hahaha i am expecting a shipment of 16x [SOMETHING] anytime now she hates it, i really need my own data center lmao
SYSTEMS
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Multi-Agent Systems in Enterprise Tool Use Architecture
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Dive into the full breakdown, experiments, and architecture in our latest blog https://
snorkel.ai/blog/multi-age
nts-in-the-context-of-enterprise-tool-use/
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#AI #AIAgents #MultiAgentSystems #EnterpriseAI #MachineLearning -
Performance Optimization and Cost Reduction for Production AI Systems
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And the most compelling thing is getting this performance while ALSO reducing costs when it’s time to take the system to production and things need to scale.
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Processing 1.3 Quadrillion Tokens Monthly Demonstrates Massive Scale
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We processed over 1.3 Quadrillion tokens last month – that's 1,300,000,000,000,000 tokens! or to put it another way that's 500M tokens a second or 1.8 Trillion tokens an hour…
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NVIDIA InferenceMAX Delivers $75M Revenue Potential Per System
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To help companies get the most value, NVIDIA systems are built to deliver as much output as possible at AI factory scale. Recent InferenceMAX v1 results show NVIDIA sets the standard:
— NVIDIA (@nvidia) 10 octobre 2025
One NVIDIA system can enable $75 million in revenue for AI companies using (tag DeepSeek AI)… https://t.co/mWYKsySFXATo help companies get the most value, NVIDIA systems are built to deliver as much output as possible at AI factory scale. Recent InferenceMAX v1 results show NVIDIA sets the standard: One NVIDIA system can enable $75 million in revenue for AI companies using (tag DeepSeek AI)
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LLM Infrastructure: Still Early, Much Work Ahead
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LLM infra right now is like Linux in the 90s we're still early & there is a lot of work to do
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Smarter physics, not bigger chips, for AI
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it’s no longer “bigger chips = better AI” it’s “smarter physics = better AI.” With analog IMC, a model doesn’t waste energy copying weights back and forth. That overhead vanishes. IBM and others already show that MoE models map well to analog designs, boosting energy and
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Home AI Server Building Best Practices Guide
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the basic rules i follow when building an AI server at home >direct lanes, x16 or x8, from CPU and never off chipset
>no risers unless absolutely necessary
>airflow must be front-to-back, no hot recirculation
>power budget for transient spikes, not just average draw
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AI latency causes user distraction during query processing
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Those few seconds when your AI is thinking for your query, is more than enough for you to get distracted close to 15 mins…
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Smart Pet Feeder with Edge AI Monitoring and Activity Tracking
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A pet feeder that thinks: waits before refilling, tracks activity, multiple camera monitoring.
Edge AI making pet care smarter (even if the cat won't always cooperate with demos )
Code & demo: https://
eu1.hubs.ly/H0nJ32W0