OpenAI 连发图像模型与网络安全专用 GPT

Images, upgraded—introducing ChatGPT Images 2.6. Now with GIFs and reference images. Plus, two new models are coming to the API with 50% faster image generation. https://t.co/kcuOhTipYR

RT @paulg: Now we'll finally learn what's in the Epstein files. Mike Johnson is no longer in a position to shut down the House in order to…

Introducing GPT‑6 Cyber: a major advance in security research that pairs stronger capabilities with better model alignment. The model powered the Linux kernel research we announced yesterday, and security teams at companies like Mozilla, Palo Alto Networks, Calif, and Cisco—alongside our own at OpenAI—are already putting it to work. GPT-6 Cyber is available to select Daybreak Red customers and we are expanding access over time. https://t.co/Nzab3Z1Td6

Our security researchers built an autonomous cyber vulnerability discovery, exploitation, and patching pipeline. In a single run with an upcoming cyber model, it validated and generated patches for 948 local privilege escalation vulnerabilities in the Linux kernel at a total API cost of $1.2 million.

RT @SteveRattner: Democrats have won more votes than any party in midterm history: 66 million and counting. https://t.co/7s6vBjTUzG

RT @PhillipsPOBrien: Watching all these Republican attempts to explain why they lost the election is painful, because they cannot come out…

RT @OfficialLoganK: Today we are rolling out Gemini Omni Flash 1.2, with: - longer video generation (15 seconds) - deeper cinematic contr…

RT @GoogleAI: Meet Gemini Omni 1.2 Flash ⚡️ We’ve made the model more cost-effective, bumped the video generation and editing limit up to…

A new way to measure how AI agents handle the routine analyses of wet-lab science—BioBasicsBench. Developed with Ligo, a biotech company focused on enzyme design, the benchmark draws on 100 tasks from real experiments to test whether agents can interpret raw lab data, identify errors, and recognize when the evidence doesn’t support a conclusion. Accelerating biological research starts with getting the everyday work right. BioBasicsBench shows where models need to improve, and helps us track what those gains mean for scientific progress, biosafety, and biosecurity. https://t.co/wN2xLk0YeW

RT @_mohansolo: We just redesigned the Antigravity app to be much more sleek and delightful to use! Hope you all enjoy it. More to come in…

RT @SamuelFitouss10: - Je ne vois AUCUNE raison de continuer à entraîner des modèles d’IA toujours plus puissants. - Guérir le cancer ? -…

The era of System One Vision Model is here! Introducing VFlash: parsing the visual world in parallel at unmatched speeds for Physical AI. Most embodied prediction tasks like object localization, robot trajectory planning, and dense 3D motion are fixed-length float vectors. For example, a bounding box is always 6 tokens, a 10-waypoint robot arm trajectory is 54: we know these beforehand. Instead of decoding one token at a time, we can output the entire geometric shape in one go. VFlash enables up to 12x faster action decoding and a 5.1x overall robot inference speedup on edge GPUs like the Jetson Thor and DGX Spark. What’s surprising is that it ends up even more accurate than the VLM backbone, with up to 61% lower 3D trajectory error. The intuition is that VFlash avoids the cascading errors of autoregressive decoding, where every coordinate is written in ink and every later point loses the chance to backspace. Everything that moves will be autonomous, and everything autonomous will need to think on its own chip. The next inference revolution is physical reasoning at the speed of reflex. And as always, it’s open paper, open source! Link in thread:

RT @GoogleDeepMind: We’re sharing new research demonstrating how AI agents can accelerate the science of stress-testing encryption. Guided…

We partnered with @fmf_org and its member firms on a new framework to help identify when bypassing an AI system's safeguards could enable serious cyber harm, and prioritize stronger protections. "...This framework is an important step toward a common methodology for evaluating and comparing the severity of cyber jailbreaks, including the capabilities they unlock and how readily they can be used. Shared approaches like this can help the AI and security communities build a clearer evidence base and prioritize improvements to safeguards." - OpenAI's Sasha Baker, Head of National Security Policy https://t.co/epOq98YPau

RT @daveeyyy_: Yann LeCun: The Al industry is stuck because every lab is chasing LLMs. Real Al agents will need to predict the consequences…

RT @_doubleAI_: 1/ What if an LLM could not just edit a model's weights, but re-architect it as it trains? We tried just that. The resulti…

RT @sean_n_wu: The Collaborative Intelligence Benchmark paper is out! We tested 18 AI models as teammates on 240 tasks. The best model sco…

RT @fouadmatin: Today’s GPT-6 Cyber release is a meaningful step for defenders: stronger vulnerability research and better alignment. We’ve…

RT @AndrewYNg: Join me and 2000 other AI engineers and builders at AI Dev in New York City, Nov 30-Dec 1! A LinkedIn study found that over…

I'm giving a Keynote talk at CoRL next Monday Nov 9, please come by at 1:30 pm at Hilton Austin! We've been cooking 👀

RT @GaoyueZhou: Introducing ID-WM: a hierarchical world model that decouples "where to go" from "how to get there." Finally, we can plan ov…

Companies are killing for good engineers right now! These guys are offering a paid first-week vacation worth up to $10,000, planned with a dedicated travel concierge for new engineers who join their team. If you refer a candidate who joins, they give you a $30,000 bonus, and the person who joined also receives one.

RT @PolymathicAI: Interested in building what’s next in AI for Science? Join us at PolymathicAI in New York (NYU + Flatiron). We are looki…

How to replace a large, expensive, and slow model with a small, cheaper, fast model and still get the same results. 7x faster and 50% fewer tokens. This is like fine-tuning, but without touching the model. Here, we teach Haiku, using Zep Agent Skills, to do what Opus 5.5 does to complete a task. • It takes 7 minutes with Opus 5.5. Only 59 seconds with Haiku. • It takes 1.4M tokens with Opus 5.5. Only 700K with Haiku.

RT @che_shr_cat: 1/ A 109M text model trained with good views matched next-token prediction with 42x fewer samples on WIT-1024 (.109 at 21.…

Wordle 1,965 4/6 ⬛⬛🟨🟨⬛ ⬛⬛⬛⬛⬛ ⬛🟩🟩🟩🟩 🟩🟩🟩🟩🟩

Wordle 1,964 5/6 ⬛🟨⬛⬛⬛ ⬛⬛🟨⬛⬛ 🟨⬛🟨🟨⬛ 🟨🟨⬛⬛🟨 🟩🟩🟩🟩🟩

RT @KenRoth: In the United States, Brazil, Hungary, Serbia and Israel, "voters are turning out in droves to cut autocrats down to size. In…

Building more software means managing more data, access rules, deployments, and monitoring. Every company I talk to is using agentic coding to do more. Codebases are growing, and so are problems. Here is the best way to manage complexity: ↓

I know many teams that are, unfortunately, reinventing all these features right now because they need good context to run agents. Here is a managed system where you connect your data, and it shapes it for agents: • It automatically cleans the data as it arrives • It organizes it • It summarizes it • It builds descriptions • It computes statistics

There are 10,000 things you can do with small models running on your local computer. Many small models today compete very well with larger models at a fraction of the cost. @thewebAI released an 8.8B-parameter model that's a dream, and now they have a Mac app that you can run on your computer.

I'm so happy most new personal agents are coming out iMessage-first instead of Slack or Discord. I know WhatsApp and Telegram are big in Europe, but in the US, iMessage is king. This looks like a nice personal agentic advisor if you want to use AI to learn and follow through on some of your goals. It connects context across apps, remembers goals, and can reach out with a useful next step before you ask.