Collaboration and openness drive innovation in artificial intelligence
summary
Claims that AI needs open collaboration and co-optimized silicon and software to move from batch analytics to real‑time intelligence across edge and cloud. Intel says it optimizes frameworks like Spark and Hadoop and deep‑learning runtimes (Caffe and Theano), and it open‑sources tooling — Trusted Analytics Platform, SNAP, Apache Spot — to accelerate model training, deploy onboard inference for autonomous vehicles and drones, and scale security and healthcare analytics; these projects are already active in pilots.
AI-written summary · about
chapters (6)
- 0:00Introduction
- 0:47The Age of Artificial Intelligence
- 1:37Innovation in AI
- 2:36Edge devices
- 3:15Software collaboration
- 3:44What is Intel doing
related talks
24mTools & Techniques for a cost optimized Analytics & AI pipeline
18mDriving Innovation with AI
09mThe AI stack from chip to analytics
16mKeynote: Open Source for AI and AI for Open Source
13mCombining algorithms and quality data to build better AI platforms
09mTackling edge computing with Intel's AI Builders program
22mThe Imperative for Open Source AI - The Path Forward to Take Down the AI Oligarchs
30mAI: unleashing the next wave
