UltraSense uses machine learning to make better touch controls in cars
UltraSense Systems announced it has created new touch-control sensors for cars that are more accurate because they use machine learning.Read More
The Grim Origins of an Ominous Methane Surge
During the coronavirus lockdowns, emissions of the potent greenhouse gas somehow soared. The culprit wasn’t humans—but the Earth itself.
Twitter Blue Explained: What Is It? How Much Does It Cost?
The relaunch of Twitter’s subscription service is pretty confusing. Here’s what users receive for their money.
10 Best Xbox Series X/S Games You Can Play Now (2022)
These are the titles that make the most of your big, burly Microsoft console.
17 Best Tech Books to Gift (2022): Biographies, Startup Histories, Exposés
Give the techie in your life access to the inner workings of the companies and characters shaping Big Tech.
Antihelium Offers Hope in the Search for Dark Matter
An experiment at the Large Hadron Collider suggests there’s a chance of catching this elusive evidence as it floats through our galactic neighborhood.
A memristor crossbar-based learning system for scalable and energy-efficient AI
Deep-learning models have proven to be highly valuable tools for making predictions and solving real-world tasks that involve the analysis of data. Despite their advantages, before they are deployed in real software and devices such as cell phones, these models require extensive training in physical data centers, which can be both time and energy consuming.
Biomanufacturing of Tomorrow Requires a Connected Company Today
Next-generation cell-based therapy and gene editing therapeutics are set to revolutionize medicine. However, to harness the scientific potential of these drugs, biomanufacturing organizations must develop new systems to handle the increased complexity of process development, manufacturing operations, and quality assurance associated with these new therapeutics. In this blog post, we discuss the shortcomings of legacy …
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RT-1: Robotics Transformer for Real-World Control at Scale
Posted Keerthana Gopalakrishnan and Kanishka Rao, Google Research, Robotics at Google Major recent advances in multiple subfields of machine learning (ML) research, such as computer vision and natural language processing, have been enabled by a shared common approach that leverages large, diverse datasets and expressive models that can absorb all of the data effectively. Although …
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Introducing Amazon SageMaker Data Wrangler’s new embedded visualizations
Manually inspecting data quality and cleaning data is a painful and time-consuming process that can take a huge chunk of a data scientist’s time on a project. According to a 2020 survey of data scientists conducted by Anaconda, data scientists spend approximately 66% of their time on data preparation and analysis tasks, including loading (19%), cleaning (26%), …
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