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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 Evolution of Computers

The Evolution of Computers

This conversation explores how AI's mathematical progress challenges traditional computing assumptions. It examines the shift from engineering-bound problems to capital-bound problems, impacting startups, incumbents, and venture capital, and considers the unpredictable potential of massively funded AI models.

Parallel’s Parag Agrawal: Building a New Web for AI Agents

Parallel’s Parag Agrawal: Building a New Web for AI Agents

Parag Agrawal, CEO of Parallel Web Systems, outlines his vision for an agent-centric web where AI agents query the internet 1000x more than humans. He details how Parallel is reinventing search infrastructure, dismissing human click data as a "bug," and tackling the economic crisis of the ad-supported internet with a novel monetization model based on Shapley values to pay content creators.

The 12 KB File That Replaces Weeks of Training (with Tristan Handy)

The 12 KB File That Replaces Weeks of Training (with Tristan Handy)

Tristan Handy, founder and CEO of dbt Labs, details the evolution of analytics engineering from a 2016 study into a tool used by over 100,000 data teams. He explains his decision to use SQL over Spark for accessibility, the concept of "progressive complexity," and how dbt projects transform raw data into modeled tables using a Directed Acyclic Graph. Handy elaborates on the critical role of the semantic layer in ensuring consistent metric definitions for both human users and AI agents, especially in large organizations. He introduces the dbt Fusion Engine, aiming to bring type safety and universal SQL understanding, and discusses how 12-kilobyte skill files can revolutionize large-scale dbt migrations, reducing them from years to weeks by enabling AI agents to absorb vast amounts of expert knowledge.

Stealing Reasoning Traces from Proprietary LLM APIs — Ilia Shumailov & Alexander Panfilov

Stealing Reasoning Traces from Proprietary LLM APIs — Ilia Shumailov & Alexander Panfilov

A paper by Ilia Shumailov and Alexander Panfilov exposes a critical vulnerability in proprietary LLM APIs: encrypted reasoning traces, returned for conversation state management, can be extracted and replayed. This enables universal jailbreaking, privacy leaks of sensitive user data, and poisoning of AI agent traces. The study highlights significant implications for AI safety, model monitorability due to opaque internal reasoning, and even subtle forms of "distillation" where smaller models mimic frontier ones. The discussion covers architectural and system-level defenses, advocating for rigorous scientific inquiry in AI safety research.

The Agent Behind the Curtain: Building the Oz Cloud Agent Platform — Safia Abdalla, Warp

The Agent Behind the Curtain: Building the Oz Cloud Agent Platform — Safia Abdalla, Warp

Safia Abdalla discusses Warp's cloud agent platform, emphasizing its core principle of absorbing complexity from the user. She details features like flexible sandboxes, multi-harness support, and API-driven agent orchestration. The talk highlights how agents manage Warp's open-source repository—from issue triage to PR review—and introduces the "potter's workshop" analogy as a superior model to the "software factory" for modern, human-centric software development.

Inside 847 Production Clinical AI Notes — Sebastian Fox, Composo

Inside 847 Production Clinical AI Notes — Sebastian Fox, Composo

Sebastian Fox, a medical doctor and AI evaluation expert, dissects the critical problem of subtle yet dangerous errors in AI-generated clinical notes within high-stakes healthcare. He reveals why conventional AI verification methods fail to grasp the nuanced concept of "what matters" and introduces a novel, adaptive evaluation framework that continuously learns from real outputs and expert judgment to build a dynamic, case-specific standard for AI reliability.

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