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Machine Learning

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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.

PhylaFlow: Hybrid flow matching in phylogenetic tree space

PhylaFlow: Hybrid flow matching in phylogenetic tree space

PhylaFlow is a hybrid flow-matching framework that navigates Billera–Holmes–Vogtmann (BHV) tree space to accelerate Bayesian phylogenetic inference. By learning geodesic paths from random trees to posterior samples, PhylaFlow efficiently initializes MCMC chains, drastically reducing the "burn-in" time. A PhylaFlow-MCMC variant, which guides MrBayes move acceptance, significantly outperforms traditional methods and even existing machine learning baselines for posterior sampling, achieving better results within the same computational budget. The work also explores conditioning on sequence embeddings, aiming for a future phylogenetics foundation model capable of zero-shot inference.

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 Last Human Code Review: Building Trust in AI-Generated Code — Itamar Friedman, Qodo

The Last Human Code Review: Building Trust in AI-Generated Code — Itamar Friedman, Qodo

Itamar Friedman discusses how the bottleneck in AI-driven development has shifted from code generation to code review. He argues that current AI models are not the constraint; rather, it's the lack of codified, accessible context for AI agents. The solution involves building context engines that cater to both human and AI needs, integrating deep architectural knowledge and historical data to transition from reviewing individual pull requests to analyzing a comprehensive software graph, ultimately leading to automated code governance and "AI wisdom."

Modern Computer Architecture & Organization • Jim Ledin & Maciej «MJ» Jedrzejewski • GOTO 2026

Modern Computer Architecture & Organization • Jim Ledin & Maciej «MJ» Jedrzejewski • GOTO 2026

Jim Ledin, author of *Modern Computer Architecture and Organization*, discusses the integration of GPUs and LLMs into his book, emphasizing architectural principles over fleeting trends. He highlights memory bandwidth as the primary bottleneck in AI, explaining the impact of High Bandwidth Memory (HBM) demand on consumer RAM. Ledin also identifies understanding pipelining and cache hierarchy as the most crucial skill for software developers to optimize code performance.

AI Agents vs Business Rules: Which Should Make Decisions?

AI Agents vs Business Rules: Which Should Make Decisions?

This video contrasts deterministic business rules with probabilistic AI agents for enterprise decision-making. It argues that instead of one superseding the other, a hybrid approach combining rules-first processing with AI agent escalation for complex, unstructured, or judgment-heavy cases, augmented by deterministic guardrails and human oversight, leads to optimal automation.

Why Most AI Agents Fail Horribly

Why Most AI Agents Fail Horribly

Maarten Grootendorst discusses the foundational understanding developers need for modern AI tools, emphasizing core LLM concepts like tokens, embeddings, and attention. He provides a pragmatic view on AI agents, distinguishing hype from practical applications like coding assistants, and explores the role of memory, guardrails, and the growing importance of open-weight models for control and efficiency in AI infrastructure.

From Restoring Sight to Reimagining the Brain, with Max Hodak

From Restoring Sight to Reimagining the Brain, with Max Hodak

Max Hodak, co-founder and CEO of Science.xyz, discusses their revolutionary PRIMA retinal implant, restoring functional vision to the blind. He elaborates on treating the brain as a computational system, unlocking new medical approaches, and explores the broader potential of neural devices—from restoring capabilities to expanding human potential, touching on identity, consciousness, and AI-brain parallels. Science's long-term vision aims to reduce human fragility by repairing, replacing, and upgrading ourselves.

Why Your Enterprise Tech Stack Isn’t Ready for AI Agents — Christopher Lovejoy & Saul Howard

Why Your Enterprise Tech Stack Isn’t Ready for AI Agents — Christopher Lovejoy & Saul Howard

Chris Lovejoy and Saul Howard discuss the critical challenges of deploying AI agents in highly regulated enterprise environments, particularly healthcare. They advocate for a "constraints-first" architectural approach, proposing three core primitives – an immutable event log for auditability, schema-driven object storage for sensitive data, and human-agent equivalency for seamless escalation – which collectively enable privacy-preserving evaluations as a fundamental byproduct of the system design, rather than being an afterthought.

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