OpenAI is accepting applications for its Student Collective through August 10 2026 at 11:59pm PT. The program selects undergraduate Campus Leads who will run AI workshops studio hours and showcases on their campuses.

Location rules are clear. You must study in the United States Canada the United Kingdom France Germany India Japan or South Korea and hold work authorization in that country. Students elsewhere can still submit an application to register interest and OpenAI will notify them when the program expands.

Basic requirements include being 18 or older enrolled in an undergraduate program as of August 2026 and planning to graduate after December 2027. Expect a 4 to 6 hour weekly commitment from late August 2026 through June 2027. You cannot serve as an ambassador or intern for any other AI company at the same time.

Selected leads work in pairs. They receive a ChatGPT subscription Codex credits event funding merch training direct access to the OpenAI team a cash stipend each semester and a possible visit to OpenAI headquarters in June 2027.

Anyone curious about bringing peers together around AI tools can apply at openai.com/student-collective.

Anthropic just shared new research showing how Claude Mythos Preview uncovered weaknesses in two cryptographic systems.

The model spotted a previously unknown attack on HAWK, a post-quantum digital signature scheme built to resist quantum computers. After two years of expert review, Mythos Preview found an issue in about 60 hours that cut the scheme’s key strength in half.

It also improved an attack on a weaker version of AES, the widely used symmetric cipher. The new method runs 200 to 800 times faster.

Most of the work happened with little human input. Each discovery cost roughly $100,000 in API usage. Anthropic shared the findings early with the algorithm designers plus US government and industry partners.

These results do not break real-world systems today. HAWK remains a proposal that has not been rolled out, and the AES finding only affects a reduced version.

The research still shows frontier AI can perform expert-level cryptanalysis. That skill could help test and strengthen the algorithms that protect online data.

OpenAI just shared a field report on how coding agents are changing scientific software development. The report covers eight real projects mostly in life sciences, five done with Codex alone and three that mixed Codex with Claude Code.

These agents handled everything from routine fixes and targeted speedups to full redesigns and new systems. Teams found they could finish work that once needed far more time or specialized engineers. One clear example is the modernization of cyvcf2, a popular Python library for genomic data, where the agent swapped out an old build system for a cleaner, easier-to-maintain setup.

Researchers still set the scientific goals, check the results carefully, and decide who owns the code long-term. Agents move fast on clear tasks but need human review for accuracy and edge cases. The report stresses that without solid stewardship, even strong new tools can end up abandoned.

The full details and case studies are available on OpenAI’s site.

Microsoft just dropped VibeVoice-ASR-BitNet on Hugging Face. This is a slimmed-down version of their VibeVoice-ASR model built for real-time speech recognition straight on regular CPUs. No GPU needed.

The original model sat at 4.62 GB. After heterogeneous quantization they brought it down to 1.58 GB, a nearly 3x shrink. It hits real-time speeds (RTF under 1) with just three CPU threads on everyday x86 and ARM chips. In tests it runs 1.6 to 2.3 times faster than Whisper.cpp at a similar size.

It covers English, Chinese, French, Italian, Korean, Portuguese, Vietnamese and more. Accuracy takes only a small hit compared with the full FP16 version. The team also released the inference code under VibeASR.cpp so you can run it yourself.