Generative AI startups were already hot with VCs. ChatGPT poured gasoline onto the fire.

• Generative AI firms, the category that ChatGPT falls under, saw big valuations in the past year.

• VCs investing in AI say they're optimistic and ready to invest in more companies in the space.

• But after a brutal 2022 many are also wary of putting too much faith — and cash — into anything new.

Generative AI, the technology that encompasses ChatGPT, DALL-E, and Lensa AI's avatar service, went bonkers viral in 2022. But even before the rise of ChatGPT, the space was buzzing as generative AI companies began raising large amounts of cash from venture capital.

Startups using generative AI rose eyeball-popping amounts in the past year, especially during an overall bad year for VC investments. Jasper, which makes AI-powered marketing materials, raised $125 million in Series A funding. Meanwhile, Runway, one of the companies behind Stable Diffusion, the model that powers Lensa AI, got $50 million in Series C, according to BuiltNYC.

Generative AI valuations are high, and VCs are excited. With VC investments falling, generative AI will at least be a bright spot in — and possibly the only bright spot in what look's to be a very gloomy 2023.

A hot market gets even hotter

Investing in generative AI and machine learning is nothing new for VCs. But the wild success of ChatGPT and the promise of even faster advancements has investors more excited than ever.

Partially thanks to the millions of people beta testing ChatGPT this winter, the next version of the tech that makes ChatGPT possible is due out as soon as this summer, and expectations are high. Founders that can figure out now how to harness ChatGPT before it makes the next evolutionary leap come with a built-in promise of a product that will assuredly will get much better.

Talia Goldberg, a partner at Bessemer, which invested in Jasper, said there are three different types within the generative AI space. There's companies like Jasper that use AI models from other companies and make applications for clients. Then there are firms that build those underlying models that power the AI. And finally, there are startups that mix both but focus on providing services for customers.