MixAtlas: Uncertainty-aware Data Mixture Optimization for Multimodal LLM Midtraining
This paper was accepted at the Workshop on Navigating and Addressing Data Problems for Foundation Models (NADPFM) at ICLR 2026.
Principled domain reweighting can substantially improve sample efficiency and downstream generalization; however, data-mixture optimization for multimodal pretraining remai...
Introducing GPT-Rosalind for life sciences research
OpenAI introduces GPT-Rosalind, a frontier reasoning model built to accelerate drug discovery, genomics analysis, protein reasoning, and scientific research workflows.
AI x Crypto: How AI Is Transforming DeFi, Exchanges, and Blockchain Development
AI is reshaping crypto—from intelligent DeFi mining and autonomous smart‑contract development to AI‑driven exchanges and quantum‑ready security. Explore how AI is becoming the operating system of modern blockchain ecosystems.
The musician-turned-biotech-founder waiting to fundraise
When Grammy-nominated singer-songwriter Aloe Blacc got COVID despite being vaccinated and boosted, he tried to fund research for a better solution. What he quickly found out? You can’t just write a check in biotech. Regulators require a commercialization plan, and philanthropy doesn’t move science t...
AI Reality Check: The Data Quality Crisis No One Wants to Admit
In this week's edition of AI Reality Check, we focus on data, specifically the availability of sufficient data quality. AI is running out of clean, human-generated data. This article exposes the hidden crisis threatening scaling laws, model reliability, and the future of frontier AI.
A Technical Deep Dive into the Essential Stages of Modern Large Language Model Training, Alignment, and Deployment
Training a modern large language model (LLM) is not a single step but a carefully orchestrated pipeline that transforms raw data into a reliable, aligned, and deployable intelligent system. At its core lies pretraining, the foundational phase where models learn general language patterns, reasoning s...
Mastering Deep Agents: Context Engineering that Actually Works
Deep Agents can plan, use tools, manage state, and handle long multi-step tasks. But their real performance depends on context engineering. Poor instructions, messy memory, or too much raw input quickly degrade results, while clean, structured context makes agents more reliable, cheaper, and easier ...
Google AI Launches Gemini 3.1 Flash TTS: A New Benchmark in Expressive and Controllable AI Voice
Google has introduced Gemini 3.1 Flash TTS, a preview text-to-speech model focused on improving speech quality, expressive control, and multilingual generation. Unlike previous iterations that prioritized simple conversion, this release emphasizes natural-language audio tags, native support for more...
5 Practical Tips for Transforming Your Batch Data Pipeline into Real-Time: Upcoming Webinar
Bringing your batch pipeline to real-time requires careful consideration. This post brings you five practical tips to make the most of your modernization efforts. Join us for an upcoming webinar to learn even more.
The post 5 Practical Tips for Transforming Your Batch Data Pipeline into Real-Time: U...
Adobe’s new Firefly AI assistant can use Creative Cloud apps to complete tasks
Adobe says the assistant can work across apps like Firefly, Photoshop, Premiere, Lightroom, Express, Illustrator and its other apps to do tasks for you.
From OpenStreetMap to Power BI: Visualizing Wild Swimming Locations
How to turn OpenStreetMap data into an interactive map of wild swimming spots using Overpass API and Power BI.
The post From OpenStreetMap to Power BI: Visualizing Wild Swimming Locations appeared first on Towards Data Science.
AI Is Writing Our Code Faster Than We Can Verify It
This is the third article in a series on agentic engineering and AI-driven development. Read part one here, part two here, part three here, and look for the next article on April 23 on O’Reilly Radar. Here’s the dirty secret of the AI coding revolution: most experienced developers still don’t really...
OpenAI updates the Agents SDK with native sandbox execution and a model-native harness, helping developers build secure, long-running agents across files and tools.