Humans change their own behavior when training AI

A new cross-disciplinary study by Washington University in St. Louis researchers has uncovered an unexpected psychological phenomenon at the intersection of human behavior and artificial intelligence: When told they were training AI to play a bargaining game, participants actively adjusted their own behavior to appear more fair and just, an impulse with potentially important implications …

Tips for Tuning Hyperparameters in Machine Learning Models

If you’re familiar with machine learning, you know that the training process allows the model to learn the optimal values for the parameters—or model coefficients—that characterize it. But machine learning models also have a set of hyperparameters whose values you should specify when training the model. So how do you find the optimal values for …

Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling

Large language models are trained on massive scrapes of the web, which are often unstructured, noisy, and poorly phrased. Current scaling laws show that learning from such data requires an abundance of both compute and data, which grows with the size of the model being trained. This is infeasible both because of the large compute …

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Build custom generative AI applications powered by Amazon Bedrock

With last month’s blog, I started a series of posts that highlight the key factors that are driving customers to choose Amazon Bedrock. I explored how Bedrock enables customers to build a secure, compliant foundation for generative AI applications. Now I’d like to turn to a slightly more technical, but equally important differentiator for Bedrock—the …

Announcing LangChain on Vertex AI for AlloyDB and Cloud SQL for PostgreSQL

Among application developers, LangChain is one of the most popular open-source LLM orchestration frameworks. To help developers use LangChain to create context-aware gen AI applications with Google Cloud databases, in March we open-sourced LangChain integrations for all of our Google Cloud databases including Vector stores, Document loaders, and Chat message history. And now, we’re excited …

Integrating Scikit-Learn and Statsmodels for Regression

Statistics and Machine Learning both aim to extract insights from data, though their approaches differ significantly. Traditional statistics primarily concerns itself with inference, using the entire dataset to test hypotheses and estimate probabilities about a larger population. In contrast, machine learning emphasizes prediction and decision-making, typically employing a train-test split methodology where models learn from …