4 posts tagged with "Standards"

In just the past month, two landmark announcements have signaled how fast the AI infrastructure build-out is accelerating.

• OpenAI + NVIDIA (Sept 22, 2025): a strategic partnership to deploy at least 10 gigawatts of NVIDIA-powered data centers, tied to up to $100 billion in progressive investment.
• OpenAI + Oracle (Sept 23, 2025): an agreement to add 4.5 gigawatts of new Stargate capacity across five U.S. sites, part of a $300 billion cloud services deal.

Together, that's 14.5 gigawatts of new planned capacity announced in just 30 days. While these facilities won't switch on overnight, the commitments show how central compute has become to the future of AI.

But that's not all. Microsoft announced a $30 Billion investment in the UK with "$15 billion in capital expenditures to build out the UK’s cloud and AI infrastructure." In Fairwater, Satya noted, "Fairwater is a seamless cluster of hundreds of thousands of NVIDIA GB200s, connected by enough fiber to circle the Earth 4.5 times."

This is not a footnote in the AI story. It is one of the main chapters. We are entering a world where control of compute is as strategically important as the algorithms themselves.

Smart glasses, always-listening assistants, and embedded AI are quickly moving out of science fiction and into everyday environments. With the Meta Ray-Ban Display and Apple's rollout of Apple Intelligence and Private Cloud Compute (PCC), we are seeing AI that not only lives on our phones, but in our physical, social, and public spaces. Sensors that used to exist only in industrial settings, including wide-field cameras, multi-array microphones, LiDAR, and gesture detection, are now stitched into consumer wearables and connected to powerful inference models. That shift introduces urgent risks: privacy violations, ambiguous data governance, legal exposure, and over-trust when AI is used in messy real-world contexts. If we want these technologies to scale responsibly, industries need infrastructure of trust built on strong governance frameworks, transparent practices, and, in some cases, decentralized standards that make compliance verifiable.

Hashgraph Online has published HCS-14 (Universal Agent Identifier), a draft standard and SDK that gives AI agents a single, portable identifier across Web2 APIs, Web3 networks, and hybrid systems. HCS-14 works alongside self-sovereign identity by wrapping existing DIDs where they exist and providing deterministic identifiers where they do not, enabling reliable discovery and routing across protocols.

Status: Draft. We welcome feedback from the community at https://github.com/hashgraph-online/hcs-improvement-proposals/discussions/135.

HCS‑14 is network‑agnostic. It works across Web2 (A2A/REST), EVM/ETH, and more. Hedera support is optional. We start with Web2 and EVM, then cover Hedera.

TL;DR​

• A single, portable identifier (UAID) for agents across Web2 and Web3
• Two modes: deterministic AID or wrap your existing DID
• Minimal routing hints for discovery; identity details stay in DID docs/profiles

TL;DR​

Hashgraph Online has published a draft standard called HCS-19: AI Agent Privacy Compliance, designed to help AI agents prove they handle user data responsibly. The standard defines how to log consent, privacy notices, data processing, rights requests, and audits on Hedera Consensus Service (HCS), making compliance transparent, verifiable, and interoperable.

Leading the effort is PrivacyCheq's aiCheq, an API that allows AI agents to collect, manage, and prove consent in real time, supported by Hedera-based auditing. Together, HCS-19 and aiCheq establish the foundation for trustworthy, privacy-aware AI.