-accelerator technology to make uranium that produces less nuclear waste when used in fission reactions.

Grokked Transformers are Implicit Reasoners.

A mechanistic journey to the edge of generalization.

We study whether transformers can learn to implicitly reason over parametric knowledge, a skill that even the most capable language models struggle with.

Continue reading “Paper page — Grokked Transformers are Implicit Reasoners: A Mechanistic Journey to the Edge of Generalization” »

‘Hervs’ date back hundreds of thousands of years – and play an important role in regulating genes.

Mann, J., Meshkin, H., Zirkle, J. et al. Mechanism-based organization of neural networks to emulate systems biology and pharmacology models. Sci Rep 14, 12,082 (2024). https://doi.org/10.1038/s41598-024-59378-9

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The fungus Talaromyces verruculosus can produce the chemical erythro-isocitric acid directly from cheap plant waste, thus making it interesting for industrial utilization.

The public’s appetite for inexpensive and powerful electronic devices continues to grow. While silicon-based semiconductors have been key to satiating this demand, a superior alternative could be wide-bandgap semiconductors. These materials, which operate at higher temperatures and handle increased power loads, are unfortunately very expensive.

Researchers at the Princeton Plasma Physics Laboratory are harnessing artificial intelligence and machine learning to enhance fusion energy production, tackling the challenge of controlling plasma reactions. Their innovations include optimizing the design and operation of containment vessels and using AI to predict and manage instabilities, significantly improving the safety and efficiency of fusion reactions. This technology has been successfully applied in tokamak reactors, advancing the field towards viable commercial fusion energy. Credit: SciTechDaily.com.

The intricate dance of atoms fusing and releasing energy has fascinated scientists for decades. Now, human ingenuity and artificial intelligence are coming together at the U.S. Department of Energy’s (DOE) Princeton Plasma Physics Laboratory (PPPL) to solve one of humankind’s most pressing issues: generating clean, reliable energy from fusing plasma.

Unlike traditional computer code, machine learning — a type of artificially intelligent software — isn’t simply a list of instructions. Machine learning is software that can analyze data, infer relationships between features, learn from this new knowledge, and adapt. PPPL researchers believe this ability to learn and adapt could improve their control over fusion reactions in various ways. This includes perfecting the design of vessels surrounding the super-hot plasma, optimizing heating methods, and maintaining stable control of the reaction for increasingly long periods.