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Session on Reasoning

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Machine Learning

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Frontier results, on device - RL Nabors, Arize

Frontier results, on device - RL Nabors, Arize

RL Nabors discusses the significant costs associated with using frontier AI models, covering security, latency, and financial implications. She introduces a framework for right-sizing AI solutions by leveraging smaller, task-specific models and Small Language Models (SLMs). The framework details how to prove task feasibility, establish success criteria with golden datasets, conduct capability evaluations (using tools like Phoenix), and select the most appropriate "Small And Good Enough" (SAGE) model. Nabors further demonstrates how prompt engineering, particularly few-shot prompting, and post-processing can close performance gaps with larger models, while advocating for continuous regression evaluations to maintain performance integrity. The overarching message is to "prototype big, deploy small" to optimize AI deployments.

Research to Reality: Bringing Frontier ML Research to Production - Vaidas Razgaitis, Higharc

Research to Reality: Bringing Frontier ML Research to Production - Vaidas Razgaitis, Higharc

Vaidas Razgaitis, Senior Research Engineer at Higharc, shares three tactical tips to accelerate the transition of novel AI/ML research into production-ready features. He emphasizes addressing the critical handoff challenge between ML researchers and software engineers through structured documentation (Research Prototype Taxonomy Document), a well-organized monorepo utilizing decoupled microservices, and a systematic approach to code decomposition and PR review. These strategies aim to improve legibility, maintainability, and delivery speed for ML-driven products.

Uncertainty-Guided Data Augmentation for Engineers | Deep Dive - Yongmin Kwon

Uncertainty-Guided Data Augmentation for Engineers | Deep Dive - Yongmin Kwon

This session details a data-efficient method for training engineering surrogate models by using uncertainty quantification (UQ) to guide geometric data augmentation. Instead of random deformations, the approach lets the deep ensemble model identify its own knowledge gaps (epistemic uncertainty), then uses Free-Form Deformation (FFD) to generate new shapes specifically in those uncertain regions. This ensures every expensive simulation run yields maximally informative data, significantly improving model accuracy for a fixed computational budget across domains like structural mechanics and aerodynamics.

Artificial Intelligence

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Session on Reasoning

Session on Reasoning

This session features two talks on optimizing and verifying AI reasoning. Hongxiang Fan discusses cross-stack co-design for efficient AI, focusing on Test-Time Scaling (TTS) challenges, optimal verification granularity, and system-level optimizations for edge deployments. Nagarajan Natarajan introduces 'Advancing Verified Reasoning' with the InterVent platform, aiming to ensure AI agents comply with complex policies through formal verification, dynamic steering, and leveraging verification signals for training. Both emphasize addressing the computational and reliability costs of advanced AI.

Multimodal & Embodied Intelligence (Pt 1), Panel on Multimodal AI: Progress, Pitfalls, Possibilities

Multimodal & Embodied Intelligence (Pt 1), Panel on Multimodal AI: Progress, Pitfalls, Possibilities

This session explored Multimodal and Embodied Intelligence, featuring talks on hybrid AI in robotics (classical vs. end-to-end), AI's role in healthcare (focusing on NCDs, deployment, and uncertainty modeling), and fundamental perception challenges in multimodal reasoning (using educational video QA and visual puzzles). A panel discussed the impact of foundation models, the blurred lines between AGI and human-like AI, critical deployment pitfalls (human factors, efficiency, architectural limits), and future directions, emphasizing task-specific models and the redefinition of 'foundation models.'

Grant Sanderson (@3blue1brown) – AI and the future of math

Grant Sanderson (@3blue1brown) – AI and the future of math

Grant Sanderson and Dwarkesh Patel discuss AI's rapid but uneven progress in mathematics, exploring whether AI can achieve true conceptual breakthroughs, the challenge of measuring creativity, and the long-term implications for human understanding and the future roles of mathematicians. They delve into the unique 'grindability' of math for AI training, the potential of formalization, and why AI currently struggles with 'theory of mind' in writing, offering advice for students navigating an AI-transformed world.

Technology

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Plenary Talk 3​: Challenges and research opportunities for global hyperscale services

Plenary Talk 3​: Challenges and research opportunities for global hyperscale services

Jim Kleewein's talk outlines the immense challenges and critical research opportunities in building and operating global hyperscale services like Microsoft 365 and Azure. He emphasizes that at this scale, traditional approaches fail, necessitating a "new golden age of applied research" across areas like continuous availability, data management, security, and sustainability. Kleewein also discusses AI's powerful but limited role, stressing the ongoing need for human expertise, and highlights the ethical imperative to prevent failures that can have life-or-death consequences.

Platforms: Build Abstractions, not Illusions • Gregor Hohpe • GOTO 2025

Platforms: Build Abstractions, not Illusions • Gregor Hohpe • GOTO 2025

Gregor Hohpe explains the critical role of platforms in managing the growing cognitive load on developers due to complex distributed systems. He contrasts platforms, driven by "economies of speed" and fostering innovation through diversity, with traditional IT services and oversimplified abstractions that create dangerous illusions. Hohpe emphasizes building platforms that provide intuitive, domain-specific abstractions to solve real business problems, rather than just repackaging existing cloud services.

Full Stack Greenfield Projects : Are they still relevant?

Full Stack Greenfield Projects : Are they still relevant?

Bharat Goenka, co-founder of Tally, discusses the company's unconventional approach to software development through "Full Stack Greenfield" projects. He explains why building every component from scratch, despite being a high-risk strategy, has been crucial for Tally's success in serving the SMB market, fostering extreme customer loyalty, and aspiring to connect 200 million businesses. The talk delves into the historical context, the philosophy of questioning and choosing constraints, and the distinction between product and custom engineering.

Recent Post

The Doctor Is No Longer the Smartest Person in the Room (with Zack Kass)

The Doctor Is No Longer the Smartest Person in the Room (with Zack Kass)

Zack Kass discusses his book, *The Next Renaissance*, emphasizing how abundant AI will reshape human life. He delves into the decreasing correlation between wealth and happiness, attributing it to modern technology, and outlines four principles for thriving in the AI age: "Go Outside," "Learn How to Learn," "Be Human," and "Lead with Optimism." Kass illustrates how AI's cognitive commoditization pushes humanity to value empathy, compassion, and other core human qualities over mere intelligence, using compelling anecdotes from healthcare and personal finance.

Why the Classroom Must Change in the Age of AI (with Zack Kass)

Why the Classroom Must Change in the Age of AI (with Zack Kass)

Zack Kass discusses how AI can revolutionize education through personalized learning, shifting the teacher's role to that of a guide. He outlines key principles from his book, "The Next Renaissance," drawing on the work of educational luminaries Eva Moskowitz, McKenzie Price, and Rudolph Steiner to advocate for a system based on accountability and self-discovery, ultimately aiming to restore the purpose of childhood beyond economic incentives.

Dreamer: the Agent OS for Everyone — David Singleton

Dreamer: the Agent OS for Everyone — David Singleton

David Singleton, former Stripe CTO, introduces Dreamer, an "operating system" for consumer-friendly AI agents. He demos building a conference app in minutes using natural language, and details the platform's architecture, developer ecosystem, and monetization model for tool builders.

Terence Tao – Kepler, Newton, and the true nature of mathematical discovery

Terence Tao – Kepler, Newton, and the true nature of mathematical discovery

Terence Tao uses the story of Kepler's discovery of planetary motion as an analogy for AI's role in science. He argues that AI excels at broad, high-temperature idea generation but requires a robust verification process to be useful. The bottleneck in science is shifting from hypothesis generation to verification and curation, a challenge current scientific structures are not equipped to handle. Tao foresees a future of human-AI collaboration where humans provide deep insights and AI explores the vast breadth of possibilities, ultimately making scientific papers richer but not necessarily deeper.

Inside Palantir: Building Software That Matters | Shyam Sankar on a16z

Inside Palantir: Building Software That Matters | Shyam Sankar on a16z

Shyam Sankar, CTO of Palantir, discusses his book 'Mobilize' and the urgent need for America to inspire its 'latent heretics.' He analyzes the AI-driven SaaS market through the lens of 'alpha versus beta software,' advocates for human agency over automation to re-industrialize, and explains how film and storytelling can rebuild national will.

Andrej Karpathy on Code Agents, AutoResearch, and the Loopy Era of AI

Andrej Karpathy on Code Agents, AutoResearch, and the Loopy Era of AI

Andrej Karpathy discusses the paradigm shift to AI agent-driven development, the future of engineering and research with his AutoResearch project, the impact on jobs, and the evolving landscape of open-source models, robotics, and education.

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