At the European Health Summit in Brussels, Greg Corrado, Distinguished Scientist at Google, released a new report authored by Implement Consulting Group and commissioned…
Annotating regions of interest in medical images, a process known as segmentation, is often one of the first steps clinical researchers take when running a new study involving biomedical images. For instance, to determine how the size of the brain’s hippocampus changes as patients age, the scientist first outlines each hippocampus in a series of brain scans. For many structures and image types, this is often a manual process that can be extremely time-consuming, especially if the regions […]
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 […]
Exclusive working session about trustworthy AI, for senior tech leaders. View PowerPoint presentation, here. AI isn’t slowing down, but poorly planned AI adoption will slow you down. Hallucinations, security risks, bloated compute costs, and “black box” outputs are already tripping up top teams, burning budgets, and eroding trust. That’s why this session blends three things you can’t get from a typical AI webinar: Practical expertise: GenAI pioneer Vincent Granville will share a real-world framework for deploying hallucination-free, secure, and […]
Even obvious solutions are hard to execute The post Politicians make the case for Downsize DC appeared first on Downsize DC.
This article is divided into four parts; they are: • Optimizers for Training Language Models • Learning Rate Schedulers • Sequence Length Scheduling • Other Techniques to Help Training Deep Learning Models Adam has been the most popular optimizer for training deep learning models.
Tune out external criticism, focus on process over outcomes, and embrace reflection and routine.
Autonomous vehicle (AV) stacks are evolving from many distinct models to a unified, end-to-end architecture that executes driving actions directly from sensor data. This transition to using larger models is drastically increasing the demand for high-quality, physically based sensor data for training, testing and validation. To help accelerate the development of next-generation AV architectures, NVIDIA today released NVIDIA Cosmos Predict-2 — a new world foundation model with improved future world state prediction capabilities for high-quality synthetic data generation […]
Key findings from OpenAI’s enterprise data show accelerating AI adoption, deeper integration, and measurable productivity gains across industries in 2025.
Learn how to make a newsletter with AI tools The post How to Create an ML-Focused Newsletter appeared first on Towards Data Science.