Latest Interviews
Showing 1–5 of 5 transcripts.
Clear all filters- Sequoia Capital22 min
Continual Learning: How AI Agents Get Better With Every Use | Arjun Karanam, Trajectory
Arjun Karanam, Ronak, Gabe, Harrison, Nico, Harvey
Trajectory, co-founded by Arjun and Ronak, addresses the lack of accumulated experience in AI by building a platform that enables models to continuously learn from the 100 trillion daily tokens generated by real-world agent interactions. The company utilizes a dual-learning architecture combining differential privacy with reinforcement learning on user-corrected traces, allowing organizations to transition from static models to systems that compound capability through automated post-training and flexible harness optimization. By abstracting complex training parameters into a 15-minute workflow, Trajectory empowers enterprises to retain ownership of their specialized models while refining agent performance directly against production traffic.
- Sequoia Capital27 min
Waymo's Dmitri Dolgov: 20 Million Rides and the Road to Full Autonomy
Dmitri Dolgov, Konstantine Buhler
Dmitry Dolgov, Waymo's co-founder, outlines a 21-year evolution from DARPA challenges to a sixth-generation autonomous fleet that has achieved 200 million fully autonomous miles and delivered over 20 million rides with a safety profile 13 times superior to human drivers. The company's architecture utilizes a multimodal "Foundation Model" integrating physics reasoning and spatial understanding to power a structured, end-to-end system across 11 cities, now accelerating toward global expansion in London and Tokyo through the newly launched Waymo Origin vehicle. This mission-driven approach bypasses incremental improvements to rapidly scale commercial deployment, treating full autonomy as an existential imperative to eliminate the 13 million annual road fatalities while transitioning the core technology into a primary family transportation tool.
- Sequoia Capital20 min
Robotics' End Game: Nvidia's Jim Fan
NVIDIA Robotics is transitioning from language-centric VLA models to World Action Models like Dream Zero, which prioritize learning physical laws through video prediction to enable zero-shot generalization. This architectural shift is supported by a new data collection strategy replacing low-efficiency teleoperation with scalable egocentric video and neural simulators, establishing a log-linear scaling law between training hours and dexterity. Looking toward 2040, Jim Phan projects the industry will achieve a "Physical Turing Test," an orchestration "Physical API" for automated fleets, and "Physical Auto-Research" where robots autonomously improve their own designs.
- Sequoia Capital32 min
OpenAI’s Sam Altman on Building the ‘Core AI Subscription’ for Your Life
Sam Altman, Jens Nordvigsen, DAN GALPIN, SAM SACCONE
OpenAI has evolved from a 14-person research lab into a commercial powerhouse driven by the GPT-3 API and the viral ChatGPT platform, which now serves 500 million weekly active users. Under Sam Altman's leadership, the organization prioritizes high-impact small teams and a vision of becoming a personalized AI operating system while navigating a market where startups outpace legacy enterprises in agility. The company's roadmap emphasizes the transition from text-based assistants to autonomous agents by 2025, with future infrastructure expected to facilitate seamless agent-to-agent communication and eventual robotics applications.
- Sequoia Capital29 min
AI's Trillion-Dollar Opportunity: Sequoia AI Ascent 2025 Keynote
Pat Grady, Sonia, Konstantin Vargas
Sequoia Capital outlines a strategic framework for the AI opportunity, predicting that the sector will disrupt both software and services markets by shifting value from selling tools to selling outcomes. The firm emphasizes investing in companies that demonstrate durable adoption and functional data flywheels, noting that 2024 marked a transition from hype to utility in vertical applications like healthcare and law. Looking ahead, the presentation predicts the emergence of an agent economy where interconnected agents manage resources and tasks, potentially enabling a "one-person unicorn" era through new management strategies.