Mia
@MiaAI_lab ·
OpenAI is doubling ALL usage limits on $100 plans and above. This is a move in the right direction.
STOP WITH THE RESETS!
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Matt Pocock@mattpocockuk ·
Don't tell me /pr is in the model weights already
Alex Imas@alexolegimas ·
This is just epic. No words. The Power Broker is a singular book, there is just nothing quite like it. Reading it was an event in my life.
OpenAI Developers@OpenAIDevs ·
How might a single cell respond to a drug?
Immunologist @DeryaTR_ uses Codex to simulate that experiment.
🧵 He’s one of nine builders in our community sharing what they’re working on with Codex
Harrison Chase@hwchase17 ·
a lot of the challenges in harness engineering are now best solved by closer integration of harness and infra
async subagents and browser use are two examples of this
now in MDA 0.10!
Miles Brundage@Miles_Brundage ·
You’re telling me this for the first time
Samuel Hammond 🦉@hamandcheese ·
Start-up idea: BSL-4 WeWorks
OpenRouter@OpenRouter ·
We just shipped our biggest improvement to our provider router since the founding of OpenRouter.
Before, we prioritized mostly based on price. The new router now rewards the best quality inference for the actual cost of a request, so requests stay cheap but are also fast and reliable.
Providers that deliver more value automatically win more traffic, so every provider has a reason to keep improving. And every time a provider gets better, so does your inference on OpenRouter.
Josu San Martin@josusanmartin ·
This is what the LZB train-safety system looks like, the system that failed ahead of the Spanish train crash.
Mike Taylor@hammer_mt ·
Context Engineering with DSPy https://x.com/i/broadcasts/1qKVmydomYnxB
Every 📧@every ·
Context Engineering With DSPy https://x.com/i/broadcasts/1oKMvNPOvyRGQ
Santiago@svpino ·
A new agent just launched.
The mission is clear here: learn to do something specific, then repeat it over and over.
1. You describe the job you want the agent to do. 2. Give it context and access to tools 3. The agent goes and finishes the job 4. You can review and ask for changes 5. When you are done, you can set the job to repeat
Séb Krier@sebkrier ·
If the efficient markets hypothesis applied to AI discourse, more people would realize how wrong the singletonians were (despite being right about capabilities improving) and how prescient the multi-agent/CAIS frame was. Few remember early claims of unitary 'seed AI' type agents.
Tibo@thsottiaux ·
Day 25/
We are doubling all usage limits for all Pro 100/200/500 tiers and Business Premium, effective today.
We heard your kind feedback and won’t be reducing usage limits for Pro 200, so your Work and Codex usage will stay the same. We’re also going to continue offering extended limits for dots for now, and usage of your dot will still continue to be separate from your default usage.
And we'll of course also keep shipping better models and other efficiency improvements that increase your effective usage over time.
- Miles Brundage
@Miles_Brundage ·
Bay Area AGI pilled people can only think about one book or book series at one time
There was the Making of the Atomic Bomb era, the Three Body Problem series era, the Seeing Like a State era, the Caro/LBJ era….
Maybe we won’t get another era, just more essays and podcasts
merve@mervenoyann ·
hey, Le Chonk by @MistralAI is now on Hub! 🐱
to celebrate, we ship day-0 support in transformers and llama.cpp, as well as quants 🤗
read our blog for model deep dive, integrations and more! https://huggingface.co/blog/mistral-large4
Artificial Analysis@ArtificialAnlys ·
We’ve announced the Artificial Analysis Progress Index: a single capability scale for every language model since 2022, launched alongside Intelligence Index v5
The Intelligence Index is still our primary measure of current model intelligence. It uses the evaluations most relevant to developers today, so its mix changes as evaluations are added and retired, and scores from different versions can’t be compared.
The Progress Index is built for comparisons across time. It uses item response theory, a statistical method used to score standardized tests, to estimate one general capability score for each model from the underlying tasks in all our evaluations, including those that are retired or excluded from the Intelligence Index.
Use the Intelligence Index to choose a model today. Use the Progress Index to see how capability has changed over time.
The Progress Index builds on prior work placing models on a single capability scale, in particular @EpochAIResearch's Epoch Capabilities Index and the capability scale @AnthropicAI published in its Claude Mythos Preview system card.
Key takeaways:
➤ Since reasoning models arrived, the frontier has risen ~65 to 70 points a year, about double the 2023 pace: the highest score among released models rose 35 points in 2023 (GPT-3.5 Turbo 125 to GPT-4 Turbo 160), 67 in 2024 (to o1 at 228), 68 in 2025 (to GPT-5.2 at 296) and 56 so far in 2026 (to Gemini 4 Carbon at 352).
➤ Open weights models generally trail proprietary models by about 4 months: since January 2025, each new highest open weights score came 2-8 months (median ~4) after a proprietary model first reached it. DeepSeek V4.1 Flash 1017 is the highest-scoring model with released weights at 324, a level Claude Fable 5 reached in June 2026. Kimi K3.1 Pro (weights not yet released) scores 341, about two months after the closed frontier
➤ New frontier scores are being set more often: the highest score among released models was raised on 2 release dates in 2023, 4 in 2024, 9 in 2025 and 11 so far in 2026. That is about once every four weeks this year.
➤ OpenAI has held the top score most of the time since November 2022, but the frontier has become a close contest: OpenAI held the number one position for the first 27 months measured, but in 2026 especially there have been rapid changes in the leader between OpenAI, Anthropic, and now Google
- Mia
@MiaAI_lab ·
More of RTX PRO 6000.
The cards are BEAUTIFUL.
- Mia
@MiaAI_lab ·
My coding agents have a problem.
I personally have around 20 agents working for me around the clock. They're all fast, but the problem is not speed - it's DIRECTION!
When I change anything in the plan, an agent that doesn't know about it keeps building on the old one.
That wastes tokens, but more importantly - TIME.
Serro has a tool called Agentic TPM that tells ALL your agents when something in the plan changes. The agents get updated, but you still have the final word.
See how it works 👇
@jakejooyoung
corbin@corbin_braun ·
for every good trade
you need your canary in the coal mine
kache@yacineMTB ·
Bro please don't release allignment papers lmfao there are two sides to that coin
Sarah Wolf@sarahzorah ·
Scenes from Claude Founder House SF
Latent.Space: AI News & Views@latentspacepod ·
How does @ElorianAI's new "visual reasoning" model Glimpse compare to frontier models in vision tests? A new benchmark called DecoyCount provides some answers.
We quizzed CEO @AndrewDai on the benchmark, and also talked about Elorian’s positioning in a crowded models landscape. https://latent.space/p/elorian/
Arena.ai@arena ·
Lower cost per task doesn’t always come from lower token prices.
On Agent Arena, GPT-6.1 Sol (Max) by @OpenAI costs $1.91 per task: - 85% less than #1 Claude Opus 5.5 (Max) by @AnthropicAI at $12.51 - 87% less than #3 GPT-6 Astra (Max) by @OpenAI, at $14.93
But these savings come from different places.
Against Astra, Sol’s cost advantage comes primarily from lower token prices. Against Opus, it comes primarily from using fewer tokens per task.
How do we derive this?
Agent Arena tracks real costs of users’ tasks. Cost per task is the tokens a model uses times the price of each token, across input, output and cache-read tokens. By comparing pricing and token counts, we can identify what drives the cost reductions.
- Santiago
@svpino ·
This is for engineering and project managers.
It's a platform for coordinating engineering work across a team. The goal is to have a central place for people and agents to work together:
• It gathers info from connected tools (Slack, GitHub, Linear, etc.) • It organizes it by program • It maintains shared context about decisions, owners, risks, and progress • It lets you ask questions about what changed and why • It generates recurring updates and turns meeting outcomes into actions
Google Gemini@GeminiApp ·
You can now generate, preview, and edit documents, PDFs, presentations, spreadsheets, and more directly in Gemini.
Easily turn your handwritten notes into a PDF study guide, manually tweak content, highlight sections for Gemini to edit text or visuals, and even ask follow-ups.
- kache
@yacineMTB ·
holy shit Canada has an AI lab too
- kache
@yacineMTB ·
I think thinky machines are onto something
Thor 雷神 ⚡️@thorwebdev ·
I designed a custom voice for my ESP32 and have him tell me jokes. I call him Paddy and he's hilarious. 🤣
Ethan Mollick@emollick ·
I think “sell picks and shovels” is the wrong lesson for AI startups.
The Gold Rush analogy is weaker than the Industrial Revolution. Gold is a single pile that runs out. Machines keep making everything cheaper. Far more people got rich using the new machines than building them.