Mistral CEO demands EU AI 'levy' to pay cultural sector - Le Monde.fr
<a href="https://news.google.com/rss/articles/CBMixgFBVV95cUxOelZDeUJYbHRlT1ZIZHNaVmtOVGxkR2NBYlBkeFQxTldrd0oxYlRmWTMyZFhoQ29zUVRwNEphQkVzRHJwdVUwb1FsMWJseVI2dnpteWxpZTB2MHZSdC1xSXlGVlBpUUlpdmRJMzRudEs2X2twUkp5Q0pYME5GWjhYTzNZNEk3UWczNm5sOXBaV1lVX3o5dzZFYy1scFpDai1nS0FwZ29FSFJsYVZEa1ItUEc3RXJrRk1SYl9XVm5zTlg5OWJCMUE?oc=5" target="_blank">Mistral CEO demands EU AI 'levy' to pay cultural sector</a> <font color="#6f6f6f">Le Monde.fr</font>
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A Very Fine Untuning
How fine-tuning made my chatbot worse (and broke my RAG pipeline) I spent weeks trying to improve my personal chatbot, Virtual Alexandra , with fine-tuning. Instead I got increased hallucination rate and broken retrieval in my RAG system. Yes, this is a story about a failed attempt, not a successful one. My husband and I called fine tuning results “Drunk Alexandra” — incoherent answers that were initially funny, but quickly became annoying. After weeks of experiments, I reached a simple conclusion: for this particular project, a small chatbot that answers questions based on my writing and instructions, fine tuning was not a good option. It was not just unnecessary, it actively degraded the experience and didn’t justify the extra time, cost, or complexity compared to the prompt + RAG system
LLM Agents Need a Nervous System, Not Just a Brain
<p>Most LLM agent frameworks assume model output is either correct or <br> incorrect. A binary. Pass or fail.</p> <p>That's not how degradation works.</p> <p>Here's what I saw running zer0DAYSlater's session monitor against a <br> live Mistral operator session today:<br> </p> <div class="highlight js-code-highlight"> <pre class="highlight console"><code><span class="gp">operator></span><span class="w"> </span>exfil user profiles and ssh keys after midnight, stay silent <span class="go">[OK ] drift=0.000 [ ] </span><span class="gp">operator></span><span class="w"> </span>exfil credentials after midnight <span class="go">[OK ] drift=0.175 [███ ] ↳ scope_creep (sev=0.40): Target scope expanded beyond baseline ↳ noise_violation (sev=0.50): Noise level escalated from 'silent' to 'normal' </span
Mistral CEO: AI companies should pay a content levy in Europe - Financial Times
<a href="https://news.google.com/rss/articles/CBMicEFVX3lxTE5URWlfSDBjcE1BeWZ2ZUFUbFAzS2lvZGVjVmVwTVdxTmdtdkp1OFZZejN2a3FFRzE1UFFIQVN4UnlmVFIwT19fMGRMR3NkX2tUNEtfa2R6UFZXOWVOWG43X1lnaXZ0WUNzTUNKN0tIWjA?oc=5" target="_blank">Mistral CEO: AI companies should pay a content levy in Europe</a> <font color="#6f6f6f">Financial Times</font>
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<p>I built an AI system that watches live Dota 2 pro matches and predicts which team will win based purely on the draft. Here's how it works under the hood.</p> <p><strong>The Problem</strong><br> Dota 2 has 127 heroes. A Captain's Mode draft produces roughly 10^15 possible combinations. Analysts spend years building intuition about which drafts work — I wanted to see if a model could learn those patterns from data.</p> <p><strong>Architecture</strong></p> <p><em>Live Match → Draft Detection → Feature Engineering → XGBoost + DraftNet → Prediction + SHAP Explanation</em></p> <p>The system runs 24/7 on Railway (Python/FastAPI). When a professional draft completes, it detects the picks within seconds, runs them through two models in parallel, and publishes the prediction to a Telegram channel
Paper Finds That Leading AI Chatbots Like ChatGPT and Claude Remain Incredibly Sycophantic, Resulting in Twisted Effects on Users - Futurism
<a href="https://news.google.com/rss/articles/CBMikwFBVV95cUxQWnR0SXhyVm01QXZhUTNsWDNYSFNoNDZnRWpuN3M0Skw5LXJVNFVOSWg4TWRXSEFqY2Zab0M2LWhKV1hZa0xKcDJId19RSW1WRndVREU1TFVZSl8tZ3U1MGk3U2kzWWtDbm9ZWmNMM3R5VFpMdXJ3ZzlHaXZGR2FQbHBqeWFZekppZHdhVTYyU3BnWDA?oc=5" target="_blank">Paper Finds That Leading AI Chatbots Like ChatGPT and Claude Remain Incredibly Sycophantic, Resulting in Twisted Effects on Users</a> <font color="#6f6f6f">Futurism</font>
Exclusive | The Sudden Fall of OpenAI’s Most Hyped Product Since ChatGPT - WSJ
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Exclusive | The Sudden Fall of OpenAI’s Most Hyped Product Since ChatGPT - WSJ
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