"It's easy to get distracted by shiny demos. Our goal at Snorkel is to focus on practical innovation, work closely with customers, and deliver real value. AI tech will continue to evolve, but data is key to success" @paroma_varma at GCP Startup Summit https://
cloudonair.withgoogle.com/events/summit-
startup-summit-23?talk=t1_s3_founderadvice
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RESEARCH
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Data Key to AI Success Over Shiny Demos
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Machine Learning AI Banking Finance 2023 Crisis Prevention
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Applications of Machine Learning and AI in Banking and Finance in 2023: Introduction Could the American recession of 2008-10 have been avoided if machine learning and artificial intelligence had been used to anticipate the stock market, identify hazards,… https://
analyticsvidhya.com/blog/2023/03/m
achine-learning-and-ai-in-banking-and-finance/?utm_source=dlvr.it&utm_medium=twitter
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Building High-Quality LLMs: Data-Centric AI Approaches
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Building high-quality #LLM is a fairly delicate effort that requires careful planning, systematic benchmarking, and iteration on data, models, & implementation. We are excited to have @togethercompute as a partner at The Future of Data-centric AI conference on Jun 7-8. Join us to
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YOLO Object Detection Tutorials with Python PyTorch Resources
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Dozens of #ComputerVision tutorials on different applications of YOLO models for #ObjectDetection and Classification using #Python and #PyTorch:
– tutorials:
https://
youtube.com/watch?v=fFCWrM
FH2UY&list=PLZCA39VpuaZZJ-aS7B7pZVrD9AtRx8-7u
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– Github notebooks: https://
github.com/roboflow/noteb
ooks
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Optimizing Deep Networks for Datacenter Performance: Complexity and Cost Tradeoffs
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It is harder than you think! It is a fun exercise to consider optimizing deep nets for high cycle times across a datacenter, but it is not at all straightforward, and the “cost of computation” goes way up versus maximizing the work that a single system can do.
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Bayesian Causal Discovery: Advanced Machine Learning Research
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Bayesian Causal discovery from @haeggee @arkrause #AISTATS2023
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Peter Grünwald e-values statistical testing methods AISTATS
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Peter Grünwald still an inspiration . We all need to go an lean about e-values and a better ways of doing statistical testing from this work. #AISTATS2023 https://
safestatistics.com -
Temporal Graph Neural Networks for Irregular Data
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Temporal graph neural nets for irregular data from @joel_oskarsson
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AGI Speed Advantage May Not Be As Obvious As Assumed
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The notion that AGIs will “think 10,000 times faster than us” isn’t as obviously true as it seems at first glance. It is under appreciated that the self driving teams struggle to make their systems operate at barely real time rates, and they are not close to AGI systems. Step
