New Release from @PacktPublishing @PacktDataML "Machine Learning Engineering on AWS: Build, deploy, and operationalize LLMs, AI agents, and generative AI systems on AWS" — at https://
amzn.to/4od7C1I ๐ช๐ต๐ฎ๐ ๐ฌ๐ผ๐ ๐ช๐ถ๐น๐น ๐๐ฒ๐ฎ๐ฟ๐ป:
Build and deploy AI agents using
COMPUTING
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New Release: Machine Learning Engineering on AWS Book
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Transaction foundation models turn financial data into intelligence with NVIDIA
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Transaction foundation models transform raw data into intelligence, trained on billions of financial events โ payments, transfers and behavioral signals. Financial institutions, like @Revolut and @Mastercard
, are already using NVIDIA accelerated computing to train foundation -
Apple’s Siri AI: Local model limited without cloud capabilities
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Last time around Apple released a lot of information about how their AI version of Siri worked between local and cloud models, not so much this time It is nice to have a Gemma-like model on device, but it is extremely limited unless it can call a smarter cloud model when needed.
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DeepAgent for competitive analysis
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deepagent for competitive analysis https://t.co/5WCFalQKTd
— Harrison Chase (@hwchase17) 8 juin 2026deepagent for competitive analysis
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New Apple Intelligence features on Safari: tab grouping, notify, describe extension
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New Apple Intelligence features on Safari > tab grouping > notify me feature
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Apple Intelligence: Personal Understanding, Web Tools, On-Screen Awareness
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Apple Intelligence: -Personal Understand in apps.
– Browse tools for web
– on screen Awareness
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Agentic features come to NotebookLM with Gemini 3.5
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The agentic features that we have been enjoying for a year and a half in ChatGPT, Claude and Gemini now finally arrive at NotebookLM. It will be able to run code in a virtual machine, work with sources, use skills, etc. That and the use of Gemini 3.5, now in NBLM ๐
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Harvard collaboration study of Perplexity Computer shows efficiency and autonomy
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We're sharing a comprehensive study of Perplexity Computer in real-world deployment in collaboration with Harvard Computer is more cost and time-efficient, unlocks cross-disciplinary search beyond the reach of multi-step search, and provides higher autonomy and quality in the
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Cost Comparison of Human and Computer Research
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Research is cheap to start but costly per step, since the human executes each one. Computing costs more upfront to delegate and verify, but little per step, since the agent executes the steps. It is worth it once a task
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Epicure compresses 4.1 million food recipes into a 2MB model
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Researchers just squeezed 4.1M food recipes into one 2MB model. Food science has always lacked a universal map of ingredients. Chefs swap items by intuition, not by structure. A new paper called Epicure compresses all of human cooking into 2 megabytes. It trains on 4.1M