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. 

Today’s AI research boom has been fueled by neural networks, which saw a big breakthrough in the 1980s and work by simulating the patterns of the human brain. Back then, the technology hit a wall because the computers of the day weren’t powerful enough to run the software. Today we have lots of data and extremely powerful computers, which makes the technique viable. 

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.

That’s already happening. In light of the success of OpenAI’s ChatGPT, Google has declared a “code red” threat situation for its core product, Search, and is looking to aggressively revamp Search with its own AI research. 

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. 

That’s not necessarily a bad thing. 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.