December 6, 2023
AI21 raises another $53M to challenge OpenAI in enterprise generative AI

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AI21, a company that competes with OpenAI to serve enterprise companies with generative AI systems, has chosen an opportune time to announce more funding.

While competitor OpenAI is grappling with internal chaos and rebellion, and may step aside after a majority of its employees supported a letter calling on that company’s board to resign, AI21 has raised its Series C round of funding. raised $53 million more, at a valuation of $1.4 billion, bringing the total to $208 million. The company has now raised $336 million.

OpenAI is one of a few other companies, including Cohere and Anthropic, that offer large language model (LLM) driven AI systems to the enterprise that compete with OpenAI, but which are not open source.

And with OpenAI looking very volatile, enterprise companies looking for security may decide to hesitate and consider other options before continuing with OpenAI products.

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Companies need choice, strength and security, said co-founder and co-CEO Yoav Shoham in an interview with VentureBeat. He said A121 works closely with enterprise companies, providing them a kind of “white-glove” service to make sure they have what they need, and that’s not something OpenAI can do. Could.

The company has 250 employees and is based in Tel Aviv. The latest investors include Intel Capital and Comcast Ventures. Those investors join many other investors, including big names like Nvidia and Google.

My initial interview with Shoham took place a few days before the weekend’s events that threw OpenAI into turmoil. When I stopped by to speak with him yesterday he declined to comment on what the OpenAI fiasco means for his company. But in his comments even before OpenAI exploded, Shoham expressed confidence about his company’s position in the market compared to OpenAI.

AI21 also said it has appointed former US ambassador to Israel and former Morgan Stanley leader Tom Nides as a board member.

OpenAI is the main company AI21 looks at when competing for deals, Shoham said, but it generally doesn’t look at anyone else. He said that his company performs well compared to OpenAI.

OpenAI did well by generating excitement with its general purpose LLMs like ChatGPT, which performs well in the chat format, and makes it easy for millions of people to play. But chat interfaces typically aren’t the best way to work with large language models, Shoham said.

ChatGPT ChatGPT is not a model for the enterprise, he said. It is an application that has a model that demands chat modality. “It’s sometimes perfect, sometimes not exactly what you want.”

By sticking with a general-purpose offering, OpenAI is “betting on brute force” and falling behind in doing specific tasks very well, but that specificity is typically what enterprise companies want. He said OpenAI is not set up business-wise to work closely with companies: “It’s just not their model,” Shoham said. OpenAI operates at scale and serves more than 100 million users, he said.

Instead, enterprise companies require robustly programmed applications to deploy, which requires a lot of work. He said scripting tools like Langchain that developers have adopted to pull into OpenAI’s LLM via API “point in the right direction, but true enterprise AI requires writing full programs.” He added: “I am sure that in two years we will not be talking about LLMs, but about ‘AI systems’,” Shoham said.

He said the big drop in prices for OpenAI’s services was the most significant announcement from OpenAI’s DevDay event two weeks ago. This shows that the company is willing to lose money to gain market share — which isn’t necessarily a bad strategy, Shoham said.

AI21, in contrast, is building both general-purpose LLMs and task-specific large language models, with algorithms around them that make them robust to those tasks, Shoham said. For example, when tested by a large financial institution, A121’s summary model ranked better than GPT-4, ChatGPT and Cloud by a large margin, Shoham said, declining to name the company.

The difficulty of working with LLMs in the enterprise has meant that those companies have been slow to adopt generative AI. However, venture interest “has grown over the last six months,” he said. “Companies have moved from sporadic experimentation to large-scale experimentation… within a year you’re going to see real money.”

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