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How Revolut Cut AI Coding Costs 90% With Self-Hosted Open Models - David Abitbol, Revolut

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Machine Learning

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Judge a Transaction by the Company It Keeps — Somya Rai & MD Sharique, EXL

Judge a Transaction by the Company It Keeps — Somya Rai & MD Sharique, EXL

EXL developed an advanced fraud detection system that augments XGBoost with Graph Neural Network (GNN) embeddings. Traditional tabular models struggle to capture fraud signals residing in transaction neighborhoods. The system's innovative design includes meticulous sampling strategies, disjoint monthly graph construction for leakage control, and a GraphSAGE architecture that aggregates mean, max, and standard deviation of neighbor features to detect subtle fraud patterns. Emphasizing explainability for regulatory compliance and analyst trust, it also features a highly optimized serving architecture achieving 3ms P99 latency, pivoting to edge prediction to reduce cache footprint from 60GB to 2-3GB. This led to a 27-33% relative lift in true positive rates and a projected $65 million incremental fraud capture.

From 15% to 90% GPU Utilization: Fix the Data Pipeline, Not the Model

From 15% to 90% GPU Utilization: Fix the Data Pipeline, Not the Model

Tarun Sunkaraneni from Amazon AGI shows how a multimodal SFT pipeline that spent about 85% of its time waiting on data was brought to roughly 90% GPU utilization. He walks through concurrency with asyncio and Ray actors, prefetching, zero-copy transfer via Ray's object store, and a network-card bottleneck that appears only at scale, and argues that the hardest part of training throughput is often keeping GPUs fed rather than optimizing the model.

Small Models, Big Results: Training a Finance Agent for Under $500 — Charles Dickens, Snorkel AI

Small Models, Big Results: Training a Finance Agent for Under $500 — Charles Dickens, Snorkel AI

Snorkel AI and UC Berkeley's Sky Computing Lab show that a 4B Qwen3 model, trained with reinforcement learning for under $500 using the rLLM framework, beats its 235B sibling on expert-validated financial question answering built from SEC 10-K filings. The talk covers the FinQA dataset construction and verification, common failure modes of frontier models, transfer to multi-table and general tool-use tasks, and ablations showing that simple data and binary rewards outperform more elaborate setups, since the real bottleneck is disciplined tool use rather than reasoning depth.

Artificial Intelligence

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Crusoe CEO Chase Lochmiller: Turning Stranded Energy Into Intelligence

Crusoe CEO Chase Lochmiller: Turning Stranded Energy Into Intelligence

Chase Lochmiller, founder and CEO of Crusoe, discusses building a vertically integrated AI infrastructure company spanning energy, data centers, manufacturing, and managed AI cloud. Topics include leading a complex organization, the Bitcoin-to-AI pivot, energy-first compute, executive coaching, firing decisions, community pushback on data centers, and lessons from climbing Everest.

How Revolut Cut AI Coding Costs 90% With Self-Hosted Open Models - David Abitbol, Revolut

How Revolut Cut AI Coding Costs 90% With Self-Hosted Open Models - David Abitbol, Revolut

David Abitbol, who leads AI operations at Revolut, shares what AI tools did to 2,000 engineers' coding time and lead time. The main finding is that self-hosting open-source GLM models delivered about 60-70% faster delivery at roughly a tenth of frontier-lab costs. He covers the GPU sizing, latency targets, tuning that made the same hardware 88% faster, and how an EU-regulated bank keeps the setup compliant.

Grokking Software Architecture • Matt Erman & Luca Mezzalira • GOTO 2026

Grokking Software Architecture • Matt Erman & Luca Mezzalira • GOTO 2026

Matt Erman, author of Grokking Software Architecture, joins Luca Mezzalira to discuss why engineering fundamentals matter more in the AI era, how architects can act as clarity engineers, a five-step architectural thinking process, Architecture Decision Records, and the risks of letting AI generate systems without human judgment.

Technology

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Mark Cuban’s Plan to Make Healthcare Affordable

Mark Cuban’s Plan to Make Healthcare Affordable

Mark Cuban and Julie Yoo discuss how transparency, direct contracting, and AI could reshape healthcare economics, from Cost Plus Drugs and modular pod manufacturing to personalized medicine, the future of physicians, and advice for founders who want to use AI to learn rather than to stop thinking.

Exploits Now Beat Patches: Open Source Security in the AI Era - Patrick Smyth, Chainguard

Exploits Now Beat Patches: Open Source Security in the AI Era - Patrick Smyth, Chainguard

Patrick Smyth of Chainguard examines how frontier AI has compressed the time between vulnerability disclosure and exploitation, leaving 30-day remediation cycles obsolete. The talk covers AI-assisted attacks, waves of supply chain malware, four attack surfaces spanning malware, known CVEs, zero days, and side doors like CI/CD, developer laptops, and agent skills, and practical defenses including cooldown periods, faster CVE remediation, and signing artifacts with SLSA and Sigstore.

Can Your AI Heat My House?

Can Your AI Heat My House?

A wide-ranging conversation on how AI inference is pushing cloud infrastructure, data centers, and hardware supply chains against physical limits, covering the rise of alt clouds, rack density and cooling, hardware lifecycles and circularity, talent shortages, heat reuse for communities, and what engineering leaders can do about resource-aware software.

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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