TPOT: Automating ML Pipelines with Genetic Algorithms in Python
You can train, evaluate, and export a full ML pipeline in Python using TPOT with just a few lines of code.
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What Is Retrieval-Augmented Generation, aka RAG?
Editor’s note: This article, originally published on Nov. 15, 2023, has been updated. To understand the latest advancements in generative AI, imagine a courtroom. Judges hear and decide cases based on their general understanding of the law. Sometimes a case — like a malpractice suit or a labor dispute — requires special expertise, so judges send court clerks to a law library, looking for precedents and specific cases they can cite. Like a good judge, large language models […]
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New method improves the reliability of statistical estimations
Let’s say an environmental scientist is studying whether exposure to air pollution is associated with lower birth weights in a particular county. They might train a machine-learning model to estimate the magnitude of this association, since machine-learning methods are especially good at learning complex relationships. Standard machine-learning methods excel at making predictions and sometimes provide uncertainties, like confidence intervals, for these predictions. However, they generally don’t provide estimates or confidence intervals when determining whether two variables are related. […]
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AI helps chemists develop tougher plastics
A new strategy for strengthening polymer materials could lead to more durable plastics and cut down on plastic waste, according to researchers at MIT and Duke University. Using machine learning, the researchers identified crosslinker molecules that can be added to polymer materials, allowing them to withstand more force before tearing. These crosslinkers belong to a class of molecules known as mechanophores, which change their shape or other properties in response to mechanical force. “These molecules can be useful […]
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A smarter way for large language models to think about hard problems
To make large language models (LLMs) more accurate when answering harder questions, researchers can let the model spend more time thinking about potential solutions. But common approaches that give LLMs this capability set a fixed computational budget for every problem, regardless of how complex it is. This means the LLM might waste computational resources on simpler questions or be unable to tackle intricate problems that require more reasoning. To address this, MIT researchers developed a smarter way to allocate […]
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A Coding Implementation of a Complete Hierarchical Bayesian Regression Workflow in NumPyro Using JAX-Powered Inference and Posterior Predictive Analysis
In this tutorial, we explore hierarchical Bayesian regression with NumPyro and walk through the entire workflow in a structured manner. We start by generating synthetic data, then we define a probabilistic model that captures both global patterns and group-level variations. Through each snippet, we set up inference using NUTS, analyze posterior distributions, and perform posterior predictive checks to understand how well our model captures the underlying structure. By approaching the tutorial step by step, we build an intuitive […]
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3 things to know about Ironwood, our latest TPU
Google’s seventh-gen Tensor Processing Unit is here! Learn what makes Ironwood our most powerful and energy-efficient custom silicon to date.
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Gemini 3 and Nano Banana Pro in Search are coming to more countries around the world.
We’re bringing our most intelligent model yet, Gemini 3 Pro, to Google Search in more countries around the world.
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As AI Grows More Complex, Model Builders Rely on NVIDIA
Unveiling what it describes as the most capable model series yet for professional knowledge work, OpenAI launched GPT-5.2 today. The model was trained and deployed on NVIDIA infrastructure, including NVIDIA Hopper and GB200 NVL72 systems. It’s the latest example of how leading AI builders train and deploy at scale on NVIDIA’s full-stack AI infrastructure. Pretraining: The Bedrock of Intelligence AI models are getting more capable thanks to three scaling laws: pretraining, post-training and test-time scaling. Reasoning models, which […]
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OpenAI, Anthropic and Block join new Linux Foundation effort to standardize the AI agent era
Anthropic, Block, and OpenAI are backing the Linux Foundation’s new Agentic AI Foundation, donating MCP, Goose, and AGENTS.md to standardize AI agents, boost interoperability, and curb proprietary fragmentation.
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