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TagAI Winter

Self-driving electric semi truck driving on highway. 3D rendering image.

Star self-driving truck firm shuts; AI not safe enough soon enough

CEO Stefan Seltz-Axmacher is blunt about the cause: Machine learning “doesn’t live up to the hype”

Starsky Robotics was not just another startup overwhelmed by business realities. In 2019, it was named one of the world’s 100 most promising start-ups (CNBC) and one to watch by FreightWaves, a key trucking industry publication. But the AI breakthroughs did not appear.

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Photo by Michal Mrozek

So Is an AI Winter Really Coming This Time?

AI did surge past milestones during the 2010s but fell well short of the hype

Maybe both. AI will require more from us, not less, because how we choose to use these tools will make an increasingly stark difference between benefit and ruin.

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Beautiful mandarin duck on the frozen lake in a park

Just a light frost—or AI winter?

It’s nice to be right once in a while—check out the evidence for yourself

About a year ago, I wrote that mounting AI hype would likely give way to yet another AI winter. Now, according to the panelists at “the world’s leading academic AI conference” the temperature is already falling.

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Fluorescent sign saying

Will artificial intelligence design artificial super-intelligence?

And then turn us all into super-geniuses, as some AI researchers hope? No, and here's why not
Because Moore's law is an exponential law, the numbers multiply rapidly and we could hit the physical limit rather suddenly. Current indications are that Moore’s law’s speed has already slowed or even ceased to be a true description of the IT industry today. Read More ›
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View of Lake Michigan from the Memorial Museum in Milwaukee, Wi

AI Winter Is Coming

Roughly every decade since the late 1960s has experienced a promising wave of AI that later crashed on real-world problems, leading to collapses in research funding.
Nearly all of AI’s recent gains have been realized due to massive increases in data and computing power that enable old algorithms to suddenly become useful. For example, researchers first conceived neural networks—the core idea powering much machine learning and AI’s notable advances—in the late 1950s. The worries of an impending winter arise because we’re approaching the limits of what massive data combined with hordes of computers can do. Read More ›