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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

Anthropic's CCA Exam as a Field-Guide for Agentic Engineering — Frank Coyle, UC Berkeley

Anthropic's CCA Exam as a Field-Guide for Agentic Engineering — Frank Coyle, UC Berkeley

Frank Coyle demystifies the Claude Certified Architect exam by dissecting key scenarios and highlighting common anti-patterns in Agentic AI design. He provides actionable best practices, emphasizing effective tool use, context management, specialized agent architectures, and cost-saving techniques, all centered on understanding what to avoid to build robust LLM applications.

Why Robotics Still Isn't Solved - But Could Be Soon | YC Paper Club

Why Robotics Still Isn't Solved - But Could Be Soon | YC Paper Club

This Paper Club delves into the current state of robotics, addressing roadblocks like the sim-to-real gap and embodiment drift. Speakers present advancements in multi-scale memory for long-horizon tasks, self-supervised embodied reasoning, zero-shot dexterous manipulation via massive simulation, and the economic imperative of teleoperation-first robotics companies, concluding with optimizations for efficient, real-time World Action Models.

CAN CHINA BEAT WAYMO?

CAN CHINA BEAT WAYMO?

This episode discusses three critical topics in AI: the true nature of recent AI agent "breakouts," arguing they highlight governance and security flaws rather than model danger; the role of AGI narratives in fueling the current AI investment bubble and questioning its sustainability; and China's aggressive strategy in the global robotaxi market, potentially outpacing Western counterparts like Waymo.

The New Primitives: Building AI Native Software — Kwindla Kramer, Daily

The New Primitives: Building AI Native Software — Kwindla Kramer, Daily

Kwindla Hultman Kramer argues that current AI agents are akin to 1995 web pages – a foundational primitive, not the ultimate destination. Drawing a historical parallel, he predicts the emergence of "AI native software" that will build upon and surpass agents, much like web applications evolved from simple web pages. He illustrates this through computing history, highlighting transformative shifts like VisiCalc's impact on accounting and the vision of Apple's Knowledge Navigator, and concludes by showcasing a game, Gradient Bang, that demonstrates the core primitives of this future AI native software.

Open Source Is Dead. Long Live Open Source. — Saoud Rizwan, Cline

Open Source Is Dead. Long Live Open Source. — Saoud Rizwan, Cline

Saoud Rizwan, founder of Cline, discusses how AI has eroded trust in open-source communities, leading projects like Zig and curl to restrict AI-generated contributions and exposing severe supply chain risks, as seen with the litellm compromise. He argues that while community open source is struggling, the economic imperative of "open weights" models is rising. Citing the high costs of closed LLMs and the success of models like GLM at Coinbase, Rizwan draws parallels to the Open Compute project, predicting a commoditization of AI inference. He urges American labs to release open-weights models to maintain technological leadership against foreign competitors and prevent lock-in.

Max Hodak: What Really Kills Deep Tech Startups?

Max Hodak: What Really Kills Deep Tech Startups?

Max Hodak, CEO of Science, reveals that deep tech startup success, exemplified by their retinal implant, is fundamentally driven by robust internal infrastructure. He argues that meticulous design of processes like purchasing, hiring, and unique 'EigenReviews' dictate a company's iterative speed. Hodak emphasizes the irreplaceable founder's judgment, action-driven information generation, and the critical role of custom operating systems, including AI-native tools, in achieving impactful outcomes in complex, capital-intensive fields like biotech.

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