• Anthropic Academy - Build with Claude

    Start developing Claude-powered applications with our comprehensive API guides and best practices

    https://www.anthropic.com/learn/build-with-claude

    What you learn (Explore by topic)
    - Claude 4
    Learn how to harness the intelligence and capability of our latest models, Claude Sonnet 4 and Claude Opus 4
    - APIs & SDKs
    Learn about Anthropic's APIs, SDKs, and other development tools
    - Agents
    Build autonomous agents and agentic systems that understand, plan, and execute complex tasks
    - Model Context Protocol (MCP)
    Build advanced applications with the Model Context Protocol
    - Claude Code
    Speed up your development with Claude Code
    - Tool use
    Extend Claude's capabilities by connecting to external tools and APIs
    - Extended thinking
    Improve Claude's ability to solve complex tasks by allowing it to reason
    - Retrieval augmented generation (RAG)
    Build effective RAG systems to enhance Claude's responses with external data
    - Prompt engineering
    Create effective prompts that maximize Claude's performance
    - Evaluations
    Test and improve Claude's performance with structured evaluations
    - Prompt caching
    Optimize performance and reduce costs by reusing Claude's responses
    - Vision
    Harness Claude's ability to understand and analyze visual information
    - Computer use
    Learn how to use Claude models to interact with a computer desktop environment
    - Hackathon hacker guide
    Resources to help you get started with Claude, whether you're hacking with us at an event or on your own
    Anthropic Academy - Build with Claude Start developing Claude-powered applications with our comprehensive API guides and best practices https://www.anthropic.com/learn/build-with-claude What you learn (Explore by topic) - Claude 4 Learn how to harness the intelligence and capability of our latest models, Claude Sonnet 4 and Claude Opus 4 - APIs & SDKs Learn about Anthropic's APIs, SDKs, and other development tools - Agents Build autonomous agents and agentic systems that understand, plan, and execute complex tasks - Model Context Protocol (MCP) Build advanced applications with the Model Context Protocol - Claude Code Speed up your development with Claude Code - Tool use Extend Claude's capabilities by connecting to external tools and APIs - Extended thinking Improve Claude's ability to solve complex tasks by allowing it to reason - Retrieval augmented generation (RAG) Build effective RAG systems to enhance Claude's responses with external data - Prompt engineering Create effective prompts that maximize Claude's performance - Evaluations Test and improve Claude's performance with structured evaluations - Prompt caching Optimize performance and reduce costs by reusing Claude's responses - Vision Harness Claude's ability to understand and analyze visual information - Computer use Learn how to use Claude models to interact with a computer desktop environment - Hackathon hacker guide Resources to help you get started with Claude, whether you're hacking with us at an event or on your own
    0 Comments ·0 Shares ·509 Views
  • Check this Repo out !

    Shubham Saboo's GitHub repository hosts a collection of LLM Apps. These applications leverage large language models (LLMs) from various providers, including OpenAI, Anthropic, and Google, and open-source models. The apps incorporate Retrieval-Augmented Generation (RAG), AI agents, multi-agent teams, and voice agent technologies. This curated list is a valuable resource for exploring the capabilities and applications of LLMs in different contexts.

    #AwesomeLLMApps #LLM #LargeLanguageModels #OpenAI #Anthropic #GoogleAI #RAG #RetrievalAugmentedGeneration #AIAgents #MultiAgentTeams #VoiceAgents #GitHub #MachineLearning #NLP #AI #Langchain #LlamaIndex #DeepLearning #AISolutions

    https://github.com/Shubhamsaboo/awesome-llm-apps
    Check this Repo out ! Shubham Saboo's GitHub repository hosts a collection of LLM Apps. These applications leverage large language models (LLMs) from various providers, including OpenAI, Anthropic, and Google, and open-source models. The apps incorporate Retrieval-Augmented Generation (RAG), AI agents, multi-agent teams, and voice agent technologies. This curated list is a valuable resource for exploring the capabilities and applications of LLMs in different contexts. #AwesomeLLMApps #LLM #LargeLanguageModels #OpenAI #Anthropic #GoogleAI #RAG #RetrievalAugmentedGeneration #AIAgents #MultiAgentTeams #VoiceAgents #GitHub #MachineLearning #NLP #AI #Langchain #LlamaIndex #DeepLearning #AISolutions https://github.com/Shubhamsaboo/awesome-llm-apps
    GitHub - Shubhamsaboo/awesome-llm-apps: Collection of awesome LLM apps with AI Agents and RAG using OpenAI, Anthropic, Gemini and opensource models.
    github.com
    Collection of awesome LLM apps with AI Agents and RAG using OpenAI, Anthropic, Gemini and opensource models. - Shubhamsaboo/awesome-llm-apps
    0 Comments ·0 Shares ·563 Views
  • The Ongoing Copyright Debate: The New York Times vs. OpenAI and Microsoft

    Recently, the New York Times (NYT) filed a lawsuit against OpenAI and Microsoft, alleging that they used millions of copyrighted NYT articles to train their AI models without permission. The lawsuit claims that OpenAI’s models sometimes generate content that closely resembles NYT articles, raising important questions about copyright infringement and the implications for generative AI technologies. While the NYT aims to protect journalistic integrity, critics argue the lawsuit lacks clarity in establishing how exactly the models regurgitate content, leaving many confused about the relationship between AI training and output.

    Experts suggest that the AI's responses may not solely derive from their training data but could also involve mechanisms like retrieval-augmented generation (RAG), which allows models to pull real-time data from the internet. If this is the case, limiting the regurgitation of copyrighted material might be technically feasible without completely hindering AI capabilities. As AI models evolve and adjustments are made to minimize such occurrences, the industry collectively continues to search for balanced solutions to address copyright concerns while enabling innovation in AI technologies.

    Hashtags
    #NewYorkTimes #OpenAI #Microsoft #CopyrightLawsuit #GenerativeAI #AIEthics #MachineLearning #DataPrivacy #TechNews #AIRegulation #DigitalMedia

    https://www.deeplearning.ai/the-batch/the-new-york-times-versus-openai-and-microsoft/
    The Ongoing Copyright Debate: The New York Times vs. OpenAI and Microsoft Recently, the New York Times (NYT) filed a lawsuit against OpenAI and Microsoft, alleging that they used millions of copyrighted NYT articles to train their AI models without permission. The lawsuit claims that OpenAI’s models sometimes generate content that closely resembles NYT articles, raising important questions about copyright infringement and the implications for generative AI technologies. While the NYT aims to protect journalistic integrity, critics argue the lawsuit lacks clarity in establishing how exactly the models regurgitate content, leaving many confused about the relationship between AI training and output. Experts suggest that the AI's responses may not solely derive from their training data but could also involve mechanisms like retrieval-augmented generation (RAG), which allows models to pull real-time data from the internet. If this is the case, limiting the regurgitation of copyrighted material might be technically feasible without completely hindering AI capabilities. As AI models evolve and adjustments are made to minimize such occurrences, the industry collectively continues to search for balanced solutions to address copyright concerns while enabling innovation in AI technologies. Hashtags #NewYorkTimes #OpenAI #Microsoft #CopyrightLawsuit #GenerativeAI #AIEthics #MachineLearning #DataPrivacy #TechNews #AIRegulation #DigitalMedia https://www.deeplearning.ai/the-batch/the-new-york-times-versus-openai-and-microsoft/
    The New York Times versus OpenAI and Microsoft
    www.deeplearning.ai
    Last week, the New York Times (NYT) filed a lawsuit against OpenAI and Microsoft, alleging massive copyright infringements. The suit claims, among...
    0 Comments ·0 Shares ·662 Views
  • Build a RAG Agent in n8n Using Supabase
    Here’s how to set up a Retrieval-Augmented Generation (RAG) agent in n8n that pulls custom data from Supabase and gives smart AI responses.
    Perfect for building AI chatbots, support agents, or internal tools all with no-code #aiautomation #aiautomationagency #aiagents #aiagency #n8n

    https://www.tiktok.com/@colekril0/video/7512847299379285290
    Build a RAG Agent in n8n Using Supabase Here’s how to set up a Retrieval-Augmented Generation (RAG) agent in n8n that pulls custom data from Supabase and gives smart AI responses. Perfect for building AI chatbots, support agents, or internal tools all with no-code #aiautomation #aiautomationagency #aiagents #aiagency #n8n https://www.tiktok.com/@colekril0/video/7512847299379285290
    @colekril0

    Build a RAG Agent in n8n Using Supabase Here’s how to set up a Retrieval-Augmented Generation (RAG) agent in n8n that pulls custom data from Supabase and gives smart AI responses. Perfect for building AI chatbots, support agents, or internal tools all with no-code #aiautomation #aiautomationagency #aiagents #aiagency #n8n

    ♬ original sound - Cole Kril
    0 Comments ·0 Shares ·641 Views
  • Build a RAG Agent in n8n Using Supabase
    Here’s how to set up a Retrieval-Augmented Generation (RAG) agent in n8n that pulls custom data from Supabase and gives smart AI responses.
    Perfect for building AI chatbots, support agents, or internal tools all with no-code #aiautomation #aiautomationagency #aiagents #aiagency #n8n

    https://vm.tiktok.com/ZMSHpq5gg/
    Build a RAG Agent in n8n Using Supabase Here’s how to set up a Retrieval-Augmented Generation (RAG) agent in n8n that pulls custom data from Supabase and gives smart AI responses. Perfect for building AI chatbots, support agents, or internal tools all with no-code #aiautomation #aiautomationagency #aiagents #aiagency #n8n https://vm.tiktok.com/ZMSHpq5gg/
    @colekril0

    Build a RAG Agent in n8n Using Supabase Here’s how to set up a Retrieval-Augmented Generation (RAG) agent in n8n that pulls custom data from Supabase and gives smart AI responses. Perfect for building AI chatbots, support agents, or internal tools all with no-code #aiautomation #aiautomationagency #aiagents #aiagency #n8n

    ♬ original sound - Cole Kril
    0 Comments ·0 Shares ·537 Views
Displaii AI https://displaii.com