Radium

“The next AI infrastructure advantage is not owning more GPUs — it’s getting more useful work out of every GPU.” A strong piece from VentureBeat on what may be the next major shift in enterprise AI infrastructure. The industry spent the last two years racing to secure GPU capacity. Now attention is turning toward utilization, orchestration, inference optimization, and overall infrastructure efficiency. As enterprise AI moves from experimentation into production, the economics increasingly depend on how efficiently compute is delivered and managed at the system level. At Radium, this is core to how we think about AI infrastructure: maximizing useful work per GPU through vertically integrated, AI-native infrastructure designed for inference efficiency at scale. #AIInfrastructure #Inference #EnterpriseAI #GPU #LLM #CloudComputing #GenerativeAI https://lnkd.in/gtMNTEpy

The Stanford HAI State of AI 2026 report was just released. Impressive effort, lots to take in. One data point that stands out: 88% of organizations are now using AI in some form. That's up significantly from prior years. But the more organizations use it, the more the costs compound. The report makes clear that inference costs vary dramatically depending on which models you run and how. Inference is becoming a real business decision. It's why we built Radium. Read the report: https://lnkd.in/gFeDS7vr

Most teams are still running AI on infrastructure that wasn’t designed for it. That’s why costs keep rising as usage scales. Radium is a drop-in alternative to OpenAI and Anthropic. Same utility, lower cost. Join the wait list: https://lnkd.in/eAU8SBPa First 500 accounts get $500 in credits.

We were glad to see Radium included as a vendor alongside AWS, Google, Microsoft, and CoreWeave in Forrester's Q1 2026 Public Cloud Platforms Landscape report. Forrester identifies AI-native clouds as an emerging disruptive force in a market long dominated by general-purpose hyperscalers. The report puts it plainly: the primary challenge for cloud customers today isn't adoption, it's uncertain ROI. After two years of asking, what can AI can do? organizations are now asking whether what they're spending is actually delivering value. For most, the answer depends less on which models they're using and more on how efficiently those models are being run, something general-purpose infrastructure was never designed to optimize for. See full article: https://lnkd.in/epDaK-Kb Adam Hendin Vijay Gadepally Natalie Klym Mona Seyum

The Wall Street Journal recently ran a piece on token costs, citing an impressive figure: one day of AI-driven development work, a $10,000 bill. The article captures something most organizations are only beginning to understand. AI is priced in tokens, but tokens don't tell you what you're actually paying for. Beneath each token sits a layered cost structure the bulk of which comprises infrastructure overhead, execution inefficiencies, and underutilized compute. As usage scales, those hidden factors compound. The result is AI spend that rises faster than expected because of how inefficiently the underlying system is running. Optimizing how AI is delivered is where the real cost difference is made. Read the full article: https://lnkd.in/ecQqpay3 Adam Hendin Vijay Gadepally Natalie Klym Mona Seyum

Radium’s first out-of-home campaign, live in Toronto! More to come. Adam Hendin Vijay Gadepally Natalie Klym Mona Seyum

As AI adoption accelerates, energy and infrastructure efficiency are becoming central challenges. Glad to see Radium's Co-Founder, Vijay Gadepally raising this conversation at SXSW. #AIInfrastructure #DataCenters #EnergyEfficiency #SXSW

If you’re at Cannes AI Festival (Feb 12–13), stop by the Radium booth! #CannesAI #AIInfrastructure #WAIFC

If you’re attending WAICF 2026, visit Radium at Booth #3 in the Ontario Pavilion! #WAICF2026 #AI #GenAI #AIInfrastructure #CloudComputing #Ontario #CanadaTech

Thank you to Timothy Rossiter and the team at TechCayman for hosting Radium’s CEO Adam Hendin and CTO Vijay Gadepally for an exceptional Innovator Insights event in the Cayman Islands. We had the chance to meet and exchange ideas with several leaders across AI and digital infrastructure. The article below distills the themes that emerged during the discussion: why enterprise-grade AI depends on robust infrastructure, how power and sovereignty are reshaping strategy, and why inference economics are becoming central to adoption. It captures the core insights we explored together and the broader direction of the industry. https://lnkd.in/gYUebDiU #AIInfrastructure #EnterpriseAI #SovereignCompute #InferenceEconomics #DigitalInfrastructure #TechCayman #Radium #NextGenCompute