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With the demise of Kite, can generative AI for code succeed? • TechCrunch

Kite, a startup development of an AI-powered coding assistant, abruptly halted last month. Despite securing tens of millions of dollars in VC support, Kite has struggled to pay the bills, founder Adam Smith revealed in a post-mortem blog post, coming up against engineering headwinds that have made it virtually impossible to find a suitable product for the market.

“Wdid not succeed in transmit our vision of AI-assisted programming because we were over 10 years too early to commercialize, i.e. the technology is not ready yet,” Smith said. “Our product was not monetized, and it took too long to figure it out.”

Kite’s failure doesn’t bode well for the many other companies pursuing — and trying to commercialize — generative AI for coding. Copilot is perhaps the most hyped example, a code generation tool developed by GitHub and OpenAI that costs $10 per month. But Smith notes that while Copilot shows great promise, it still has “a long way to go” – estimating that it could cost upwards of $100 million to create a “production quality” tool capable of synthesizing code. reliably.

To get a sense of the challenges ahead for players in the generative code space, TechCrunch spoke to startups developing AI systems for coding, including Tabnine and DeepCode, which Snyk acquired in 2020. The service de Tabnine predicts and suggests next lines of code based on context and syntax, like Copilot. DeepCode works a bit differently, using AI to notify developers of bugs as they code.

Tabnine CEO Dror Weiss has been transparent about what he sees as the barriers to mass adoption of code synthesis systems: the AI ​​itself, the user experience, and monetization.

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