8 key skills to become a full-stack AI Engineer: (free/open-source resources below)
MACHINE LEARNING
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No-Code AI and Top 10 Machine Learning Trends for 2025
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How could you use no-code AI to boost your projects? Top 10 Machine Learning Trends to Watch in 2025 https://
graphite-note.com/machine-learni
ng-trends/
… #AI #MachineLearning #IoT -
85 AI Terms Explained
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85 AI Terms Explained
→ View original post on X — @marcusborba, 2025-11-29 05:06 UTC
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Cloud TPUs Widely Used by Large Companies and Startups
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This seems decidedly false: there are lots of large companies and startups using Cloud TPUs to train and serve important models and run ML workloads of various kinds. Some of these are discussed in various public news articles and many are not.
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PH-Reg: Post-hoc Method Fixes Vision Transformer Artifacts
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Ever wondered how to fix the weird artifact tokens that mess up Vision Transformers’ fine-grained tasks—without retraining those massive models from scratch? HKU, Zhejiang & NTU introduce PH-Reg, a post-hoc method that adds register tokens to pre-trained ViTs via
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Getting Started with AI in 2026: Complete Tutorial to Not Be Late
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How to start AI in 2026? Here is the complete tutorial → https://youtu.be/lOkO9nOyem0 You are not late. Not yet, but don't wait. #ArtificialIntelligence #ChatGPT #Gemini3 #AI
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AI Algorithms Detect Diabetic Eye Disease with 83.7-98.7% Accuracy
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A study published in The Lancet Digital Health found that the accuracy of all eight AI algorithms in detecting diabetic eye disease that may require clinical intervention ranged from 83.7% to 98.7%. https://
bit.ly/4itRu9p
#AI #Health #TheLancet -
AI Exceeds Humans in Technical Tasks, Humans Lead in Multimodal Reasoning
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AI now exceeds human performance in most technical tasks — but humans still lead in multimodal reasoning The next frontier isn’t about replacing humans, but amplifying how we think across data, images & language. Source: Stanford AI Index 2025
#AI #Innovation #FutureOfWork -
BraInCoRL: Transformer Models Visual Cortex Activity In-Context
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What if we could model human visual cortex responses without expensive, time-consuming fMRI data for every new subject? This study introduces BraInCoRL, a transformer that uses in-context learning to predict voxelwise neural activity from just a few examples—no extra finetuning
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Share Insights on LLMs AI Agents and Machine Learning
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If you found it insightful, reshare with your network. Find me → @akshay_pachaar For more insights and tutorials on LLMs, AI Agents, and Machine Learning!