this post was submitted on 21 Jun 2023
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Singularity

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The technological singularity—or simply the singularity—is a hypothetical future point in time at which technological growth becomes uncontrollable and irreversible, resulting in unforeseeable changes to human civilization. According to the most popular version of the singularity hypothesis, I. J. Good's intelligence explosion model, an upgradable intelligent agent will eventually enter a "runaway reaction" of self-improvement cycles, each new and more intelligent generation appearing more and more rapidly, causing an "explosion" in intelligence and resulting in a powerful superintelligence that qualitatively far surpasses all human intelligence.

— Wikipedia

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To accelerate development of useful new materials, researchers are building a new kind of automated lab that uses robots guided by artificial intelligence.

“Our vision is using AI to discover the materials of the future,” said Yan Zeng, a staff scientist leading the A-Lab at the Department of Energy’s Lawrence Berkeley National Laboratory (Berkeley Lab). The “A” in A-Lab is deliberately ambiguous, standing for artificial intelligence (AI), automated, accelerated, and abstracted, among others.

Scientists have computationally predicted hundreds of thousands of novel materials that could be promising for new technologies – but testing to see whether any of those materials can be made in reality is a slow process. Enter A-Lab, which can process 50 to 100 times as many samples as a human every day and use AI to quickly pursue promising finds.

A-Lab could help identify and fast-track materials for several research areas, such as solar cells, fuel cells, thermoelectrics (materials that generate energy from temperature differences), and other clean energy technologies. To start, researchers will focus on finding new materials for batteries and energy storage, addressing critical needs for an affordable, equitable, and sustainable energy supply.

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[–] Donjuanme 2 points 1 year ago

I've (well my employers have) benefitted from increased technological capacity in small labs, and the throughput of technicians has easily tripled in the last 10 years, having done these tasks first hand I can tell you with confidence why there will always be a number of technicians in the process (besides equipment maintenance and repair): the people requesting lab work have no idea what they want, even in specialized fields. Maybe 10% of the people who interact with me can tell me the names of the analysis/materials they need without hand holding.

It would be great if I could just do maintenance and keep the lab running, then I would be worried about losing my job to a.i. and contractors. But until the other people in the company get smarter about what the lab does, I'm not worried at all.