My biggest takeaway: Cloud may be the engine.
AI may be the brain.
But mobile networks are becoming the nervous system. And nervous systems decide how fast, secure, and intelligent the body can act. If you are building AI products or investing in infrastructure, this shift
SYSTEMS
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Mobile Networks: The Nervous System of Cloud and AI Infrastructure
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AI Agents Require More Than GPUs: Network Infrastructure Matters
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When AI agents act on real-time data, three things become mission critical: → Reliable connectivity
→ Secure data flows
→ Low latency If your network drops, lags, or gets compromised, the AI fails. This is why “AI-ready” is not just about GPUs. It is about differentiated -
Supermemory achieves 99% SOTA memory system, open source release incoming
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ESTO ES UNA LOCURA! Supermemory ha alcanzado un sistema de memoria SOTA del 99%. Los agentes de IA ahora recordarán TODO. PD:Lo publicarán como código abierto en 11 días
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Sakana AI System Visualizes Cognitive Warfare on Social Media
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[Yomiuri Shimbun] Sakana AI's proprietary system visualizes "cognitive warfare" on SNS
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Why AI Implementation Fails Inside Companies
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The real reason AI is failing inside companies? Let’s say it. A company decides to go all-in on AI. The CEO announces the vision.
The CTO aligns.
The CIO gets the budget. Then the real transformation begins. Chief AI Officer.
AI Center of Excellence.
AI Ethics.
AI Governance. -
ByteDance Open-Sources DeerFlow 2.0 Autonomous Multi-Agent Framework
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🚨China’s ByteDance just open‑sourced DeerFlow 2.0 – a SuperAgent harness for truly autonomous AI agents.
— Futurepedia – Learn to Leverage AI (@futurepedia_io) 23 mars 2026
Key features
▪️ Hierarchical multi‑agent orchestration
▪️ Docker sandbox with real filesystem + bash
▪️ On‑demand tools/skills to keep context lean
▪️ Model‑agnostic (GPT‑4,… pic.twitter.com/xMX9axjI9RChina’s ByteDance just open‑sourced DeerFlow 2.0 – a SuperAgent harness for truly autonomous AI agents. Key features Hierarchical multi‑agent orchestration Docker sandbox with real filesystem + bash On‑demand tools/skills to keep context lean Model‑agnostic (GPT‑4,
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Personal Record: 5 Billion Tokens Daily Usage Achievement
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I thought my previous 5b tokens a day record was high
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Building MCP Servers in Production Workshop March 29
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See this @PacktPublishing is hosting a workshop on March 29 on “Building MCP Servers in Production”, led by Peder Holdgaard Pedersen — for engineers designing secure, scalable systems that support AI Agents. Find more details and register here: https://
eventbrite.com/e/building-mcp
-servers-in-production-tickets-1982519419953?aff=kirk
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Compute Becomes Primary Bottleneck for AI Testing Infrastructure
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I feel my main velocity limitation lately isn't token speed anymore, it's compute. Running tests in parallel is taxing; can't wait for better cloud worker integration.
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AI Sustainability: Architecture and Data Movement Strategy
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AI sustainability goes beyond energy. It comes down to architecture. Data movement. Execution. From my conversation with @cwellise at @Equinix at @NVIDIAGTC: Boards need to move from reporting → operating discipline. The leaders who embed this will win. Watch the latest #CXOSpice here: piped.video/1MUp9fq0IH8 #DataCenter #Sustainability #AIInfrastructure #EquinixPartner #NVIDIAPartner
→ View original post on X — @yuhelenyu, 2026-03-22 17:54 UTC