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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

Speed and Scale: How Today's AI Datacenters Are Operating Through Hypergrowth

Speed and Scale: How Today's AI Datacenters Are Operating Through Hypergrowth

Kris Beevers, CEO of NetBox Labs, explores the hypergrowth in AI infrastructure, detailing how teams are compressing the design, build, and deployment cycle from years to months. The discussion covers the primary bottlenecks like power and logistics, the critical need for intent-driven automation, and the role of a standardized data model in managing the immense complexity from physical cabling to logical configuration.

Handling AI-Generated Code: Challenges & Best Practices • Roman Zhukov & Damian Brady

Handling AI-Generated Code: Challenges & Best Practices • Roman Zhukov & Damian Brady

Roman Zhukov (Red Hat) and Damian Brady (GitHub) explore the evolving landscape of AI-assisted software development, discussing its impact on developer workflows, code quality, security, and the future of developer roles. They emphasize that while AI tools are powerful amplifiers, human oversight remains essential for quality, security, and legal compliance.

Building the GitHub for RL Environments: Prime Intellect's Will Brown & Johannes Hagemann

Building the GitHub for RL Environments: Prime Intellect's Will Brown & Johannes Hagemann

Prime Intellect's Will Brown and Johannes Hagemann discuss the paradigm shift from static prompting to dynamic, environment-based AI development. They introduce their Environments Hub, a platform aimed at democratizing frontier-level training and enabling companies to build specialized models by compounding institutional knowledge.

From PhD Side Project to $500M ARR: Will Falcon’s PyTorch Lightning Story

From PhD Side Project to $500M ARR: Will Falcon’s PyTorch Lightning Story

Will Falcon, CEO of Lightning AI, discusses the company's merger with Voltage Park to create a full-stack AI neo-cloud. He delves into the capabilities of Lightning AI Studio, a comprehensive platform for AI development, and recounts the origin story of PyTorch Lightning, from a personal research tool to a world-leading open-source framework.

Securing AI Agents with Zero Trust

Securing AI Agents with Zero Trust

This post explores how to secure modern agentic AI systems by applying the core principles of Zero Trust. It details the unique attack surfaces of AI agents, such as prompt injection and model poisoning, and outlines a comprehensive security architecture including non-human identity management, AI firewalls, and the critical role of human oversight.

Episode 13 - The Thinking Behind Ads in ChatGPT

Episode 13 - The Thinking Behind Ads in ChatGPT

Asad Awan from OpenAI details the company's principled approach to introducing ads in ChatGPT. He explains how user trust, privacy, and control are prioritized, ensuring a strict separation between model answers and advertisements, and outlines a future where AI simplifies advertising for businesses.

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