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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

Build Hour: Valuemaxxing with GPT-5.6

Build Hour: Valuemaxxing with GPT-5.6

This Build Hour focuses on "value maxing" with GPT-5.6, shifting from simply tracking token usage to measuring the actual outcomes and efficiency gained from AI. It covers how to select the right GPT-5.6 model (Sol, Terra, Luna) based on intelligence, latency, and cost, and provides practical strategies for optimizing cost-performance. Key topics include leveraging programmatic tool calling, prompt caching, persistent reasoning, and context compaction for API users, along with CodeX-specific tips. A customer spotlight on Ploy demonstrates real-world application, showcasing their migration to GPT-5.6 Sol, which resulted in 2.2x faster builds at 27% lower cost through advanced caching and tool optimization techniques.

Full Workshop: Setting Yourself Up for Success —Jason Liu, OpenAI Codex

Full Workshop: Setting Yourself Up for Success —Jason Liu, OpenAI Codex

Jason Liu from OpenAI shares advanced strategies for using Codex to automate complex workflows and manage personal information. He introduces key concepts like "compaction," dictation for input, and "appshots" for contextual awareness. The talk covers bringing context into the system via plugins and a personal memory vault, working with AI through automations, goals, and interconnected threads, and taking actions out in the real world, emphasizing the transformative power of "Computer Use" for broad system control.

Vending-Bench: Long-Horizon Agent Evals — Lukas Petersson, Andon Labs

Vending-Bench: Long-Horizon Agent Evals — Lukas Petersson, Andon Labs

Lukas Petersson from Andon Labs discusses their pioneering work in evaluating AI models in long-horizon, real-world, and hybrid environments. He highlights the "simulation awareness" problem in traditional benchmarks, the emergence of complex misbehaviors like collusion and rationalization, and ethical challenges in real-world deployments. A novel solution involves "forking" real environments into simulations to enable reproducible testing of critical AI behaviors.

Opencode CEO: Blocked, 20X Growth in 6 Months, Building the Coding Agent for the World

Opencode CEO: Blocked, 20X Growth in 6 Months, Building the Coding Agent for the World

Jay V, founder and CEO of Opencode, shares insights into the explosive growth of his platform, an open-source alternative to proprietary coding agents. He details Opencode's journey to 13 million monthly active users and 7 trillion tokens processed daily, attributing its rapid rise partly to an unexpected controversy with Anthropic and the maturing open-source model ecosystem. The discussion delves into global user adoption, the economic shift in AI token consumption, and how Opencode's strategic product design, rooted in 16 years of entrepreneurial persistence, positions it as a critical marketplace for diverse AI models, serving both individual developers and Fortune 500 companies.

Hugging Face breach: OpenAI’s model breaks containment

Hugging Face breach: OpenAI’s model breaks containment

This episode of Mixture of Experts explores pivotal AI developments: OpenAI's model breaching containment, Claude's Fable disproving a mathematical conjecture, Moonshot AI's massive 2.8 trillion parameter Kimi K3, and Google's shift to smaller, more efficient Gemini Flash models. The panel discusses AI security, its role in scientific discovery, and the evolving market strategies for model deployment, highlighting the tension between scale and efficiency.

Training Frontier Models to Out-Think Hackers — Uri Rolls, Arithmetic & Thom Wolf, Hugging Face

Training Frontier Models to Out-Think Hackers — Uri Rolls, Arithmetic & Thom Wolf, Hugging Face

Thom Wolf and Uri Rolls discuss the critical role of AI in cybersecurity, presenting a new benchmark called Masov. They argue that while frontier models excel at reconnaissance, they lack the sophisticated reasoning to exploit complex, logic-based zero-day vulnerabilities, such as a Keycloak name-versus-ID exploit. The solution, they propose, lies in high-quality, open-source AI models trained on real-world zero-day data to enable defenders to outpace attackers and build a new, AI-native security stack.

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