Training and doing hyperparameter search on multiple models (in screenshot: xgboost, svm and random forest) simultaneously on a tabular dataset using AutoTrain Advanced without writing a single line of code! Try AutoTrain Advanced now!
MACHINE LEARNING
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FSD12 and Evolution of Machine Learning in Autonomous Driving
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FSD12 seems like a significant advance but surely it isn’t quite right to say that all previous systems have been rule based. There’s a lot of ML in previous systems, and there have even been end-to-end ones, like Nvidia’s early demo, right? Still, amazing if it works reliably.
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Google Maps Improves Route Suggestions Using Inverse Reinforcement Learning
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Presenting world-scale inverse reinforcement learning (IRL) in Google Maps. Learn how RHIP, a new IRL algorithm, along with advances in graph compression & parallelization led to relative improvement in the quality of suggested routes in Google Maps. → https://
goo.gle/3EBAc75 -
Optimizing OSS Models with System Prompts RAG Fine-tuning
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We use established fast and simple techniques to improve OSS model performance. These techniques include system prompts to generate less verbose answers, RAG to reduce hallucinations and fine-tuning to improve accuracy. (7/10)
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OSS Models Close Gap With Proprietary Tools via Techniques
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As seen on the @huggingface leaderboard, these techniques reduce the gap between proprietary and OSS models significantly and make OSS models useful for tool manipulation. https://
huggingface.co/spaces/qianton
g-xu/toolbench-leaderboard
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Open Source vs Proprietary AI Models: Performance Gap Analysis
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We benchmark a wide variety of OSS and proprietary models from @AiEleuther @Meta @BigscienceW @StabilityAI @OpenAI @TIIuae @salesforce @BigCodeProject @databricks and others. We see a huge gap between proprietary models and OSS models. (5/10)
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Gradient Descent Research Incubated at Google AI Becomes Osmo
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Very pleased to have helped incubate this research led by @awiltschko and many others within @GoogleAI
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osmo.ai. The power of gradient de-scent methods! -
SAS Energy Forecasting Improves LADWP Predictions and Service Reliability
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“Transforming volumes of data into more accurate predictions with SAS Energy Forecasting means better decisions for LADWP and more dependable and reliable service for our millions of customers,” said Bingbing Zhang, Data Analyst @LADWP
. http://
2.sas.com/6013P2Cj1 #ExploreSAS -
Top AI Leaders Balance Management with Individual Contributor Technical Work
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It seems to be not a coincidence that some of the strongest leaders in AI who manage large teams frequently do very low-level technical work. Jeff Dean doing weekly IC (individual contributor) work while managing 3k+ people at Google Research is the canonical example, but I've
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Apple GPU Shaders Enable ML Operations in New iPhone
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For those following the GPU stuff with the new iPhone at the apple show its shaders that it's referring to are the same operators (mps) for its ML tasks.