When OpenAI started giving private demonstrations of its new GPT-4 technology in late 2022, its skills shocked even the most experienced A.I. researchers. It could answer questions, write poetry and generate computer code in ways that seemed far ahead of its time.
More than two years later, OpenAI has released its successor: GPT-4.5. The new technology signifies the end of an era. OpenAI said GPT-4.5 would be the last version of its chatbot system that did not do “chain-of-thought reasoning.”
After this release, OpenAI’s technology may, like a human, spend a significant amount of time thinking about a question before answering, rather than providing an instant response.
GPT-4.5, which can be used to power the most expensive version of ChatGPT, is unlikely to generate as much excitement at GPT-4, in large part because A.I. research has shifted in new directions. Still, the company said the technology would “feel more natural” than its previous chatbot technologies.
“What sets the model apart is its ability to engage in warm, intuitive, naturally flowing conversations, and we think it has a stronger understanding of what users mean when they ask for something,” said Mia Glaese, vice president of research at OpenAI.
In the fall, the company introduced technology called OpenAI o1, which was designed to reason through tasks involving math, coding and science. The new technology was part of a wider effort to build A.I. that can reason through complex tasks. Companies like Google, Meta and DeepSeek, a Chinese start-up, are developing similar technologies.
The goal is to build systems that can carefully and logically solve a problem through a series of discrete steps, each one building on the last, similar to how humans reason. These technologies could be particularly useful to computer programmers who use A.I. systems to write code.
These reasoning systems are based on technologies like GPT-4.5, which are called large language models, or L.L.M.s.
L.L.M.s learn their skills by analyzing enormous amounts of text culled from across the internet, including Wikipedia articles, books and chat logs. By pinpointing patterns in all that text, they learned to generate text on their own.
To build reasoning systems, companies put L.L.M.s through an additional process called reinforcement learning. Through this process — which can extend over weeks or months — a system can learn behavior through extensive trial and error.
By working through various math problems, for instance, it can learn which methods lead to the right answer and which do not. If it repeats this process with a large number of problems, it can identify patterns.
OpenAI and others believe this is the future of A.I. development. But in some ways, they have been forced in this direction because they have run out of the internet data needed to train systems like GPT-4.5.
Some reasoning systems outperforms ordinary L.L.M.s on certain standardized tests. But standardized tests are not always a good judge of how technologies will perform in real-world situations.
Experts point out that the new reasoning system cannot necessarily reason like a human. And like other chatbot technologies, they can still get things wrong and make stuff up — a phenomenon called hallucination.
OpenAI said that, beginning Thursday, GPT-4.5 would be available to anyone who was subscribed to ChatGPT Pro, a $200-a-month service that provides access to all of the company’s latest tools.
(The New York Times sued OpenAI and its partner, Microsoft, in December for copyright infringement of news content related to A.I. systems.)
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