OpenAI 主攻 COBOL 等遗留代码现代化

Our latest model advances bring stronger capabilities for building and migrating software in low-resource programming languages such as COBOL, Fortran, and Visual Basic. These languages power software that banks, governments, and businesses depend on. Progress here means understanding decades of business logic and helping developers modernize those systems while preserving what works. We’re building these capabilities around the challenges developers and enterprise customers bring us. If your team is working on these systems, tell us which languages and workflows we should tackle next. https://t.co/2TbnkQixJ1

RT @FredLambert: Everything Yann said here is roughly correct, and Musk knows it, which is why he responded like a 14-year-old. https://t.c…

RT @ylecun: @spiroskaye @elonmusk I'm definitely not anti-achievement and never criticized real achievements, including by Elon. I even own…

RT @JustinWolfers: Washington has discovered a brilliant financial strategy. Cut benefits for people who need them, cut taxes for people wh…

We’ve acquired Orchestra Bio, a platform that helps biopharma teams coordinate the complex process of drug development. Together, we’ll build on Rosalind, our AI models and tools for life sciences research, to streamline those operations and help new treatments reach patients sooner. Welcome @ashokaraj_ and team! https://t.co/vi51OhznQn

In 1994, software was dead. People told me programming was for nerds and that I should become a doctor or a lawyer instead. In 2004, software was dead. People told me that someone from India would take my job for $5/hour. In 2014, software was dead. People told me that no-code was going to kill every job and doom my career. In 2024, software was dead with Devin, Windsurf, Copilot, and OpenAI o1. We kill software every 10 years, and yet the demand for good Software Engineers has never been higher.

RT @SamCKx: Yann LeCun, one of the world’s foremost AI, machine-learning and robotics researchers, an engineer, NYU professor and ACM Turin…

RT @SteveRattner: Trump has raised $330 million from private donors for his White House ballroom. About half have received federal contrac…

Why would anyone spend money buying apps when they could spend 10x that amount buying tokens and wasting their weekends building everything from scratch?

We built a robotics data engine with Astra-level performance at 125x lower cost. And we are open-sourcing the weights today! Introducing Flora, a suite of open models to parse the physical world and turn raw footage into rich training signals. Flora already powers our in-house data engine, labeling 200K hours of videos a day on 500 GPUs. We created it to scale the frontier for robot learning. Now you own the weights too. Flora gives you: - High-quality, timestamped captions to curate and filter human egocentric and robot data; - Dense progress rewards for quality control and RL post-training; - Rubrics scoring for real-world benchmarking Try it today, links in thread:

RT @SkinnerPm: Our country is threatening our allies because a vile rich person wants us to. Sometimes our stupidity is made starker with i…

RT @KenRoth: It speaks to the unchecked power of the American presidency that a single warped occupant of the Oval Office can transform the…

Instead of generating videos, Viggel’s JST-2 outputs 3D characters that move in their environment. It combines character, motion, and scene generation into a single model: • Upload a photo and it creates the character • Describe how you want it to move, or upload a reference video • Generate the world around it from text or a photo

RT @lrozen: after illegally cutting down 400 trees on it last weekend

I still remember when the goal was to make these models sound like people. And now we are in the "emotion" phase. There's absolutely no way I can tell these voices apart from real people. Listen to the examples and how easy it is to generate emotional text by describing how the voice should sound. You can simply ask for "embarrassed," and the voice will change to match.

Great way to explore new product concepts or compare alternatives with 3D designs! This is an engineering world model. You give it a text prompt or an image, and it generates a 3D assembly. Look at the examples: it breaks a design into smaller parts, creates each part in 3D, and assembles them.

Speed up your code like crazy! Maxwell is a new kind of AI. It's a code execution model that speeds up your code on CPUs and GPUs. "Code execution models" are a new category of AI. Maxwell is the first one, but this category will explode in popularity, and you'll see why. Say you have a script that moves and processes some data. You integrate your code with Maxwell, run it, and let it observe how it runs on your hardware and analyze the data your script moves around. Maxwell will identify bottlenecks and look for faster algorithms and machine instructions for your workload. As long as your script runs, Maxwell rewrites the binary to make it faster. In one example, Maxwell made a pandas pipeline 38.4x faster. It used more CPU cores, combined processing steps, reduced unnecessary memory reads and writes, and selected the right algorithms for the data the script was processing. For example, imagine you want to check whether a number belongs to a collection. You could use hashing, but if the numbers occupy a small, dense range, a compact bitmap can make that check much faster. In short, that's one of the algorithmic data-dependent tricks Maxwell can leverage to speed things up. Here is the most impressive part of all of this: Maxwell produces a machine-checked mathematical proof that each replacement preserves the original behavior. Basically, any code they modify will always produce the same output as the old one. This is really cool for anyone working on AI or data engineering workflows. You will squeeze much more work from the hardware without rewriting your application. You can try out your scripts using Maxwell by going to this link: https://t.co/wrMA61o2xB Thanks to the @_doubleAI_ team for partnering with me on this post.

This is pretty interesting: An open-source memory and activity-recording layer for developers using coding agents such as Claude Code, Cursor, Codex, and OpenCode. The idea is to collect session history across tools and turn it into reusable knowledge. After a session, this creates a candidate "lesson" you can approve, making it available to future agents.

Here is a model that was trained specifically to create layered designs. This is good because you can use it to design something, but you can also modify it later in any other editing software. Usually, when you generate an image with a regular model, you get a bunch of pixels. Vyb does something different: it builds a structured composition containing text, vector graphics, and photos. And all of these remain individually editable.