AI Data Platform
No mentions found
This entity hasn't been tracked yet, or Iris is still building its knowledge base.
Related Articles from SNS
Architectural Evolution and Selection Framework for Database Systems in AI-Ready Data Platforms
arXiv:2606.08317v1 Announce Type: new Abstract: The rise of polyglot data management and AI-ready database architectures has created a complex design space across diverse database paradigms. However, architecture selection in modern enterprise environments continues to rely heavily on ad-hoc engineering intuition, with limited systematic frameworks to guide decision-making across heterogeneous database systems.
Meta Partners With Reliance on Its First AI Data Center in India
Meta Partners With Reliance on Its First AI Data Center in India Meta Platforms Inc. is partnering with Reliance Industries Ltd. to build its first AI data center in India, adding to a wave of investment in tech infrastructure globally. As part of the deal, tycoon Mukesh Ambani’s Reliance will build a 168-megawatt data center in Jamnagar — where it also runs the world’s largest single-site oil refinery — that Facebook’s parent will lease, the companies said in a statement on Wednesday. The...
Nvidia announces deals with South Korea's SK Hynix, Naver and Doosan for AI data centres
Nvidia announces deals with South Korea's SK Hynix, Naver and Doosan for AI data centres (Corrects key words for media clients to NVIDIA-SOUTHKOREA/ from NVIDIA-SOUTH KOREA/) By Heekyong Yang SEOUL, June 8 : Nvidia on Monday announced deals with South Korea's SK Hynix, Naver and Doosan Group to build AI data centres and use the U.S. chip firm's technology, as it looks to continue driving the AI boom. The agreements come during a high-profile trip by Nvidia CEO Jensen Huang to South Korea...
Microsoft announces Project Solara, its take on an AI agent platform
Microsoft announces Project Solara, its take on an AI agent platform The company demoed Solara on an Echo Show-style smart display and a smart key badge. Microsoft has announced that it's building a platform for AI agents. It's called Project Solara, and at Build 2026 the company showed it powering two different reference devices, a smart display and a smart key badge.
DigMethpy: An AI-driven platform for accelerating methane pyrolysis catalyst discovery
An AI-driven platform for accelerating methane pyrolysis catalyst discovery Lisa Lock Scientific Editor Robert Egan Associate Editor Researchers have developed a new artificial intelligence-powered platform that could significantly speed up the discovery of catalysts for methane pyrolysis, a promising technology for producing hydrogen with lower carbon emissions. Hydrogen is widely regarded as an important component of future clean-energy systems. However, many current methods of hydrogen...
Are Economists Open to AI? Text as Data as Survey on Professional Sentiment and Academic Research Trends
arXiv:2606.01958v1 Announce Type: new Abstract: Traditional surveys are costly, hard to reconstruct retrospectively, and vulnerable to self-presentation bias. Raw internet text is abundant but noisy, weakly structured, and platform-selected. We introduce TaDaS (Text as Data as Survey), a framework that converts naturally occurring text into survey-like evidence by linking a question corpus to an answer corpus through cross-dataset semantic retrieval.
How Much of Data-Center Activism Is Really AI Slop?
Americans are wary of AI in general, and they are especially suspicious of the AI data centers that are popping up across the country like enormous mushrooms. A majority do not want a new data center built in their town. Across the country, community groups have organized to protest individual projects, and activists have successfully lobbied local and state politicians to place moratoriums on the facilities’ construction.
KForge: LLM-Driven Cross-Platform Kernel Generation for AI Accelerators
arXiv:2606.02963v1 Announce Type: new Abstract: Production inference increasingly targets a heterogeneous mix of accelerators. Agentic pipelines interleave reasoning, tool calls, and multi-agent coordination, each with distinct compute and memory profiles. For optimal efficiency, each stage should run on the accelerator best suited to it.