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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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Why Leibniz Couldn't Find the Mind Inside the Mill (Joscha Bach)

Why Leibniz Couldn't Find the Mind Inside the Mill (Joscha Bach)

Joscha Bach lays out his Machine Consciousness Hypothesis, the claim that consciousness is a simple biological learning algorithm which self-organising machines might rediscover. The discussion covers causal patterns and software, why IIT and the explanatory gap fail to explain experience, zombies and LLM self-reports, functionalism, Gödel and the Ruliad, and what evidence could ever settle the question.

I Made a Fruit Fly Review My Code - Nick Nisi, WorkOS

I Made a Fruit Fly Review My Code - Nick Nisi, WorkOS

Nick Nisi argues that human reviewers have become the bottleneck in software development and demonstrates a simulated fruit fly connectome trained to judge code quality, reaching about 88% accuracy in testing. He then proposes a tiered review system where team skills, classifiers, and automated reviewers send only risky pull requests to people, backed by verifiable proof.

Why We Rebuilt Microsoft Office From Scratch for AI Agents - Yijia Liang, Compound AI

Why We Rebuilt Microsoft Office From Scratch for AI Agents - Yijia Liang, Compound AI

Yijia Liang, founder of Compound and former finance analyst, explains why personal agents succeeded and what finance needs beyond them: multiplayer agents with their own inboxes, a headless Office engine rebuilt with agents, and agent swarms that navigate massive data rooms and models while keeping every output grounded in citations.

Technology

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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.

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.


Recent Post

Why cultivating agency matters more than cultivating skills in the AI era | Max Schoening (Notion)

Why cultivating agency matters more than cultivating skills in the AI era | Max Schoening (Notion)

Max Schoening, Head of Product at Notion, discusses how AI is reshaping software development. He argues that agency—the drive to effect change—is now more critical than specific skills, as AI makes the first 10% of any project 'free'. Schoening introduces his 'tiny core' theory for great products, debates the 'SaaSpocalypse', and emphasizes the growing importance of software quality and taste in an era of exploding software quantity.

How RAG, GraphRAG, and Context Engineering Improve AI Performance

How RAG, GraphRAG, and Context Engineering Improve AI Performance

Martin Keen explains that context, not model intelligence, is the biggest bottleneck in AI. He introduces Context Engineering, its four pillars (Connected Access, Knowledge Layer, Precision Retrieval, Runtime Governance), and advanced techniques like GraphRAG to build more reliable, context-aware AI systems.

⚡️ Competing with ChatGPT and Sierra, building a $10M ARR company — Yasser Elsaid, Founder, Chatbase

⚡️ Competing with ChatGPT and Sierra, building a $10M ARR company — Yasser Elsaid, Founder, Chatbase

Yaser Al, founder of Chatbase, shares his journey of bootstrapping the company from a side project to a $10M ARR business. He details his product-led growth strategy, the evolution of the tech stack from early RAG to a multi-model harness, and his vision for AI agents as 'Chief Customer Officers'.

Mastering AI Pricing: Flexible & Agile Monetization — Mayank Pant, Stripe

Mastering AI Pricing: Flexible & Agile Monetization — Mayank Pant, Stripe

This talk outlines the challenges of AI pricing, where traditional SaaS models fail due to unpredictable compute costs and margin pressure. It presents a five-step framework for developing a successful hybrid pricing strategy, emphasizing value alignment, customer trust, and rapid iteration as key competitive advantages.

Waymo's Dmitri Dolgov: 20 Million Rides and the Road to Full Autonomy

Waymo's Dmitri Dolgov: 20 Million Rides and the Road to Full Autonomy

Dmitri Dolgov, co-CEO of Waymo, discusses the 20-year journey from the DARPA challenge to full autonomy. He explains the Waymo Foundation Model—a multimodal world action model powering the driver, simulator, and critic—and how their "end-to-end plus" architecture enables superhuman safety and exponential scaling.

Baseten CEO Tuhin Srivastava on Custom Models, and Building the Inference Cloud

Baseten CEO Tuhin Srivastava on Custom Models, and Building the Inference Cloud

Baseten CEO Tuhin Srivastava discusses the explosive growth in AI inference, driven by the adoption of specialized and post-trained open-source models. He covers the strategic importance of owning the software layer on top of compute, navigating the severe GPU supply crunch with a multi-cloud fabric, the evolving landscape of AI workloads, and the operational lessons learned from scaling 30x in one year.

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