Oxygen isn’t always a good thing. Of course, people—and most organisms—cannot live without it. But oxygen can also be quite toxic and lead to profound health consequences.
I’ve been playing with local AI models; AI you can run on your own computer for years now. Each year it gets better and better. Similar to the online cloud-based frontier models (you know them). I won’t go into all the advantages of running open source models on your own local hardware, the reasons are somewhat obvious.
Spielberg’s Disclosure Day reopened a question I’ve carried since childhood: what happens when humanity learns it was never alone?
Exactly how those dendrites form is still up for debate. While the interface between the battery’s electrolyte and electrodes has been the focus of most research, another culprit is the boundary where two grains of electrolyte in a solid material meet. Researchers know these boundaries can seed dendrites within electrolytes, although the effects have been difficult to study.
Now researchers at MIT and the Technical University of Munich have uncovered why such boundaries can lead to dendrites: Hidden electrical imbalances across the boundaries affect how the electrolyte conducts electrical charges, which influences how the ions and electrons move through the material during battery operation. In a paper published today in Nature Nanotechnology, the researchers characterized the electrical and chemical behavior of the boundaries and showed that adjusting how the electrolyte is processed enhances the movement of ions while reducing electron leakage. This adjustment can increase critical current density by more than 300 percent, which could enable solid-state batteries that charge faster and last longer.
Here I discuss definition of set, subset, proper subset, de Morgan’s law, Associative law, Cartesian product with theory and solve two maths problem.
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In the next decade, AI will likely undergo more significant changes than only becoming more independent; it will also grow more cognitive. AI systems will act as interconnected ecosystems that are capable of contextual awareness, cooperative reasoning, ongoing learning, and adaptive decision-making in almost every facet of society, rather than isolated applications.
Large language models of today are remarkable due to their ability to produce and anticipate information. Persistent memory, multimodal perception, long-term planning, causal reasoning, and self-directed learning within strictly regulated bounds will probably be characteristics of the AI of 2036. Similar to biological neural networks, millions of specialized AI agents will work together to create dynamic intelligence fabrics that continuously optimize national defense, manufacturing, transportation, financial markets, healthcare delivery, and energy grids.
The line between workforce and software will become increasingly hazy. Hundreds of thousands of AI agents working continuously alongside human employees may be employed by organizations as digital workforces. A customized constellation of AI advisers, researchers, legal assistants, financial analysts, engineers, and cybersecurity specialists working around the clock could be present for every knowledge worker. This shift signifies the emergence of an entirely new digital labor force in addition to automation.
Further reading.
Thumbnail image credit: Paper cited in video.
Unsupervised sensory-motor associative learning by human brain explant in-a-dish enables movement imitation by robot.
https://www.researchsquare.com/articl…
The lab.
Not alive. but not dea: disembodied human brains used for drug testing.
https://www.science.org/content/artic…
#science #brain #technology #news #explained