Rodrigo Liang ретвитнул
Following Cerebras’ IPO, @RodrigoLiang joined @Bloomberg with @mattmiller1973 and @daniburgz
to explain why inference could become the biggest business in tech.
Watch here: bloomberg.com/news/videos/20…
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Rodrigo Liang
376 posts
Rodrigo Liang
@RodrigoLiang
Co-founder & CEO @SambaNovaAI
Palo Alto, CA Присоединился Ocak 2019
129 Подписки1.4K Подписчики
Rodrigo Liang ретвитнул
The next AI war won’t be about training models.
It’ll be about:
➡️ Inference costs
➡️ Compute shortages
➡️ Scaling AI profitably
Following Cerebras’ IPO, @RodrigoLiang joined @Bloomberg with @mattmiller1973 and @daniburgz to explain why inference could become the biggest business in tech.
Enterprise AI demand is exploding. The infra race is just getting started.
Watch here ⤵️
bloomberg.com/news/videos/20…
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Rodrigo Liang ретвитнул
UK sovereign AI is becoming reality.
Together with Argyll , we’ve launched a sovereign AI inference cloud built on SambaNova’s full-stack AI platform — designed for performance, efficiency, and control without the trade-offs of traditional infrastructure.
As AI adoption scales, sovereignty can’t just be a label. It has to be demonstrated through infrastructure ownership, operational control, energy efficiency, and where intelligence is deployed.
This deployment delivers:
⚡ High-performance AI inference
🌍 Renewable-powered infrastructure
🔋 ~10kW rack density with air-cooled systems
🏗️ Disaggregated architecture across UK data centers
🧠 SambaNova RDUs for efficient large-scale AI
This is what the next generation of AI infrastructure looks like.
Read more via DatacenterDynamics ⤵️
lnkd.in/eAqaBqtr
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Cerebras IPO signals that the market has clearly moved to inference. That’s where costs stack up, where systems break. Where scale either works… or doesn’t.
AI won’t be decided by who trains the biggest model. But who can make inference economics actually work at global scale.
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Rodrigo Liang ретвитнул
Thank you @ArtificialAnlys for verifying our speeds, as always 🦾
@MiniMax_ai M2.7 is running the FASTEST on SambaCloud. Try it now: cloud.sambanova.ai
Artificial Analysis@ArtificialAnlys
MiniMax-M2.7 is now available across six inference providers on Artificial Analysis, with significant differentiation in speed and price @SambaNovaAI leads on speed at 435 output tokens/s, >3x faster than any other provider. @FireworksAI_HQ, @novita_labs, @togethercompute, and @GMI_cloud have all matched @MiniMax_AI's first-party API pricing, while SambaNova is 2x higher. Key takeaways: ➤ Fireworks and SambaNova are on the Pareto frontier for Speed vs. Price. At 127 output tokens/s and ~$0.22 per 1M tokens blended, Fireworks is ~2.2x faster than MiniMax's first-party API at the same blended price, whereas SambaNova delivers 435 output tokens/s but at ~2-3.5x the blended price of the other providers (depending on cache usage) ➤ SambaNova is the fastest provider at 435 output tokens/s, ~3.4x the next fastest provider (Fireworks at 127 output tokens/s). The remaining providers run substantially slower: MiniMax’s first-party API at 57 output tokens/s, Novita at 54, GMI at 41, and Together AI at 29 ➤ Cache discounts vary across providers. Fireworks, MiniMax, Novita, and Together AI offer 80% cache hit discounts, while GMI and SambaNova do not offer a discount. For cache-heavy workloads, this can materially increase the relative pricing for GMI and SambaNova ➤ Optimal provider choice depends on workload. SambaNova may be more suited to latency-sensitive deployments, albeit at a higher cost, while Fireworks may be more suitable for high-volume workloads that are not as latency-sensitive
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Rodrigo Liang ретвитнул
MiniMax M2.7 is now running FASTEST on SambaCloud 🚀
Built for coding, OpenClaw, and self-evolving agent workflows.
Available today across Enterprise & Dev tiers.
Try it now: sambanova.ai/blog/build-sel…
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Rodrigo Liang ретвитнул
Rodrigo Liang ретвитнул
📣 ICYMI: Devs, SambaCloud delivers MiniMax 2.5 at the fastest speed (400 t/s)—verified by @ArtificialAnlys.
Try it now: cloud.sambanova.ai/dashboard?utm_…
Take a look at those benchmarks 👇
GIF
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Rodrigo Liang ретвитнул
🦞 @openclaw is powerful, but running agentic workflows on big, slow models kills the magic.
The fix? Smaller, specialized models + our ultra-fast AI infra. Speed = intelligence. 🚀
Check out the blog ⬇️
sambanova.ai/blog/the-openc…
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Rodrigo Liang ретвитнул
When the @NYSE celebrates you 🥹
Humbled & thrilled to see our name take flight above the trading floor! A legendary tribute to our $350M+ Series E & collab with @Intel.
NYSE team: Thank you for making this milestone magic.
sambanova.ai/press/sambanov…
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Rodrigo Liang ретвитнул
A defining inflection point for the infrastructure powering the next AI era.
Congratulations to @SambaNovaAI on raising $350M and unveiling the fastest chip purpose-built for Agentic AI, in collaboration with @intel.
This is not just a funding round. It’s a market signal that the industry is moving decisively from pilots to production. With the launch of SN50, SambaNova is redefining what production-grade AI infrastructure looks like: scalable, high-performance systems engineered to power fleets of AI agents across entire data centers.
As Co-Founder and CEO, @RodrigoLiang puts it:
“AI is no longer a contest to build the biggest model. With the SN50 and our deep collaboration with Intel, the real race is about who can light up entire data centers with AI agents that answer instantly, never stall, and do it at a cost that turns AI from an experiment into the most profitable engine in the cloud.”
SambaNova continues to demonstrate what it means to build at the foundation layer, where silicon, performance, efficiency and real-world deployment converge.
We are honoured to have such visionaries within the RAISE Summit ecosystem.
The next era of AI won’t be trained. It will be operationalized.
👇 sambanova.ai/press/sambanov…
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Rodrigo Liang ретвитнул
The future of AI inference data centers will be heterogenous as AI agents and workloads become more diverse and complex. We are working on a multi-year collaboration for @intel #Xeon and @SambaNovaAI RDU based AI compute racks to meet this growing need. newsroom.intel.com/data-center/in…
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SN50 is here.
✅5X faster than competitive chips.
✅3X lower cost than GPUs.
✅Built for the agentic era, inference at true cloud scale.
We’re also announcing a multi-year collaboration w/ @intel to unlock the next wave of AI infra.
bit.ly/3P0ua8k
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Rodrigo Liang ретвитнул
What if we measured intelligence?
New research from @Stanford introduces Intelligence per Joule, a metric that actually reflects value, not just speed 🚀
And our SN40L RDU delivers 4X better energy efficiency by computing smarter, not harder.
Read more: sambanova.ai/blog/best-inte…
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Let’s go! Thanks for the support @olesovhcom
SambaNova@SambaNovaAI
🚀 @OVHcloud has chosen SambaNova to power its new ultra-low-latency, high-scale AI Endpoints. With SambaStack, OVH delivers: • Fast inference • Energy efficiency • 99.8% uptime SLA • Largest open-source models support • Real-time & batch endpoints sambanova.ai/solutions/ovh-…
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Rodrigo Liang ретвитнул
New independent study of energy usage for AI inference from local to cloud computing. To better normalize AI value across models, they introduce two key metrics : Intelligence per Watt (power) and Intelligence per Joule (energy). Research by @Avanika15
@HazyResearch @StanfordAILab @JonSaadFalcon 👇
SambaNova@SambaNovaAI
Our RDU delivers 4X more intelligence per joule than Nvidia’s latest B200 Blackwell chip. Research from Stanford introduces "Intelligence per Joule", a new metric that best explains AI efficiency from chips to models. Learn more about this benchmark: sambanova.ai/blog/best-inte…
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Rodrigo Liang ретвитнул
Great work by @JonSaadFalcon @Avanika15 @Azaliamirh @etash_guha and others at @HazyResearch !
Power is one of the biggest constraints to adding more compute for AI! Glad to see they have validated what we have been saying at @SambaNovaAI for awhile. We are the most power efficient chip out there (4-5x better!).
Jon Saad-Falcon@JonSaadFalcon
Data centers dominate AI, but they're hitting physical limits. What if the future of AI isn't just bigger data centers, but local intelligence in our hands? The viability of local AI depends on intelligence efficiency. To measure this, we propose intelligence per watt (IPW): intelligence delivered (capabilities) per unit of power consumed (efficiency). Today’s Local LMs already handle 88.7% of single-turn chat and reasoning queries, with local IPW improving 5.3× in 2 years—driven by better models (3.2×) and better accelerators (1.7×). As local IPW improves, a meaningful fraction of workloads can shift from centralized infrastructure to local compute, with IPW serving as the critical metric for tracking this transition. (1/N)
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Had a wonderful visit with His Excellency this week in Palo Alto! Thank you for the visit and the partnership all these years!
SPAENG@Spa_Eng
Communications Vice Minister Meets with SambaNova CEO to Enhance AI Investments. spa.gov.sa/en/N2421987 #SPAGOV
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🦾 @SambaNovaAI & @Stanford's new ACE framework is giving AI memory & the ability to learn from every success & mistake. This is a shift from static models to self-improving systems. At SambaNova, we're building the infra to make this a reality.
Paper: arxiv.org/abs/2510.04618
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Honored to welcome @KanishkaNarayan MP, the UK’s Parliamentary Under-Secretary of State for AI and Online Safety, to SambaNova today.
As he begins his vital new role, it’s inspiring to see the UK’s ambition and commitment to driving tech prosperity.
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