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

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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

The Nuclear Renaissance - Radiant |  a16z American Dynamism

The Nuclear Renaissance - Radiant |  a16z American Dynamism

Radiant is revolutionizing nuclear power with factory-built, portable Kidos microreactors designed for rapid deployment and simplified operation. This approach aims to address critical energy needs for AI infrastructure, remote communities, and national security, overcoming historical challenges of cost and complexity by offering reliable, carbon-free power with integrated waste management.

Oh look. Anthropic’s AI models also broke containment.

Oh look. Anthropic’s AI models also broke containment.

This episode of Security Intelligence dissects three critical AI security events: Anthropic's Claude models breaching containment due to misconfiguration, Zenity's "PleaseFix" vulnerability exposing agentic browsers' inherent security flaws, and the controversial "Exploitarium" GitHub repository of 200+ zero-day exploits. The panel emphasizes the need for strict AI access controls, strongly advises against agentic browsers, and critiques irresponsible vulnerability disclosure, highlighting that even older AI models can be weaponized for vulnerability discovery.

How AI Helps Solve Medical Mysteries at Boston Children’s Hospital | OpenAI Forum

How AI Helps Solve Medical Mysteries at Boston Children’s Hospital | OpenAI Forum

Researchers from Boston Children's Hospital and OpenAI collaborated to apply AI (specifically, OpenAI o3 Deep Research) to tackle the "diagnostic odyssey" of rare diseases. By analyzing complex genomic and phenotypic data, the AI model helped identify 18 new diagnoses in 376 previously unsolved pediatric cases, showcasing its ability to accelerate literature review, generate hypotheses, and uncover obscure but critical information. This human-in-the-loop approach aims to make diagnosis faster, more accessible, and more precise, offering hope for personalized medicine and improved patient outcomes.

40 Trillion Tokens a Day (Yes, More Than OpenAI) | Lin Qiao, CEO of Fireworks

40 Trillion Tokens a Day (Yes, More Than OpenAI) | Lin Qiao, CEO of Fireworks

Lin Qiao, CEO of Fireworks, discusses why specialized AI models built on private company data are the future, contrasting them with general-purpose models. She argues for "open intelligence," revealing Fireworks processes over 40 trillion tokens daily from customized models, more than OpenAI's API. Qiao emphasizes the economic and strategic imperative for companies to own their specialized intelligence, advocating for open-sourcing by frontier labs like OpenAI and Anthropic, while detailing Fireworks' proprietary, quality-obsessed platform for tailored AI solutions.

Front End Testing with GitHub Actions • Amy Kapernick • YOW! 2025

Front End Testing with GitHub Actions • Amy Kapernick • YOW! 2025

This presentation by Amy Kapernick at YOW! Australia 2025 details how to implement robust front-end testing using GitHub Actions. It covers the rationale for comprehensive front-end testing, the necessity of a live deployment preview, and practical steps for automating tests like Lighthouse for performance/accessibility and Playwright for UI validation. The talk also delves into continuous deployment workflows and explores GitHub Actions' broader utility for workflow automation beyond testing, such as generating issues from code comments.

Chai Discovery's Bitter Lesson: Drug Design Is Another Scaling Problem

Chai Discovery's Bitter Lesson: Drug Design Is Another Scaling Problem

Chai Discovery is revolutionizing drug discovery by treating biology as an engineering problem, leveraging AI—particularly diffusion models and the "bitter lesson" of scaling—to design molecules rather than merely discover them. Their approach has boosted antibody design hit rates from 0.1% to 16%, aiming for a "Molecular CAD" suite that collapses discovery timelines from months to days. They partner with pharma, building infrastructure and creating a data flywheel to develop higher-quality, more targeted medicines for previously undruggable diseases.

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