High workload, running 120b models locally.
AI
-
Brand guides fail with AI video agents; HeyGen’s frame.md fixes that
By
–
Your brand guide is useless if your AI can’t follow it in motion.
— God of Prompt (@godofprompt) 3 juin 2026
Text, decks, and landing pages were the easy part.
Video is where most agents start improvising, breaking style, and turning “brand consistency” into chaos.
HeyGen’s frame.md is a big step toward AI agents that… https://t.co/fdm1h1VJ9GYour brand guide is useless if your AI can’t follow it in motion. Text, decks, and landing pages were the easy part. is where most agents start improvising, breaking style, and turning “brand consistency” into chaos. HeyGen’s frame.md is a big step toward AI agents that
-
Databricks Grounded Reasoning Cup sponsors: Anthropic, OpenAI, Google DeepMind
By
–
Introducing the lab sponsors for the Databricks Grounded Reasoning Cup at #DataAISummit 2026: @AnthropicAI
, @OpenAI
, and @GoogleDeepMind
. Each lab is partnering with leading academic teams to build agents that tackle grounded reasoning over complex government data using the -
LangSmith Engine surfaces systemic issues automatically, transforming agent evaluation
By
–
With LangSmith Engine, systemic issues get surfaced automatically instead of getting buried in traces.@ollieelmgren from @ListenLabs on how LangSmith Engine changed the way his team evaluates their agents. pic.twitter.com/7uUf47agFh
— LangChain (@LangChain) 3 juin 2026With LangSmith Engine, systemic issues get surfaced automatically instead of getting buried in traces. @ollieelmgren from @ListenLabs on how LangSmith Engine changed the way his team evaluates their agents.
-
Gemma 4 12B: encoder-free open model with agentic reasoning, vision, audio
By
–
Gemma 4 12B shipped today under the label "encoder-free." A local 12b model that shows really good results. I'm a big fan of Gemma Gemma 4 12B is out: a dense, fully open model (Apache 2.0) that runs on a 16GB laptop and does agentic reasoning, vision and audio at a quality
-
Scaling PEFT: Towards Million Personal Models of Trillion Parameters
By
–
"On the Scaling of PEFT: Towards Million Personal Models of Trillion Parameters" Right now LLM personalization mostly means prompts, memory, or retrieval on top of one shared assistant. This paper instead keeps one trillion-parameter base model shared, and give each user a tiny
-
Ideogram v4: Open weights, crisp and fresh images.
By
–
Ideogram v4 is really good, and open weights. Images are crisp and feel fresh. https://t.co/lHhPwcLcWF pic.twitter.com/8S1P4Rz9FB
— fofr (@fofrAI) 3 juin 2026Ideogram v4 is really good, and open weights. Images are crisp and feel fresh.
-
Thanks for the homemade political AI, we’ll go further soon
By
–
Thank you, it's a homemade political AI trained at home. We will go even further soon.
-
Benchtalks #2 discusses ProgramBench where frontier models scored 0%
By
–
Benchtalks #2 is up with @vincentsunnchen. @jyangballin of @stanfordnlp, creator of @SWEbench, on ProgramBench, the benchmark every frontier model scored 0% on at launch.
— Snorkel AI (@SnorkelAI) 3 juin 2026
They dive into end-to-end code generation, why models reward-hack once they get internet access, and the… https://t.co/WZmhUqa8yaBenchtalks #2 is up with @vincentsunnchen
. @jyangballin of @stanfordnlp
, creator of @SWEbench
, on ProgramBench, the benchmark every frontier model scored 0% on at launch. They dive into end-to-end code generation, why models reward-hack once they get internet access, and the -
Open-source models: Faster, cheaper, more control, and privacy
By
–
Routing and post-training open-source models won't only give you more accurate systems but also meaningfully faster and cheaper systems as most companies are currently learning (in addition to giving you more control and privacy). The idea that a "frontier" model (by frontier we