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DARPA has launched a competition to find AI solutions that can help with sourcing critical minerals.

Critical minerals are raw, non-fuel materials that are vital for manufacturing products that are essential to national security.

DARPA is teaming up with the US Geological Survey (USGS) to explore how machine learning and AI can accelerate critical mineral assessments.

By scientists from Inserm, CNRS, and Université de Montpellier at the Structural Biology Center in Montpellier. The nano-robot could lead to a closer study of the mechanical forces applied at microscopic levels, which are important for various biological and pathological processes.

The study was published in Nature Communications.

Cellular Mechanosensitivity

Realize that today’s AI is not able to “think” in any fashion on par with human thinking. When you interact with Alexa or Siri, the conversational capacities might seem akin to human capacities, but the reality is that it is computational and lacks human cognition. The latest era of AI has made extensive use of Machine Learning (ML) and Deep Learning (DL), which leverage computational pattern matching. This has led to AI systems that have the appearance of human-like proclivities. Meanwhile, there isn’t any AI today that has a semblance of common sense and nor has any of the cognitive wonderment of robust human thinking.

ML/DL is a form of computational pattern matching.


AI Asymmetry is getting larger and worsening, particularly via the advent of fully autonomous systems, and for which society needs to be aware of and considering devising remedies such as arming more with AI to essentially fight fire with fire.