Latest Interviews

Sterling Anderson, Co-Founder, Aurora - MIT Self-Driving Cars

Sterling Anderson, Lex, Wayne Nikola, Luke, Kasha

Aurora, founded by former Tesla Autopilot head Sterling Anderson, has partnered with Volkswagen and Hyundai to deploy a software-centric autonomous platform leveraging deep learning and multi-modal sensors. The company addresses critical forecasting challenges by testing systems that reduced collision rates by 72% while increasing operational speeds in prior research, aiming to exceed human safety standards before scaling. With a core team including ex-Google and ex-Uber experts, Aurora intends to integrate its technology into existing fleets and future vehicle interiors once statistical safety thresholds are met, while proactively planning for workforce transitions in the transportation sector.

The World Through an API

Martin Casado

Andreessen Horowitz General Partner Martin Casado argues that the computing industry is undergoing a final stage of market disaggregation, shifting from bundled software to an economy driven entirely by Application Program Interfaces. This transition lowers barriers to entry for domain experts by codifying complex logic into machine-readable APIs, a shift Ovum data suggests will expand the total addressable market by a factor of ten. Consequently, the investment landscape is pivoting toward three distinct themes: API-first startups that bypass traditional user interfaces, new infrastructure required to secure and manage this distributed layer, and aggregation marketplaces that help developers navigate the proliferation of specialized services.

Sam Altman - Startup Investor School Day 1

Sam Altman, Jeff

Discussions among top angel investors emphasize a power law strategy that targets 100x–1000x returns through "generation-defining" companies, requiring founders to demonstrate obsession, rapid learning, and high integrity over conventional valuation metrics. The event highlights that successful sourcing relies on founder networks and cold outreach rather than herd behavior, while investors must maintain pro-rata rights to avoid dilution in top-quartile follow-on rounds. Ultimately, long-term success depends on prioritizing founders with massive potential over existing market categories, providing deep support during crises to foster the rapid iteration necessary for billion-dollar exits.

Geoff Ralston's Intro - Startup Investor School Day 1

Geoff Ralston

Y Combinator launched its inaugural hybrid Startup Investor School, a four-day program in Mountain View and online that educates accredited and non-accredited investors on startup selection and deal mechanics. The curriculum, delivered by volunteer instructors from the startup ecosystem, concludes with virtual and in-person invitations to Winter 2018 Demo Days for select participants. Additionally, the initiative establishes a crowd-sourced knowledge repository and leverages historical case studies to refine investor decision-making capabilities.

Startup Investor School Day 1 Live Stream

Jeff, Sam Altman, Carolyn Levy, Kirstie

Y Combinator hosted a four-day course for accredited and non-accredited investors, featuring Sam Altman's analysis of the power law and founder evaluation alongside Carolyn Levy and Kirstie Nathoo's technical breakdown of the SAFE instrument. The curriculum emphasized that successful angel investing requires prioritizing massive upside potential over failure rates while navigating conversion mechanics, valuation caps, and pro-rata rights through tools like AngelCalc. Outcomes include a permanent open-source knowledge repository and a cohort of investors equipped to make independent, high-impact decisions on Y Combinator's Winter 2018 startups.

Ben Horowitz on Product Distribution and Sales Channels

Ben Horowitz

Sales channel strategy must align with specific product characteristics and target customer dynamics, as demonstrated by Workday's direct sales force for complex enterprise software and Salesforce's evolution from inside to outside sales as it moved upmarket. Founders should prioritize these functional requirements over personal preferences to avoid critical mismatches, such as attempting to sell a jumbo jet through a retail shoe store. Ultimately, effective distribution relies on matching the sales method to decision-making structures and installation complexities rather than adopting strategies based on founder comfort or peer success.

Stephen Wolfram: Computational Universe | MIT 6.S099: Artificial General Intelligence (AGI)

Stephen Wolfram

The presentation establishes that artificial general intelligence emerges not from mimicking biological brain architecture but by mining the computational universe for sophisticated programs constrained by computational irreducibility. It details how Wolfram Alpha and the Wolfram Language implement this theory by converting human intent into symbolic code to automate algorithmic discovery and manage complex knowledge domains without relying on simplified ethical axioms. Ultimately, the speaker advocates for a paradigm shift in education toward computational thinking, enabling humans to collaborate with systems that solve problems and generate proofs beyond intuitive human capacity.

Shriram Krishnamurthi: Curriculum Design as an Engineering Problem: Lessons from the Field

Shriram Krishnamurthi, Emmanuel Schanzer, Kathi Fisler, Laurie, Askle, James, Shetha, Eric Alata, Kathy, Dharan, Kenny, Yaron, Alice O'Neill, Papert

Bootstrap addresses critical equity and rigor gaps in computer science education by embedding computing concepts directly into mandatory Algebra, Data Science, and Physics curricula rather than relying on scarce specialized teachers or elective courses. This systems-engineering approach utilizes functional programming and a structured "Design Recipe" to scaffold mathematical thinking for all students, successfully mitigating the barriers of after-school programs and traditional silos. Facing scaling challenges due to limited administrative staff and bureaucratic resistance, the organization now prioritizes teacher professional development and is developing middle school modules like Bootstrap Junior to extend this integrated framework to earlier grades.

Sacha Arnoud, Director of Engineering, Waymo - MIT Self-Driving Cars

Sacha Arnoud, Lex

Following its 2017 spin-off from Google, Waymo has accelerated autonomous driving operations by completing over 4 million miles and launching the first public driverless fleet in Phoenix using custom-equipped Chrysler Pacifica vehicles. The company leverages deep learning and Google's TensorFlow infrastructure to process multimodal sensor data from LiDAR, radar, and cameras, enabling robust perception and planning within a closed-loop system of 25,000 simulated cars. Looking forward, Waymo is expanding its operating domain to complex urban environments like San Francisco while refining its technical architecture to prioritize safety and generalization over memorized scenarios.

Ray Kurzweil: Future of Intelligence | MIT 6.S099: Artificial General Intelligence (AGI)

Ray Kurzweil

Futurist and Google Director Ray Kurzweil outlines the convergence of exponential computing, deep learning, and his hierarchical neocortical model to explain the trajectory toward artificial general intelligence and "longevity escape velocity." He details how modern AI systems are evolving from limited pattern recognition to adult-level language comprehension while arguing that automation will drive massive job creation and economic growth rather than permanent unemployment. Despite acknowledging existential risks from advanced biotechnology and AI, Kurzweil maintains that humanity is entering its most peaceful era and will soon merge with technology through brain extenders to transcend biological limitations.

MIT AGI: Building machines that see, learn, and think like people (Josh Tenenbaum)

Josh Tenenbaum

Josh Tenenbaum and the Center for Brains, Minds, and Machines argue that current deep learning systems are limited specialized tools that fail to replicate human general intelligence due to a lack of common sense and world modeling. To achieve true Artificial General Intelligence, the proposal advocates for a reverse-engineering approach that integrates cognitive science with engineering to build probabilistic programs capable of "programming" internal models of physics and psychology. This methodology aims to bridge the gap between industry's data-driven pattern recognition and the foundational, low-data learning mechanisms observed in human infants.

MIT AGI: Artificial General Intelligence

MIT's 6S099 course adopts an engineering-first methodology to construct intelligent systems, explicitly prioritizing mechanistic understanding over speculative futurism to address the critical gap between current AI capabilities and human-level intelligence. The curriculum features a roster of industry and academic leaders, including Andrej Karpathy, Ilya Sutskever, and Josh Tenenbaum, who dissect fundamental challenges in deep learning, cognitive modeling, and biological versus artificial network efficiency. Students actively engage with these themes through rigorous projects such as the "Ethical Car" simulation and "DreamVision," while supplementary sessions explore the legal, ethical, and scientific implications of autonomous weapons, emotion generation, and rapid few-shot learning.

The Autonomy Ecosystem: Finance (5 of 8)

Frank Chen

The transition from private gas-powered vehicles to electric autonomous fleets will redirect capital from consumer markets toward fleet operators, fundamentally shifting insurance and financing models from B2C to B2B structures. Forecasts suggest that while Level 5 autonomy could prevent 95% of accidents and enable fleet self-insurance, it simultaneously threatens to eliminate the $740 billion used car market and disrupt a $14.4 billion annual advertising sector reliant on vehicle sales. Beyond ownership changes, the lifecycle of these vehicles introduces new utility opportunities through battery repurposing for grid storage while recycling raw materials into new manufacturing cycles.

The Autonomy Ecosystem: Public Infrastructure (2 of 8)

Frank Chen

Accelerating transitions to autonomous electric fleets are rendering traditional gasoline tax models obsolete, prompting urgent infrastructure investments and the exploration of new per-ride revenue strategies across the Asia-Pacific region. Simultaneously, urban planners are reimagining city layouts by repurposing vast areas previously dedicated to parking and car corridors into multi-use spaces, leveraging real-time data to optimize traffic flow and reclaiming land for pedestrian and green zones. This shift promises a three-dimensional urban evolution that eliminates vehicle idling, drastically increases lane throughput, and integrates vertical expansion through tunnels and aerial corridors.

The Autonomy Ecosystem: Where and How It Begins (1 of 8)

Frank Chen

In a presentation analyzing the convergence of autonomous driving and electrification, Frank Chen of Andreessen Horowitz argues that fleet economics and rapid battery cost declines will drive a transition from private gas vehicles to shared electric fleets within the next decade. This shift is accelerated by regulatory bans in nations like Norway and the Netherlands, alongside new entrants like Dyson and scaled investments by incumbents such as Daimler, which collectively position 2030 as the inflection point where ride-hailing becomes cheaper than car ownership. Consequently, the event details how these six systemic changes will reshape global infrastructure, energy, and the justice system while re-enfranchising demographics previously excluded from personal mobility.