Not everyone seems to be convinced of the return on investment of generative AI. But many investors are, in accordance with the most recent figures from funding tracker PitchBook.
In the third quarter of 2024, VCs invested $3.9 billion in generative AI startups across 206 deals, in accordance with PitchBook. (That doesn't count OpenAI's $6.6 billion round.) And $2.9 billion of that funding went to U.S.-based corporations in 127 deals.
Biggest third-quarter gainers included coding assistant Magic ($320 million in August), enterprise search provider Glean ($260 million in September) and business analytics firm Hebbia ($130 million in July). . China's Moonshot AI raised $300 million in August, and Sakana AI, a Japanese startup focused on scientific discovery, closed a $214 million tranche last month.
Generative AI, a broad cross-section of technologies that features text and image generators, coding assistants, cybersecurity automation tools and more, has its critics. Experts query the reliability of the technology and, within the case of generative AI models trained on copyrighted data without permission, its legality.
But VCs are effectively betting that generative AI will gain a foothold in large and profitable industries and that its long-term growth is not going to be hindered by the challenges it faces today.
Maybe they're right. A Forrester report predicts 60% of generative AI skeptics will use the technology – knowingly or unknowingly – for tasks starting from summarization to creative problem solving. That's quite a bit rosier than Gartner's forecast Earlier this yr, it announced that 30% of generative AI projects will probably be abandoned past proof of concept by 2026.
“Large customers are rolling out production systems that leverage startup tools and open source models,” said Brendan Burke, senior emerging technology analyst at PitchBook, in an interview with TechCrunch. “The recent wave of models shows that latest generations of models are possible and may excel in scientific areas, data retrieval and code execution.”
A formidable hurdle to widespread adoption of generative AI is the technology's enormous computational cost. Bain analysts project in a current study that generative AI will lead corporations to construct gigawatt-scale data centers – data centers that use five to twenty times the quantity of power that the typical data center uses today – putting strain on an already strained labor and power supply chain.
There is already generative AI-driven demand for data center power extend the lifespan of coal-fired power plants. Morgan Stanley Estimates If this trend continues, global greenhouse gas emissions may very well be thrice higher by 2030 than without the event of generative AI.
Several of the world's largest data center operators, including Microsoft, Amazon, Google and Oracle, have announced investments in nuclear energy to offset their increasing needs for non-renewable energy. (In September, Microsoft announced it might source power from the infamous Three Mile Island nuclear power plant.) But it could take time Years before these investments bear fruit.
Investments in generative AI startups show no signs of slowing down – negative externalities be damned. ElevenLabs, the viral voice cloning tool, is reportedly trying to boost $3 billion in funding, while Black Forest Labs, the corporate behind the infamous X image generator, is reportedly about to boost $100 million in funding -Dollar negotiated.
