Tokenless

Tokenless

When Running Your Own AI Models Beats Paying for APIs - Steven Latré, imec

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
THE $800B COMPUTE TRAP

THE $800B COMPUTE TRAP

Ben Lorica and Evangelos Simoudis work through Anthropic's S-1 filing, weighing its striking growth and improving unit economics against compute commitments, falling prices from open-weight models, and dependence on coding. They then examine SpaceX's emerging neocloud business and close with a debate over proposed frontier AI regulation, from self-improvement limits to independent testing and incident disclosure.

When Running Your Own AI Models Beats Paying for APIs - Steven Latré, imec

When Running Your Own AI Models Beats Paying for APIs - Steven Latré, imec

Steven Latré, who leads AI at the semiconductor research center imec, presents a benchmarking study of what it really costs to move long-running coding agents from commercial APIs to self-hosted GPUs. Across thousands of SWE-bench Pro runs, the study finds that hardware costs rise in steps rather than smoothly, that concurrency limits matter more than raw accuracy, that break-even GPU utilization ranges from about 89% on small systems to about 15% on 8x B200 machines, and that harness choice can halve GPU time for the same results.

Voice AI Where One Wrong Question Breaks the Rules - Shiv Indap, Upstart & Brooke Hopkins, Coval

Voice AI Where One Wrong Question Breaks the Rules - Shiv Indap, Upstart & Brooke Hopkins, Coval

Shiv Indap of Upstart and Brooke Hopkins of Coval walk through automating loan verification calls in a heavily regulated lending environment. They cover the compliance traps that shape the agent's behavior, moving human review beyond a Google Sheet, and raising LLM judge agreement with human reviewers from 33% to 92%. The talk then lays out a continuous loop of live monitoring, human review queues, simulation-based testing of fixes, and self-healing agents, with humans signing off on every change.

Technology

View All
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

Shipping Production AI Inside Government — William Tarr, Ministry of Justice (DO NOT PUBLISH)

Shipping Production AI Inside Government — William Tarr, Ministry of Justice (DO NOT PUBLISH)

The UK Ministry of Justice Justice AI Unit operates as a startup within government, deploying engineers directly into prisons and probation offices. This 'forward deployed' model enables rapid, user-centric AI product development, overcoming bureaucratic hurdles by prioritizing real-world feedback and agile implementation to empower frontline staff and solve critical operational challenges.

GTM Is You - Victoria Melnikova, Evil Martians

GTM Is You - Victoria Melnikova, Evil Martians

Victoria Melnikova discusses optimal Go-To-Market strategies for developer tools and AI startups, asserting that a founder's personal brand is the most underrated competitive advantage in 2026. She covers foundational GTM hygiene, the strategic importance of San Francisco, effective advertising and event tactics, embracing unconventional marketing, and the critical role of authenticity and personal connection in building trust and cutting through digital noise.

Beyond the Harness: A Journey Towards Adaptative Engineering - Rajiv Chandegra, Annicha Labs

Beyond the Harness: A Journey Towards Adaptative Engineering - Rajiv Chandegra, Annicha Labs

Rajiv Chandegra introduces adaptive engineering, a new AI design philosophy. He argues that as AI models become more powerful and interact with complex, dynamic real-world problems, the traditional 'fixed harness' approach—predictable but brittle—will become obsolete. Drawing on complexity science, he explains how adaptive engineering allows the AI system's structure (harness) to emerge and adapt dynamically during runtime, mirroring natural self-organizing systems. This shift redefines the engineer's role to designing constraints and fostering horizontal intelligence in multi-agent coordination.

How we taught agents to use good retrieval - Hanna Lichtenberg, Mixedbread AI

How we taught agents to use good retrieval - Hanna Lichtenberg, Mixedbread AI

Mixedbread AI addresses the "Oracle Gap" – the disparity between LLM reasoning and retrieval capabilities – by developing agents trained to use advanced search tools effectively. They demonstrate how current LLMs generate poor queries due to training biases and introduce a sophisticated agent harness with diverse search tools and a unique training regimen, including supervised fine-tuning and reinforcement learning with custom rewards, to teach agents to form precise semantic queries. This approach significantly improves performance on benchmarks like Oblique Congress and Snowflake's Match QA, closing the gap between theoretical perfect retrieval and real-world agent performance.

What if the harness mattered more than the model? - Aditya Bhargava, Etsy

What if the harness mattered more than the model? - Aditya Bhargava, Etsy

Aditya Bhargava argues that the 'harness' (the surrounding logic and tools) is more critical than the underlying LLM model itself for building effective AI agents. He proposes that focusing on sophisticated harness design, supported by his new language Agency, can enable local, open-source models to achieve performance comparable to large proprietary models, thereby reducing dependency and fostering innovation.

Build AI Systems for Discernment, Not Approval - Angel Ortmann Lee, Duolingo

Build AI Systems for Discernment, Not Approval - Angel Ortmann Lee, Duolingo

The talk addresses the critical flaw in human-in-the-loop AI: humans often surrender cognitive effort, leading to "automation bias" rather than true discernment. Through a Duolingo English Test case study and various interaction design examples, it demonstrates how engineering the human-AI interface—rather than just the model or oversight—can elicit critical thinking, generate high-quality data, and foster a virtuous cycle of AI improvement.

← PreviousNext →

Stay In The Loop! Subscribe to Our Newsletter.

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