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BlackLight Power says it’s developing a revolutionary energy source—and it won’t let the laws of physics stand in its way

7 min read
Randell Mills
Photo: David Yellen

This is part of IEEE Spectrum’s SPECIAL REPORT: WINNERS & LOSERS 2009, The Year's Best and Worst of Technology.

Randell Mills Wizard of Watts: Randell Mills, founder of BlackLight Power, says his reactor liberates energy from hydrogen in a totally new way. Photo: David Yellen

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Water Scarcity Concerns Drive Semiconductor Industry to Adopt New Technologies

Boosting water recycling at fabs by up to 98 percent keeps chip production on target

3 min read
Pipes and gauges in a small brightly lit space

The inside of Gradiant's mobile unit showcasing the CFRO system which is under the company's RO infinity product line

Gradiant

In these days of seemingly neverending chip shortages, more and greater varieties of semiconductors are in demand. Chip fabs around the world are now racing to catch up to the world's many microelectronic needs. And chip fabs need a lot of water to operate.

By some estimates, a large chip fab can use up to 10 million gallons of water a day, which is equivalent to the water consumption of roughly 300,000 households.

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Meta Aims to Build the World’s Fastest AI Supercomputer

The AI Research SuperCluster could help the company develop real-time voice translations

3 min read
A brightly lit, high-ceilinged room with rows of silvery-black cabinets and yellow pipes near the ceiling.

Meta’s new AI supercomputer.

Meta

Meta, parent company of Facebook, says it has built a research supercomputer that is among the fastest on the planet. By the middle of this year, when an expansion of the system is complete, it will be the fastest, Meta researchers Kevin Lee and Shubho Sengupta write in a blog post today. The AI Research SuperCluster (RSC) will one day work with neural networks with trillions of parameters, they write. The number of parameters in neural network models have been rapidly growing. The natural language processor GPT-3, for example, has 175 billion parameters, and such sophisticated AIs are only expected to grow.

RSC is meant to address a critical limit to this growth, the time it takes to train a neural network. Generally, training involves testing a neural network against a large data set, measuring how far it is from doing its job accurately, using that error signal to tweak the network’s parameters, and repeating the cycle until the neural network reaches the needed level of accuracy. It can take weeks of computing for large networks, limiting how many new networks can be trialed in a given year. Several well-funded startups, such as Cerebras and SambaNova, were launched in part to address training times.

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Electric utility infrastructure habitually falls prey to overgrown Right-of-Way, high winds, and harsh weather. Impactful events causing outages are increasing in frequency, and need to be endured without major disruptions in electric service. This webinar will discuss the application of covered aerial conductor to "harden" the electric utility grid so that unpredictable events don't result in unsustainable outages.

Speaker:

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