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Deciding on AI models is as much of a technical decision and it is a strategic one. But choosing open, closed or hybrid models all have trade-offs.
While speaking at this year’s VB Transform, model architecture experts from General Motors, Zoom and IBM discussed how their companies and customers consider AI model selection.
Barak Turovsky, who in March became GM’s first chief AI officer, said there’s a lot of noise with every new model release and every time the leaderboard changes. Long before leaderboards were a mainstream debate, Turovsky helped launch the first large language model (LLM) and recalled the ways open-sourcing AI model weights and training data led to major breakthroughs.
“That was frankly probably one of the biggest breakthroughs that helped OpenAI and others to start launching,” Turovsky said. “So it’s actually a funny anecdote: Open-source actually helped create something that went closed and now maybe is back to being open.”
Factors for decisions vary and include cost, performance, trust and safety. Turovsky said enterprises sometimes prefer a mixed strategy — using an open model for internal use and a closed model for production and customer facing or vice versa.
IBM’s AI strategy
Armand Ruiz, IBM’s VP of AI platform, said IBM initially started its platform with its own LLMs, but then realized that wouldn’t be enough — especially as more powerful models arrived on the market. The company then expanded to offer integrations with platforms like Hugging Face so customers could pick any open-source model. (The company recently debuted a new model gateway that gives enterprises an API for switching between LLMs.)
More enterprises are choosing to buy more models from multiple vendors. When Andreessen Horowitz surveyed 100 CIOs, 37% of respondents said they were using 5 or more models. Last year, only 29% were using the same amount.
Choice is key, but sometimes too much choice creates confusion, said Ruiz. To help customers with their approach, IBM doesn’t worry too much about which LLM they’re using during the proof of concept or pilot phase; the main goal is feasibility. Only later they begin to look at whether to distill a model or customize one based on a customer’s needs.
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