Read more: http://
agidefinition.ai/paper.pdf
@akshay_pachaar
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AGI Definition: Cognitive Versatility Beyond Single Task Excellence
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Finally, we have a definition for AGI! A recent paper breaks down what it actually means to reach human-level AI, and the results are surprising. Here's what matters: AGI isn't about passing a single test or excelling at one task. It's about matching the cognitive versatility
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MCP Guidebook and YouTube Playlist Resources
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Here you go: MCP Guidebook: http://
dailydoseofds.github.io/mcp-book/ YouTube playlist: http://
youtube.com/watch?v=XMVzT8
X0QTA&list=PLiz92QIWb30HMIZwwxah-7xyMcrNUfWwz
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MCP is Much More Than Just a Tool Calling Alternative
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Absolutely! MCP is a lot more than just a tool calling alternative!
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MCP Beyond Tool Calling: Two-Way Communication Between AI Apps
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MCP is getting so good! Most developers think MCP is just another tool calling standard, but that’s just scratching the surface. Here's what makes MCP powerful (explained with examples): Unlike simple tool calling, MCP creates a two-way communication between your AI apps and
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Continual Learning and Human-Like Memory in AI Agents
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Continual learning is the key! This is probably why building human like memory for agents is getting so big. @zep_ai @danielchalef
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Share AI, Mathematics and Machine Learning Insights
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If you found it insightful, reshare with your network.
— Akshay 🚀 (@akshay_pachaar) 27 septembre 2025
Find me → @akshay_pachaar ✔️
For more insights and tutorials on AI, Mathematics and Machine Learning! https://t.co/DrcSzcaOH4If you found it insightful, reshare with your network. Find me → @akshay_pachaar For more insights and tutorials on AI, Mathematics and Machine Learning!
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Understanding LLM Internal Architecture: Interactive Transformer Guide
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How LLMs work under the hood?
— Akshay 🚀 (@akshay_pachaar) 27 septembre 2025
This is the best place to visually understand the internal workings of a transformer-based LLM.
Explore tokenization, self-attention, and more in an interactive way: pic.twitter.com/Sk8yK5VpESHow LLMs work under the hood? This is the best place to visually understand the internal workings of a transformer-based LLM. Explore tokenization, self-attention, and more in an interactive way:
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Wrap-up Post on LLMs, AI Agents, and Machine Learning Insights
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That's a wrap! If you found it insightful, reshare with your network. Find me → @akshay_pachaar For more insights and tutorials on LLMs, AI Agents, and Machine Learning!