Resource library

Large-scale neural network models combining text and images have made incredible progress in recent years. However, it remains an open question to what extent such models encode compositional representations of the concepts over which they operate, such as correctly identifying red cube by reasoning over the constituents red and cube. In this work, we focus on the ability of a…

While current vision algorithms excel at many challenging tasks, it is unclear how well they understand the physical dynamics of real-world environments. Here we introduce Physion, a dataset and benchmark for rigorously evaluating the ability to predict how physical scenarios will evolve over time. Our dataset features realistic simulations of a wide range of physical phenomena, including rigid and soft-body…

Insurance claims processing has long required a lot of tedious and expensive human labor, but artificial intelligence (AI) can help.

Gideon Mann, head of ML Product and Research at Bloomberg LP, chatted with Snorkel CEO Alex Ratner about building BloombergGPT.

Snorkel Flow makes it easy to fine tune LLMs like GPT-3.5 Turbo to work better for specific domain and enterprise requirements.

Sessions at the Future of Data-Centric AI covered LLMs, gen AI, and more. All recordings are now publicly available. See them here!

Most data science leaders expect to customize LLMS, but the process of making LLMs work for your business is still a fresh challenge.

Ai and ML offer new avenues for credit scoring solutions and could usher in a new era of fairness, efficiency, and risk management.

Data labeling remains a core requirement for machine learning projects—especially in the age of genAI and LLMs. Here’s a handy guide.