Why tech giants are hedging their bets on OpenAI

Microsoft owns a 49% stake in OpenAI, having invested billions of dollars in the maker of ChatGPT. But the tech titan is also an investor in Inflection AI, which has a chatbot called Pi and is seen as a rival to OpenAI.

And the big AI funding announcements keep on coming. Last week, Reuters reported that Google plans to invest hundreds of millions in Character.AI, which builds personalized bots. In late October, Google said it had agreed to sink up to $2 billion into Anthropic, a key rival to OpenAI.

What’s happening here? Looking beyond the headline numbers and the hype surrounding AI startups, those investments in several OpenAI competitors show that it’s still early days for large language models (LLMs). With their money and resources, Big Tech players are hedging their bets by backing several potential winners, industry experts say.

In addition to the OpenAIs and Anthropics of the world, thousands of other companies are developing AI apps.

Tech giants benefit from supporting the growth of large language models

Microsoft, Google, and Amazon recognize that the future of AI, and the LLM market in particular, will involve integrating technologies from multiple vendors in both the enterprise and consumer spaces, said Scott Beechuk, an enterprise investor at Norwest Venture Partners. In the evolving ecosystem, companies that position themselves as key players supporting the growth and integration of LLM technologies stand to benefit the most, added Beechuk, who previously worked at Salesforce.

For those businesses, sometimes the investment is more of a “land grab to secure their position” in the AI industry, said Ivana Delevska, founder and CIO of Spear Invest, an investment firm focused on industrial technology.

Tech giants want to showcase their own chips and cloud computing services

In other cases, big companies are using investments and partnerships to provide and showcase their own products and grow their existing business. For instance, Amazon is investing up to $4 billion in Anthropic, which now trains its models on Amazon’s proprietary hardware.

Delevska says she expects to see more such alliances with major tech firms, which are flush with cash, because the funding environment for startups is tighter than in the past. Also, the cost of computing power needed for training AI models can be prohibitive—north of hundreds of millions of dollars.

Already, Microsoft is benefiting from its investment in OpenAI, which has driven more business to Azure, its cloud computing platform.

Talent for building AI companies is scarce

Tellingly, many leaders of AI startups belong to the same small circle. For example, Anthropic was founded by former OpenAI execs, while Character.AI was launched by onetime Google engineers who are expected to receive a huge investment from their ex-employer. This shows how scarce the talent is for building AI companies, which could ramp up the competition to invest in breakout businesses.

So, how can smaller players stand out in the fast-moving AI market? Both Beechuk and Delevska said that companies with the best chance of scaling will have proprietary data or provide unique solutions.

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