10 Ways to Use Embeddings for Tabular ML Tasks
Embeddings — vector-based numerical representations of typically unstructured data like text — have been primarily popularized in the field of natural language processing (NLP).
Over-Searching in Search-Augmented Large Language Models
Search-augmented large language models (LLMs) excel at knowledge-intensive tasks by integrating external retrieval. However, they often over-search – unnecessarily invoking search tool even when it does not improve response quality, which leads to computational inefficiency and hallucinations by incorporating irrelevant context. In this work, we conduct a systematic evaluation of over-searching across multiple dimensions, including …
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How Omada Health scaled patient care by fine-tuning Llama models on Amazon SageMaker AI
This post is co-written with Sunaina Kavi, AI/ML Product Manager at Omada Health. Omada Health, a longtime innovator in virtual healthcare delivery, launched a new nutrition experience in 2025, featuring OmadaSpark, an AI agent trained with robust clinical input that delivers real-time motivational interviewing and nutrition education. It was built on AWS. OmadaSpark was designed …
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Anthropic launches Cowork, a Claude Desktop agent that works in your files — no coding required
Anthropic released Cowork on Monday, a new AI agent capability that extends the power of its wildly successful Claude Code tool to non-technical users — and according to company insiders, the team built the entire feature in approximately a week and a half, largely using Claude Code itself. The launch marks a major inflection point …
New Proposed Legislation Would Let Self-Driving Cars Operate in New York State
New York governor Kathy Hochul says she will propose a new law allowing limited autonomous vehicle pilots in smaller cities. Full-blown services could be next.
From brain scans to alloys: Teaching AI to make sense of complex research data
Artificial intelligence (AI) is increasingly used to analyze medical images, materials data and scientific measurements, but many systems struggle when real-world data do not match ideal conditions. Measurements collected from different instruments, experiments or simulations often vary widely in resolution, noise and reliability. Traditional machine-learning models typically assume those differences are negligible—an assumption that can …
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MANZANO: A Simple and Scalable Unified Multimodal Model with a Hybrid Vision Tokenizer
Unified multimodal Large Language Models (LLMs) that can both understand and generate visual content hold immense potential. However, existing open-source models often suffer from a performance trade-off between these capabilities. We present Manzano, a simple and scalable unified framework that substantially reduces this tension by coupling a hybrid image tokenizer with a well-curated training recipe. …
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16 Best Heat Protectant Sprays for Wet and Dry Hair (2026)
I’ve spent almost a year testing dozens of heat protectants for hair. Whether you’re blow-drying, curling, or straightening, these are the best formulas I’ve found.
Best Deals for New Year’s Resolutions: Sleep, Fitness, and More (2026)
Whether you’re hitting the gym or tracking your schedule, these discounts on WIRED-approved gear can help.
AdaBoN: Adaptive Best-of-N Alignment
Recent advances in test-time alignment methods, such as Best-of-N sampling, offer a simple and effective way to steer language models (LMs) toward preferred behaviors using reward models (RM). However, these approaches can be computationally expensive, especially when applied uniformly across prompts without accounting for differences in alignment difficulty. In this work, we propose a prompt-adaptive …