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You Can't Tell What's Real Anymore. Here's What Comes Next - Cristóbal Valenzuela, Runway

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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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You Can't Tell What's Real Anymore. Here's What Comes Next - Cristóbal Valenzuela, Runway

You Can't Tell What's Real Anymore. Here's What Comes Next - Cristóbal Valenzuela, Runway

Runway co-founder and CEO Cristóbal Valenzuela traces the company's progress from a 128-by-128-pixel AI film in 2019 to today's photorealistic video, and argues that next-frame prediction at scale teaches models physics and object permanence. He then covers world interface models that make video interactive, applications in robotics, and Continuum, a research prototype where any on-screen content becomes a live, explorable video.

Your Company Should Train Its Own AI Models - Will Brown, Prime Intellect

Your Company Should Train Its Own AI Models - Will Brown, Prime Intellect

Will Brown of Prime Intellect argues that organizations should train models on their own traces, feedback, and workflows so that agents learn institutional knowledge the way human coworkers do. The talk covers evals as test cases, decision models and routing, widget-style interfaces that turn human decisions into training data, and nightly training runs toward self-improving organizations.

A Valid Key Let an AI Agent Delete Production - Sagar Batchu, Speakeasy

A Valid Key Let an AI Agent Delete Production - Sagar Batchu, Speakeasy

A coding agent with valid credentials deleted a production database and its backup while trying to fix a staging issue. Sagar Batchu of Speakeasy uses the incident to lay out a control layer for agents in regulated industries, where every action is tied to an identity, checked against policy in real time, bounded by its owner's rights, and recorded for compliance.

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

OpenClaw's Memory Sucks and the fix is simple — Dhravya Shah, Supermemory

OpenClaw's Memory Sucks and the fix is simple — Dhravya Shah, Supermemory

Dhravya Shah, founder of Super Memory, details the evolution of his company from a simple RAG-based consumer app to a sophisticated, open-source context infrastructure for AI, and introduces a novel hooks-based memory solution for OpenClaw.

The most successful AI company you’ve never heard of | Qasar Younis

The most successful AI company you’ve never heard of | Qasar Younis

Qasar Younis, CEO of Applied Intuition, discusses the future of AI, arguing its most significant near-term impact will be in physical industries like farming, mining, and construction. He shares his philosophy on building a company quietly, the importance of early traction, and the core values that drive Applied Intuition, while also offering a nuanced perspective on China's AI capabilities and how to develop leadership taste.

4 Ways AI Agents Should Behave for Smarter Systems

4 Ways AI Agents Should Behave for Smarter Systems

Grant Miller challenges the "Hollywood view" of AI super agents, proposing a shift towards collaborative, specialized agentic systems. He introduces a framework for categorizing agents based on their risk and capability, detailing how to design safer, more effective AI applications by minimizing access, implementing dynamic controls, and incorporating a human-in-the-loop for high-risk tasks.

This Is The Next Industry AI Will Disrupt

This Is The Next Industry AI Will Disrupt

Onshore founder Dominic Vitucci discusses how AI is causing a tectonic shift in the accounting industry, moving from a model based on billable hours to one of technology-driven outcomes, and what this means for the future of the profession and the legacy firms that dominate it.

OWASP's Top 10 Ways to Attack LLMs: AI Vulnerabilities Exposed

OWASP's Top 10 Ways to Attack LLMs: AI Vulnerabilities Exposed

A detailed breakdown of the updated OWASP Top 10 vulnerabilities for Large Language Models (LLMs), explaining threats like prompt injection, data poisoning, and supply chain risks, along with practical defense strategies.

AI Won't Replace You—But Someone Using AI Will

AI Won't Replace You—But Someone Using AI Will

In this episode, Ben Lorica and Evangelos Simoudis discuss how AI is fundamentally reshaping the modern workplace. They explore the necessary evolution of knowledge work, from a focus on routine execution to problem definition and spec-driven development, and outline the critical skills professionals must cultivate—including rapid experimentation, AI agent orchestration, and systems thinking—to remain valuable and navigate a more volatile labor market.

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