Advancements in whole genome sequencing have ignited a revolution in digital biology. Genomics programs across the world are gaining momentum as the cost of high-throughput, next-generation sequencing has declined. Whether used for sequencing critical-care patients with rare diseases or in population-scale genetics research, whole genome sequencing is becoming a fundamental step in clinical workflows and …
Why we must address the many potential ethical and regulatory considerations of ChatGPT and other advanced AI tools.Read More
The movie seems destined for internet infamy but doesn’t live up to the promise of its viral trailer.
The human retina not only senses light signals, but also processes them simultaneously by capturing their rich dynamics, thus accelerating the task-dependent learning in the down-stream visual cortex. This synergy of both the retina and the visual cortex has inspired in-sensor multi-task learning.
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When you build and train a PyTorch deep learning model, you can provide the training data in several different ways. Ultimately, a PyTorch model works like a function that takes a PyTorch tensor and returns you another tensor. You have a lot of freedom in how to get the input tensors. Probably the easiest is …
Read more “Training a PyTorch Model with DataLoader and Dataset”
Hey there, We are planning something and wanted to give you a sneak peek. Yes, it’s about ChatGPT and the Chatbot Conference. We are working on bringing you an event that will blow your mind. We can’t say too much right now, but trust us, you won’t want to miss this. We have big plans …
Posted by Aviral Kumar, Student Researcher, and Sergey Levine, Research Scientist, Google Research Reinforcement learning (RL) algorithms can learn skills to solve decision-making tasks like playing games, enabling robots to pick up objects, or even optimizing microchip designs. However, running RL algorithms in the real world requires expensive active data collection. Pre-training on diverse datasets …
Read more “Pre-training generalist agents using offline reinforcement learning”
Over the last 10 years, a number of players have developed autonomous vehicle (AV) systems using deep neural networks (DNNs). These systems have evolved from simple rule-based systems to Advanced Driver Assistance Systems (ADAS) and fully autonomous vehicles. These systems require petabytes of data and thousands of compute units (vCPUs and GPUs) to train. This …
Read more “Modular functions design for Advanced Driver Assistance Systems (ADAS) on AWS”
The do-it-yourself climate modeling movement is here. Researchers from Northwestern University and Argonne National Laboratory have been launching NVIDIA Jetson-driven edge computing Waggle devices across the globe to collect hyper-local climate information. Waggle is an open source sensor platform for edge computing developed by Argonne. Working with this, scientists share open-source AI code designed for …
Read more “DIY Urban AI: Researchers Drive Hyper-Local Climate Modeling Movement”