billions spent on AI inference and your AI provider’s word is enough? estimated $23B in inference infrastructure spending in 2026 and its projections imply roughly $39B in 2027. this shows the growing spending base that depends on reliable inference. there’s evidence of limited visibility into these services as 189 API endpoints were monitored for more than four months and detected 37 suspected changes across 29 endpoints, and it accounts to ~15% of those monitored. this shows that the endpoint behaviour can change without users knowing the cause. @miranetwork’s Sterling addresses this through five checks, model identity, tool calls, parameter handling, silent failures and declared context windows. these checks run every two hours, scores are public, and requests go to providers that pass. the commercial value is in connecting those measurements to routing decisions, where developers can act on provider quality without building the monitoring system themselves its growth would depend on three things: → how much inference traffic it attracts → whether customers stay after launch discounts end → the margin retained after provider and verification costs the verification is necessary because it gives customers assurance and hence a reason to stay https://x.com/arndxt_xo/status/2118389630093688891

Mezzanine @mezzanine_fi (see below!) is the only project I have made a seed investment into in the last three years here in brypto-land... https://x.com/rektdiomedes/status/2117829311306559523

a hack destroyed @Enter_Elysium today https://x.com/the_smart_ape/status/2118103175253397630