Video summary

CES 2026 Keynote with Caterpillar's Joe Creed

Main summary

Key takeaways

Technology

Overview

Caterpillar framed itself at CES 2026 as the “invisible layer” of the modern tech stack — the physical infrastructure (construction, mining, power) that underpins digital services — and described how it is embedding connectivity, AI, autonomy and analytics into that layer.

  • CEO Joe Creed delivered the keynote emphasizing how physical infrastructure (roads, mines, data center power) is becoming data-driven and responsive via sensors, connectivity, software and AI.
  • The company presented an integrated strategy combining edge AI, digital twins, autonomous machines and a cloud-native data platform to improve safety, uptime, productivity and sustainability.
  • A safety-first approach and rigorous reliability/trust controls were repeatedly emphasized.

Key technological concepts and platforms

  • Invisible layer: physical infrastructure instrumented with sensors, connectivity and software to become responsive and data-driven.
  • Edge AI / on-machine intelligence: perception, planning, control and speech recognition executed on the machine to provide low latency and offline capability.
  • Digital twins & AI factories: fleet sensor data is ingested to retrain models and redeploy improvements across fleets.
  • Multimodal AI agents: coordinated agents handling speech, text, images and video to perceive, reason, plan and act.
  • Safety-first design: pairing rapid innovation with stringent reliability, safety and trust controls.

Products, features and demos

Helios

  • Cloud-native, event-driven digital platform unifying data from ~1.5M connected assets.
  • Capabilities: handles thousands of messages/sec, millions of data pipelines/day, and stores >16 PB of reusable, high-quality data.
  • Serves as the foundation for AI, analytics and services.

CAT AI assistant (“Cat”)

  • Multimodal assistant built on Helios and edge compute; presented as a single interface (voice/chat) for operators and technicians.
  • Demonstrated capabilities:
    • Voice/chat queries for fuel efficiency, maintenance schedules, parts lists, utilization and warning light diagnostics.
    • Proactive notifications and recommendations (for example, topping up generator fuel before storms).
    • Field guidance for technicians (walkthroughs, parts provisioning) and in-cab co‑pilot tips for operators.
    • Safety demo: operator sets an overhead “ceiling” (e.g., 13 ft); the machine automatically slows/prevents movement near power lines.
  • Stated to be going live this quarter with in-field application validation underway.

Thor (on-machine platform)

  • NVIDIA-powered on-machine platform that runs advanced models and control logic for robust edge AI in remote or off-grid locations.
  • Designed to support energy-efficient models for imperfect connectivity environments.

Autonomous machine portfolio (construction)

  • Previewed autonomous versions of wheel loader, dozer, haul truck, excavator and compactor.
  • Intended to orchestrate jobsite workflows and improve safety, consistency and productivity.

Autonomous mining

  • Longstanding, proven Level‑4 autonomy deployed for decades in mining.
  • Fleet stats cited: >11 billion tons moved and >385 million km autonomously with no reported injuries.
  • Customer case: Luxstone quarry driverless fleet hauled >2M tons.

Partnerships & enabling technology

  • NVIDIA: collaboration on robotics, edge AI and accelerated computing (NVIDIA Isaac, Jetson, Thor). Focus on running perception/planning/control at the edge and updating models via a central AI factory.
  • Customer collaborations showcased, including Luxstone quarry and an upcoming WM landfill demo at the Caterpillar exhibit.

Deployment, timelines & operational notes

  • CAT AI assistant demoed live and said to be “going live this quarter.”
  • Emphasis on edge-first deployment: on‑machine models and energy-efficient inference for areas with limited connectivity.
  • Strategy centers on integrating hardware and software to improve safety, uptime, productivity and sustainability.

Workforce and social implications

  • Caterpillar announced a $25M commitment for workforce training, education and partnerships to reskill workers for AI/autonomy roles (operators → fleet/site orchestrators, technicians, data scientists).
  • Repeated emphasis that people remain central and that machines are intended to augment roles rather than simply replace workers.

Tutorials and usage guidance highlighted

  • Operator/technician voice command examples (how to ask “Hey Cat” for fuel efficiency, maintenance parts, symptom diagnosis).
  • Walkthrough of setting and enforcing a geofence/ceiling for safety in the cab.
  • Technician guidance: parts lists, repair steps, and scheduling service with a local dealer.

Speakers and sources

  • Gary Shapiro — Executive Chair and CEO, Consumer Technology Association (intro)
  • Joe Creed — CEO, Caterpillar (keynote)
  • Auggie (Auggie) Redzig — Chief Digital Officer, Caterpillar (Helios & CAT AI assistant demo)
  • Jamie Miner — Chief Technology Officer, Caterpillar (autonomy preview)
  • Deepu (Deep Tala) — Vice President, Robotics & Edge AI, NVIDIA (partnership remarks)
  • Mark Perks — Caterpillar booth demonstrator (Cat 306 mini excavator demo)

Rate this summary

Your feedback will help improve summaries.

Improve this summary

Reprocess with a stronger model when the summary feels incomplete or inaccurate.

Pro

Translate summary in another language

Pro

Ask questions to this video

Chat for follow-up questions, clarifications, and source-backed answers.

Coming soon

Share this summary

Original video