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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

LLM vs. SLM vs. FM: Choosing the Right AI Model

LLM vs. SLM vs. FM: Choosing the Right AI Model

A guide to understanding the differences between Large Language Models (LLMs), Small Language Models (SLMs), and Frontier Models (FMs). Learn the unique strengths of each model type and see practical use cases for document classification, customer support, and incident response to help you choose the right model for your AI project.

Fully Connected Tokyo: [Hands-on workshop] Automation of document workflows in financial industry

Fully Connected Tokyo: [Hands-on workshop] Automation of document workflows in financial industry

This workshop by Upstage demonstrates how to automate financial document workflows using a combination of their specialized Document AI (Document Parse) and Large Language Models (LLMs). The session covers building robust information extraction pipelines, addressing challenges like varied templates and data formatting, and implementing systematic evaluation using Weights & Biases Weave. It also presents real-world case studies from the insurance industry, showcasing significant improvements in efficiency and data utilization.

Architecting Self-Healing Enterprise Operations: AI + DevSecOps | Akshay Mittal  | SW Engineer | 4K

Architecting Self-Healing Enterprise Operations: AI + DevSecOps | Akshay Mittal | SW Engineer | 4K

Akshay Mittal discusses the evolution of enterprise AI, focusing on the crucial shift from reactive to predictive security through AI-augmented DevSecOps. He explores how to productionize agentic AI workflows using AIOps and Kubernetes, and emphasizes the non-negotiable need for explainable AI (XAI) in critical systems.

Build Hour: Apps in ChatGPT

Build Hour: Apps in ChatGPT

Learn how to design, build, and enhance real-time, multi-player applications within ChatGPT using the Apps SDK and Codex. This guide covers the core architecture, an AI-first development workflow, and best practices for creating valuable user experiences.

Why AI Agents Forget Everything (And How To Fix That)

Why AI Agents Forget Everything (And How To Fix That)

Mem0 is building a model-neutral, persistent memory layer for AI agents to solve the fundamental statelessness of LLMs. Co-founders Taranjeet Singh and Deshraj Yadav discuss their hybrid memory architecture, which reduces cost and latency compared to context stuffing, and their vision for a future where user memory is portable across all AI applications.

The new AI race: Enterprise innovation in 2026

The new AI race: Enterprise innovation in 2026

Experts discuss OpenAI's new ad model for ChatGPT, the breakout moment for agentic coding with Claude Code, IBM's "Enterprise in 2030" report on the shift from AI efficiency to innovation, and Hugging Face's new "Open Responses" standard for agent APIs.

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