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Bonjour, Marty. Petite prophecy from the passenger seat: your brief has opinions. Ok, Marty, ready to hit the brief? I will go source by source. If one grabs you, say "hold up, dig into that one", "expand on that", or "tell me the whole thing", and I will read the full article text underneath it. You can also say "send to Gen" when you want that story carried forward. From Discord, I have 3 headlines: - 📰 News — Anthropic launches roadshow for proposed initial public offering. @News - ANTHROP\C 📰 News — Anthropic launches roadshow for proposed initial public offering -Summary: Today we launched the roadshow for our proposed initial public offering of Class A common stock. We have applied... - 🧠Alignment — Diluting Poisoned Fine-Tuning Data Can Strengthen Its Effect. @News - ANTHROP\C 🧠Alignment — Diluting Poisoned Fine-Tuning Data Can Strengthen Its Effect -Summary: We published research on "homeopathic learning," a phenomenon where poisoned fine-tuning data that does little... - 🧠Alignment — Worse Together: How Performance Breaks Down in Multi-User Multi-Agent Teams. @News - ANTHROP\C 🧠Alignment — Worse Together: How Performance Breaks Down in Multi-User Multi-Agent Teams -Summary: We studied what happens when each user delegates a task to their own AI agent and those agents... That is Discord. Say "next" to keep rolling, or stop me on any headline. From AI Daily Brief, I have 1 headline: - Claude Fable 5.2: The Most Powerful Model Yet, But What Is It For? With the Anthropic IPO approaching, the new flagship has arrived: Fable 5.2 and Mythos 5.2. It is unusually easy to call it the best model that has ever existed, and unusually hard to say exactly when and where most... That is AI Daily Brief. Say "next" to keep rolling, or stop me on any headline. From Hugging Face Daily Papers, I have 1 headline: - e-means: outperforming k-means (in one-tenth the epochs). Lloyd's k-means algorithm is a long-running standard for clustering, with applications in data analysis, retrieval, quantization and data curation. In this paper, we introduce an exponential moving average... That is Hugging Face Daily Papers. Say "next" to keep rolling, or stop me on any headline. From arXiv AI and ML Watch, I have 3 headlines: - Medical Image Segmentation: Foundation Model Adaptation versus Task-Specific Training. Foundation models pretrained on large natural-image collections are increasingly adapted for medical image segmentation, in the expectation that they will replace models trained for each task. Most comparisons... - TorchCurves: Differentiable Parametric Curves. We present TorchCurves, a PyTorch library that treats vector-valued parametric curves as learnable primitives. Its central operation maps batches of scalar inputs to points on curves represented in B-spline or... - Toward Foundation Detection Models via Example-Based Grounding in EM-DETR. DeepLearning (DL)-based Computer-Aided Diagnostic (CAD) systems have shown great promise in supporting clinicians, but their performance heavily depends on the availability of large, well-annotated datasets. In... That is arXiv AI and ML Watch. Say "next" to keep rolling, or stop me on any headline. From Latent.Space, I have 3 headlines: - [AINews] Mercor $750m Series D at $20B valuation, $3B run rate. Our usual bar for making a fundraise a title story these days is a decacorn ($10B) valuation. We missed Mercor’s $10B Series C last year when it had less than $500m in revenue, but knew we wouldn’t have to wait too... - AI Engineer Code Summit: OpenAI on New Ways of Working With Codex. AI Engineer Code Summit kicked off today with a series of workshops, including from leading frontier labs OpenAI, Anthropic and Google DeepMind. I attended the OpenAI workshop, intriguingly titled “New Ways of... - NaiveAI Promises 2,100 Tokens per Second. How Well Does It Code? Editor’s note: With this post, we are launching a new series focused on trying new models and products with unbiased reviews. Reach out with suggestions to tips@latent.space. Naive-N0.5-Flash is a new open-weights... That is Latent.Space. Say "next" to keep rolling, or stop me on any headline.
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