The smallest robotic arm you can imagine is controlled by artificial intelligence
Researchers used deep reinforcement learning to steer atoms into a lattice shape, with a view to building new materials or nanodevices.
Modeling Heart Rate Response to Exercise with Wearable Data
This paper was accepted at the workshop “Learning from Time Series for Health” at NeurIPS 2022. Heart rate (HR) dynamics in response to workout intensity and duration measure key aspects of an individual’s fitness and cardiorespiratory health. Models of exercise physiology have been used to characterize cardiorespiratory fitness in well-controlled laboratory settings, but face additional …
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Stable Diffusion with Core ML on Apple Silicon
Today, we are excited to release optimizations to Core ML for Stable Diffusion in macOS 13.1 and iOS 16.2, along with code to get started with deploying to Apple Silicon devices. Figure 1: Images generated with the prompts, “a high quality photo of an astronaut riding a (horse/dragon) in space” using Stable Diffusion and Core …
A conversation with Kevin Scott: What’s next in AI
The post A conversation with Kevin Scott: What’s next in AI appeared first on The AI Blog.
Will You Find These Shortcuts?
Posted by Katja Filippova, Research Scientist, and Sebastian Ebert, Software Engineer, Google Research, Brain team Modern machine learning models that learn to solve a task by going through many examples can achieve stellar performance when evaluated on a test set, but sometimes they are right for the “wrong” reasons: they make correct predictions but use …
Build a robust text-based toxicity predictor
With the growth and popularity of online social platforms, people can stay more connected than ever through tools like instant messaging. However, this raises an additional concern about toxic speech, as well as cyber bullying, verbal harassment, or humiliation. Content moderation is crucial for promoting healthy online discussions and creating healthy online environments. To detect …
Data: the Rx to faster, patient-centric clinical trials
Out of necessity, the life sciences industry has accelerated the innovation and experimentation of drug and device development. The sector, which has traditionally been slow-moving when it comes to clinical trials—for reasons ranging from regulatory, to trial recruitment, to quality control—is now looking towards cloud technology to speed up the process and find new innovative …
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McKinsey State of AI 2022 highlights stubborn adoption plateau
McKinsey has released its State of AI 2022 report, revealing key findings on AI’s use and adoption globally over the past five years.Read More
CES 2023 is targeting 100K attendees and millions of square feet of booths | Gary Shapiro
CES 2023 will have about 100,000 attendees, or more than double the number last year during the Omicron wave, according to the CTA.Read More
How MIT is training AI language models in an era of quality data scarcity
As more sophisticated AI language models are developed, more quality data is needed for training them. MIT is working to solve this issue.Read More