Aria Networks, Inc.

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Aria Networks, Inc.

Aria Networks, Inc.

@AriaNetworks

Networks that Think.

Palo Alto, CA Katılım Ekim 2025
164 Takip Edilen270 Takipçiler
Aria Networks, Inc.
Aria Networks, Inc.@AriaNetworks·
24 hours out. Chip benchmarks tell you what one component can do. They can't tell you where inference performance is actually decided: the fabric connecting prefill, decode, KV cache, and storage. Tomorrow at @RaiseSummit, our CEO @MansourKaram joins @dylan522p of @SemiAnalysis_ to follow one inference request through the AI factory and pinpoint where token efficiency is won or lost. 🗓️ Thursday, July 9 | 3:20 pm 📍 RAISE Summit, Paris #DeepNetworking #AIInference
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Aria Networks, Inc.
Aria Networks, Inc.@AriaNetworks·
To everyone building the infrastructure behind this era of AI and taking today to fire up the grill instead: thank you, and happy 4th! We'll be back to obsessing over "Networks that Think" tomorrow. 🇺🇸
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Mansour Karam
Mansour Karam@mansourkaram·
AI infra drives AI economics. Thanks @NasdaqExchange. Managed inference providers win by choosing the metrics that matter, then out-innovating everyone at optimizing them. Copy the vanilla playbook, get commodity margins. More with @dylan522p at @RaiseSummit next week.
Nasdaq Exchange@NasdaqExchange

.@AriaNetworks Founder & CEO @mansourkaram joins @Nasdaq to discuss AI-powered network operations, intelligent automation, and the evolving infrastructure powering tomorrow’s enterprises.

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Aria Networks, Inc.
Aria Networks, Inc.@AriaNetworks·
When an AI training run degrades, the hard part isn't fixing it. It's finding it. NIC, fabric, xPU, and job data all live in separate tools, so every incident becomes manual correlation under pressure. Worse, utilization can look healthy while a microburst that's invisible at 1-second resolution stalls the whole job. Deep Networking was built for exactly this: microsecond telemetry that sees what 1-second hides, plus agents that handle correlation and root-cause diagnosis on their own. See how 👉 @Aria_Networks" target="_blank" rel="nofollow noopener">youtube.com/@Aria_Networks
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Aria Networks, Inc.
Aria Networks, Inc.@AriaNetworks·
What decides inference performance in a modern AI cluster? Not the chip. Everyone benchmarks the chip. The harder question is the network connecting thousands of them — where efficiency is quietly won or lost. July 9 at @RaiseSummit, @mansourkaram and @dylan522p take it apart. Using @SemiAnalysis_ ' InferenceX framework, they'll map the Pareto frontier of inference — throughput, latency, power, cost per token — and the architecture underneath: prefill/decode, storage access, distributed serving, scale-out and scale-up fabrics. The through-line is the fabric itself — the layer per-chip benchmarks miss. Exactly where Aria's Deep Networking lives. 🔥 Inside the AI Inference Cluster: Measuring What Matters 📅 Thu July 9 · 3:20 PM See you all there! raisesummit.com
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Aria Networks, Inc.
Aria Networks, Inc.@AriaNetworks·
Agents that act, not dashboards that watch. The default assumption: collect more telemetry, and intelligence follows. It doesn't. Specialized agents handle correlation, tool selection, and diagnosis without manual triage. This is what a Network that Thinks looks like. youtu.be/5NXWqcaaDUU
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Aria Networks, Inc.
Aria Networks, Inc.@AriaNetworks·
AI workloads don't fail because of compute. They fail because the network wasn't built for them. @AriaNetworks's Deep Networking platform is optimized hardware, expansive telemetry, and layer-appropriate intelligence built to work as one system. Purpose-built AI switches that keep every GPU communicating at wire speed. Software that captures telemetry at up to 10,000x the resolution of incumbent tools, correlates it across hosts and switches, and moves you from alert to resolution without the guesswork. And white-glove deployment with Field Engineers embedded in your team from day one. Most vendors give you parts. Aria gives you a system. Learn more: arianetworks.com/product @djspry
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Aria Networks, Inc.
Aria Networks, Inc.@AriaNetworks·
The network looks healthy. So why is my training job slow? It's not healthy. You just can't see it yet. At 1-second resolution, everything looks fine. Zoom into microseconds and the microburst stalling your training jobs and burning inference tokens shows up immediately. Aria's Deep Networking sees telemetry others can't reach — 200 measurements per interval, straight from the Aria Switch ASIC. You can't fix what you can't see. It takes three pillars working together: 1. Fine-grained telemetry: sharp enough to catch microbursts coarse monitoring averages away. 2. An end-to-end view: from job to silicon, stragglers included, so a slow run points to the contended port. 3. Agentic operation: it correlates the data and pinpoints root cause, turning hours of forensics into a question you just ask. See the difference for yourself. Aria. Networks That Think. youtu.be/_UgnSumi-9o?si…
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Mansour Karam
Mansour Karam@mansourkaram·
Inference performance is decided across the cluster, not just the chip. Excited to join @dylan522p at @RaiseSummit on July 9 to unpack the full inference stack, and why the network is essential to scaling AI efficiently. This is exactly the problem @AriaNetworks is focused on.
RAISE Summit@RaiseSummit

Everyone benchmarks the chip. Far fewer measure the thing that actually decides inference performance: the network connecting them. Inside a modern AI inference cluster, per-chip specs only tell you part of the story. Real efficiency is won or lost across the fabric that links prefill to decode, connecting storage to compute, and coordinating thousands of accelerators. It's the layer most benchmarks miss, and the layer where real-world performance is increasingly decided.  This July 9, @MansourKaram, Founder & CEO at @AriaNetworks, joins Dylan Patel (@dylan522p), Founder, CEO & Chief Analyst at @SemiAnalysis_, to walk through the entire inference stack and pinpoint where efficiency is won or lost. Using SemiAnalysis's InferenceX framework as a lens, they'll map the real tradeoffs among throughput, interactivity, latency, power, and cost per token. What does it take to understand performance inside a modern AI inference cluster? Join Mansour and Dylan this July 9 on the Ada Lovelace Stage at 3:20 PM to hear where they land.  Limited tickets to RAISE Summit remain.  🔗 Secure your ticket: hubs.li/Q04lBDKp0

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Aria Networks, Inc.
Aria Networks, Inc.@AriaNetworks·
When people picture AI networking, they picture the backend fabric connecting GPUs. Fair. But the frontend network is quietly becoming just as critical for inference, and it gets almost no attention. There are different networks at play in an inference cluster, and they don't all matter equally for every workload. Treating them as one undifferentiated "fast pipe" leaves a lot of performance on the table. This is where granular, real-time visibility changes the game. You can't optimize what you can't see, and you can't act on what you can only see after the fact. The frontend is the next frontier in inference performance. Most of the industry hasn't noticed yet. To learn more, check out: arianetworks.com #DeepNetworking #NetworksThatThink
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Keşfet

@RaiseSummit @mansourkaram @dylan522p @MansourKaram @SemiAnalysis_ @NasdaqExchange @Nasdaq @djspry