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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

Build Hour: AgentKit

Build Hour: AgentKit

A deep dive into OpenAI's AgentKit, demonstrating how to visually build, deploy, and optimize multi-step, tool-calling agents using Agent Builder, ChatKit, and the integrated Evals platform.

Sam, Jakub, and Wojciech on the future of OpenAI with audience Q&A

Sam, Jakub, and Wojciech on the future of OpenAI with audience Q&A

Sam Altman and Yakob present OpenAI's updated strategy, detailing a concrete research roadmap towards an automated AI researcher by 2028, a vision for an open AI platform, and massive infrastructure plans totaling $1.4 trillion. They also introduce a new corporate structure with a non-profit foundation focused on using AI to cure diseases and build AI resilience.

Commure: The AI Operating System for Healthcare

Commure: The AI Operating System for Healthcare

Tanay Tandon, co-founder and CEO of Commure, discusses his journey from building a medical device in college to creating an AI operating system for healthcare. He covers the pivot from hardware to software, the power of LLMs in automating revenue cycle and clinical documentation, and his vision for a future where AI liberates physicians from administrative burdens and fundamentally reshapes patient care.

Building the Real-World Infrastructure for AI, with Google, Cisco & a16z

Building the Real-World Infrastructure for AI, with Google, Cisco & a16z

AI is driving an unprecedented buildout of physical infrastructure. Experts from Google and Cisco discuss the "AI industrial revolution," where power, compute, and networking are the new scarce resources, demanding a complete reinvention of the technology stack from silicon to software.

Connection is Everything • Ken Hughes • GOTO 2025

Connection is Everything • Ken Hughes • GOTO 2025

In an increasingly digital world, genuine human connection is paramount. This presentation explores the shift in consumer values across seven generations, urging developers to move beyond transactional software and focus on four key pillars: making the user the center of their world (the 'Blue Dot' consumer), exceeding their ever-rising expectations, embracing the 'phygital' reality shaped by AI, and building deep, relational connections, exemplified by Taylor Swift's fan engagement.

Is ChatGPT Atlas safe? Plus: invisible worms, ghost networks and the AWS outage

Is ChatGPT Atlas safe? Plus: invisible worms, ghost networks and the AWS outage

A discussion on the security risks of new AI browsers like ChatGPT Atlas, the rise of malware distribution through trusted platforms like YouTube, the emergence of "post-infrastructure" malware like GlassWorm, corporate negligence in mobile security, and the critical lessons in resiliency from the recent AWS outage.

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