Introducing shopping research, a new experience in ChatGPT that does the research to help you find the right products.
It’s everything you like about deep research but with an interactive interface to help you make smarter purchasing decisions.
Shopping research asks smart clarifying questions, researches deeply across the internet, reviews quality sources, and builds on ChatGPT’s understanding of you from past conversations and memory to deliver a personalized buyer’s guide in minutes.
With shopping research, ChatGPT learns what you like as you shop.
You can guide the results by marketing suggested items as “Not interested” or “More like this.”
This allows the research to adapt based on your real-time feedback.
Shopping research does the heavy lifting, searching across the internet for prices, availability, reviews, specs, and images—surfacing options as it goes.
Shopping research in ChatGPT can help you find lookalikes so you can get the style you want at the price, fit, or availability that meets your needs.
To help with holiday shopping, we’re making usage for shopping research in ChatGPT nearly unlimited for all plans through the holidays.
Because it’s great at finding gifts, too.
Shopping research is starting to roll out today on mobile and web for logged-in ChatGPT users on Free, Go, Plus, and Pro plans.
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In the coming weeks, we plan to start testing ads in ChatGPT free and Go tiers.
We’re sharing our principles early on how we’ll approach ads–guided by putting user trust and transparency first as we work to make AI accessible to everyone.
What matters most:
- Responses in ChatGPT will not be influenced by ads.
- Ads are always separate and clearly labeled.
- Your conversations are private from advertisers.
- Plus, Pro, Business, and Enterprise tiers will not have ads.
Here's an example of what the first ad formats we plan to test could look like.
Introducing ChatGPT Health — a dedicated space for health conversations in ChatGPT. You can securely connect medical records and wellness apps so responses are grounded in your own health information.
Designed to help you navigate medical care, not replace it.
ChatGPT Health can help you navigate everyday questions and spot patterns over time, so you feel more informed, prepared, and confident for important medical conversations.
If you choose, ChatGPT Health lets you securely connect medical records and apps like Apple Health, MyFitnessPal, and Peloton to give personalized responses.
To preserve chain-of-thought (CoT) monitorability, we must be able to measure it.
We built a framework + evaluation suite to measure CoT monitorability — 13 evaluations across 24 environments — so that we can actually tell when models verbalize targeted aspects of their internal reasoning. openai.com/index/evaluati…
Monitoring a model’s chain-of-thought is far more effective than watching only its actions or final answers.
The more a model “thinks” (longer CoTs), the easier it is to spot issues.
RL at today’s frontier doesn’t seem to wreck monitorability and can help early reasoning steps. But there’s a tradeoff: smaller models run with higher reasoning effort can be easier to monitor at similar capability — at the cost of extra inference compute (a “monitorability tax”).
Accelerating scientific progress is one of the most impactful ways AI can benefit society. Models can already help researchers reason through hard problems — but doing this well means testing models on tougher evaluations and in real scientific workflows grounded in experiments.
We’re releasing a new eval to measure expert-level scientific reasoning: FrontierScience.
This benchmark measures PhD-level scientific reasoning across physics, chemistry, and biology.
It contains hard, expert-written questions (both olympiad-style problems and longer research-style tasks) designed to reveal where models succeed and where they fall short. openai.com/index/frontier…
GPT-5.2 is our strongest model on the FrontierScience eval, showing clear gains on hard scientific tasks.
But the benchmark also reveals a gap between strong performance on structured problems and the open-ended, iterative reasoning that real research requires.
GPT-5.2 Instant, Thinking, and Pro are rolling out today, starting with Plus, Pro, Business, and Enterprise plans. Free and Go users will get access tomorrow.
Most neural networks today are dense and highly entangled, making it difficult to understand what each part is doing.
In our new research, we train “sparse” models—with fewer, simpler connections between neurons—to see whether their computations become easier to understand.
Unlike with normal models, we often find that we can pull out simple, understandable parts of our sparse models that perform specific tasks, such as ending strings correctly in code or tracking variable types.
We also show promising early signs that our method could potentially scale to understand more complex behaviors.