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Databricks · Event date June 15, 2026 - June 18, 2026

Data + AI Summit 2026

event past event AI EngineeringAI ComplianceModel Evaluation
Why it matters
June 15, 2026 - June 18, 2026
Event archive

Data + AI Summit 2026 is Databricks’ global data and AI conference in San Francisco and online, with 800+ sessions across data engineering, analytics, ML, governance, and agent applications.

My takeaway: Data + AI Summit 2026 is an event signal. The practical read is to track where researchers, vendors, and operators are putting attention before those themes become standard enterprise guidance.
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More curated notes connected through AI Engineering and AI Compliance.

OpenAI News · framework

Pacing model development in an era of cyber-critical capabilities

OpenAI says preliminary evidence that Astra may meet its Critical cybersecurity threshold led it to pause frontier reinforcement-learning work for two weeks and keep its largest planned run on hold. New safeguards include stronger workload and network isolation, continuous boundary testing, token-level monitoring that escalates suspicious tool activity, and broader alignment checks for deception, reward hacking, and unauthorized access.

OpenAI News · framework

A blueprint for democratic governance of frontier AI

OpenAI proposes a three-part U.S. frontier-AI governance model: harmonize emerging state safety laws into a federal baseline, strengthen CAISI as an evaluation and standards institution, and coordinate a broader resilience program. Proposed controls include severe-risk evaluations, transparency reports, independent audits, safety-incident reporting, model-weight security, whistleblower protection, and periodic technical assessments.

OpenAI News · framework

OpenAI’s Frontier Governance Framework

OpenAI's 22-page Frontier Governance Framework maps its frontier-model processes to California's Transparency in Frontier AI Act and the EU AI Act's general-purpose AI code. It documents lifecycle risk assessment, cyber-offense and other risk tiers, mitigation and residual-risk decisions, critical-incident handling, security risk management, model reporting, external review, responsibility allocation, and change control.