Lifeboat Foundation

Do #AI companies work?

“The market needs to be irrational for you to stay solvent.”

Workplace AI tools can do tasks by themselves. Getting them to stop is the problem.

The Hubbard model is a studied model in condensed matter theory and a formidable quantum problem. A team of physicists used deep learning to condense this problem, which previously required 100,000 equations, into just four equations without sacrificing accuracy. The study, titled “Deep Learning the Functional Renormalization Group,” was published on September 21 in Physical Review Letters.

Dominique Di Sante is the lead author of this study. Since 2021, he holds the position of Assistant Professor (tenure track) at the Department of Physics and Astronomy, University of Bologna. At the same time, he is a Visiting Professor at the Center for Computational Quantum Physics (CCQ) at the Flatiron Institute, New York, as part of a Marie Sklodowska-Curie Actions (MSCA) grant that encourages, among other things, the mobility of researchers.

He and colleagues at the Flatiron Institute and other international researchers conducted the study, which has the potential to revolutionize the way scientists study systems containing many interacting electrons. In addition, if they can adapt the method to other problems, the approach could help design materials with desirable properties, such as superconductivity, or contribute to clean energy production.

Artificially intelligent Maxwell’s demon for optimal control of open…

A team of researchers used reinforcement learning (RL) to optimize feedback control strategies in quantum systems.

Prof. Tim Rocktäschel, AI researcher at UCL and Google DeepMind, talks about open-ended AI systems. These systems aim to keep learning and improving on their own, like evolution does in nature.

TOC:
00:00:00 Introduction to Open-Ended AI and Key Concepts.
00:01:37 Tim Rocktäschel’s Background and Research Focus.
00:06:25 Defining Open-Endedness in AI Systems.
00:10:39 Subjective Nature of Interestingness and Learnability.
00:16:22 Open-Endedness in Practice: Examples and Limitations.
00:17:50 Assessing Novelty in Open-ended AI Systems.
00:20:05 Adversarial Attacks and AI Robustness.
00:24:05 Rainbow Teaming and LLM Safety.
00:25:48 Open-ended Research Approaches in AI
00:29:05 Balancing Long-term Vision and Exploration in AI Research.
00:37:25 LLMs in Program Synthesis and Open-Ended Learning.
00:37:55 Transition from Human-Based to Novel AI Strategies.
00:39:00 Expanding Context Windows and Prompt Evolution.
00:40:17 AI Intelligibility and Human-AI Interfaces.
00:46:04 Self-Improvement and Evolution in AI Systems.

Continue reading “Open-Ended AI: The Key to Superhuman Intelligence?” »

The startup from MIT’s CSAIL says its Liquid Foundation Models have smaller memory needs thanks to a post-transformer architecture.

Artificial intelligence applications are experiencing a boom and expected to be mainstream technologies in the near future. However, these applications run on classic computing hardware and are extremely power-hungry.

With the help of AI, 15 passages have been deciphered from a 2,000-year-old unrolled Herculaneum scroll, providing a glimpse into the thoughts of an ancient philosopher.

As technology advances, Big Data will play an increasingly important role in protecting Earth from asteroids. By harnessing the power of data analytics, AI, and machine learning, scientists can monitor and predict asteroid movements with greater accuracy than ever before. This enables us to develop early warning systems and potentially deflect asteroids before they can cause harm. Aspiring data scientists interested in contributing to such significant fields can gain the necessary skills by enrolling in a data science course in Chennai, where they can learn to utilize these advanced tools and techniques.