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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 AI Systems for Discernment, Not Approval - Angel Ortmann Lee, Duolingo

Build AI Systems for Discernment, Not Approval - Angel Ortmann Lee, Duolingo

The talk addresses the critical flaw in human-in-the-loop AI: humans often surrender cognitive effort, leading to "automation bias" rather than true discernment. Through a Duolingo English Test case study and various interaction design examples, it demonstrates how engineering the human-AI interface—rather than just the model or oversight—can elicit critical thinking, generate high-quality data, and foster a virtuous cycle of AI improvement.

Software in the Age of Agents | The a16z Show

Software in the Age of Agents | The a16z Show

This conversation explores the shift in enterprise software as AI agents become primary users, moving towards 'headless' architectures where data and logic, rather than UIs, hold key value. It delves into the enduring stickiness of systems like SAP, driven by deep business process codification, and highlights that 'exception handling' is central to enterprise complexity. The discussion identifies new startup opportunities arising from AI, focusing on enhancing existing systems and bridging organizational functions rather than direct competition.

Inside Zipline's Autonomous System: 140M Miles, Zero Incidents

Inside Zipline's Autonomous System: 140M Miles, Zero Incidents

Zipline co-founder Keller Rinaudo Cliffton and Eric Watson discuss how their autonomous logistics system evolved from addressing critical needs in Rwanda to becoming the largest commercial autonomous system globally. They highlight that the drone is only 15% of the solution, emphasizing the deep integration of software, vertical hardware design, advanced safety protocols like compute failover, and extensive testing required. The discussion also covers the immense market potential for autonomous delivery, the impending cost-effectiveness over traditional methods, and the necessary transformation of air traffic control to support a future of pervasive aerial autonomy.

The AI Threat Almost No One Is Working On (with Benjamin Todd)

The AI Threat Almost No One Is Working On (with Benjamin Todd)

Benjamin Todd provides an updated career strategy for the AI era, explaining why 'follow your passion' is flawed and what truly builds fulfillment. He details the ABZ framework for planning under deep uncertainty and the 'moving bottleneck' concept to stay valuable as AI advances. The discussion highlights that a human-level digital worker quickly becomes superhuman and maps critical AI risks including power-seeking AI, extreme power concentration, and engineered pandemics, emphasizing that individual careers can be a powerful lever for good in these transformative times.

The Pipeline Is Dead - Iris ten Teije, Sky Valley Ambient Computing

The Pipeline Is Dead - Iris ten Teije, Sky Valley Ambient Computing

This talk fundamentally challenges the long-standing 'frozen artifact' model of software distribution, arguing it's obsolete due to the collapsing cost of software changes (driven by AI) and persistent demand for personalization. Iris ten Teije introduces Differ's vision of 'adaptive software' using a 'stem and divergences' architecture, where each user runs a unique, live-adapted version. The presentation delves into the complex architectural, testing, and coordination challenges of this new paradigm, emphasizing the need for robust infrastructure to manage user-specific, mutable software safely.

SWE-Marathon: Evaluating Coding Agents at Billion-Token Scale - Rishi Desai, Abundant AI

SWE-Marathon: Evaluating Coding Agents at Billion-Token Scale - Rishi Desai, Abundant AI

SWE-Marathon introduces a benchmark for long-horizon autonomous software engineering, pushing coding agents from bug fixes to full project ownership. It highlights the critical need for robust, multi-layered verification and anti-cheat mechanisms to prevent reward hacking in tasks spanning hundreds of millions of tokens, revealing that current agents achieve only a 26% success rate.

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