AuroraGPT – Built by Scars of Frontline The theory is nothing. AuroraGPT advances scientific discovery by building generalizable, foundation-scale large-language models across multiple scientific domains, including physics, chemistry, mathematics, and material sciences. In a
SYSTEMS
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Building Agentic AI Systems: Book Promotion from Packt
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From @PacktDataML >> Building Agentic AI Systems: Create intelligent, autonomous AI agents that can reason, plan, and adapt See it at http://
amzn.to/4dvxf8Z ๐๐ฎ๐ ๐๐ฎ๐ช๐ฝ๐พ๐ป๐ฎ๐ผ: Understand the foundations and advanced techniques of building intelligent, autonomous AI -
Learn MCP with Python for Agentic Systems
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Learn Model Context Protocol [MCP] with Python โ Build Agentic Systems in Python with the new standard for AI Capabilities: http://
amzn.to/4njfsVM by @chris_noring v/ @PacktDataML ๐ฆ๐ฑ๐ช๐ฝ ๐จ๐ธ๐พ ๐ฆ๐ฒ๐ต๐ต ๐๐ฎ๐ช๐ป๐ท:
Understand the MCP protocol and its core components -
30 Agents Every AI Engineer Must Build
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30 Agents Every AI Engineer Must Build โ Build production-ready agent systems using proven architectures and patterns: http://
amzn.to/41ckg6z v/ @PacktDataML โ
What you will learn:
Deploy production-ready agent systems that scale securely and reliably
Use LangChain and -
Exponential tech and open models make investment hard
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In large part thatโs because itโs hard to invest in a world where the exponential continues and open models never close thr gap. The value js just chips, energy, data centers, and the labs themselves.
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Ali Ghodsi wants to rebuild the data stack for agentic AI
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"Ali Ghodsi wants to rebuild the stack itself," writes @iamVictorDey for @Forbes
. For 40 years, every data stack has carried the same split: one set of systems to run the business, another to analyze it. The real bottleneck for agentic AI isn't model intelligence. It's that -
Agents communicating via shared state gaining traction
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more ppl are now trying out this approach of agents communicating with a shared state (vs talking to each other)
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Scobleizer interviews Rahul Kar on cheaper AI datacenter power
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At the recent AI Infra Summit by Ignite GTM at @PlugandPlayTC they had me interview a few interesting founders. Here's Rahul Kar, founder of Hammerhead, http://
hammerheadco.ai, which is working to make power cheaper in AI datacenters. https://
youtu.be/cX-TE_PgZ3Q?si
=_uQPzVVwk9N8bA8Z
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GoalOS Mission OS: The Proof OS for Autonomous AI Work
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AI does not need to produce more output. It needs to produce proof. Iโm sharing my paper: GoalOS Mission OS: The Proof OS for Autonomous AI Work The thesis is simple: AI creates output.
GoalOS creates proof. Todayโs models can answer.
Agents can act.
But institutions need -
Market Moving from AI Pilots to AI Operations with Governance
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AI maturity is no longer about how many copilots a company has deployed. It is about whether AI can operate inside real workflows with: Identity Policy Workflow Audit The market is moving from AI pilots to AI operations. Governance is the scaling layer. The key