Tata SD-WAN for DC connectivity in the AI age https://
cloudcomputing-news.net/news/tata-sd-w
an-for-dc-connectivity-in-the-ai-age/?utm_source=dlvr.it&utm_medium=twitter
… #Cloud #Automation #Data #EnterpriseAI #DataEngineering #DigitalTransformation #AgenticAI #CTO
COMPUTING
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Tata SD-WAN Enables Enterprise AI Data Center Connectivity Solutions
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Unbounded Indexing Challenges in High-Ingestion Systems
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Indexes aren’t the problem. Unbounded indexing in high-ingestion systems is. IoT, observability, AI telemetry, financial feeds all share the same pattern: → continuous ingestion
→ append-only data
→ time-based queries
→ massive retention Eventually the architecture -
5G Latency Critical for Real-Time Sports Technology Applications
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Latency becomes visible in real time in use cases like the Automated Balls and Strikes (ABS). High-speed capture and 5G processing must stay perfectly in sync, because even small delays break trust in the outcome. @TMobileBusiness
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Data Analytics Roadmap 2026: Key Developments and Strategies
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#DataAnalytics Roadmap 2026
by @Python_Dv #DataScience #BigData -
AetheroSpace Launches Phobos Satellite for Orbital Intelligence
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Congrats to our friends @AetheroSpace on their (literal) launch! 🚀🛰️ https://t.co/8vyM7te7is
— Gill Verdon (@GillVerd) 31 mars 2026Congrats to our friends @AetheroSpace on their (literal) launch! 🚀🛰️ Edward (@somefoundersalt) Proud to announce that Phobos, the second @AetheroSpace satellite, was successfully launched to orbit earlier this morning We’re partnered with @BoozAllen on this mission to demonstrate capabilities for adaptive event detection using high-fidelity Earth observation data collected on orbit This will enable satellites to achieve faster, smarter, decision-making on orbit, and is a major step towards building the orbital intelligence layer for defense needs! — https://nitter.net/somefoundersalt/status/2038788178002522343#m
→ View original post on X — @bobgourley, 2026-03-31 05:05 UTC
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AI Diagnoses ER Patients More Accurately Than Doctors in New Study
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Early days, nobody wants to over-invest in side-quests and non-standardized concepts that might end up being swallowed by the models themselves. The focus is now on building a strong foundation rather than anything else.
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Structured AI reasoning over raw scale
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The takeaway for builders:
The future of reliable AI isn’t just bigger parameters. It’s giving models structured, verifiable environments to reason in. Typed control flow > open-ended code generation. Paper: http://
arxiv.org/abs/2603.20105
Code: http://
github.com/lambda-calculu
s-LLM/lambda-RLM
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LLMs struggle with long inputs
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The problem: LLMs choke on long inputs. The usual fix? Bigger context windows. More parameters. More RAM. But there’s a deeper issue. When you let a model write its own recursive code to manage memory, you get infinite loops, broken outputs, and unpredictable costs. Brute
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T-Mobile and NVIDIA Explore Edge AI for Reduced Latency Performance
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From #GTC26: AI performance depends heavily on architecture. @TMobileBusiness and NVIDIA are exploring how edge compute can reduce latency by processing data closer to where it’s created. ⚡ fierce-network.com/broadband… T-Mobile for Business Partner #EdgeAI
→ View original post on X — @haroldsinnott, 2026-03-31 00:42 UTC
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Data Centers Research: Epoch AI Resource Analysis
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A lot of the starting point for data came from @EpochAIResearch
's excellent resource https://
epoch.ai/data/data-cent
ers
…, with some additional research (mostly backward looking) and some extrapolations