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Nov 24, 2025 7 tweets 2 min read Read on X
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.

openai.com/index/chatgpt-…
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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More from @OpenAI

Feb 13
GPT-5.2 derived a new result in theoretical physics.

We’re releasing the result in a preprint with researchers from @the_IAS, @VanderbiltU, @Cambridge_Uni, and @Harvard. It shows that a gluon interaction many physicists expected would not occur can arise under specific conditions.

openai.com/index/new-resu…
Gluons carry the strong nuclear force, which is the force that binds quarks together inside protons and neutrons.

Without the strong force, atomic nuclei would not exist.

It is one of the four fundamental forces of nature and a core part of the Standard Model of particle physics.
For decades, one specific gluon interaction (“single-minus” at tree level) was widely treated as having zero amplitude, meaning it was assumed not to occur.

When an amplitude is zero, physicists may ignore it. But this preprint shows that the conclusion is too strong: in a carefully defined situation — where the particles’ motions satisfy a specific alignment condition — the amplitude is not zero.
Read 6 tweets
Feb 5
We worked with @Ginkgo to connect GPT-5 to an autonomous lab, so it could propose experiments, run them at scale, learn from the results, and decide what to try next. That closed loop brought protein production cost down by 40%.
GPT-5 was connected to an autonomous lab: it designed experiments, the lab executed them, and the results informed the next designs across six iterations.

In this setup, GPT-5 designed batches of experiments, the lab executed them, and the data fed back into the next round. We repeated that cycle six times, exploring 36,000+ reaction compositions across 580 automated plates.Image
We found that the improvements came from identifying combinations that work well together and that hold up in the realities of high-throughput automation.

GPT-5 identified low-cost reaction compositions that humans had not previously tested in this configuration. Cell-free protein synthesis (CFPS) has been studied for years, but the space of possible mixtures is still large. When you can propose and execute thousands of combinations quickly, you can find workable regions that are easy to miss with a manual workflow.
Read 4 tweets
Jan 27
Introducing Prism, a free workspace for scientists to write and collaborate on research, powered by GPT-5.2.

Available today to anyone with a ChatGPT personal account: prism.openai.com
Prism offers unlimited projects and collaborators in a single, cloud-based, LaTeX-native workspace.

GPT-5.2 works inside your project with access to paper structure, equations, references, and surrounding context—right where the work happens. Image
Prism removes version conflicts and setup overhead—making powerful scientific tools easier to adopt and more accessible to researchers everywhere.

openai.com/prism
Read 4 tweets
Jan 16
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.Image
Here's an example of what the first ad formats we plan to test could look like. Image
Facts about the ads test in ChatGPT: Image
Read 4 tweets
Jan 7
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.

Join the waitlist to get early access.

openai.com/index/introduc…
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.
Read 6 tweets
Dec 18, 2025
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. Image
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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”).
Read 5 tweets

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