The economy is down, but AI is hot. Where do we go from here?
This is a far cry from the field’s reputation in the 1990s, when Wooldridge was finishing his PhD. AI was still seen as a weird, ...
...fringe pursuit; the wider tech sector viewed it in a similar way to how established medicine views homeopathy, he says.
New breakthroughs, such as the chatbot ChatGPT and the text-to-image model Stable Diffusion, seem to come every few months.
Technologies like ChatGPT are not fully explored yet, and both industry and academia are still working out how they can be useful, says Stone.
Instead of a full-blown AI winter, we are likely to see a drop in funding for longer-term AI research and more pressure to make money using the technology, says Wooldridge.
Researchers in corporate labs will be under pressure to show that their research can be integrated into products and thus make money, he adds. Stone sees parallels to what happened at Bell Labs.
If Big Tech’s AI labs, which dominate the sector, turn away from deep, longer-term research and focus too much on shorter-term product ...
...development, exasperated AI researchers may leave for academia, and these big labs could lose their grip on innovation, he says.
There are a lot of smart people looking for jobs at the moment. Venture capitalists are looking for new startups ...
...to invest in as crypto fizzles out, and generative AI has shown how the technology can be made into products.
This moment presents the AI sector with a once-in-a-generation opportunity to play around with the potential of new technology. Despite all the gloom around the layoffs, it’s an exciting prospect.
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