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Machine Learning

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Anaximander: Interactive Orchestration and Evaluation of Geospatial Foundation Models

Anaximander: Interactive Orchestration and Evaluation of Geospatial Foundation Models

This talk introduces Anaximander, a system designed to bridge the gap between traditional, GUI-driven Geographic Information System (GIS) workflows and modern, code-heavy machine learning practices. Anaximander integrates geospatial foundation models directly into QGIS, allowing experts to interactively orchestrate, run, and evaluate models for tasks like semantic segmentation and object detection on satellite imagery.

Efficient Reinforcement Learning – Rhythm Garg & Linden Li, Applied Compute

Efficient Reinforcement Learning – Rhythm Garg & Linden Li, Applied Compute

At Applied Compute, efficient Reinforcement Learning is critical for delivering business value. This talk explores the transition from inefficient synchronous RL to a high-throughput asynchronous 'Pipeline RL' system. The core challenge is managing 'staleness'—a side effect of in-flight weight updates that can destabilize training. The speakers detail their first-principles systems model, based on the Roofline model, used to simulate and find the optimal allocation of GPU resources between sampling and training, balancing throughput with algorithmic stability and achieving significant speedups.

The GPU Uptime Battle

The GPU Uptime Battle

Andy Pernsteiner, Field CTO of VAST Data, discusses the immense challenges of transitioning AI projects from prototype to production. He highlights the critical role of data infrastructure, the high cost of GPU downtime, and the necessity of building resilient, scalable platforms that can withstand real-world failures like power outages in massive data centers. The conversation emphasizes a shift in mindset towards empathy, better requirement gathering, and closer collaboration between data scientists and platform engineers to bridge the gap between development and operations.

Artificial Intelligence

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Building durable Agents with Workflow DevKit & AI SDK - Peter Wielander, Vercel

Building durable Agents with Workflow DevKit & AI SDK - Peter Wielander, Vercel

Learn how Vercel's open-source Workflows platform simplifies deploying durable, observable, and long-running AI agents by abstracting away the infrastructure complexities of queues, databases, and error handling.

Why humans are AI's biggest bottleneck (and what's coming in 2026) | Alexander Embiricos (OpenAI)

Why humans are AI's biggest bottleneck (and what's coming in 2026) | Alexander Embiricos (OpenAI)

Alexander Embiricos, product lead for OpenAI's Codex, discusses the vision of AI as a proactive software engineering teammate, the product decisions that led to its explosive 20x growth, and why the real bottleneck to AGI-level productivity is shifting from model capability to human review speed.

Why humans are AI's biggest bottleneck (and what's coming in 2026) | Alexander Embiricos (OpenAI)

Why humans are AI's biggest bottleneck (and what's coming in 2026) | Alexander Embiricos (OpenAI)

Alexander Embiricos, product lead for OpenAI's Codex, discusses the vision of AI as a proactive software engineering teammate, not just a tool. He covers the product decisions that led to Codex's 20x growth, how it enabled shipping the Sora Android app in 18 days, and why the real bottleneck to AGI-level productivity is shifting from model capability to human review speed and interaction.

Technology

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Mental models for building products people love ft. Stewart Butterfield

Mental models for building products people love ft. Stewart Butterfield

Stewart Butterfield, co-founder of Slack and Flickr, shares the product frameworks and leadership principles that guided his success. He delves into concepts like "utility curves" for feature investment, the "owner's delusion" in product design, and why focusing on "comprehension" is often more important than reducing friction. He also introduces powerful mental models for organizational effectiveness, such as combating "hyper-realistic work-like activities" and applying Parkinson's Law to team growth.

Intuit CEO Sasan Goodarzi’s Grown-Up CEO Playbook

Intuit CEO Sasan Goodarzi’s Grown-Up CEO Playbook

Intuit CEO Sasan Goodarzi discusses the operational playbook for reinventing a 40-year-old company, from its slow transition to SaaS to its early adoption of AI. He shares insights on winning the SMB market by treating small businesses like consumers, building effective channel partnerships, and developing a platform strategy. Goodarzi also details his leadership philosophy, emphasizing that grit and curiosity are more critical than raw talent.

From Hardware Hacker to CTO: Building Teams That Scale • Meri Williams & Charles Humble

From Hardware Hacker to CTO: Building Teams That Scale • Meri Williams & Charles Humble

Experienced CTO Meri Williams shares hard-won insights on scaling technology teams, moving from a reluctant manager to a seasoned leader. The discussion covers practical wisdom on avoiding the 'Google trap' of inappropriately copying big tech, the high-leverage impact of investing in onboarding, and the critical importance of diversity in building products that serve everyone.


Recent Post

The Mathematical Foundations of Intelligence [Professor Yi Ma]

The Mathematical Foundations of Intelligence [Professor Yi Ma]

Professor Yi Ma presents a unified mathematical theory of intelligence built on two principles: parsimony and self-consistency. He challenges the notion that large language models (LLMs) understand, arguing they are sophisticated memorization systems, and demonstrates how architectures like the Transformer can be derived from the first principle of compression.

The Mathematical Foundations of Intelligence [Professor Yi Ma]

The Mathematical Foundations of Intelligence [Professor Yi Ma]

Professor Yi Ma presents a unified mathematical theory of intelligence based on two principles: Parsimony and Self-Consistency. He argues that current AI, particularly LLMs, excels at memorization by compressing already-compressed human knowledge (text), but fails at true abstraction and understanding. His framework, centered on maximizing the coding rate reduction of data, provides a first-principles derivation for architectures like Transformers (CRATE) and explains phenomena like the effectiveness of gradient descent through the concept of benign non-convex landscapes.

The arrival of AGI | Shane Legg (co-founder of DeepMind)

The arrival of AGI | Shane Legg (co-founder of DeepMind)

Shane Legg, Chief AGI Scientist at Google DeepMind, outlines his framework for AGI, predicting 'minimal AGI' within years and 'full AGI' within a decade. He details a path to more reliable systems and introduces 'System 2 Safety' for building ethical AI. Legg issues an urgent call for society to prepare for the massive economic and structural transformations that advanced AI will inevitably bring.

The arrival of AGI | Shane Legg (co-founder of DeepMind)

The arrival of AGI | Shane Legg (co-founder of DeepMind)

Shane Legg, Chief AGI Scientist at Google DeepMind, outlines his framework for AGI levels, predicts a 50% chance of minimal AGI by 2028, and discusses the profound societal and economic transformations that will follow.

Efficient Reinforcement Learning – Rhythm Garg & Linden Li, Applied Compute

Efficient Reinforcement Learning – Rhythm Garg & Linden Li, Applied Compute

At Applied Compute, efficient Reinforcement Learning is critical for delivering business value. This talk explores the transition from inefficient synchronous RL to a high-throughput asynchronous 'Pipeline RL' system. The core challenge is managing 'staleness'—a side effect of in-flight weight updates that can destabilize training. The speakers detail their first-principles systems model, based on the Roofline model, used to simulate and find the optimal allocation of GPU resources between sampling and training, balancing throughput with algorithmic stability and achieving significant speedups.

Efficient Reinforcement Learning – Rhythm Garg & Linden Li, Applied Compute

Efficient Reinforcement Learning – Rhythm Garg & Linden Li, Applied Compute

A deep dive into the challenges and solutions for efficient Reinforcement Learning (RL) in enterprise settings. The talk contrasts synchronous and asynchronous RL, explains the critical trade-off of "staleness" versus stability, and details a first-principles system model used to optimize GPU allocation for maximum throughput.

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