Category: FAANG

Multimodal large language models (MLLMs) are increasingly deployed in real-world, agentic settings where outputs must not only be correct, but also conform to predefined data schemas. Despite recent progress in structured generation in textual domain, there is still no benchmark that systematically evaluates schema-grounded information extraction and reasoning over visual inputs. In this work, we …

Read more “SO-Bench: A Structural Output Evaluation of Multimodal LLMs”

Scientists are using AlphaFold to strengthen a photosynthesis enzyme for resilient, heat-tolerant crops.

The Next Generation of Audit Logging at Palantir Every day, organizations entrust Palantir platforms with their most sensitive data and critical operations. From government agencies coordinating national security missions to healthcare providers safeguarding patient information to financial institutions detecting fraud, our customers depend on us to help them make decisions that matter. This trust isn’t given …

Read more “Building Trust at Scale”

AV1 — Now Powering 30% of Netflix Streaming Liwei Guo, Zhi Li, Sheldon Radford, Jeff Watts Streaming video has become an integral part of our daily lives. At Netflix, our top priority is delivering the best possible entertainment experience to our members, regardless of their devices or network conditions. One of the key technologies enabling this is AV1, …

Read more “AV1 — Now Powering 30% of Netflix Streaming”

Automated interpretability aims to translate large language model (LLM) features into human understandable descriptions. However, these natural language feature descriptions are often vague, inconsistent, and require manual relabeling. In response, we introduce semantic regexes, structured language descriptions of LLM features. By combining primitives that capture linguistic and semantic feature patterns with modifiers for contextualization, composition, …

Read more “Semantic Regexes: Auto-Interpreting LLM Features with a Structured Language”

Explore how AlphaFold has accelerated science and fueled a global wave of biological discovery.

Continuous cardiovascular monitoring can play a key role in precision health. However, some fundamental cardiac biomarkers of interest, including stroke volume and cardiac output, require invasive measurements, e.g., arterial pressure waveforms (APW). As a non-invasive alternative, photoplethysmography (PPG) measurements are routinely collected in hospital settings. Unfortunately, the prediction of key cardiac biomarkers from PPG instead …

Read more “Hybrid Modeling of Photoplethysmography for Non-Invasive Monitoring of Cardiovascular Parameters”