AI, American Science Cloud, and the Genesis Mission#

Chin Guok (ESnet)

• Why: The clearest public statement of how AI workloads are rewriting the requirements for a national-scale research WAN. AmSC is a congressionally mandated (OBBB Act/H.R.1) DOE project — an AI-focused, federated, science-optimized cloud integrating data, models, and HPC across DOE facilities, as a cornerstone of the Genesis Mission (doubling US R&D productivity within a decade, 26 named S&T challenges).
• What: Beyond the program overview, the talk gives concrete networking consequences: ESnet7 is expected to deploy 50–70% above the current historical growth trend to accommodate AI workflows; benchmark models can spend over 50% of time in networking; emerging AI science (autonomous labs, fast-feedback experiments, interactive agents) needs negotiable service guarantees and QoS, not best-effort pipes. Supporting work: NetBurst event-centric forecasting of bursty traffic, SENSE for secure application-driven multi-domain programming, EJFAT load balancing and real-time streaming at 100 Gbps+, in-network caching showing ~70% data reuse, High-Touch per-packet visibility, and netFound (a network-security foundation model with UCSB).
• How: AmSC treats the network as a co-designed fabric with compute/storage/accelerators (explicitly citing hyperscaler practice), exposing AmSC and IRI APIs as a common framework to incorporate disparate resources into frictionless multi-cloud science workflows.
• Where applicable: US DOE-specific program; the traffic forecasts are cited from third-party analyses (Cisco, Gartner) and should be treated as directional rather than measured. Still, this is the requirements document that will shape ESnet7 — and a preview of the "AI WAN" demands every large operator is starting to face.