/3 DFlash replaces the autoregressive draft head with a block diffusion model. The drafter gets the target model's hidden states injected into the KV cache of every draft layer (not just the first like EAGLE-3). One denoising step. Entire block of 16 tokens produced in a single
AI
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DFlash 6x lossless acceleration on Qwen3-8B
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Diffusion LLMs have been losing to autoregressive models for two years. UC San Diego just found the one thing they're actually better at: not generating, drafting. DFlash hits 6x lossless acceleration on Qwen3-8B. 2.5x faster than EAGLE-3. Check out the detailed breakdown
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Abridge uses LangSmith for core evals of AI-generated clinical notes
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LangSmith for Startups Spotlight: @AbridgeHQ
— LangChain (@LangChain) 25 juin 2026
✅ Transforms patient-clinician conversations into contextually aware, clinically useful, and billable AI-generated notes.
✅ Deployed across 250 of the largest health systems in the country.
✅ Uses LangSmith as its core evals… pic.twitter.com/Ko3sSY4v0WLangSmith for Startups Spotlight: @AbridgeHQ Transforms patient-clinician conversations into contextually aware, clinically useful, and billable AI-generated notes. Deployed across 250 of the largest health systems in the country. Uses LangSmith as its core evals
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GLM 5.2 enables trusted open model for automated research tasks
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1/2 This is obviously not a comprehensive benchmark, but it’s clear that we finally have an open model that can be trusted and depended upon on difficult research tasks. You can easily run autoresearch yourself with GLM 5.2 by changing ‘arxiv’ to ‘autoarxiv’ for any arXiv URL:
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Comparison of GLM 5.2 and Opus 4.8 on SDPO paper reproduction
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Here’s a fun comparison between GLM 5.2 and Opus 4.8 on a one-shot reproduction of the SDPO paper This is a hard task: the model must resolve messy verl issues and then run ablations to completion and confirm the paper’s claims. – GLM 5.2 costs $6.21 while Opus 4.8 cost us
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Airwallex targets cross-border payments for AI agents with Airi and T:0
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Everyone's teaching AI agents to shop. Almost nobody is solving the boring part:
— Chubby♨️ (@kimmonismus) 25 juin 2026
letting them move the money, pay across borders, keep the books, stay compliant.
That's the gap Airwallex is going after, with Airi (faster agent checkout today, a real wallet in the works) and T:0… https://t.co/TdPBxF4o5TEveryone's teaching AI agents to shop. Almost nobody is solving the boring part: letting them move the money, pay across borders, keep the books, stay compliant. That's the gap Airwallex is going after, with Airi (faster agent checkout today, a real wallet in the works) and T:0
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Training step with refined scaffold and reward hacking guards
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Each training step has the model propose a refined scaffold for a task, which it then uses to generate a solution, with reward flowing back to both stages. There are three layers of guard against reward hacking. As DeepReinforce states, the 9B variant achieves a score of 43.1 on
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DeepReinforce releases Ornith-1.0 self-improving open-source coding model
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DeepReinforce has released Ornith-1.0, their new self-improving family of open-source models designed for agentic coding. > Ornith-1.0 learns to write its own task scaffolds during training rather than relying on human-designed harnesses. > The 397B MoE flagship can match
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Hyperagent gives each agent its own dedicated cloud machine
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We spent two years calling things agents that fall over the second nobody's watching.
— Chubby♨️ (@kimmonismus) 25 juin 2026
A setup tied to one laptop, one wifi, and one person awake at 1am to restart it when it breaks is closer to a pager than to autonomy.
Hyperagent gives every agent its own cloud machine that… https://t.co/VAkGZuAUDoWe spent two years calling things agents that fall over the second nobody's watching. A setup tied to one laptop, one wifi, and one person awake at 1am to restart it when it breaks is closer to a pager than to autonomy. Hyperagent gives every agent its own cloud machine that
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Trying to replace Fable with an ensemble of smaller models
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Me trying to replace Fable with an ensemble of smaller models pic.twitter.com/0dATTnoMbn
— Peter Gostev (@petergostev) 25 juin 2026Me trying to replace Fable with an ensemble of smaller models