The pace of investment in artificial intelligence is slowing, but AI is still hotter than ever
In line with a difficult and uncertain economic climate, the pace of investment in the burning artificial intelligence technology space has slowed somewhat over the past year. However, things are still hot and AI is seeing plenty of progress, tempered by concerns about security and liability. Interestingly, much of its development has moved from laboratories to commercial enterprises.
These are the conclusions reached by two leading tech venture capitalists, Nathan Benaich of Air Street Capital and Ian Hogarth plural, described in their annual summary of the state of the AI. The report covers all facets of AI, from developments with DeepMind at Nvidiarapidly expanding processing capabilities. There are also many 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 it eased off in 2022. In 2022, investment in startups using AI slowed with the wider market. Private companies using AI are expected to raise 36% less money in 2022 compared to the previous year, but are still on track to exceed the 2020 level. “It’s comparable to investing in all the startups and scale-ups in the world,” they observe. Further, they note, “enterprise software is the most invested category globally, while robotics captures the largest share of venture capital investment in AI.”
At the same time, there has been a slowdown, although less extreme, in investment in SaaS startups and scaleups using AI – are expected to reach $41.5 billion by the end of the year, down 33% from last year. This is even higher than in 2020 venture capital investment in AI SaaS startups and scale-ups.
Significantly, the report’s co-authors observe, there has also been a drying up of academic AI research as funding for multi-year projects ended, with much of the research now shifting to the commercial sector. This means more startups and scale-ups on the horizon. “Once considered untouchable, talent in Tier 1 AI labs is going wild and becoming entrepreneurial,” say Benaich and Hogarth. “Alumni work on AGI, AI security, biotechnology, fintech, energy, development tools, and robotics.”
They add that “the hiring freeze and the dissolution of AI labs are precipitating the formation of many startups from giants such as DeepMind and Open AI.” Even big tech giants are seeing a loss of talent to startups. Meta, for example, is “closing its centralized AI research group after letting it run without pressure on the product roadmap for nearly 10 years.” Moreover, “all but one of the authors of the historical article which presented neural networks based on transformers left Google to build their own startups in general artificial intelligence, chatbots, early AI biotechnology, and blockchain,” they note. For example, they say, AnthropC raised $580 million in 2022, Inflection raised $225 million, and co:here raised $125 million.
Global 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 examined the prevalence of AI “unicorns” emerging in nations around the world. concluding that the United States leads these high-potential startups, followed by China and the United Kingdom. A total of 292 AI unicorns have emerged in the United States in 2022, with a combined enterprise value of $4.6 trillion. Overall, they add, “despite a significant drop in investment in US-based startups and scale-ups using AI, they still account for more than half of AI investment globally. “.
Also in 2022, big tech companies continued to “extend their AI clouds and form big partnerships with AI startups,” say Benaich and Hogarth. “Hyperscalers and challenger AI compute vendors have significant AI compute partnerships, including Microsoft’s billion-dollar investment in OpenAI. We expect more to come.
For the coming year, Benaich and Hogarth predict that more than $100 million will be invested in “organizations dedicated to AI alignment over the next year as more and more people take aware of the risk we face in letting AI capabilities outpace security.” Additionally, they predict that a “major user-generated content side will negotiate a commercial settlement with a startup producing AI models (like OpenAI) for training on their user-generated content corpus.”
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