So whats the next big fad .... "Context Engineering". So WHAT IS CONTEXT ENGINEERING? 𝟭. It’s Feature Engineering—but for AI Agents. (*Check what's feature engineering down below) 𝟮. The art of filling the context window with exactly what’s needed. 𝟯. You’re managing “working memory” like an operating system manages RAM. 𝟰. Agents need engineered context: instructions, tools, memories, examples, feedback. 𝟱. Poor context = forgotten steps, broken tools, bad decisions. 𝟲. Long-running agents hit context limits fast—engineering is essential. 𝟳. Vibe coding doesn’t scale—context engineering does. In the context of AI prompting, feature engineering refers to the process of creating, selecting, and transforming input data (features) to improve the performance of a machine learning model. It involves using domain expertise and various techniques to make the data more suitable for the AI model to learn from and generate better outputs. Check the following links for context: - Langchain Explanation on what it is: https://youtu.be/4GiqzUHD5AA?si=BEIThE_HOT-i3I9T - First post l saw talking about this was by Andrej Karpathy (@karpathy): https://x.com/karpathy/status/1937902205765607626 - And you may wish to follow this lady she dove right into it detail ... never mind hte course it hella expensive !: https://x.com/MaryamMiradi/status/1940810454013518178 #contextengineering #featureengineering #aiagents #langchain #promptengineering #aioptimization #machinelearning #contextwindow #workingmemory #aiprompting #vibecoding #aiperformance #contextualization #aitraining #aiscaling

Google's AI Learning Resources: A Comprehensive Guide Google offers a wealth of resources for individuals looking to expand their knowledge and skills in Artificial Intelligence. From YouTube playlists offering practical tutorials to dedicated learning portals, Google provides various avenues for exploring AI concepts and applications. The provided links lead to three particularly valuable resources: A YouTube playlist likely containing AI tutorials and explainers, Google's "Learn AI Skills" portal, and Google Cloud's Machine Learning/AI training section. These resources collectively cater to a wide range of skill levels, from beginners seeking introductory concepts to experienced developers looking to implement AI solutions within the Google Cloud ecosystem. Whether you are interested in understanding the basics of machine learning or mastering specific AI tools, Google's learning resources offer a structured and accessible pathway to acquiring valuable AI expertise. #GoogleAI #LearnAISkills #GoogleCloudAI #MachineLearning #ArtificialIntelligence #AITraining #GoogleCloud #TensorFlow #Keras #AIeducation #AIML #DeepLearning #AITutorials #GoogleforAI https://ai.google/learn-ai-skills/ https://grow.google/intl/ssa-en/#filter https://cloud.google.com/learn/training/machinelearning-ai https://youtube.com/playlist?list=PLTZYG7bZ1u6piogbmszA_TzDyR3K85Qn9&si=K2RRhUNvjlVhq8rT

Anthropic secured a ruling affirming fair use in AI training, but faces trial for using pirated books. Amazon's Project Reneer aims to enhance AI capabilities, while Google donates A2A protocol to the Linux Foundation. Additionally, AI's impact on marketing and hiring practices is reshaping industries, raising concerns about authenticity and overregulation. #anthropic #projectreneer #fairuse #ai #aitraining #linuxfoundation #a2aprotocol #googleai #amazonai #aimarketing #aiethics #aihiring #generativeai #machinelearning #artificialintelligence https://youtu.be/jpvM94HRi44