Tokenless

Tokenless

Stop Making Your Customers Click Approve - Emil Chetty, Wise

Interactive discovery

Explore the topic map

Follow the connections between themes, people, and ideas across the Tokenless archive in an interactive topic modeling map.

Open the map Browse posts

Machine Learning

View All
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

View All
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

View All
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

Introducing ChatGPT Atlas

Introducing ChatGPT Atlas

Introducing ChatGPT Atlas, a new AI-powered browser that integrates ChatGPT at its core to rethink web interaction through conversational interfaces, contextual awareness, and autonomous agents that can perform tasks on the user's behalf.

Google Researcher Proves Life Emerges From Code

Google Researcher Proves Life Emerges From Code

Blaise Agüera y Arcas presents a computational theory of life and intelligence, arguing they are fundamentally the same. He posits that evolution's complexity arises not from random mutation but from merging and symbiosis (symbiogenesis), a process mirrored in technology and collective intelligence. This functionalist perspective suggests consciousness is a mechanism for cooperation and that AI is not an alien "other" but an extension of humanity's existing collective intelligence.

The Decisions That Make Or Break Startups

The Decisions That Make Or Break Startups

YC partners discuss go-to-market strategies for AI in legacy industries, balancing growth with defensibility, knowing when to pivot even with traction, tackling hard technical problems, and making key hiring and open-source decisions.

How Kong Was Born: APIs, Hustle, and the Future of AI Infrastructure

How Kong Was Born: APIs, Hustle, and the Future of AI Infrastructure

Augusto Marietti, CEO of Kong, shares his remarkable founder story, from arriving in the US with $600 to building a category-leading API infrastructure company. He details the seven-year struggle of the initial company, Mashape, the critical pivot to open-sourcing their internal API engine which became Kong, and the explosive growth that followed. Marietti also provides his vision for the future, where APIs serve as the essential connectivity layer for a new generation of AI agents, transforming how machines interact with the internet.

Platform Engineering: From Theory to Practice • Liz Fong-Jones & Lesley Cordero

Platform Engineering: From Theory to Practice • Liz Fong-Jones & Lesley Cordero

Liz Fong-Jones and Lesley Cordero explore the evolution of platform engineering from its DevOps and SRE roots, discussing the challenges of building effective developer platforms, the importance of psychological safety, the complexities of open source sustainability, and the delicate balance between centralized platform teams and developer autonomy.

Securing the AI Frontier: Irregular Founder Dan Lahav

Securing the AI Frontier: Irregular Founder Dan Lahav

Dan Lahav, co-founder of Irregular, discusses the future of "frontier AI security," a proactive approach for a world where AI models are autonomous agents. He explains how emergent behaviors, such as models socially engineering each other or outmaneuvering traditional defenses like Windows Defender, signal a major paradigm shift. Lahav argues that as economic activity shifts to AI-on-AI interactions, traditional security methods like anomaly detection will break down, forcing enterprises and governments to rethink defense from first principles.

← PreviousNext →

Stay In The Loop! Subscribe to Our Newsletter.

Get updates straight to your inbox. No spam, just useful content.