Optimizing PyTorch Model Inference on AWS Graviton
Tips for accelerating AI/ML on CPU — Part 2 The post Optimizing PyTorch Model Inference on AWS Graviton appeared first on Towards Data Science.
Tips for accelerating AI/ML on CPU — Part 2 The post Optimizing PyTorch Model Inference on AWS Graviton appeared first on Towards Data Science.
Ceramics — the humble mix of earth, fire and artistry — have been part of a global conversation for millennia. From Tang Dynasty trade routes to Renaissance palaces, from museum vitrines to high-stakes auction floors, they’ve carried culture across borders, evolving into status symbols, commodities and pieces of contested history. Their value has been shaped by aesthetics and economics, empire and, now, technology. This figure visualizes 20 representative Chinese ceramic craftsmanship styles across seven historical periods, ranging from […]
It’s unusual to be in the situation of reviewing a book no one will like. I don’t mean that literally; a handful of people will appreciate Paul Kingsnorth’s new book, Against the Machine, probably the same people who have followed his work for the past decade. Continue Reading…
Announcing: 𝗪𝗪-𝗣𝗚𝗗 — 𝗪𝗲𝗶𝗴𝗵𝘁𝗪𝗮𝘁𝗰𝗵𝗲𝗿 𝗣𝗿𝗼𝗷𝗲𝗰𝘁𝗲𝗱 𝗚𝗿𝗮𝗱𝗶𝗲𝗻𝘁 𝗗𝗲𝘀𝗰𝗲𝗻𝘁 I just released WW-PGD, a small PyTorch add-on that wraps standard optimizers (SGD, Adam, AdamW, etc.) and applies an epoch-boundary spectral projection using WeightWatcher diagnostics. Elevator pitch: WW-PGD explicitly nudges each layer toward the Exact Renormalization Group (ERG) critical manifold during training. 𝗧𝗵𝗲𝗼𝗿𝘆 𝗶𝗻 𝘀𝗵𝗼𝗿𝘁 • HTSR critical condition: α ≈ 2 • SETOL ERG condition: trace-log(λ) over the spectral tail = 0 WW-PGD makes these explicit optimization targets, rather than […]
India has given OpenAI, Google, and other AI firms 30 days to respond to its proposed royalty system for training on copyrighted content.
From enhancing assistive technology to addressing the digital divide, developers built mobile-first solutions to address real-world problems in the Gemma 3n Impact Chall…
Women ran an experiment to see if LinkedIn’s new algo was being sexist and thought they proved it. But there’s more complexity involved, experts say.
Reducing total cost of ownership (TCO) is a topic familiar to all enterprise executives and stakeholders. Here, I discuss optimization strategies in the context of AI adoption. Whether you build in-house solutions, or purchase products from AI vendors. The focus is on LLM products, featuring new trends in Enterprise AI to boost ROI. Besides the technological aspects, I also discuss the human aspects. I discussed the topic at a recent webinar. You can watch the recording, here. What is […]
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How to keep moving forward when your organization’s strategy is evolving and conditions keep shifting.