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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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Bringing Continual Learning to Every Company: Trajectory’s Ronak Malde

Bringing Continual Learning to Every Company: Trajectory’s Ronak Malde

Ronak Malde, co-founder of Trajectory, argues that agents need to learn continuously from real-world experience instead of relying on offline batch updates. He covers how training custom models has become accessible to companies, two research directions (Group Size-1 GRPO and a meta-grader for reward propagation), the Harvey and Rogo results, the distinction between continual learning and recursive self-improvement, and a vision of product builders as gardeners who shape products that grow on their own.

Why Waiting for the Next AI Model Can Pay Off - John Stecher, Blackstone & Scott Worland, Norm AI

Why Waiting for the Next AI Model Can Pay Off - John Stecher, Blackstone & Scott Worland, Norm AI

Blackstone CTO John Stecher and Norm AI CTO Scott Worland discuss how to build AI agent systems that remain useful as models improve. They cover why data strategy and straight-through processing come first, how to weigh ROI against waiting for a better model, how evals anchor financial-services work, and why Norm rebuilt its platform after a large hand-labeled eval set exposed the cost of over-engineered code.

How We Took an AI Agent From 41% to 97% Accurate - Milind Sunil Shah, Brainbase Labs

How We Took an AI Agent From 41% to 97% Accurate - Milind Sunil Shah, Brainbase Labs

Milind Sunil Shah of Brainbase Labs presents a six-step framework for improving back-office agents, illustrated with a Domino's project that tracks competitor pizza prices across websites and delivery apps. Accuracy rose from 41% to 97%, cost per source fell from $2 to $1, and run time dropped from 129 to 71 minutes, all through instructions, skills, and playbooks rather than a new model. The talk covers kickoff, ontology, benchmarks and evals, a narrow first agent, iteration, and handing off the full loop.

Technology

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What iPhone Packaging Reveals About the Robotics Opportunity

What iPhone Packaging Reveals About the Robotics Opportunity

Tutor Intelligence CEO Josh Gruenstein explains why robotics is a systems problem spanning AI, hardware, manufacturing, and customers, and how deploying robots into real factories and warehouses, with human tutors as backup, generates the data that makes them more capable. The discussion covers the company's own robot designs, its focus on small and mid-sized businesses, the economics of flexible robotic labor, and the implications for American manufacturing and supply chains.

Why Founders Are Betting Big on Factories, Mines, and Energy

Why Founders Are Betting Big on Factories, Mines, and Energy

Erin Price-Wright and Connor Love unpack the AD50 and the rebuilding of America's industrial base, covering how defense demand is financing manufacturing capacity for commercial markets, how AI is reshaping factory economics, how a new generation of founders applies lessons from SpaceX, Tesla, Anduril, and Palantir to mining, energy, and manufacturing, and why private capital is now willing to fund physical infrastructure before government demand is guaranteed.

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.

Recent Post

Learning Python Programming • Fabrizio Romano & Naomi Ceder • GOTO 2025

Learning Python Programming • Fabrizio Romano & Naomi Ceder • GOTO 2025

Author Fabrizio Romano discusses his decade-long journey writing "Learning Python Programming," detailing the book's evolution from GUI-focused content to command-line applications. He explores the controversial but ultimately beneficial introduction of typing in Python, the role of AI as a powerful tool for developers, and the critical importance of nurturing junior talent rather than replacing them with AI, emphasizing the enduring need for fundamental programming skills and human expertise.

The Missing Piece in the AI for BI Puzzle

The Missing Piece in the AI for BI Puzzle

Yoni Leitersdorf, CEO of Solid, explains that directly applying Large Language Models (LLMs) to databases for text-to-SQL fails due to a lack of business context. He introduces the concept of a semantic layer as a critical "Rosetta Stone" that translates raw data into a meaningful format AI can understand, enabling reliable and accurate data interaction.

No Priors Ep. 134 | With Palo Alto Networks CEO Nikesh Arora

No Priors Ep. 134 | With Palo Alto Networks CEO Nikesh Arora

Nikesh Arora, CEO of Palo Alto Networks, discusses the transformative impact of AI on search, enterprise business models, and cybersecurity. He explores the shift from search to agentic AI, the challenges and opportunities for enterprise adoption, and how AI is fundamentally compressing cyberattack timelines while enabling new, data-centric defense strategies.

Detecting Compromise of Passkey Storage on the Cloud

Detecting Compromise of Passkey Storage on the Cloud

Mazharul Islam from the University of Wisconsin—Madison introduces CASPER, a novel deception-based framework designed to detect the misuse of passkeys stolen from cloud storage providers. CASPER uses a system of decoy secrets and passkeys to enable relying parties (websites) to identify and flag unauthorized login attempts, effectively balancing security, usability, and deployability without disrupting the user experience.

Encrypted Access Logging for Online Accounts: Device Attributions without Device Tracking

Encrypted Access Logging for Online Accounts: Device Attributions without Device Tracking

Client-Side Encrypted Access Logging (CSAL) is a proposed protocol that uses OS-level cryptography and FIDO2-style attestations to create trustworthy, privacy-preserving account activity logs, resolving the tension between preventing user tracking and accurately detecting account compromise.

RevenueCat: Powering Subscriptions for the App Economy

RevenueCat: Powering Subscriptions for the App Economy

In a YC interview, RevenueCat co-founders Jacob Eiting and Miguel Carranza discuss their journey from experiencing the pain of in-app purchases to building a critical piece of infrastructure for the mobile economy. They cover their early-stage conviction, the keys to selling to developers, and the operational and personal lessons learned while scaling to a globally distributed team.

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