How multimodal A.I. of real time smartwatch data can automatically detect a person's loss of pulse—sudden cardiac death—and notify emergency services https://
nature.com/articles/s4158
6-025-08810-9
… @GoogleDeepMind @jesunshine @Nature
MACHINE LEARNING
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Multimodal AI Detects Sudden Cardiac Death via Smartwatch Data
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AI Detects Brain Abnormalities Missed by Radiologists
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A study suggests that artificial intelligence (AI) could help detect abnormalities in the brain linked to epilepsy that radiologists can sometimes miss. https://
bit.ly/4ihOR9c
#research #AI #epilepsy #healthcare #IoT #GenAI #technews -
AI Tool Predicts Most Effective Diabetes Medication for Patients
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Researchers have suggested that a new “personalised” online tool that predicts the most effective medication for individual patients with type 2 diabetes could benefit millions of people. https://
bit.ly/3CXXGGt #healthcare #research #diabetes #type2diabetes -
Respecting IP Rights and Data Ethics in AI Development
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I'm not trying to claim that my AI/ML work has always been perfect from the IP & data-rights perspective, but it's consistently been important. To those asking "how do we inspire" those reluctant: you can start with respecting basic rights and taking it from there…
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Random Kernels Replace Learned Statistics in Image Processing
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Welcome to new followers who arrived from here!
— Alex J. Champandard 🌱 (@alexjc) 26 février 2025
FYI: the code in 2016 used about 80Mb of statistics (convolution kernels) learned by training on ImageNet dataset. I since figured out how to make it work with random kernels. The style images used were out-of-Copyright. https://t.co/lZPj08zpESWelcome to new followers who arrived from here! FYI: the code in 2016 used about 80Mb of statistics (convolution kernels) learned by training on ImageNet dataset. I since figured out how to make it work with random kernels. The style images used were out-of-Copyright.
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Engineers, Scientists, and Analysts: The Three Pillars of Real AI
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The reality? Engineers build the pipelines, Scientists extract intelligence, and Analysts turn numbers into decisions. Without all three, AI remains a fantasy.
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Three Distinct Data Roles Leaders Must Understand
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I still see leaders confuse Data Engineers, Data Scientists, and Data Analysts, treating them interchangeably. The reality? Engineers build the pipelines, Scientists extract intelligence, and Analysts turn numbers into decisions. Without all three, AI remains a fantasy.
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Leveraging Personalized AI For Content Marketing Strategy
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Leveraging Personalized AI For Content Marketing
#AI #AIio #BigData #ML #NLU #Futureofwork @lexfridman @sama @kaifulee @ID_AA_Carmack @karpathy @2morrowknight @ylecun http://
ow.ly/mpHL30sK3nA -
Meta PARTNR: Benchmark for Multi-Agent Planning and Reasoning
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Meta PARTNR is a benchmark for planning and reasoning in embodied multi-agent tasks. This large-scale human and robot collaboration benchmark was core to our recent demos and also informs our work as scientists and engineers pushing this field of study forward. pic.twitter.com/bM1ghMXeS2
— AI at Meta (@AIatMeta) 25 février 2025Meta PARTNR is a benchmark for planning and reasoning in embodied multi-agent tasks. This large-scale human and robot collaboration benchmark was core to our recent demos and also informs our work as scientists and engineers pushing this field of study forward.
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Embrace Artificial Intelligence, Don’t Fear It
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Embrace Artificial Intelligence, Don't Fear It
#AI #AIio #BigData #ML #NLU #Futureofwork @HaroldSinnott @fogoros @iainljbrown @NandoDF @katecrawford @drhassanrashidi @YuHelenYu http://
ow.ly/m5pG30sK3nz