Not everyone is convinced of the return on investment of generative AI. But many investors are, judging by the latest numbers from funding tracker PitchBook.
According to PitchBook, in Q3 2024, VCs invested $3.9 billion in generative AI startups across 206 deals. (That doesn't include OpenAI's $6.6 billion round.) And $2.9 billion of that money went to U.S.-based companies across 127 deals.
The biggest winners in Q3 included coding assistant Magic ($320 million in August), enterprise search provider Glean ($260 million in September), and business analytics company Hebbia ($260 million in July). $130 million). China's Moonshot AI raised $300 million in August, and Sakana AI, a Japanese startup focused on scientific discovery, completed a $214 million tranche last month.
Generative AI is a broad technology that includes text and image generators, coding assistants, cybersecurity automation tools, and more, but it has its critics. Experts question the reliability of this technology, and its legality in the case of generative AI models trained using copyrighted data without permission.
But VCs are effectively betting that generative AI will gain a foothold in a large and profitable industry, and that its long-tail growth will be unaffected by the challenges it currently faces.
Perhaps they are right. A Forrester report predicts that 60% of generative AI skeptics will knowingly or unknowingly adopt the technology for tasks ranging from summarization to creative problem solving. This is considerably more optimistic than Gartner's prediction earlier this year that 30% of generative AI projects would be abandoned after proof of concept by 2026.
“Large customers are deploying production systems using startup tools and open source models,” Brendan Burke, senior analyst for emerging technologies at PitchBook, told TechCrunch in an interview. “The latest wave of models shows that a new generation of models is possible and can be better at science, data retrieval, and code execution.”
One of the major hurdles to widespread adoption of generative AI is the technology's massive computational requirements. In a recent study, Bain analysts found that generative AI could help companies build gigawatt-scale data centers (data centers that consume 5 to 20 times more power than today's average data center). It predicts the economy will accelerate, underscoring already strained labor and power supply chains. .
Already, generative AI-powered data center power demands are extending the lifespan of coal-fired power plants. Morgan Stanley estimates that if this trend continues, global greenhouse gas emissions could be three times higher between now and 2030 than they would have been had generative AI not been developed. I am.
Some of the world's largest data center operators, including Microsoft, Amazon, Google, and Oracle, have announced investments in nuclear power to offset their increasing use of non-renewable energy. (In September, Microsoft announced it would tap power from the infamous Three Mile Island nuclear power plant.) But it could take years for these investments to bear fruit.
Investment in generative AI startups shows no signs of slowing down. Negative externalities are anathema. Viral voice cloning tool Eleven Labs is reportedly aiming to raise funding at a valuation of $3 billion, while Black Forest Labs, the company behind X's infamous image generator, is reportedly looking to raise $1 billion The company is said to be in talks for a $100 million funding round.