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Buried in Coursera’s 300-page prospectus: two failed merger attempts, competing bidders, a rogue shareholder, and a combined market cap that shrank from $3.8 billion to $1.7 billion.
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Academic Writing Made Easy
Mechanics of Materials I: Fundamentals of Stress & Strain and Axial Loading
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Explore Google's Gemini expansion: new app, advanced features, 1.5 Pro model with 2M token context, integration in Workspace, and innovative tools like NotebookLM and context caching.
Explore OpenAI's Swarm framework through code examples, learning concepts and applications for multi-agent systems. Gain insights into routines, agent handoffs, context injection, and function calling.
Explore the mechanics of GUI agents through Agent-S, examining hierarchical planning, memory systems, and computer interfaces for enhanced agent interactions.
Explore Claude 3's new models, comparing capabilities and performance through demos and benchmarks. Gain insights into Anthropic's latest AI advancements and their practical applications.
Explore recent advancements in LLM applications, focusing on personalization, curation, and innovative summarization techniques using new models like Claude 3: Haiku for improved note-taking and content processing.
Explore advanced Colab features: secrets management, snippets, AI assistance, custom VMs, and browser extensions for enhanced code development and productivity.
Explore Gemini 1.5 Pro's code capabilities through CrewAI, a framework for building AI agent systems. Learn to create and run multi-agent bots, integrate Gemini models, and leverage search tools.
Explore Mistral Large's capabilities, benchmarks, and function calling through code examples and comparisons with Mistral Medium, showcasing its potential for advanced language tasks.
Explore building custom AI crews using CrewAI, comparing sequential and hierarchical processes with practical coding examples and insights.
Learn to create an advanced AI agent using LangGraph, Llama 3, and Groq. Explore key concepts, workflow, and implementation steps for building sophisticated language models and graph-based agents.
Explore Llama 3.2's multimodal capabilities, edge computing potential, and performance benchmarks. Learn about its vision-tuned models, lightweight versions, and integration with Ollama.
Explore custom tools for AI agents, enhancing functionality and building effective LLM agents. Learn tool categories, implementation strategies, and best practices for optimal performance.
Explore key trends in LLMs: increasing intelligence, faster processing, cost reduction, and expanding context windows. Gain insights for developing advanced AI applications and agents.
Explore RAG fusion technique to enhance retrieval-augmented generation models, combining multiple search queries and ranking results using reciprocal rank fusion with LangChain implementation.
Explore LangGraph for building LLM agents: learn about StateGraph, nodes, edges, and practical implementations with code examples and tutorials.
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