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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

Chelsea Finn: Building Robots That Can Do Anything

Chelsea Finn: Building Robots That Can Do Anything

Developing general-purpose robots requires a shift from specialized, single-task systems to broad foundation models. This is achieved through a combination of large-scale, diverse, real-world data collection and a specific training methodology: pre-training on all available data and then fine-tuning on a curated, high-quality subset of demonstrations. This recipe, combined with architectural innovations to preserve the capabilities of Vision-Language Model (VLM) backbones, enables robots to perform complex, long-horizon tasks, generalize to unseen environments, and respond to open-ended human instructions.

907: Neuroscience, AI and the Limitations of LLMs — with Dr. Zohar Bronfman

907: Neuroscience, AI and the Limitations of LLMs — with Dr. Zohar Bronfman

Zohar Bronfman discusses why current LLMs are not on a path to AGI, contrasting their combinatorial creativity with the transformational, domain-general intelligence of humans. He argues that predictive models, not generative ones, deliver the most business value and explains how his platform, Pecan AI, automates the critical data preparation bottleneck to democratize predictive analytics for all businesses.

OpenAI Just Released ChatGPT Agent, Its Most Powerful Agent Yet

OpenAI Just Released ChatGPT Agent, Its Most Powerful Agent Yet

The OpenAI team details the creation of a new, powerful AI agent in ChatGPT, achieved by unifying the Deep Research and Operator models. They cover its unified architecture with shared state across tools, the reinforcement learning techniques used for training, and the critical safety measures required for an agent that can take real-world actions.

The Future of Software Development - Vibe Coding, Prompt Engineering & AI Assistants

The Future of Software Development - Vibe Coding, Prompt Engineering & AI Assistants

A discussion on the state of technical infrastructure, focusing on how AI and Large Language Models represent a new, fourth foundational pillar alongside compute, network, and storage. The talk covers how AI is disrupting software itself, the investment landscape, and the future of the developer profession.

Intern talk: Distilling Self-Supervised-Learning-Based Speech Quality Assessment into Compact Models

Intern talk: Distilling Self-Supervised-Learning-Based Speech Quality Assessment into Compact Models

This research explores the distillation and pruning of large, self-supervised speech quality assessment models into compact and efficient versions. Starting with the high-performing but large XLSR-SQA model, the work details a process of knowledge distillation using a teacher-student framework with a diverse, on-the-fly generated dataset. The resulting compact models successfully close over half the performance gap to the teacher, making them suitable for on-device and production applications where model size is a critical constraint.

Anthropic co-founder: AGI predictions, leaving OpenAI, what keeps him up at night | Ben Mann

Anthropic co-founder: AGI predictions, leaving OpenAI, what keeps him up at night | Ben Mann

Ben Mann, co-founder of Anthropic, discusses the accelerating progress in AI, forecasting superintelligence by 2028. He details Anthropic's safety-first mission, the "Economic Turing Test" for AGI, the mechanisms of Constitutional AI, and why focusing on alignment created Claude's unique personality.

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