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Pace Of Artificial Intelligence Investments Slows, But AI Is Still Hotter Than Ever

In line with a rocky and uncertain economic climate, the pace of investments flowing into the red-hot artificial intelligence technology space has cooled somewhat this past year. Things are still red hot, however, and AI is seeing a lot of progress, mitigated by concerns over safety and responsibility. Interestingly, much of its development has moved out of labs and into commercial ventures.

These are the conclusions drawn by two leading venture capitalists in the tech space, Nathan Benaich of Air Street Capital and Ian Hogarth of Plural, outlined in their annual summary of the state of AI. The report covers all facets of AI, from developments with DeepMind to NVIDIA’s rapidly expanding processing capabilities. There are also numerous implications for AI from a business perspective.

For starters, it turns out that 2021 was a banner year for the AI business sector, but then softened in 2022. In 2022, investment in startups using AI has slowed down along with the broader market. Private companies using AI are expected to raise 36% less money in 2022 versus the previous year, but are still on track to exceed the 2020 level. “This is comparable with the investment in all startups and scaleups worldwide,” they observe. In addition, they note, “enterprise software is the most invested category globally, while robotics captures the largest share of VC investment into AI.”

At the same time, there has been a softening, though less extreme, for investments in SaaS startups and scaleups using AI — expected to reach $41.5 billion by the end of the year, down 33% from last year. This is still higher than in 2020 VC investment in AI SaaS startups and scaleups.

Significantly, the report’s co-authors observe, there has also been a drying up of academic research in AI as multi-year project funding concludes, with much of the research now shifted to the commercial sector. That means more startups and scaleups on the horizon. “Once considered untouchable, talent from Tier 1 AI labs is breaking loose and becoming entrepreneurial,” Benaich and Hogarth state. “Alums are working on AGI, AI safety, biotech, fintech, energy, dev tools and robotics.”

They add that “hiring freezes and the disbanding of AI labs precipitates the formation of many startups from giants including DeepMind and OpenAI.” Even the large tech behemoths are seeing some loss of talent to startups. Meta, for example, is “folding their centralized AI research group after letting it run free from product roadmap pressure for almost 10 years.” In addition, “all but one author of the landmark paper that introduced transformer-based neural networks have left Google to build their own startups in artificial general intelligence, conversational agents, AI first biotech and blockchain,” they note. For example, they relate, Anthrop\C raised $580 million in 2022, Inflection raised $225 million, and co:here raised $125 million.

Worldwide Investment in Startups and Scaleups Using AI:

  • 2018 $72 billion
  • 2019 $65 billion
  • 2020 $69.5 billion
  • 2021 $111.4 billion
  • 2022 $47.5 billion (projected)

Benaich and Hogarth also looked at the prevalence of AI “unicorns” emerging across nations of the world. concluding the United States leads in these high-potential startups, followed by China and the United Kingdom. A total 292 AI unicorns emerged within the US in 2022, with a combined enterprise value of $4.6 trillion. Overall, they add, “despite significant drop in investment in US based startups and scaleups using AI, they still account for more than half of the AI investment worldwide.”

Also in 2022, the big tech companies continued to “expand their AI clouds and form large partnerships with AI startups,” Benaich and Hogarth state. “The hyperscalers and challenger AI compute providers are tallying up major AI compute partnerships, notably Microsoft’s $1 billion investment into OpenAI. We expect more to come.”

For the year ahead, Benaich and Hogarth predict more than $100 million will be invested in “dedicated AI-alignment organizations in the next year as more people become aware of the risk we are facing by letting AI capabilities run ahead of safety.” In addition, they predict that a “major user-generated content side will negotiate a commercial settlement with a startup producing AI models (such as OpenAI) for training on their corpus of user generated content.”

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