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Machine Learning

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Guardians of the State: An Air-Gapped AI Fortress for Consumer Data — Rachna Srivastava, DFPI

Guardians of the State: An Air-Gapped AI Fortress for Consumer Data — Rachna Srivastava, DFPI

Rachna Srivastava discusses building a legally defensible AI system for financial fraud detection, emphasizing that generative AI has eroded traditional trust. Her team at DFPI engineered an offline, hardware-secured data pipeline using Kafka, Spark, and semantic routing to ensure explainability, reproducibility, and auditability. They implemented a one-way data diode for secure learning and Apache Iceberg for time-travel queries, asserting that "trust is a physical property" built into the system's core.

Invited Research Talk: Measuring Generalization in EEG Foundation Models

Invited Research Talk: Measuring Generalization in EEG Foundation Models

This talk presents a multi-dimensional evaluation and interpretability framework for EEG foundation models. It reveals that current models often fail to outperform supervised baselines for BCI tasks, lack robustness to sparse channels, and exhibit an aperiodic low-frequency bias, making them better at capturing subject-specific rather than task-specific information. The analysis highlights critical deficiencies and suggests future directions for pre-training objectives and data collection to improve generalization.

Can LLMs Write Fast Multi-GPU Kernels? — Simran Arora, Together AI

Can LLMs Write Fast Multi-GPU Kernels? — Simran Arora, Together AI

Simran Arora discusses the critical bottleneck shift in large AI workloads from GPU compute to inter-GPU communication. Her team's solution, ParallelKittens, offers a set of primitives to optimize multi-GPU kernels by leveraging fundamental transfer mechanisms and compute-communication overlapping. They introduce ParallelKernelBench, a benchmark to evaluate AI models' ability to generate such kernels, revealing that while models can handle syntax, they struggle with deeper reasoning about communication patterns and hardware trade-offs.

Artificial Intelligence

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AI-Native Organisations Run on Skills: How to Structure and Scale Them — Imad Touil, QuantumBlack

AI-Native Organisations Run on Skills: How to Structure and Scale Them — Imad Touil, QuantumBlack

Imad Touil explores the critical need for governing AI skills within organizations, asserting that skills represent the true repository of enterprise know-how. He contrasts simplified coding agent loops with complex, real-world product lifecycles, demonstrating how ungoverned skills lead to technical debt—including duplication, quality degradation, security risks, and lack of discoverability. Proposing a microservices-inspired approach, Touil outlines a centralized skills platform and human-led governance model essential for achieving deterministic workflows, boosting productivity, and mitigating risks in AI-native enterprises.

Your Code Has Bugs. Lean4 Has Proofs: Formal Verification for Engineers — Varun Pant, AWS

Your Code Has Bugs. Lean4 Has Proofs: Formal Verification for Engineers — Varun Pant, AWS

Varun Pant introduces formal verification as the solution to reliably validate AI-generated code, proposing a division where humans define specifications and machines handle code and proof. He details Lean's role as a unified language for code and proof, exemplified by an AI rewriting zlib with 32,000 lines of proof, and AWS's Cedar using Lean specs with Rust production code reconciled by 100 million nightly tests. The talk also covers deductive verification with solvers and future cross-language verification with Strata, aiming for "provably correct" software.

How to Get Your Org to Adopt Coding Agents (Without Shipping Garbage) — Eyal Blum, Figma

How to Get Your Org to Adopt Coding Agents (Without Shipping Garbage) — Eyal Blum, Figma

Figma's internal AI agent adoption journey faces challenges like reduced developer agency, skepticism from senior engineers, and communication inefficiency. Solutions include investing in verification, using a testing pyramid for agent review, prioritizing detailed planning over prompting, engaging skeptics to build AI safety roadmaps, and implementing attention-aware communication by clearly marking AI-generated content.

Technology

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Platform Engineering for Developers, Architects & the Rest of Us • Daniel Bryant • GOTO 2025

Platform Engineering for Developers, Architects & the Rest of Us • Daniel Bryant • GOTO 2025

Daniel Bryant discusses platform engineering for software developers and architects, emphasizing treating platforms as internal products with developers as customers. He outlines a three-layered architecture, the evolution from monolithic systems to microservices, and the importance of 'golden bricks' over 'golden paths' for composability. Key takeaways include API-first design, minimizing cognitive load, avoiding leaky abstractions, and measuring success through frameworks like DORA and DevEx to achieve speed, safety, and scale.

Modern Enterprise Architecture: Architecting for Outcomes • Simon Rohrer • GOTO 2025

Modern Enterprise Architecture: Architecting for Outcomes • Simon Rohrer • GOTO 2025

Simon Rohrer challenges traditional Enterprise Architecture (EA) principles, proposing a modern approach focused on outcomes, continuous evolution, and socio-technical alignment. He outlines five key tenets: Aligning Value, People & Technology; achieving Better Value Sooner, Safer, Happier; implementing Continuous Conversational & Automated Governance; scaling DevOps across the enterprise; and fostering Evolutionary Enterprise Architecture.

Elon's Former Battery Chief on Making Transformers 100x Smaller | Drew Baglino, Heron Power

Elon's Former Battery Chief on Making Transformers 100x Smaller | Drew Baglino, Heron Power

Drew Baglino, former Tesla Powertrain & Energy head and now CEO of Heron Power, reveals why the current electricity grid is inadequate for the explosive growth of AI data centers. He explains how Heron Power's wideband gap power semiconductors will revolutionize grid-to-chip infrastructure, cutting power losses by half, shrinking massive transformers by 100x, and transforming data centers into grid-positive assets for a more efficient and sustainable energy future.


Recent Post

“Engineers are becoming sorcerers” | The future of software development with OpenAI's Sherwin Wu

“Engineers are becoming sorcerers” | The future of software development with OpenAI's Sherwin Wu

Sherwin Wu, head of engineering for OpenAI’s API platform, discusses the radical transformation of software engineering. He shares how 95% of OpenAI engineers use Codex to manage fleets of AI agents, cutting code review times from 15 to 3 minutes. Wu explores the widening productivity gap, the changing role of managers in an AI-first world, and why "models will eat your scaffolding for breakfast", urging developers to build for where AI is going, not where it is today.

After Q-Day: Quantum Applications at Scale • Matthew Keesan • YOW! 2025

After Q-Day: Quantum Applications at Scale • Matthew Keesan • YOW! 2025

Matthew Keesan from IonQ discusses the imminent arrival of "Q-Day"—the moment quantum computers will break current public-key encryption. He explains the fundamentals of quantum computing, including superposition and entanglement, details the hardware roadmap that places this threat within the decade, and explores the promising applications of this new computing paradigm in AI, drug discovery, and materials science, issuing a call to action for software engineers to get involved.

Inference at Scale:Breaking the Memory Wall

Inference at Scale:Breaking the Memory Wall

Sid Sheth, CEO of d-matrix, details their memory-centric approach to AI inference hardware, focusing on their Digital In-Memory Compute (DIMC) architecture. He explains how DIMC, an augmented SRAM technology, minimizes data movement to solve the memory bottleneck, delivering significant gains in latency and energy efficiency, particularly for the 'decode' phase of large language models.

Rivian’s Roadmap to AI Architecture and Autonomy with Founder and CEO RJ Scaringe

Rivian’s Roadmap to AI Architecture and Autonomy with Founder and CEO RJ Scaringe

Rivian CEO RJ Scaringe discusses the company's complete pivot from a rules-based '1.0' autonomy system to a vertically integrated, neural network-based architecture. He outlines the essential ingredients for success in autonomous driving—from custom inference chips to a robust data flywheel—and explains why a software-defined vehicle architecture is non-negotiable for survival. Scaringe also touches on the upcoming R2 model, the importance of market choice, and how superior, proprietary data will be the key differentiator in the age of AI-driven vehicles.

Security & DevEx: Can We Have Both? • Abby Bangser, Adrian Mouat & Holly Cummins • GOTO 2025

Security & DevEx: Can We Have Both? • Abby Bangser, Adrian Mouat & Holly Cummins • GOTO 2025

In this panel discussion, Holly Cummins, Abby Bangser, and Adrian Mouat explore the inherent conflict between security and developer experience. They argue that traditional security, often driven by fear and restrictive policies, can lead to 'Shadow IT' and greater insecurity. The solution proposed is a platform engineering approach, which centralizes security expertise to provide secure defaults, infrastructure guardrails, and a clear shared responsibility model, thus enabling development teams to deliver value quickly and safely without needing to become security experts themselves.

OpenClaw and Claude Opus 4.6: Where is AI agent security headed?

OpenClaw and Claude Opus 4.6: Where is AI agent security headed?

A panel of cybersecurity experts discusses the security risks of the rapid adoption of AI agents, the "move fast and break things" development culture, the lessons from the Notepad++ supply chain breach, and the professionalization of ransomware by groups like DragonForce.

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