Microsoft rolls out Copilot Cowork more broadly and lets AI models check each other's work - the-decoder.com
<a href="https://news.google.com/rss/articles/CBMitAFBVV95cUxPTnBRTDdxQndod0F3UWtIT1hHc0pDVnF5MnRKR0gzeHZ6RGhiSHVKakFoa3U4SVBLM1J6bkxNQmFwZUY2UlZPbVFDUEFQR3NnWUhBdE8zME9oVFBibXZnNy11cWtQbDBWSEJWamJkbktYc2E4XzlpZTcyVVdfMS1ENDZIdC1jNzFVaUgxS25xZHdUVkk0dE0ySEV6RFJ6WkR2SzF6NmFJVFdsQy1uUWJsZEtxMTU?oc=5" target="_blank">Microsoft rolls out Copilot Cowork more broadly and lets AI models check each other's work</a> <font color="#6f6f6f">the-decoder.com</font>
Could not retrieve the full article text.
Read on GNews AI Copilot →Sign in to highlight and annotate this article
Conversation starters
Daily AI Digest
Get the top 5 AI stories delivered to your inbox every morning.
More about
modelcopilot
Quoting Soohoon Choi
<blockquote cite="https://www.greptile.com/blog/ai-slopware-future"><p>I want to argue that AI models will write good code because of economic incentives. Good code is cheaper to generate and maintain. Competition is high between the AI models right now, and the ones that win will help developers ship reliable features fastest, which requires simple, maintainable code. Good code will prevail, not only because we want it to (though we do!), but because economic forces demand it. Markets will not reward slop in coding, in the long-term.</p></blockquote> <p class="cite">— <a href="https://www.greptile.com/blog/ai-slopware-future">Soohoon Choi</a>, Slop Is Not Necessarily The Future</p> <p>Tags: <a href="https://simonwillison.net/tags/slop">slop</a>, <a href="https://simonwillison.net/ta
Como o Ataque à Cadeia de Suprimentos do NPM Axios Acontece (E Como Proteger Seus Projetos de API)
<h2> TL;DR </h2> <p>Em 31 de março de 2026, invasores comprometeram a conta npm do mantenedor principal do Axios, o cliente HTTP JavaScript mais popular com 83 milhões de downloads semanais. Eles publicaram versões maliciosas (1.14.1 e 0.30.4) contendo um RAT (Cavalo de Troia de Acesso Remoto) multiplataforma que rouba credenciais, chaves SSH e tokens de nuvem de máquinas de desenvolvedores. Faça downgrade para o Axios 1.14.0 imediatamente, rotacione todos os segredos e escaneie seu sistema em busca de indicadores de comprometimento.</p> <p><a href="https://apidog.com/?utm_source=dev.to&utm_medium=wanda&utm_content=n8n-post-automation" class="crayons-btn crayons-btn--primary">Experimente o Apidog hoje</a> </p> <h2> Introdução </h2> <p>Axios processa mais requisições HTTP do que qua
Why Domain Knowledge Is the Core Architecture of Fine-Tuning and RAG — Not an Afterthought
<p>--</p> <p>Foundation models are generalists by design. They are trained to be broadly capable across language, reasoning, and knowledge tasks — optimized for breadth, not depth. That is precisely their strength in general use cases. And precisely their limitation the moment you deploy them into a domain that demands depth.</p> <p>Fine-tuning and Retrieval-Augmented Generation (RAG) exist to close that gap. But here is where most teams make a critical mistake: <strong>they treat fine-tuning as a data volume problem and RAG as a retrieval engineering problem.</strong> Neither framing is correct.</p> <p>Both are fundamentally <strong>domain knowledge problems.</strong> This post makes the technical case for why — grounded in architecture, not anecdote.</p> <h2> What Foundation Models Actua
Knowledge Map
Connected Articles — Knowledge Graph
This article is connected to other articles through shared AI topics and tags.
More in Models
Quoting Soohoon Choi
<blockquote cite="https://www.greptile.com/blog/ai-slopware-future"><p>I want to argue that AI models will write good code because of economic incentives. Good code is cheaper to generate and maintain. Competition is high between the AI models right now, and the ones that win will help developers ship reliable features fastest, which requires simple, maintainable code. Good code will prevail, not only because we want it to (though we do!), but because economic forces demand it. Markets will not reward slop in coding, in the long-term.</p></blockquote> <p class="cite">— <a href="https://www.greptile.com/blog/ai-slopware-future">Soohoon Choi</a>, Slop Is Not Necessarily The Future</p> <p>Tags: <a href="https://simonwillison.net/tags/slop">slop</a>, <a href="https://simonwillison.net/ta
Como o Ataque à Cadeia de Suprimentos do NPM Axios Acontece (E Como Proteger Seus Projetos de API)
<h2> TL;DR </h2> <p>Em 31 de março de 2026, invasores comprometeram a conta npm do mantenedor principal do Axios, o cliente HTTP JavaScript mais popular com 83 milhões de downloads semanais. Eles publicaram versões maliciosas (1.14.1 e 0.30.4) contendo um RAT (Cavalo de Troia de Acesso Remoto) multiplataforma que rouba credenciais, chaves SSH e tokens de nuvem de máquinas de desenvolvedores. Faça downgrade para o Axios 1.14.0 imediatamente, rotacione todos os segredos e escaneie seu sistema em busca de indicadores de comprometimento.</p> <p><a href="https://apidog.com/?utm_source=dev.to&utm_medium=wanda&utm_content=n8n-post-automation" class="crayons-btn crayons-btn--primary">Experimente o Apidog hoje</a> </p> <h2> Introdução </h2> <p>Axios processa mais requisições HTTP do que qua
Why Domain Knowledge Is the Core Architecture of Fine-Tuning and RAG — Not an Afterthought
<p>--</p> <p>Foundation models are generalists by design. They are trained to be broadly capable across language, reasoning, and knowledge tasks — optimized for breadth, not depth. That is precisely their strength in general use cases. And precisely their limitation the moment you deploy them into a domain that demands depth.</p> <p>Fine-tuning and Retrieval-Augmented Generation (RAG) exist to close that gap. But here is where most teams make a critical mistake: <strong>they treat fine-tuning as a data volume problem and RAG as a retrieval engineering problem.</strong> Neither framing is correct.</p> <p>Both are fundamentally <strong>domain knowledge problems.</strong> This post makes the technical case for why — grounded in architecture, not anecdote.</p> <h2> What Foundation Models Actua
Mercor confirmed it was affected by a recent supply chain attack involving LiteLLM; hacker group Lapsus$ claims it accessed and stole Mercor's data (Jagmeet Singh/TechCrunch)
Jagmeet Singh / TechCrunch : Mercor confirmed it was affected by a recent supply chain attack involving LiteLLM; hacker group Lapsus$ claims it accessed and stole Mercor's data — Mercor, a popular AI recruiting startup, has confirmed a security incident linked to a supply chain attack involving the open-source project LiteLLM.
Discussion
Sign in to join the discussion
No comments yet — be the first to share your thoughts!