Artists of Intelligence with Harpreet Sahota

Harpreet Sahota

Deep technical conversations on physical AI, robotics, AI agents, and developer craft with Harpreet Sahota.

  1. 06/12/2024

    Abi Aryan — The Death of Feature Stores: Where MLOps Fails for LLMs and Autonomous Agents

    Abi Aryan (Author of LLMOps with O'Reilly) analyzes the architectural divergence between classical MLOps and LLMOps: why feature engineering has shifted downstream, the limitations of non-deterministic models in production, and how to structure AI engineering teams.

    Abi Aryan — The Death of Feature Stores: Where MLOps Fails for LLMs and Autonomous Agents

  2. 06/12/2024

    Dr. Tristan Behrens — Symbolic AI, Transformers, and Why Autoregressive Music Cannot Tell a Story

    Dr. Tristan Behrens explains the mechanics of generative audio intelligence: tokenizing symbolic MIDI data into autoregressive sequences, training GPT architectures on music corpora, and the fundamental limitations of sequence models in global narrative structure.

    Dr. Tristan Behrens — Symbolic AI, Transformers, and Why Autoregressive Music Cannot Tell a Story

  3. 06/12/2024

    Glenn Jocher — From Particle Physics to YOLOv8: Decoupled Heads, Anchor-Free Detection, and Real-Time Inference

    Glenn Jocher (Founder of Ultralytics and creator of YOLOv5/YOLOv8) discusses the evolution of real-time computer vision: moving from two-stage architectures to anchor-free detection, optimizing loss functions, and balancing accuracy against low-level edge hardware constraints.

    Glenn Jocher — From Particle Physics to YOLOv8: Decoupled Heads, Anchor-Free Detection, and Real-Time Inference

  4. 06/12/2024

    Josh Tobin — You Are Monitoring Your Models Wrong: Data Drift, Foundation Models, and Production Feedback Loops

    Josh Tobin (Founder & CEO of Gantry, ex-OpenAI) explains why classical statistical drift detection creates alert fatigue, how model development differs in production, and why rapid iteration and feedback loops outperform pre-deployment modeling perfection.

    Josh Tobin — You Are Monitoring Your Models Wrong: Data Drift, Foundation Models, and Production Feedback Loops

  5. 06/12/2024

    Kausthub Krishnamurthy — Closed vs. Open World Robotics: When Cloud MLOps Collides with Hardware Constraints

    Kausthub Krishnamurthy (Senior ML Engineer at Nearmap) analyzes the systems gap between web-scale software and physical robotics: closed vs. open-world operational spaces, strict latency and power budgets, and why simulation-driven development is necessary.

    Kausthub Krishnamurthy — Closed vs. Open World Robotics: When Cloud MLOps Collides with Hardware Constraints

  6. 06/12/2024

    Kyle Kranen — Why Message Passing Breaks at Scale (and How GNNs Actually Run in Production)

    Kyle Kranen (Senior Deep Learning Engineer at NVIDIA) details the computational reality of Graph Neural Networks: sparse matrix multiplication, exponential neighborhood expansion, and why production pipelines decouple graph embeddings from downstream inference models.

    Kyle Kranen — Why Message Passing Breaks at Scale (and How GNNs Actually Run in Production)

  7. 06/17/2022

    Dr. Lara Pence — The Friction of High Performance: Managing Psychological Strain in Technical Work

    Clinical psychologist Dr. Lara Pence explores the emotional architecture of builders: managing cognitive friction, dismantling the perfectionism trap, and building resilience in high-stakes, ambiguous engineering environments.

    Dr. Lara Pence — The Friction of High Performance: Managing Psychological Strain in Technical Work

  8. 06/10/2022

    Jonathan Javier & Jerry Lee — Deconstructing Tech Hiring: Algorithmic Filters, Referral Mechanics, and Candidate Asymmetries

    Wonsulting founders Jonathan Javier and Jerry Lee break down the quantitative realities of the technology hiring funnel: bypassing ATS keyword filters, reversing recruiter search indexing, and building defensible career leverage.

    Jonathan Javier & Jerry Lee — Deconstructing Tech Hiring: Algorithmic Filters, Referral Mechanics, and Candidate Asymmetries
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Deep technical conversations on physical AI, robotics, AI agents, and developer craft with Harpreet Sahota.

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