[ad_1]
Not everyone is convinced of the return on investment in AI. But many investors do, based on the latest numbers from fund-tracking firm PitchBook.
In the third quarter of 2024, venture capital firms invested $3.9 billion in AI startups through 206 deals, per PitchBook. (This does not include OpenAI’s $6.6 billion round.) $2.9 billion of this financing went to US-based companies across 127 deals.
Some of the biggest winners in Q3 were programming assistant Magic ($320 million in August), enterprise search provider Glean ($260 million in September), and business analytics company Hebbia ($130 million in July). Chinese startup 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 range of technologies that includes text and image generators, coding assistants, cybersecurity automation tools, and more, has its critics. Experts question the reliability of the technology, and – in the case of generative AI models trained on copyrighted data without permission – its legitimacy.
But venture capital firms are effectively betting that generative AI will gain a foothold in large, profitable industries and that its long-term growth will not be affected by the challenges it faces today.
Maybe they were right. A The Forrester report predicts 60% of generative AI skeptics will adopt the technology – intentionally or unintentionally – for tasks ranging from summarizing to creative problem solving. This is rosier than Gartner prediction Earlier this year, 30% of generative AI projects will be abandoned after proof of concept by 2026.
“Big customers are rolling out production systems that leverage startup tools and open source models,” Brendan Burke, senior emerging technology analyst at PitchBook, told TechCrunch in an interview. “The recent wave of models shows that new generations of models are possible and may excel in the fields of science, data retrieval, and code execution.”
One of the formidable obstacles to widespread adoption of AI is the technology’s massive computational requirements. Bain analysts project recently He studies That generative AI will prompt companies to build gigawatt-sized data centers — data centers that consume between 5 and 20 times the amount of energy the average data center consumes today — underscores an already strained labor and electricity supply chain.
Already, AI-driven production demand for data center power already exists extension The life of coal-fired plants. Morgan Stanley Estimates If this trend continues, global greenhouse emissions between now and 2030 could be three times higher than if generative AI had not been developed.
Many of the world’s largest data center operators, including Microsoft, Amazon, Google and Oracle, have announced investments in nuclear power to offset their growing non-renewable energy consumption. (In September, Microsoft announced that it would draw power from the notorious Three Mile Island nuclear plant.) But it may take a long time. Years Before those investments pay off.
Investments in AI startups show no sign of slowing down, especially negative externalities. ElevenLabs, the viral audio cloning tool, is reportedly seeking to raise $3 billion in funds, while Black Forest Labs, the company behind the popular X image generator, is said to be in talks for a $100 million funding round.
[ad_2]