Learning DeepVariant’s hidden powers
AI

Learning DeepVariant’s hidden powers

Examining DeepVariant To better understand what DeepVariant is learning from its training data, we used a set of simple clustering and visualization methods to summarize the information captured in the model’s high dimensional data. In partnership with collaborators on the Google Genomics team, we first loaded examples into the Integrated Genomics Viewer (IGV), a widely-used […]

Learning DeepVariant’s hidden powers
AI

Taking medical imaging embeddings 3D

Over recent years, developers and researchers have made progress in efficiently building AI applications. Google Research has contributed to this effort by providing easy-to-use embedding APIs for radiology, digital pathology and dermatology to help AI developers train models in these domains with less data and compute. However, these applications have been restricted to 2D imaging,

Learning DeepVariant’s hidden powers
AI

Evaluating and enhancing probabilistic reasoning in language models

To understand the probabilistic reasoning capabilities of three state-of-the-art LLMs (Gemini, GPT family models), we define three distinct tasks: estimating percentiles, drawing samples, and calculating probabilities. These tasks reflect key aspects of interpreting probability distributions, such as understanding where a sample falls within a distribution (percentiles), generating representative data (sampling), and assessing the likelihood of

Learning DeepVariant’s hidden powers
AI

HDR photo editing with machine learning

High dynamic range (HDR) photography techniques can accurately capture a scene’s full range of brightness values — from those of its darkest shadows to its brightest light sources. However, when the time comes to view the resulting HDR photos, many displays are only capable of showing a limited range of brightness levels. This discrepancy means

Demis Hassabis & John Jumper awarded Nobel Prize in Chemistry
AI

Demis Hassabis & John Jumper awarded Nobel Prize in Chemistry

This morning, Co-founder and CEO of Google DeepMind and Isomorphic Labs Sir Demis Hassabis, and Google DeepMind Director Dr. John Jumper were co-awarded the 2024 Nobel Prize in Chemistry for their work developing AlphaFold, a groundbreaking AI system that predicts the 3D structure of proteins from their amino acid sequences. David Baker was also co-awarded

Learning DeepVariant’s hidden powers
AI

Augmented object intelligence with XR-Objects

The implementation of XR-Objects involves four steps: (1) detecting objects, (2) localizing and anchoring onto objects, (3) coupling each object with an MLLM for metadata retrieval, and (4) executing actions and displaying the output in response to user input. We use Unity and its AR Foundation to bring these together to build a system that

Learning DeepVariant’s hidden powers
AI

Predicting fetal well-being from cardiotocography signals using AI

Cardiotocography (CTG) is a doppler ultrasound–based technique used during pregnancy and labor to monitor fetal well-being by recording fetal heart rate (FHR) and uterine contractions (UC). CTG can be done continuously or intermittently, with leads placed either externally or internally. External CTG involves the use of two sensors placed on the birthing parent’s belly: an

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