If AI output does not show where the answer came from, reviewers have to check the work manually, slowing the process.
LLMS
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AI assistant automates low-risk tasks from individual channels
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We’ve created channels for everyone on our team. If you need something from Susie, you go to Susie’s channel and you ask for something. Susie’s Claude reviews the requests 24/7. If Susie’s Claude deems it low risk, it just executes the task and confirms in the thread. If
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Sports AI with Colin Cowherd live on FOX Sports
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Sports AI with Colin Cowherd is live in the FOX Sports App.
— ElevenLabs (@ElevenLabs) 24 juin 2026
Ask questions about FIFA World Cup group stage, fantasy football picks, and bold takes on who is struggling this season. He'll give you a real answer, push back if he thinks you're wrong, and leave you with a gut check… pic.twitter.com/0iuXqQCjWoSports AI with Colin Cowherd is live on the FOX Sports app. Ask questions about the FIFA World Cup group stage, fantasy football picks, and hot takes on who's struggling this season. He'll give you a straight answer,
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AI21Labs lands #1 on DeepResearch Bench II without new agents
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1/3 We just landed #1 on DeepResearch Bench II without building a single new agent.
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OpenAI and Broadcom Unveil Revolutionary AI Chip
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OpenAI has announced its first AI chip, designed and produced in partnership with Broadcom. > New state-of-the-art in performance per watt.
> OpenAI models were used to accelerate its development.
> Will be deployed at gigawatt scale. -
Jalapeño chip tests with ML workloads including GPT-5.3-Codex-Spark
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Engineering samples of the Jalapeño chip run machine learning workloads in the lab at target production frequency and power, including GPT-5.3-Codex-Spark. I hope this is not the limit.
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OpenAI unveils Jalapeño, its custom AI chip for LLM inference
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OpenAI just unveiled Jalapeño, its first custom AI chip built from the ground up for LLM inference. It's OpenAI going deeper into the full stack: chips, cores, memory, network, racks, scheduling, deployment, and product experience.
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Insights from running 350M GTM agents: caching, bounding, fairness
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At Interrupt, @Clay's Head of AI @jeffbarg shared insights from running 350m GTM agents a month.
— LangChain (@LangChain) 24 juin 2026
✅ Caching can cut LLM costs up to 70%
✅ Bounding tool calls often improves quality, not just cost
✅ Fairness queues matter once you have real multi-tenant load
Worth 12 minutes if… pic.twitter.com/2qbvyct3lxAt Interrupt, @Clay
's Head of AI @jeffbarg shared insights from running 350m GTM agents a month. Caching can cut LLM costs up to 70% Bounding tool calls often improves quality, not just cost Fairness queues matter once you have real multi-tenant load Worth 12 minutes if -
Waiting for Fable’s return while relying on Codex.
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Same haha, been leaning on Codex in the meantime but it's not the same, counting the days till Fable's back.
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Default per-task routing prevents overpaying for single model
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Per-task routing is just going to be the default, no single model wins every prompt and pretending one does is how you overpay.