Google DeepMind breaks new ground with ‘Mirasol3B’ for advanced video analysis
Google DeepMind announces Mirasol3B, a new multimodal AI system for understanding long videos, but questions remain about real-world applicability.Read More
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Google DeepMind announces Mirasol3B, a new multimodal AI system for understanding long videos, but questions remain about real-world applicability.Read More
Need some smart home gadgets or toiletries? Target started its holiday sale early, with a price-match guarantee.
Engineers have developed a high-throughput, multimaterial 3D inkjet printer that uses computer vision to rapidly and automatically control the amount of material being deposited during the printing process in real time. This enables the use of a wide range of materials for fabrication.
Researchers in Australia have harnessed AI to produce solar cells from the mineral perovskite in just a matter of weeks, bypassing years of human labor and human error to optimize the cells.
Reinforcement learning forms the backbone of OfferFit’s automated marketing solution, which ingests data about its clients’ customers.Read More
Researchers at Carnegie Mellon University and Google DeepMind recently developed RoboTool, a system that can broaden the capabilities of robots, allowing them to use tools in more creative ways. This system, introduced in a paper published on the arXiv preprint server, could soon bring a new wave of innovation and creativity to the field of …
Read more “A system that allows robots to use tools creatively by leveraging large language models”
Generative AI is shaping the future of identity access management by improving outlier behavior analysis and guarding against new threats.Read More
The agreement between Hollywood actors, studios, and streamers isn’t perfect. But it could set the tone for how future labor movements confront changes brought about by artificial intelligence.
From ChatGPT to DALL-E, deep learning artificial intelligence (AI) algorithms are being applied to an ever-growing range of fields. A new study from University of Toronto Engineering researchers, published in Nature Communications, suggests that one of the fundamental assumptions of deep learning models—that they require enormous amounts of training data—may not be as solid as …
Read more “New study finds bigger datasets might not always be better for AI models”
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