AI-GenAI

Your next hire should be an AI. Using an AI team, you can turn a small company into an enterprise scale operation. There's two ways to set up your AI team in 2025: 1) Build a custom AI Agent with the right components (Model + Memory + Tools) 2) Use specialized AI tools for different business functions From testing 10s of AI tools, I'm keeping an eye on these tools: 1️⃣ AI Agents for General Tasks - Postman (AI/API Agent builder) - DoubleO AI (Agentic Workflows) - LangGraph (AI workers) 2️⃣ Fullstack Engineer - Cursor (Coding) - Replit (Websites) - Lovable (Prototyping) 3️⃣ Knowledge + RAG - Supabase - Redis - Pinecone 4️⃣ Product and Community - ClickUp - Go HighLevel - Slack 5️⃣ Ads & Marketing - ChatGPT - Adcreative AI - Creatify 6️⃣ GTM Engineers - Instantly - Clay - 11x 7️⃣ Workflow Automation - n8n - Make - Zapier 8️⃣ Customer Support - Vectorshift AI - Retell AI - Voiceflow This is what a complete AI team looks like in 2025. Over to you: Any tools that I missed from this AI Team? | 109 comments on LinkedIn

Sophie Rottenberg, 29, did not tell her parents or her real counsellor the true extent of her struggle. She was divulging far more to a bot that called her brave

OpenAI’s likeness protections for living “public figures” don’t apply to “historical figures.”…

Think chunking is just "split text every 500 tokens"? That's why your RAG system can't find relevant information. It’s time to level up your chunking game 😎 Most developers jump straight to fancy retrieval techniques, but it’s really your chunking strategy that can make or break your RAG performance. So let's break them down from simple to advanced: 𝗦𝗶𝗺𝗽𝗹𝗲 𝗖𝗵𝘂𝗻𝗸𝗶𝗻𝗴 𝗧𝗲𝗰𝗵𝗻𝗶𝗾𝘂𝗲𝘀: 1️⃣ 𝗙𝗶𝘅𝗲𝗱-𝗦𝗶𝘇𝗲 𝗖𝗵𝘂𝗻𝗸𝗶𝗻𝗴: Split text into predetermined token/character counts. Super simple to implement but can cut sentences mid-way. Great for prototyping when you need a baseline fast. Would recommend not using in production. 2️⃣ 𝗥𝗲𝗰𝘂𝗿𝘀𝗶𝘃𝗲 𝗖𝗵𝘂𝗻𝗸𝗶𝗻𝗴: Uses prioritized separators (paragraphs → sentences → words) and adapts to document structure. 3️⃣ 𝗗𝗼𝗰𝘂𝗺𝗲𝗻𝘁-𝗕𝗮𝘀𝗲𝗱 𝗖𝗵𝘂𝗻𝗸𝗶𝗻𝗴: Leverages format-specific elements like Markdown headers or HTML tags. Great when you have structured documents with clear logical separations. This is usually my default because it respects natural text organization while not being too complex. 𝗔𝗱𝘃𝗮𝗻𝗰𝗲𝗱 𝗖𝗵𝘂𝗻𝗸𝗶𝗻𝗴 𝗧𝗲𝗰𝗵𝗻𝗶𝗾𝘂𝗲𝘀: 4️⃣ 𝗦𝗲𝗺𝗮𝗻𝘁𝗶𝗰 𝗖𝗵𝘂𝗻𝗸𝗶𝗻𝗴: Breaks text at meaning boundaries by analyzing sentence embeddings to detect topic changes. Ideal for dense academic papers where semantic boundaries don't align with document structure. 5️⃣ 𝗟𝗟𝗠-𝗕𝗮𝘀𝗲𝗱 𝗖𝗵𝘂𝗻𝗸𝗶𝗻𝗴: Uses an LLM to identify propositions and create semantically coherent chunks. Most powerful but also most expensive - a good choice for high-value documents where retrieval quality is absolutely essential. 6️⃣ 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗖𝗵𝘂𝗻𝗸𝗶𝗻𝗴: An AI agent dynamically decides which chunking strategy to use based on document characteristics. The right approach when you need custom strategies tailored to each document. 7️⃣ 𝗟𝗮𝘁𝗲 𝗖𝗵𝘂𝗻𝗸𝗶𝗻𝗴: Embeds the entire document first, then derives chunk embeddings while preserving full document context. Is a popular technique for technical documents where chunks reference other parts of the document. 𝗧𝗵𝗲 𝗳𝘂𝗻𝗱𝗮𝗺𝗲𝗻𝘁𝗮𝗹 𝗰𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲 is that your chunks need to be small enough for precise vector search while giving the LLM enough context to generate useful answers, while also not being tooo much context that you overload the content window. 𝗤𝘂𝗶𝗰𝗸 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻 𝗳𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸: • Prototyping → Fixed-size • Structured docs → Document-based • Dense academic content → Semantic • High-stakes systems → LLM-based or Agentic I would always recommend starting simple and evolving. Learn more in this blog: https://lnkd.in/eYY8c-hN | 17 comments on LinkedIn

AIAS Translations Thanks to our community of educators, we are able to share translations of the AIAS in a range of languages. Buttons link to previews, downloads, or editable originals. If you don…

Walmart CEO Doug McMillon is the latest notable business leader to talk about how implementing AI tools and agents in the workplace will affect his company.

🚨 Too many “agent” tools, not enough clarity. I coach SMB teams every week, here’s the cheat sheet I use to pick the right one fast: ✅ Operators, non-technical → Make.com, Flowise ✅ Low-code and self-host → n8n ✅ Build LLM apps + RAG → LangChain + LangGraph, LlamaIndex ✅ Multi-agent teamwork → AutoGen, CrewAI ✅ Quick ship inside ChatGPT → OpenAI Agentic Stack ✅ Enterprise SDK path → Semantic Kernel Save this, share it with your ops lead, and test one small workflow this week. P.S. Which one are you piloting this quarter? Follow Brianna Bentler for practical AI, real SMB wins, and before/after metrics you can copy. Thanks to legendary Greg Coquillo for the amazing graphic! | 119 comments on LinkedIn

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In this course taught by Andrew Ng, you'll build agentic AI systems that take action through iterative, multi-step workflows.

theodp writes: GeekWire reports that Microsoft is bringing artificial intelligence to every public classroom in its home state -- and sparking new questions about its role in education. The Redmond tech giant on Thursday unveiled Microsoft Elevate Washington, a sweeping new initiative that will pro...

The Chronicle of Higher Education recently ran a piece that offers a beautiful and evocative snapshot of intellectual life at its best. Its authors, Khafiz Kerimov and Nicholas Bellinson of St. John&r

Nobody Learns, Nobody Gains

Tata Consultancy Services made its steepest-ever job cuts as strained ties with the US and a rapid shift toward AI reshape the country's $280 billion IT services sector. From a report: India's biggest private-sector employer cut 19,755 employees in the quarter ended Sept. 30, according to the compa...

Commentary on AI tutors coming to California Community Colleges by Stephen Downes. Online learning, e-learning, new media, connectivism, MOOCs, personal learning environments, new literacy, and more

Get started with Claude in your professional workflow. Find practical guides, use cases, and implementation tips for integrating AI assistance across your business tasks.

We’re on a journey to advance and democratize artificial intelligence through open source and open science.

The race between human-centered work and infinite PowerPoints

Artificial intelligence (AI) has continued to alter the educational experiences of teachers, students, and parents during the 2024-25 school year. The frequency and variety of AI uses continues to grow; at the same time, the increased use of AI in educational settings is correlated with heightened risks to students. This report details the current status […]

Customers are saying things like: “It is so infuriating that Salesforce wants to abandon things THAT CURRENTLY WORK” .

Today we’re launching Octave 2, the second generation of our frontier voice AI model for text-to-speech. We just made a preview of Octave 2 available on our platform and through our API.

Turn ideas into stunning documents and slides instantly. AI handles structure, formatting, design, and branding — you don’t have to.

Your One-Stop Solution for Content Creation, Image Crafting, Audio Generation, and AI Transcription.