/5 Researchers from Stanford and MIT introduce Meta-Harness: An end-to-end optimization of model harnesses Meta-Harness is a system that automatically searches for better harness code for LLM applications. They argue that LLM performance depends not only on model weights, but
RESEARCH
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Anthropic Research Identifies Emotional Activation Patterns in Claude Sonnet 4.5
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/4 Anthropic reveals Claude uses “desperate” vectors to influence decisions Anthropic looks inside Claude Sonnet 4.5 and finds something unexpected: the model stores patterns that act like emotions. These are not feelings, but measurable activation patterns inside the network.
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Stanford researchers evaluate visual reasoning in multimodal models
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/2 Stanford shows Claude and GPT generate visual reasoning without image input Stanford researchers release MIRAGE, a method to test how multimodal models use images. They take GPT-5.1, Gemini-3-Pro, Claude Opus 4.5, and Gemini-2.5-Pro and remove every image from six benchmarks.
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Google Research on AI Agent Traps and Alibaba’s Qwen3.6-Plus Release
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/3 Google shows how the web itself can hijack AI agents with Agent Traps Alibaba launches Qwen3.6-Plus, a hosted model built for agent workflows instead of single http://
prompts.It targets agent workflows by combining reasoning, memory, and tool execution in one system. -
Princeton Study Analyzes Energy and Scaling Costs of AI Reasoning Models
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/1 Princeton study shows reasoning models use 79× more energy per query Princeton University researchers analyze how modern AI systems scale in energy, cost, and reasoning. They estimate a next-gen model training run uses 11 billion kWh, while a single reasoning query uses 33 Wh
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Deep Learning TensorFlow Keras Build Deploy ML Models
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Deep Learning with TensorFlow and Keras — Build and Deploy Supervised, Unsupervised, Deep, and Reinforcement Learning Models (3rd Ed., 667 pages): http://
amzn.to/3gitVEJ v/ @PacktDataML —————
#DataScientist #DataScience #AI #MachineLearning #ML -
Probability and Statistics Essentials for Data Science and Machine Learning
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Probability and Statistics Essentials for #DataScience and #MachineLearning, with 200+ examples and pictures [Kindle Edition]: http://
amzn.to/43a7tmo -
Mathematics of Machine Learning Book Review and Guide
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Get "Mathematics of Machine Learning" here: http://
amzn.to/4eN7i52 by @TivadarDanka v/ @PacktDataML —
GitHub: https://
github.com/cosmic-cortex/
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Here is my review: 𝗧𝗵𝗲 𝗦𝗲𝘁 𝗢𝗳 𝗠𝗮𝘁𝗵𝗲𝗺𝗮𝘁𝗶𝗰𝗮𝗹 𝗔𝗹𝗴𝗼𝗿𝗶𝘁𝗵𝗺𝘀 𝗧𝗵𝗮𝘁 𝗟𝗲𝗮𝗿𝗻 𝗙𝗿𝗼𝗺 𝗘𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲 This -
Practical Guide to Reinforcement Learning from Human Feedback
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New release from @PacktDataML available at http://
amzn.to/3PMn1ZL A Practical Guide to Reinforcement Learning from Human Feedback (RLHF). Amazon Summary: RLHF is a powerful approach to AI alignment and human-centered machine learning. By combining reinforcement learning -
MIT Offers 35 Free Machine Learning Courses on edX
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MIT: 35 Best Courses in Machine Learning! @MIT Explore a world of knowledge with free online courses from MIT on edX, featuring lessons in AI, machine learning, computer science engineering, circuits and electronics, Genetics, data science, statistics and much more. Many people are unaware that edX hosts an incredible collection of free online courses from some of the top educational institutions globally. You can dive into everything from AI to Python programming without any cost. A significant number of these courses are crafted by MIT experts. We highly encourage you to take advantage of this opportunity, and to kickstart your learning journey, here’s a curated selection of the best free online courses from MIT that you can explore this month: #BigData #Analytics #DataScience #AI #MachineLearning #IoT #IIoT #PyTorch #Python #RStats #TensorFlow #Java #JavaScript #ReactJS #GoLang #CloudComputing #Serverless #DataScientist #Linux #Programming #Coding #100DaysofCode References Green, J. (2024, December 11). MIT: 35 best courses in machine learning! Mashable. Retrieved December 11, 2024, from mashable.com/article/free-mi…
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