NVIDIA AI Infrastructure ✓
@NVIDIAAIInfra · Santa Clara, CA · joined 25 Nov 2009
AI factories for the era of AI reasoning.
79 850Followers
1 673Following
12 255Posts total
78.3KViews on collected posts
Ultimi post
Cerchiamo nuovi post…
Our own @j_boitano joins @Cisco's Jeetu Patel on the #SplunkConf26 keynote stage on Monday to talk agentic AI, resilience, and what it actually takes to operate at machine speed.
Tune in ⤵️
3.9K views · 32 likes
· 4 reposts · 4 replies
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@NVIDIAAIInfra @KineticaHQ That AMD EPYC 9655P part has half the mem BW of Vera CPU. Try with Venice (has 30% more mem BW than Vera) soon it arrives: https://t.co/JSaNFBDMJ5
@AMD
55 views · 3 likes
· 0 reposts · 0 replies
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AI agents are putting more work back on the CPU.
Hear Ian Finder and @redpandadata's CEO Alexander Gallego explain how the NVIDIA Vera CPU with extreme co-design delivers the performance needed to keep GPUs productive and accelerate AI at scale.
Tune in now ⤵️
7K views · 57 likes
· 6 reposts · 9 replies
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Our compute is designed for the long run. @OrnnExchange breaks down the data: https://t.co/UzSQPi6MrE
11.8K views · 155 likes
· 22 reposts · 4 replies
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@NVIDIAAIInfra @KineticaHQ Vera lists up to 1.2TB/s of memory bandwidth. The EPYC 9655P is 12-channel DDR5, so roughly 600GB/s. That's about 2x before a single query runs. The measured win is 2.7x on a 720M-row scan-and-aggregate suite, which is bandwidth-bound. Most of this was
43 views · 3 likes
· 0 reposts · 0 replies
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@NVIDIAAIInfra @KineticaHQ I would like to test one. Could you send me one?
AGI needs it 😼
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· 0 reposts · 0 replies
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NVIDIA Vera CPU “won every single query. Every run. Every time.” … vs flagship x86 CPUs.
@KineticaHQ, known for its vectorized database architecture built for modern CPUs and NVIDIA GPUs, is sharing early results of NVIDIA Vera CPU testing.
Kinetica reports that Vera led every
17.2K views · 204 likes
· 19 reposts · 11 replies
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The fastest chip on the spec sheet isn't always the one doing the most useful work. 💭
In the latest episode of "Hello, Agent!", @emaxerrno talks with Ian Finder from @nvidia about Vera, a CPU built for a world where agents, not humans, are the primary consumers of compute. https
7.6K views · 4 likes
· 1 reposts · 0 replies
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How do you turn years of supply-chain expertise into a system that learns?
In collaboration with @PalantirTech, we built a governed decision-intelligence workflow that combines Palantir Foundry, NVIDIA cuOpt and Nemotron to help supply-chain planners optimize faster, with https
11.3K views · 160 likes
· 14 reposts · 6 replies
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🚀 Kinetica received early access to test @nvidia's new Vera CPUs — the results are impressive!
Head to the blog for more details on results + methodology: https://t.co/WebSDPR4nC https://t.co/Io7r1pkBFA
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The agentic enterprise is taking the #splunkconf26 stage.
Tune in to see how organizations like @nvidia and @awscloud transform security, observability, and operations with AI-powered workflows grounded in trust and proven at scale.
📆 https://t.co/W5gNyxE2uu https://t.co/cxF9BI
4.8K views · 15 likes
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Rispetto ad account della stessa dimensione
11 post degli ultimi 90 giorni, accanto alla fascia di 10K–100K follower. arriva a più persone rispetto ad account della stessa dimensione.
Visualizzazioni mediane6 955questo account924mediana per 10K–100K
Copertura, %8.71%questo account3.62%mediana per 10K–100K
Interazione, %1.36%questo account1.52%mediana per 10K–100K
| Metrica | Questo account | Mediana per 10K–100K | Rapporto |
|---|---|---|---|
| Visualizzazioni mediane per post | 6 955 | 924 | 7.53× |
| Copertura (visualizzazioni ÷ follower) | 8.71% | 3.62% | 2.41× |
| Tasso di interazione | 1.36% | 1.52% | 0.90× |
Altri account di questa fascia → Confronta con un altro account → Come sono costruiti questi parametri →
Growth & engagement
How the posts we collected actually performed: views and reaction rate post by post, what the audience did with them, and where the follower count goes.
Views per post
4.8K8 Sep
14.5K10 Sep
11.3K
7.6K
17.2K
198
43
11.8K11 Sep
7K
55
3.9K13 Sep
Last 11 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.
Engagement rate per post
0.39%8 Sep
0.04%10 Sep
1.60%
0.07%
1.36%
1.52%
6.98%
1.53%11 Sep
1.04%
5.45%
1.02%13 Sep
Reactions — likes, reposts, replies and quotes — divided by views. Median for 10K–100K accounts is 1.52%.
What the audience does
Likes79.8%641 in total
Reposts8.8%71 in total
Replies4.2%34 in total
Bookmarks7.1%57 in total
Share of every reaction we collected for this account. Replies mean argument, reposts mean endorsement, bookmarks mean the post was worth keeping.
The follower curve appears once this account has two daily snapshots — we take one a day, and this one is on its first.
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