25 killer AI tools across the stack Bots: ChatGPT, Claude, Bard/Gemini, Bing AI Video: Runway, HeyGen, Veed, Pictory Images: Midjourney, DALL-E 3, Leonardo, Firefly Slides: Tome, http://
Slides.ai, Decktopus, http://
Beautiful.ai Productivity: Taskade,
@ingliguori
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25 AI Tools: Bots, Video, Images, Slides, Productivity
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AI Tools Reach Infrastructure Scale: ChatGPT Dominates with 4.7B Monthly Visits
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AI tool usage at scale is here. ChatGPT: 4.7B monthly visits (Jan 2025)
Canva: 887M
Google Translate: 595M
DeepSeek: 268M (massive surge) http://
Character.AI: 226M
Perplexity: 133M
Gemini: 118M
Claude: 105M AI isn’t a trend anymore — it’s infrastructure. What’s your #1 -
Eight-Step AI Process: From Problem Definition to Responsible Deployment
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AI isn’t magic. It’s a process. 8 steps:
define problem
collect/prepare data
choose model
train
evaluate
fine-tune
deploy
ensure ethics & safety Real value comes from running this loop well. #AI #MachineLearning #DataScience #ResponsibleAI -
ML Workflow: Data Understanding to Deployment and Monitoring
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ML isn’t magic — it’s a workflow. 1. understand data 2. choose right algorithm 3. train 4. test 5. optimize 6. deploy + monitor + retrain The winners are the teams who run this loop consistently. #MachineLearning #AI #DataScience #MLops
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LLM Types Powering AI Agents: General-Purpose to Open-Source
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AI Agents = LLMs + orchestration Here are the main types of LLMs powering them General-purpose (GPT, Claude) Domain-specific (Legal, Finance, etc.) RAG-based (real-time knowledge) Tool-augmented (API actions) Open-source (LLaMA, Mistral) The game is no
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Large Concept Models: AI Architecture Beyond Token-Level Processing
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Large Concept Models (LCM): A New Frontier in AI Beyond Token-Level Language Models https://
linkedin.com/pulse/large-co
ncept-models-lcm-new-frontier-ai-beyond-giuliano-liguori–dnj3f
… via @ingliguori -
Beyond Prompts: Building Scalable LLM Systems
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Most people are using LLMs wrong. They focus on prompts.
Winners focus on systems. Shift from: One-shot prompts
to Iterative AI workflows Generic models
to Task-specific model selection Simple answers
to Structured execution plans LLMs scale when: • -
AI Agent Levels: From Automation to Superintelligent Personas
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AI agents have levels 1. Rule-based (if-then automation) 2. Tool-using assistants 3. Strategic multi-step agents 4. Context-aware autonomous agents 5. Superintelligent digital personas (theoretical AGI) We’re moving from “AI that responds” → to “AI that executes
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AgentOps: Full Stack for Scaling Autonomous AI Agents
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AgentOps = MLOps for autonomous AI. To scale agents in production you need the full stack: planning memory/context execution (tools/APIs/code) monitoring optimization governance infrastructure Agents don’t scale without operations. #AgentOps #AIAgents
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AI Mastery Roadmap: Your Complete Guide to Artificial Intelligence
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AI Mastery Roadmap – Your GPS to mastering artificial intelligence in 2025 and beyond. Whether you're a beginner or aiming to become an AI architect, this roadmap from Mindstream is one of the clearest, most actionable visual guides I’ve seen. It walks you step-by-step from: