X日报 · AI科技

our team's first week of having both sol and fable
the crazy thing is 30% of our cost was on fable https://t.co/8yVddGEuBg

He takes scamming to a whole new level

Introducing ChatGPT Work, a new agent in ChatGPT powered by Codex and GPT-5.6.

It can take action across your apps and files, stay with a project for hours if needed, and turn a goal into finished work.

It’s a whole new way to get work done. https://t.co/uGbvjU1LsV

Introducing ChatGPT Work, a new agent in ChatGPT powered by Codex and GPT-5.6.

It can take action across your apps and files, stay with a project for hours if needed, and turn a goal into finished work.

It’s a whole new way to get work done. https://t.co/uGbvjU1LsV

Thank you to the 7M active users who are now using Codex and ChatGPT Work.

We have added a banked reset to everyone's account to celebrate the milestone. You can apply the reset in the desktop app or on web and it will replenish the weekly usage for you.

Have fun out there.

i really like openai's new chatgpt "Work" feature

not everything involves programming, as sometimes you need help with project planning, content review, research, PDFs, or spreadsheets

so i'd summarize this:

need an answer? chat
need to code? codex
need to plan, research, or review? work

a lot of people haven’t realized how much more capable Chat has become in the last few days

how much of Codex is now available directly inside @ChatGPTapp on mobile and the web.

the Codex desktop app is great. I obviously live there.

but now, inside ChatGPT, you can tap Work on mobile or the web to hand off a task that runs in the cloud, no computer needed.
you can also tap Remote to pick up and continue work already running on your computer.

start at your desk, keep things moving on your phone, or kick off something new wherever you are.

agents shouldn’t care which screen you started from.

ChatGPT Sites is now in public beta.

You can turn a prompt, file, or rough idea into a dashboard, project tracker, report, prototype, or lightweight app:

build and edit directly in ChatGPT Work or Codex
test in a private preview publish and share with a URL

Rolling out across paid plans. Enterprise admins can control public publishing.

I discovered a great use case for GPT-Live today: Personalized, interactive news briefings.

I have a scheduled task in ChatGPT to create a personalized newscast. I’ve been having Chat read that aloud using the text-to-speech button on replies. But today I wondered: Can GPT-Live read this to me and then I can ask it questions as it’s going, and then it resumes where it left off?

The answer is yes! You can just hit the GPT-Live button in an existing thread and talk about it, and that includes a scheduled task thread. You can ask questions, ask for additional research, and do anything else GPT-Live allows, and it will address your request and then resume reading where it left off. This is really cool.

New OpenAI GPT-live voice model feels light years ahead of the previous voice experience. Ran through a test exec coaching session during my morning workout and it was shockingly good. Listened intently, never cut me off, and responded within milliseconds.

The new ChatGPT voice is quite impressive to use, really worth a minute to try it out on your phone. (while staying aware that the voice model is not going to be as smart as a full thinking model)

(1) Today we're releasing Muse Spark 1.1 -- a strong agentic and coding model at a very low price. It's available through our new Meta Model API and in Meta AI.

Today, I shared with the OpenAI team that I have decided to leave my full-time role at OpenAI and transition to being a part-time advisor.

Three months ago, I had to go on medical leave after a severe exacerbation of a chronic illness I’ve lived with for seven years. During that time, it became clear that the road to recovery would be much longer and more complex than I had anticipated—and that I needed to focus on it fully.

When I went on leave, many people told me I was courageous for prioritizing my health. The truth is that I am only making this decision now because I failed to make it many times before.

Over the years, doctors, friends, colleagues, and loved ones encouraged me to slow down. Two years after I got sick, Facebook offered me the opportunity to take a full year of medical leave. I didn’t even pause to consider it. I immediately said no. At the time, Zuck told me I should play the long game. I wish I had listened.

Looking back, I realize that a lot of what made me successful also made this decision incredibly difficult.

I grew up believing that opportunities were precious and that when they appeared, you grabbed them with both hands. That mindset carried me from a small town in southern France to opportunities I never could have imagined. By the time I turned 40, I had already gotten to do more than I’d ever dreamed possible as a kid growing up in Sète.

I love building. My work has always given me a deep sense of purpose. OpenAI in particular felt like a role that my entire career had been building toward, which made this decision even harder.

But what I’m learning now is that grit and endurance are not the only skills required to have impact over decades. Sometimes the harder thing is to stop, listen, and trust that taking care of yourself today makes it possible to contribute for much longer tomorrow.

This experience has also strengthened my conviction about why this work matters.

It has been a jarring experience to spend my days helping build the future while simultaneously navigating a disabling disease that still has no cure.

Over the last seven years, I’ve spent countless hours in doctors’ offices, dealing with symptoms, treatments, insurance, uncertainty, and all the invisible work that comes with being a patient. Like millions of others living with chronic illness, I’ve experienced firsthand how difficult healthcare can be to navigate, even when you have every possible advantage.

More than ever, I believe that some of the most important opportunities for AI lie in helping people solve real problems in their daily lives: their health, their finances, their time and the everyday burdens that shape human experience.

In particular, curing disease is the most important thing AI could accomplish. I’m excited to continue working towards cures through OpenAI but also through my work with @ChronicleBioAI and @CODA_research.

I’m deeply grateful to @sama, @gdb and the OpenAI board for their support during this time and for offering a way for me to continue contributing to the mission without sacrificing my chances of recovery. I’m also so thankful to my team and the many extraordinary colleagues I’ve had the privilege to build alongside.

For now, my focus is recovery. But my belief in the potential of technology to solve deeply human problems has never been stronger.

Today, I shared with the OpenAI team that I have decided to leave my full-time role at OpenAI and transition to being a part-time advisor.

Three months ago, I had to go on medical leave after a severe exacerbation of a chronic illness I’ve lived with for seven years. During that time, it became clear that the road to recovery would be much longer and more complex than I had anticipated—and that I needed to focus on it fully.

When I went on leave, many people told me I was courageous for prioritizing my health. The truth is that I am only making this decision now because I failed to make it many times before.

Over the years, doctors, friends, colleagues, and loved ones encouraged me to slow down. Two years after I got sick, Facebook offered me the opportunity to take a full year of medical leave. I didn’t even pause to consider it. I immediately said no. At the time, Zuck told me I should play the long game. I wish I had listened.

Looking back, I realize that a lot of what made me successful also made this decision incredibly difficult.

I grew up believing that opportunities were precious and that when they appeared, you grabbed them with both hands. That mindset carried me from a small town in southern France to opportunities I never could have imagined. By the time I turned 40, I had already gotten to do more than I’d ever dreamed possible as a kid growing up in Sète.

I love building. My work has always given me a deep sense of purpose. OpenAI in particular felt like a role that my entire career had been building toward, which made this decision even harder.

But what I’m learning now is that grit and endurance are not the only skills required to have impact over decades. Sometimes the harder thing is to stop, listen, and trust that taking care of yourself today makes it possible to contribute for much longer tomorrow.

This experience has also strengthened my conviction about why this work matters.

It has been a jarring experience to spend my days helping build the future while simultaneously navigating a disabling disease that still has no cure.

Over the last seven years, I’ve spent countless hours in doctors’ offices, dealing with symptoms, treatments, insurance, uncertainty, and all the invisible work that comes with being a patient. Like millions of others living with chronic illness, I’ve experienced firsthand how difficult healthcare can be to navigate, even when you have every possible advantage.

More than ever, I believe that some of the most important opportunities for AI lie in helping people solve real problems in their daily lives: their health, their finances, their time and the everyday burdens that shape human experience.

In particular, curing disease is the most important thing AI could accomplish. I’m excited to continue working towards cures through OpenAI but also through my work with @ChronicleBioAI and @CODA_research.

I’m deeply grateful to @sama, @gdb and the OpenAI board for their support during this time and for offering a way for me to continue contributing to the mission without sacrificing my chances of recovery. I’m also so thankful to my team and the many extraordinary colleagues I’ve had the privilege to build alongside.

For now, my focus is recovery. But my belief in the potential of technology to solve deeply human problems has never been stronger.

♥️ GPT-5.6 is a major step forward for health, both at the frontier and at cost.

These models push the frontier of performance per dollar, bringing the best health intelligence to all. The smallest variant, GPT-5.6 Luna, evaluated at the lowest reasoning effort, outperforms GPT-5.5 at the highest reasoning effort–despite costing 25x less. The largest variant, GPT-5.6 Sol, sets a new high bar at cost.

Another especially cool result: physicians found fewer flaws in GPT-5.6 responses than physician-written responses.

We collected diverse tasks that remain difficult for recent OpenAI models, across patient-facing and clinician-facing use cases. We asked speciality-matched physicians to write responses to these tasks with unlimited time and web access. We then asked other physicians to compare responses side-by-side, blinded to their source. Physicians were asked to comment on areas of improvement across five axes: accuracy, communication, completeness, instruction following, and health decision helpfulness. We then reported the fraction of responses across sources rated perfectly across all axes, across 20,000 total axis ratings. GPT-5.6 Sol appeared strongest, although all GPT-5.6 models performed significantly better than physicians.

GPT-5.6 is a major step forward for health intelligence.

Across the lineup, we’re delivering stronger performance at lower cost: GPT-5.6 Luna outperforms GPT-5.5 at its highest reasoning setting while costing 25x less.

Together, these advances raise quality while making advanced models accessible to more people globally.

Rest assured that GPT 5.6 Sol will stay in the ChatGPT subscription you pay for. Including Go, Plus and Pro subscriptions. At least until we ship an even better model.

Today we present Morpheus, a persistent enterprise simulation platform designed to make Continual Learning a reality. Morpheus is the world’s first real world Reinforcement Learning environment.

Every Reinforcement Learning environment operates in the game world. Benchmarks like Atari, OpenAI Gym, MuJoCo, and Procgen are all small, game-like worlds that reset every few minutes.

But the real world never resets. A business keeps running and evolving everyday.

We tested how frontier LLMs would perform in realistic and dynamic business environments 🧬on Morpheus. The main conclusion was that LLMs are not continual learners.

🧵Here’s how we did it and what we learned:

Yesterday, we made GPT-5.6 Sol Ultra generally available. Today, we're sharing that it produced a proof of the 50-year-old Cycle Double Cover Conjecture using 64 subagents in just under one hour. We're sharing the prompt and proof below. We're excited to see what you all do with Ultra!

BREAKING - OFFICIAL RESULTS: GPT-5.6 Sol by @OpenAI is 1st overall on Design Arena with an Elo of 1353.

This puts GPT-5.6 Sol above Claude Fable 5 by @AnthropicAI and in the same performance band as GLM 5.2 by @Zai_org on frontend design.

This is an 18-position and 60-point Elo leap from GPT-5.5.

GPT-5.6 Sol also establishes a new Pareto frontier for preference vs. speed, faster than any model at this performance.

Congratulations to the @OpenAI team on the launch!

GPT-5.6 Sol is a breakthrough in complex reasoning and data analysis.

Here, it analyzes hundreds of pages across a lending deal, reconciles terms across agreements, financials, diligence, collateral, and risk materials, flags issues, and saves a source-cited report to Box. https://t.co/vqo99MHhgg

GPT 5.6 Sol is Insane for web designers!

Prompt ↓ https://t.co/r8kWamEva4

GPT-5.6 Sol Ultra found me a solution to another Erdos problem not long after this one.

Problem #793 asks about asymptotic of a 2-primitive set. GPT again came up with an extremely short and elegant construction that enhances original Erdos method used to prove a weaker result.

GPT-5.6 Sol, Terra, and Luna from @OpenAI are now generally available on Amazon Bedrock. Three tiers of intelligence, from flagship reasoning to fast inference, running on Bedrock's next-generation inference engine built for high-performance, security, scale, and reliability. https://t.co/Hn2z5M2Jp2

OpenAI Build Week is here.

The challenge starts July 13. Across the week, join live sessions and community events with builders around the world.

Registration is open.
Bring the idea sitting in your backlog.
Build it with Codex. https://t.co/9g0oROTIqk

We stand at a critical crossroads in the debate over AI governance in the United States, and it feels like we are inching closer to a very serious battle over whether or not open source models will even be allowed in an environment where a new de facto licensing regime has been taking shape.

Lacking formal congressional statutory frameworks or clear administration rules (like the diffusion rule revision), we appear to be left with a sporadic, arbitrary, non-transparent process for model review. The fiction of “voluntary” agreements hangs over this debate, and some large model developers are already showing an incredible willingness to bend over backwards to accommodate national security-related officials / orders that the rest of us are not privy to. It's a very opaque process. And those model developers are expected to play ball with those officials, or else their models get pulled from the market or held up for long periods. Or they will lose any government procurement contracts they have. There is nothing “voluntary” about it when that Sword of Damocles hangs in the room.

As this mess worsens, at some point the question of how to handle open source models will come into sharper focus because it will have to. I've even heard some rumors lately that something may be coming from the admin on this front to address this.

Needless to say, if this informal new AI model review regime expands and takes on more pre-vetting characteristics / requirements, it is hard to see how open source players could comply with such quasi-licensing of AI models. Specifically, if this ambiguous new regime is accompanied by a general presumption of ‘restrict-until-permitted,’ then that would spell doom for open source. That is a very dark path for our country.

Worse yet, of course, would be a move by national security officials to more directly restrict open source models and capabilities. If that happens, then we would be right back in the thick of a Clipper Chip-like battle along the lines of what we saw in the late 1990s. That is a much darker path for America.

Meanwhile, open source developers have no “golden shares” or other goodies to offer the government to make their problems go away.

Let’s be clear: If our government takes the dark path, it will become the single most important battle over computational freedom of modern times. It is time for people to make a stand in defense of open source before it is too late.