In Q3 2024, investments in generative AI businesses exceeded $3.9 billion.
According to the most recent data from funding tracker PitchBook, programming worker Magic ($320 million in August), enterprise search suppliers Glean ($260 million in September), and business intelligence firm Hebbia ($130 million in July) were among the top winners in Q3 2024. China’s Moonshot AI obtained $300 million in August, and Sakana AI, a Japanese start-up focused on scientific discovery, closed a $214 million section last month. While not all investors are convinced of generative AI’s return on investment, a significant portion of this funding went to U.S.-based companies across 206 deals, according to PitchBook.
There are critics of generative AI, a wide range of technology that includes cybersecurity automation tools, coding assistants, text and image generators, and more. The technology’s dependability and, in the case of generative AI models trained on copyrighted data without authorization, its legality are questioned by experts.
However, VCs are essentially betting that generative AI
Will establish itself in sizable and lucrative businesses and that the obstacles it currently faces won’t affect its long-term growth.
They might be correct. According to a Forrester survey, 60% of people who are skeptical of generative AI will use the technology, whether they realize it or not, for activities like summarizing and solving creative problems. Gartner predicted earlier this year that 30% of generative AI initiatives will be shelved after proof-of-concept by 2026, although that figure is far more optimistic.
In an interview with TechCrunch
Brendan Burke, senior analyst of emerging tech at PitchBook, stated that “large customers are rolling out production systems that take advantage of startup tooling and open source models.” “The most recent generation of models demonstrates that new generations of models are feasible and may perform exceptionally well in data retrieval, code execution, and scientific domains.”
The enormous computing demands of generative AI
Represent a significant barrier to its broad adoption. According to a recent report by Bain analysts, generative AI will push businesses to construct gigawatt-scale data centers, which use five to twenty times as much power as the typical data center today. This would put additional strain on the already overburdened labor and electrical supply chains.
The need for data center electricity driven by generative AI is already extending the life of coal-fired plants. According to Morgan Stanley, if this pattern continues, global greenhouse gas emissions might triple between now and 2030 compared to what they would have been in the absence of generative AI.
To counteract their growing reliance on nonrenewable energy, a number of the biggest data center operators in the world, including Microsoft, Amazon, Google, and Oracle, have declared plans to invest in nuclear. (Microsoft said in September that it would use electricity from the notorious Three Mile Island nuclear power facility.) However, it can be years before such investments pay off.
Negative externalities be damned, investments in generative AI businesses are not slowing down. According to reports, Black Forest Labs, the firm that created X’s infamous picture generator, is negotiating a $100 million investment round, while ElevenLabs, the popular voice cloning program, is looking to raise $3 billion.
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