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

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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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The Benchmark With No Instructions — Tufa Labs (ARC-AGI-3)

The Benchmark With No Instructions — Tufa Labs (ARC-AGI-3)

Tim Scarfe visits Tufa Labs to explore their top-ranking ARC-AGI-3 system, a benchmark for agentic intelligence that challenges LLMs in goal discovery and action efficiency. The team delves into the complexities of fractured representations, the role of human priors, and whether LLMs truly plan or merely simulate it effectively, all while balancing the bitter lesson with AI safety concerns.

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.'

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

Mainframe modernization explained: COBOL and AI

Mainframe modernization explained: COBOL and AI

Experts from IBM discuss the nuanced role of AI in mainframe modernization, the immense infrastructural and product challenges behind global AI adoption, and the critical need for a multi-layered, security-by-design framework for the safe deployment of AI agents.

Dylan Patel Explains the AI War While Cooking | In-Context Cooking

Dylan Patel Explains the AI War While Cooking | In-Context Cooking

Dylan Patel of SemiAnalysis discusses the AI arms race, highlighting the massive $200B+ hyperscaler capex, the true semiconductor bottlenecks shifting from data centers back to fabs, the geopolitical chess game surrounding Taiwan and TSMC, and Nvidia's strategic battle against vertical integration.

Hardware Realization and Implementation Security Evaluation of HQC, A NIST PQC Standard

Hardware Realization and Implementation Security Evaluation of HQC, A NIST PQC Standard

This talk by Sanjay Deshpande from Northwestern University explores the critical transition to Post-Quantum Cryptography (PQC) in response to the threat quantum computers pose to current public-key algorithms. It provides a deep dive into the Hamming Quasi-Cyclic (HQC) algorithm, a code-based candidate for NIST standardization. The session focuses on the challenges and innovations in creating efficient and secure hardware implementations of HQC, covering performance optimization for polynomial multiplication and countermeasures against side-channel attacks.

GeoMind: A Multi-Agent Framework for Geospatial Decision Support

GeoMind: A Multi-Agent Framework for Geospatial Decision Support

GeoMind is a multi-agent framework designed to empower non-technical users, such as disaster responders, to perform complex geospatial analysis using natural language. It bridges the gap between Large Language Models and advanced GIS workflows by employing a team of specialized AI agents that can query, join, and analyze multi-layered vector and raster data to provide timely, actionable insights during emergencies.

AI is critical for humanity’s survival: Cisco President on the AI revolution | Jeetu Patel

AI is critical for humanity’s survival: Cisco President on the AI revolution | Jeetu Patel

Jeetu Patel, President and CPO at Cisco, shares his frameworks for transforming a 90,000-person company to be AI-first, building great companies, and leading at scale. He discusses Cisco's critical role in the AI infrastructure buildout, the necessity of AI for humanity's future, and his counterintuitive principles on communication and strategy.

Learn Docker in a Month of Lunches • Elton Stoneman & Bret Fisher • GOTO 2026

Learn Docker in a Month of Lunches • Elton Stoneman & Bret Fisher • GOTO 2026

Docker educators Bret Fisher and Elton Stoneman discuss the second edition of Stoneman's book, "Learn Docker in a Month of Lunches". They explore why Docker fundamentals remain crucial in a Kubernetes-dominated world, the evolution of the container ecosystem over the past five years, and the key skills that differentiate a Docker expert from a beginner, such as multi-platform builds, security, and configuration management.

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