How ChatGPT search paves the way for AI agents
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OpenAI’s Olivier Godement, head of product for its platform, and Romain Huet, head of developer experience, are on a whistle-stop tour around the world. Last week, I sat down with the pair in London before DevDay, the company’s annual developer conference. London’s DevDay is the first one for the company outside San Francisco. Godement and Huet are heading to Singapore next.
It’s been a busy few weeks for the company. In London, OpenAI announced updates to its new Realtime API platform, which allows developers to build voice features into their applications. The company is rolling out new voices and a function that lets developers generate prompts, which will allow them to build apps and more helpful voice assistants more quickly. Meanwhile for consumers, OpenAI announced it was launching ChatGPT search, which allows users to search the internet using the chatbot. Read more here.
Both developments pave the way for the next big thing in AI: agents. These are AI assistants that can complete complex chains of tasks, such as booking flights. (You can read my explainer on agents here.)
“Fast-forward a few years—every human on Earth, every business, has an agent. That agent knows you extremely well. It knows your preferences,” Godement says. The agent will have access to your emails, apps, and calendars and will act like a chief of staff, interacting with each of these tools and even working on long-term problems, such as writing a paper on a particular topic, he says.
OpenAI’s strategy is to both build agents itself and allow developers to use its software to build their own agents, says Godement. Voice will play an important role in what agents will look and feel like.
“At the moment most of the apps are chat based … which is cool, but not suitable for all use cases. There are some use cases where you’re not typing, not even looking at the screen, and so voice essentially has a much better modality for that,” he says.
But there are two big hurdles that need to be overcome before agents can become a reality, Godement says.
The first is reasoning. Building AI agents requires us to be able to trust that they will be able to complete complex tasks and do the right things, says Huet. That’s where OpenAI “reasoning” feature comes in. Introduced in OpenAI’s o1 model last month, it uses reinforcement learning to teach the model how to process information using “chain of thought.” Giving the model more time to generate answers allows it to recognize and correct mistakes, break down problems into smaller ones, and try different approaches to answering questions, Godement says.
But OpenAI’s claims about reasoning should be taken with a pinch of salt, says Chirag Shah, a computer science professor at the University of Washington. Large language models are not exhibiting true reasoning. It’s most likely that they have picked up what looks like logic from something they’ve seen in their training data.
“These models sometimes seem to be really amazing at reasoning, but it’s just like they’re really good at pretending, and it only takes a little bit of picking at them to break them,” he says.
There is still much more work to be done, Godement admits. In the short term, AI models such as o1 need to be much more reliable, faster, and cheaper. In the long term, the company needs to apply its chain-of-thought technique to a wider pool of use cases. OpenAI has focused on science, coding, and math. Now it wants to address other fields, such as law, accounting, and economics, he says.
Second on the to-do list is the ability to connect different tools, Godement says. An AI model’s capabilities will be limited if it has to rely on its training data alone. It needs to be able to surf the web and look for up-to-date information. ChatGPT search is one powerful way OpenAI’s new tools can now do that.
These tools need to be able not only to retrieve information but to take actions in the real world. Competitor Anthropic announced a new feature where its Claude chatbot can “use” a computer by interacting with its interface to click on things, for example. This is an important feature for agents if they are going to be able to execute tasks like booking flights. Godement says o1 can “sort of” use tools, though not very reliably, and that research on tool use is a “promising development.”
In the next year, Godemont says, he expects the adoption of AI for customer support and other assistant-based tasks to grow. However, he says that it can be hard to predict how people will adopt and use OpenAI’s technology.
“Frankly, looking back every year, I’m surprised by use cases that popped up that I did not even anticipate,” he says. “I expect there will be quite a few surprises that you know none of us could predict.”
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