We’ve reached a new milestone in the uncanny valley, folks: AIs are now Rickrolling humans.

In a now-viral post on X-formerly-Twitter, Flo Crivello, the CEO of the AI assistant firm Lindy, explained how this bizarre memetic situation featuring Rick Astley’s 1987 hit “Never Gonna Give You Up” came to pass.

Known as “Lindys,” the company’s AI assistants are intended to help customers with various tasks. Part of a Lindy’s job is to teach clients how to use the platform, and it was during this task that the AI helper provided a link to a video tutorial that wasn’t supposed to exist.

“If pursued, we might see by the end of the decade advances in AI as drastic as the difference between the rudimentary text generation of GPT-2 in 2019 and the sophisticated problem-solving abilities of GPT-4 in 2023,” Epoch wrote in a recent research report detailing how likely it is this scenario is possible.

But modern AI already sucks in a significant amount of power, tens of thousands of advanced chips, and trillions of online examples. Meanwhile, the industry has endured chip shortages, and studies suggest it may run out of quality training data. Assuming companies continue to invest in AI scaling: Is growth at this rate even technically possible?

In its report, Epoch looked at four of the biggest constraints to AI scaling: Power, chips, data, and latency. TLDR: Maintaining growth is technically possible, but not certain. Here’s why.

The recently passed bill will impact most large AI firms in the world.

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I’m also worried that being on A.I.’s bad side could have dire consequences.

Today’s chatbots mostly seem like harmless assistants and homework helpers.

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When I set out to improve my tainted reputation with chatbots, I discovered a new world of A.I. manipulation.

Image: Prof Thomas Hartung.

Over just a few decades, computers shrunk from massive installations to slick devices that fit in our pockets. But this dizzying trend might end soon, because we simply can’t produce small enough components. To keep driving computing forward, scientists are looking for alternative approaches. An article published in Frontiers in Science presents a revolutionary strategy, called organoid intelligence.

The simplified approach makes it easier to see how neural networks produce the outputs they do.

Forward-looking: We’re approaching a point where traditional copper interconnections won’t be able to carry enough data to keep GPUs and other specialized chips fully utilized. The AI market is urgently demanding a next-generation solution to this interconnection bottleneck, and Broadcom appears to be working on an optics-based solution that is closer to the chip itself.

Broadcom is developing new silicon photonics technology aimed at significantly increasing the bandwidth available to GPUs and other AI accelerators. By utilizing co-packaged optics (CPOs), the fabless chip manufacturer aims to integrate optical connectivity components directly into GPUs, enabling higher data rates while simultaneously reducing power requirements.

The company has been working on CPO solutions for several years and showcased its latest advancements at the recent Hot Chips convention. Broadcom’s “optical engine” reportedly delivers a total interconnect bandwidth of 1.6 TB/sec, equivalent to 6.4 Tbit/sec or 800 GB/sec in each direction.