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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

Multi Agent AI and Network Knowledge Graphs for Change — Ola Mabadeje, Cisco

Multi Agent AI and Network Knowledge Graphs for Change — Ola Mabadeje, Cisco

A product manager from Cisco's incubation group, Outshift, details a solution that uses a multi-agent AI system combined with a dynamic network knowledge graph to solve critical issues in IT change management. The system integrates with ITSM tools like ServiceNow to automate impact assessment, test plan generation, and pre-production validation in a "digital twin" environment, significantly reducing production failures.

Wisdom-Driven Knowledge Augmented Generation at Scale - Chin Keong Lam, Patho AI

Wisdom-Driven Knowledge Augmented Generation at Scale - Chin Keong Lam, Patho AI

A deep dive into building expert AI systems using a Wisdom-Driven Knowledge Graph. This approach enhances Knowledge-Augmented Generation (KAG) to surpass traditional Retrieval-Augmented Generation (RAG) by enabling systems to understand, reason, and provide expert-level quantitative analysis and advice.

The Moonshot Podcast Deep Dive: Jeff Dean on Google Brain’s Early Days

The Moonshot Podcast Deep Dive: Jeff Dean on Google Brain’s Early Days

Google DeepMind’s Chief Scientist Jeff Dean discusses the origins of his work on scaling neural networks, the founding of the Google Brain team, the technical breakthroughs that enabled training massive models, the development of TensorFlow and TPUs, and his perspective on the evolution and future of artificial intelligence.

Genie 3: An infinite world model with Shlomi Fruchter and Jack Parker-Holder

Genie 3: An infinite world model with Shlomi Fruchter and Jack Parker-Holder

Professor Hannah Fry speaks with Jack Parker-Holder and Shlomi Fruchter about Genie 3, a general-purpose world model that generates diverse, interactive environments from prompts. The discussion covers its auto-regressive nature, which enables the creation of consistent, explorable worlds, its key differences from video models like Veo, and its foundational role in training AI agents and advancing toward AGI.

How Intercom rose from the ashes by betting everything on AI | Eoghan McCabe (founder and CEO)

How Intercom rose from the ashes by betting everything on AI | Eoghan McCabe (founder and CEO)

Eoghan McCabe, founder and CEO of Intercom, shares the unfiltered story of transforming a multi-billion dollar, stagnating SaaS business into a rapidly growing, AI-first company. He details the necessity of 'founder mode,' a radical cultural overhaul, and why having nothing to lose is the ultimate advantage in the AI era.

No Priors Ep. 128 | With DeepLearning.AI Founder Andrew Ng

No Priors Ep. 128 | With DeepLearning.AI Founder Andrew Ng

Andrew Ng discusses the rise of agentic AI, moving beyond scale as the sole driver of progress. He explores how AI-assisted coding is creating a new startup paradigm, shifting the bottleneck from engineering to product management and favoring technical founders. Ng argues for smaller, highly-skilled teams and predicts AI will profoundly empower individuals across all job functions.

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