ai#
100 picked talks tagged ai, newest conference first.
Open vSwitch and OVN 2026 Fall Conference#
@Scale: Product 2026#
- Beyond “Good Enough”: How deployments accelerate research at the Audio AI Frontier
- Chasing a Moving Target: Going AI-Native on Edits' Video Seek Engine
- Content Accessibility at Scale: AI Voice Translations at Meta
- Fireside Chat: Designing for the Agentic Era
- Flywheel of Media Models & Product Velocity
- From On-Call to Always-On
- Live Panel: AI Generated Media Provenance at Scale
- ML Video Codec (MLVC): Research to Product
- Preview Player Reliability and the Agentic Defense Loop on Edits
- Rhythm - Anticipatory Intelligence for Organizations
- Ship Fast, Break Nothing: How AI Tests What AI Builds
- The future is products that grow themselves!
AI Engineer New York 2026#
- Everything will be Simulated
- Frontier Models for Acting in Space and Time
- Great Agents Start with Great Infrastructure
- How Compute Markets Work
- Process Supervision for Agents That Do Long-Horizon Work
- Security in the Age of AI: Recent Attacks, Incidents & Defenses
- Self-Improving Organizations
- The Dark Pools of Compute
- The Machine that Changed the World, vAI
- Your Agent Is a Lethal Trifecta (and What to Do About It)
- Your Company Has No Model of Itself: Bootstrapping a World Model from Slack, Decks and Meetings
@Scale: Networking 2026#
- Lightning Talk - AI4NI @Runtime
- Lightning Talk - The Plan That Learns
- Live Panel: Building at the Roofline — Planning and Delivering Gigawatt-Scale AI Infrastructure
AI Engineer World's Fair 2026#
- Agents at Scale: Inside MiniMax's Model and the Infrastructure Behind It
- Are LLM Performance Benchmarks Reliable?
- Beyond Static Intelligence: Evaluating Continual Learning
- Can LLMs write fast multi-GPU kernels? We built a benchmark to find out.
- Computer Use at the Edge of the Statistical Precipice
- Harnessing Collective Agent Intelligence for Open Science
- KV Cache-Aware Routing and P/D Disaggregation on Kubernetes: The Parts Public Benchmarks Don't Show
- Large clusters for small models
- Modular: Taming the AI Hardware Cambrian Explosion
- Operating Distributed Inference Systems at Scale
- Routing LLM Inference in Production: From Engine Signals to Policy
- Running a 20T-Token Data Pipeline: Infrastructure Lessons from Production
- Seeing the Plumbing: Profiling vLLM Speculative Decoding on NVIDIA Blackwell
- Taking Reinforcement Learning Cross Datacenter
- Two Bugs That Hid in Plain Sight: A vLLM Debugging Detective Story
- What If Your Chip Design Team Moved Like a Single Body?
- Your LLM Stack Is a 2008 Database With Better Marketing: Why ML Security Is Dominated by Misconfiguration, Not Missing Features
@Scale: Systems & Reliability 2026#
- AI Storage Blueprint
- Building Privacy Aware Infrastructure in the AI-Native Era
- Extending Meta to the Public Cloud
- Our Journey to Safely Unleash Agents at Meta Scale
- Securing Production Debugging at Hyperscale
- Taming AI Infrastructure Failures with Agentic Debugging
- The Agentic Infrastructure Gap: In-Distribution Languages Make It a Coding Problem
@Scale: AI & Data 2026#
- Agent Memory at Meta Scale: One Query Language for Graph, Vector, and Memory
- Agentic Data Flywheel: A Multi-Agent System for Scalable Multimodal Training Data Production
- Agentic Inference Optimization for RecSys ML models
- Architecting Infrastructure for the AI Native Future: Scaling Autonomous Agents on Google TPUs
- ASEA: Autonomous Agents for ML Serving Efficiency at Scale
- Cache the Session, Not the Data: 40x Faster ML Iteration with a Shared Sidecar at Meta
- Citrine: Catching Million-Dollar ML Anti-Patterns Before They Ship
- Data Governance in the World of Agents
- Designing for Human Agency in AI-Augmented Software: A Quality Attribute Approach
- Evaluating Opsmate: Grading AI Incident Investigations at Scale
- How Meta Scaled AI Training Storage via Data Normalization
- LP Planner: Synchronization-Aware Sharding Optimization for Large-Scale DLRM Model Training
- Meta-ML: Supercharging ML Productivity at Scale with AI-Native Infrastructure
- Scaling Batch Graph Processing to Trillions of Edges
- SparkSentry: Autonomous Error Detection, Triage, and Repair for Spark at Scale
- The Agent Feed: A Communication Layer for Multi-Agent Collaboration
- XStream: Meta's unified stream processing service
TNC26 (GÉANT research networking conference)#
- AI, American Science Cloud, and the Genesis Mission
- Building AI That Works: ESnet's Pragmatic Approach to AI-Driven Operational Excellence
- Federated Network Troubleshooting: Deploying HAWAT and Looking Glass Across the R&E Community
- From Public Cloud AI to National Infrastructure: Lessons from Sunet Scribe
- Honeypots and beyond – LLMs in cyberdefence
- Saz: Engineering Safe Agentic Workflows for Real-World Operations
- Traffic at 3am: Armed with a Toothpick against AI Scrapers
MCP Dev Summit North America 2026#
- Bridging Kernel Space and AI: Building an MCP Server for Linux Scheduler Observability - Daniel Hodges, Meta
- Durable, Asynchronous, and Tricky: Implementing MCP Tasks in Practice - Cornelia Davis, Temporal
- Every API Is a Tool for Agents - Matt Carey, Cloudflare
- Evolution, Not Revolution: How MCP Is Reshaping OAuth - Aaron Parecki, Okta
- From One MCP Server To an Ecosystem: When MCP Stops Being a Server and Becomes a Platform - Vaibhav Tupe, Equinix
- Interceptors for MCP: A Production-Tested Standard for Agentic Middleware - Kurt Degiorgio & Cannis Chan, Bloomberg
- Keynote: Duolingo's AI Slackbot: An Enterprise Assistant With 180+ MCP Tools - Aaron Wang, Software Engineer, Duolingo Inc
- Keynote: MCP @ Amazon Scale - James Hood, Principal Software Engineer, Amazon Web Services
- Keynote: Operating MCPs at Enterprise Scale: Uber's Journey - Meghana Somasundara, Agentic AI Lead & Rush Tehrani, Head of Engineering, Agentic AI Platform, Uber Technologies, Inc.
- Kubernetes-Native Agent Discovery: A Unified Registry for MCP Servers and Skills - Carlos Santana, AWS
- MCP at 18 Months: Protocols, Patterns, and What We Didn't See Coming - Shaun Smith, Hugging Face
- MCP Servers in the Wild: Managing Tool Complexity at Scale - Arnav Balyan, Concierge AI
- MCP Traffic Handling at Scale: Stateless Design, Proxies, and the Road Ahead - Erica Hughberg, Tetrate & Boteng Yao, Google
- MCPwned: Hacking MCP Servers With One Skeleton Key Vulnerability - Jonathan Leitschuh, Independent
- One Spec, Ten SDKs, Zero Excuses: Conformance Testing MCP - Paul Carleton, Anthropic
- Stateless: The Future of MCP Transports - Shaun Smith, Hugging Face & Kurtis Van Gent, Google
- Towards Building Safe & Secure Agentic AI - Dawn Song, UC Berkeley; UC Berkeley Center for Responsible Decentralized Intelligence & Matt White, Linux Foundation/PyTorch Foundation
- What if MCP was Symmetric? - Jerome Swannack, Anthropic
Open Networking & Edge Summit 2025#
- AI - Lessons Learnt from World's Largest Network
- AI-RAN and Open Source: Building Scalable Dataset Pipelines for AI Training
- Sponsored Session: Ready for Impact: EVE Steps from 10k Kubernetes Clusters to Edge AI
ONE Summit 2024#
- Harnessing Observability with AI for Edge Applications: Innovations in APM/T - Fatih E. Nar, Red Hat
- Introduction to Photonic Disaggregated Computing Architecture - Shigeru Kotabe, Fujitsu
- Kubeflow & Istio, a Perfect Match! Investigating Istio’s Role in MLOps - Nina Polshakova & Peter Jausovec, Solo.io
- The Dark Side of AI: The Hidden Supply Chain Risks in Open-Source AI Models - Guy Nachshon, Checkmarx