Search: “models”

Presumably GPT-imagegen-2 (aka ChatGPT Images 2.0 aka gpt-image-2) works as a tool which the models generate prompts for? I wish we could see those prompts, like back in the DALL-E 3 days https://simo

I upgraded my Claude token counter tool to compare different models and Opus 4.7 does appear to use 1.46x times the tokens for text and up to 3x the tokens for images - it's priced the same as Opus 4.

An obvious way to release Mythos class models with uncertain autonomous ability is to make them only available on the website, like Gemini Deep Think or ChatGPT Pro. Minimal risk of being used for aut

Claude remains irreducibly Claude. If you know, you know. (The fact that models have distinct personalities that are consistent across generations is technically interesting, it also makes it very eas

Is there somewhere a collection of the best agent/coding harnesses for each models, especially open-source and local ones? In my opinion, the biggest reason why people are struggling with open/local m

It is going to be like what happened in coding: as soon as models crossed a certain threshold (Opus 4.5, GPT-5.2, Gemini 3), suddenly Claude Code & Codex were viable. Before that, it was all about cod

let's go open-source and local models! Uber's CTO told @LauraBratton5 that AI coding tools—particularly Anthropic’s Claude Code—has already maxed out its 2026 AI budget 📈 “I'm back to the drawing boar

I'm releasing the 34 slides on how we design and train best-in-class edge models at @liquidai I presented these slides yesterday at @aiDotEngineer They cover model architecture, pre-training, scaling

A good example of why open weight and open source models are important - they permit users to fine-tune specific use cases with greater cost efficiency. As has been the case in other technology market

I was curious about how omni decision models could be used in rescue workers bodycams or smart glasses, so I decided to build a quick demo. I went with @liquidai d1-omni-600M since it supports both vi

Satya is spot on. The interesting engineering problem isn’t just making models behave, it’s building systems that don’t need to trust them in the first place. We’re working on some pretty fun problems

A new breed of startups is emerging to help businesses use AI smarter and cheaper, shifting towards open Chinese models and giving the likes of OpenAI and Anthropic a run for their billions. Read more

Great report from Google and MIT. Co-designing ML models and the accelerators is an exciting research direction. This report introduces Coco, an agent platform TPU architects use for hardware and mode

Introducing North 2. Enterprises have been compromising on agentic AI for years: platforms that aren't scalable, models that aren't sovereign, control without enterprise-grade security. That ends toda

Banger paper from Meta Superintelligence Labs. They find something super interesting and unexpected. (bookmark it) Base models with a light harness often solve more agentic tasks than their RL post-tr

We'll be spending a lot more time trying to understand the outputs of language models. A few thoughts, tips & tricks: Writing. Something I've had success with: Ask your LLM to explain something in ASD

Took a while, but here it is, a mega write-up on language models for text classification and, of course, Jev. It's basically a visual guide to RNNs, CNNs, transformers, and calibration, with hands-on

btw i had no idea what i was doing when i started this but learned so much about models in the process and feel like i have a much better sense of what’s happening under the hood managing someone (an

A lot of alignment issues would be sorted if companies had to be 100% transparent on datasets used for training models. No cyber or biological (outside standard medical) data allowed for base models T

Every answer in Perplexity starts with embedding and ranking models picking the most relevant results for the query. Today we published research on how we built SoTA serving infrastructure behind thos

Benchmarking AI systems is a continual process that co-evolves with the models. New benchmarks challenge AI capabilities with emerging questions to shape the directions and feedback signal of the rese

I see a lot of my TL freaking out about this Here is the reality: Frontier models will one shot just about anything at 10,000 tokens per second in a few years Do you really think we can monitor that?

14/ If frontier labs are serious about defense, they should offer cyber models to defenders at cost and stop fighting open weights through the regulatory channel. They created the problem, and for muc

OpenAI is proposing to remove access to its models in Cursor on November 12. OpenAI, Cursor CEO, and Anthropic founder all weighed in on X with so much subtly, I had to go Nancy Drew mode and dissect

Tenet came out of a close collaboration with @ItsJulioPereyra @nikogrupen @calvincongelado @gabepereyra: many base models, recipes, and data approaches; many runs, rollbacks, and harness revisions to

Tenet came out of a close collaboration with @PereyraJulio @nikogrupen @calvincongelado @gabepereyra: many base models, recipes, and data approaches; through many runs, rollbacks, and harness revision

‘Open Models, Production Agents’ is underway! Tonight means another event hosted at FriendliAI's San Francisco HQ. A very lively turn out, and a stellar lineup of panelists exploring how open models a

The post titled “Welcome @ATT to open models!” announces AT&T’s participation in open‑source AI model initiatives. It references the Ollama platform and cites Amir Efrati’s comment on the growing tren

'OCR is just a feature now. Frontier models will eat it.' We hear this constantly. The data says otherwise. Across three GPT generations, parsing accuracy gained ~24 points, while cost per page 4x'd.

Clément Delangue, CEO of Hugging Face, said the company’s focus on open‑weight AI models helped it withstand a hacking incident involving an unreleased OpenAI model. He also noted that China is leadin

Kimi K3 rivals Anthropic and OpenAI’s top models at a fraction of the cost. 3 / 1M input tokens. 15 / 1M output. $0.30 / 1M cached You can now route your hardest reasoning to an open model without pay

The demand for GLM-5.2 and other frontier-level open models has been surging on Ollama's cloud. We're adding capacity in anticipation for some very large models next week! To make sure Ollama's infras

AI has started building its own successors. It's happening right now. Humans still kick most of it off, but the models are already training the next models, and each version builds a better version fa

Long-running models can solve hard open-ended problems, but their persistence can create safety risks that shorter-horizon evaluations miss. We’re sharing what we learned from studying a long-running

ICYMI - you can now build recursive language models (RLMs) with deepagents: the main agent can write custom code to recursively call subagents! this is super flexible -- the harness can take any shape

Factory (@FactoryAI) CEO Matan Grinberg (@matanSF) says 'In the next 12 months, 90% of tokens will be going to open models.' Enterprises are already shifting rapidly.. 'At the beginning of the year, <

This post discusses Baseten's partnership efforts to democratize access to open-weight models for use in AI agents, making advanced model capabilities available to a broader audience. The initiative a

'Alex really hit the nail on the head, by sending data to a company that has extremely smart models, you are really giving up your business's recipe for them to copy.' Our CEO @vipulved when asked abo

'Most enterprise workflows don't require frontier AI models. Outside of coding, tasks like summarization, document generation, and briefing can often be handled effectively by lower-cost open-source m

With inference scale and research scale to drive efficiency, and ever-improving frontier models as brains, this would be a way for the Labs to undercut even open weights models. Some companies will st

Open models are the future, and that future starts now GLM 5.2 has become my daily driver. here’s how and why: You can start building with GLM 5.2 in minutes: 1️⃣ Download dcode 2️⃣ Select your model

As open models get stronger, more workloads move into the competitive inference market. That pushes the real fight toward speed, cost, reliability, and control. Together AI is where open models become

You don't need Fable for the most complex tasks, from training models for protein prediction to optimising compilers Our open source Zenith harness takes base models to the top of FrontierSWE via adap

As this post points out, contrary to what many say, the US government could absolutely effectively ban open weights models. That doesn’t mean you won’t be able to download the weights & run them, but

This X/Twitter broadcast by Clem Delangue (CEO of Hugging Face) likely provides an introduction to running open source AI models locally on personal machines, covering topics such as benefits of local

Live Stream: Welcome to open source AI Lots of new folk are starting out on their journey with open models. Come join our livestream with all your questions about local models, open coding agents, and