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GPT-5.6 Sol, FIFA AI & Wall Street’s AI nerves

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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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GPT-5.6 Sol, FIFA AI & Wall Street’s AI nerves

GPT-5.6 Sol, FIFA AI & Wall Street’s AI nerves

OpenAI's new GPT-5.6 Sol model sparks debate on AI safety and release strategies, while Wall Street expresses growing skepticism over the long-term economics of frontier AI models. The discussion also touches on AI's impact on the FIFA World Cup and a thought-provoking paper comparing LLM anthropomorphism to Age of Empires II "goats."

The Prompt Is Still a Punch Card - Ted Johnson, JoinIn AI

The Prompt Is Still a Punch Card - Ted Johnson, JoinIn AI

Ted Johnson argues that current AI interfaces, particularly prompting, operate on an outdated "batch processing" protocol akin to punch cards. Despite advanced LLM capabilities, this interface design forces humans to adapt to machines, hindering natural interaction. He advocates for a shift towards human-compatible interfaces where AI actively participates in real-time conversation, leveraging its intelligence to remove user burdens and amplify human potential.

How Nuclear Will Unlock Energy Abundance with Valar Atomics Founder Isaiah Taylor

How Nuclear Will Unlock Energy Abundance with Valar Atomics Founder Isaiah Taylor

Valar Atomics founder Isaiah Taylor discusses how his company is rapidly advancing nuclear energy through hardware iteration, manufacturing, and a unique regulatory pathway. He explains their intrinsic safety philosophy, the strategic importance of vertical integration for speed and cost reduction, and their venture-backed approach to building gigasites. Taylor highlights how the demand for AI compute is a major driver for nuclear, showcasing their direct powering of an NVIDIA Blackwell chip, and casts a compelling vision for a future of "hyper-technoindustrialism" enabled by abundant, cheap atomic energy.

Technology

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Are Your Tests Slowing You Down? • Trisha Gee • GOTO 2025

Are Your Tests Slowing You Down? • Trisha Gee • GOTO 2025

Trisha Gee delivers a compelling talk on Developer Productivity Engineering (DPE) for testing, dissecting common pain points in writing, troubleshooting, and running tests. She advocates for strategic use of IDEs, advanced tooling like build caches and predictive test selection (leveraging ML), and a disciplined approach to test design to overcome these challenges, emphasizing that good tests serve as crucial living documentation.

The new post-quantum cryptography executive order. Plus: What is Q-Day, really?

The new post-quantum cryptography executive order. Plus: What is Q-Day, really?

This episode delves into Q-Day, the anticipated future when quantum computers can break public key cryptography, and the U.S. Executive Order accelerating the transition to post-quantum cryptography. Experts discuss why Q-Day is a gradual process rather than a sudden event, the critical importance of "crypto-agility" as a long-term strategy, and the necessity for organizations to begin immediate discovery and planning to secure data against "collect now, decrypt later" threats. The discussion also touches upon the broader, transformative benefits of quantum computing beyond just security.

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.

Recent Post

Enterprise AI Operations: The Missing Piece

Enterprise AI Operations: The Missing Piece

Rani Radhakrishnan, Principal at PwC, discusses the convergence of MLOps and IT operations, the practicalities of deploying AI agents, and the strategic considerations for scaling and sustaining AI initiatives in the enterprise. The conversation covers the shift from experimentation to ROI, the importance of human-in-the-loop processes, and the evolving skillsets required for future-ready IT.

Accelerating Growth Through Optimizing GPU Usage // Sahil Khanna // AI in Production 2025

Accelerating Growth Through Optimizing GPU Usage // Sahil Khanna // AI in Production 2025

Adobe's journey in building a sophisticated AI Compute Platform to tackle the immense challenges of GPU optimization for training large-scale generative models like Firefly. The talk covers their custom-built solutions for resource management, developer productivity, and automated fault tolerance.

Post-training best-in-class models in 2025

Post-training best-in-class models in 2025

An expert overview of post-training techniques for language models, covering the entire workflow from data generation and curation to advanced algorithms like Supervised Fine-Tuning (SFT), Direct Preference Optimization (DPO), and Reinforcement Learning (RL), along with practical advice on evaluation and iteration.

Automating Large Scale Refactors with Parallel Agents - Robert Brennan, AllHands

Automating Large Scale Refactors with Parallel Agents - Robert Brennan, AllHands

A deep dive into orchestrating swarms of AI agents for large-scale code refactoring. Learn practical workflows, task decomposition strategies, and context-sharing patterns, demonstrated with a real-world case study on migrating a large codebase.

Hacking AI Systems: How to (Still) Trick Artificial Intelligence • Katharine Jarmul • GOTO 2025

Hacking AI Systems: How to (Still) Trick Artificial Intelligence • Katharine Jarmul • GOTO 2025

To build secure AI systems, we must first learn to break them. Katharine Jarmul explores the landscape of adversarial AI, detailing how attackers exploit fundamental weaknesses in deep learning models—from poisoned training data and overparameterization to the attention mechanism itself. This talk provides a practical taxonomy of attacks and a primer on building robust defenses.

The End of the Junior Data Engineer?

The End of the Junior Data Engineer?

Matthew Glickman, CEO of Genesis Computing, discusses the rise of AI data agents designed to automate complex data engineering workflows. He covers the "last 10%" problem in enterprise AI, the unique value of targeting the data engineer persona, and how these agents can tackle challenges like legacy system migration and knowledge capture, ultimately giving valuable time back to data teams.

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