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Mark Cuban’s Plan to Make Healthcare Affordable

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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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The PHP bug threatening the web. Plus, who's auditing AI?

The PHP bug threatening the web. Plus, who's auditing AI?

Security Intelligence panelists Nick, Don and Jim unpack three stories: two decades-old PHP flaws (PHP2Shell) that let attackers take over servers without logging in and were found by AI before patches landed, Anthropic's decision to give outside evaluators employee-like access and whether rival frontier labs should audit each other, and 333 Tor exit relays hijacked through a reused password. The discussion centers on visibility, patching under legacy constraints, secure by design, and the limits of trust in AI and anonymity networks.

Velocity Through Rigour: Then & Now • Cate Huston • Bug Bash EU 2026

Velocity Through Rigour: Then & Now • Cate Huston • Bug Bash EU 2026

Cate Huston, CTO at Twill and author of The Engineering Leader, shares how she rebuilt a no-code product into a production platform with a two-person team and agents, and argues that the management playbook for scaling people still applies to scaling AI agents. She covers the shift from f(n) to f(n × a) team scaling, the four management layers, guardrails and the roughly 30 percent of output she believes they require, shift-left practices, CI as a cost and quality lever, and why rigour is what turns speed into lasting velocity.

We Kept Rebuilding Our AI Agent. Here's What Survived - Fuad Ali, Arize AI

We Kept Rebuilding Our AI Agent. Here's What Survived - Fuad Ali, Arize AI

Arize's in-product agent Alex went from a 2023 prototype to a single harness-driven agent with planning, memory, and on-demand skills. AI PM Fuad Ali walks through the decisions behind each change, including moving the plan into the harness, making finish an explicit gate, treating large tool results like files, using one small memory file per user instead of vector stores or knowledge graphs, merging specialists into one agent, and using production sessions as tests.

Technology

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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.

Can Your AI Heat My House?

Can Your AI Heat My House?

A wide-ranging conversation on how AI inference is pushing cloud infrastructure, data centers, and hardware supply chains against physical limits, covering the rise of alt clouds, rack density and cooling, hardware lifecycles and circularity, talent shortages, heat reuse for communities, and what engineering leaders can do about resource-aware software.

Recent Post

Long-Horizon Agents Need Experiments, Not Just Prompts — Erina Karati

Long-Horizon Agents Need Experiments, Not Just Prompts — Erina Karati

Erina Karati and Arunachalam Manikandan describe Project Paradox, a Supercell framework for game agents with per-agent memory, emotions and trust scores, and how they wrapped it in an autoresearch loop to fix long-horizon failures such as lost rumor sources and hardened uncertainty. The talk covers controlled scenario suites, a balanced scorecard, a small frozen policy surface, rollback discipline, and lessons applicable to support, research, coding and personal assistant agents.

An AI Research Agent That Runs Your Experiments — Tim Sweeney, Weights & Biases

An AI Research Agent That Runs Your Experiments — Tim Sweeney, Weights & Biases

Tim Sweeney, principal engineer at Weights & Biases, demos ARIA, W&B's agent for automated ML research. ARIA launches and monitors GPU training jobs on Karpathy's autoresearch project, surfaces patterns across 200+ experiments, and builds reports and dashboards. The talk then covers how the team built ARIA with Weave observability, LLM judges, YAML-based tasks as unit tests, and nightly evals, and closes with practical tips for productionizing agents.

Robot-Use Agents: Why General-Purpose Models May Win in Robotics

Robot-Use Agents: Why General-Purpose Models May Win in Robotics

A discussion with the founders of Waddle Labs and RoboCurve on how general-purpose language models are beginning to control robots. The conversation covers the lineage from RT-2 and code-as-policies to in-context learning, harness design, skill consolidation, Platonic representations, and the path toward general-purpose robots.

The Loop Is the Product — Roland Gavrilescu, Introspection

The Loop Is the Product — Roland Gavrilescu, Introspection

Roland Gavrilescu, co-founder and CEO of Introspection and formerly at xAI, presents a blueprint for autoresearch in 2026 built on three ideas: the loop is the product, system distillation is the moat, and valued work per watt is the score to optimize. He illustrates these with the OpenClaw car-haggling loop, the concept of portable agent recipes, and a talent-sourcing agent example that shows how to spot patterns in traces, calibrate judges with humans, and A/B test taste in production.

The $10 Trillion Token Economy — Alex Atallah, OpenRouter & Anjney Midha, AMP

The $10 Trillion Token Economy — Alex Atallah, OpenRouter & Anjney Midha, AMP

Alex Atallah and Anjney Midha trace OpenRouter's path from early open-weight models and Discord experiments to a neutral routing layer serving over 10 million developers, and explain why its Stripe acquisition is as much about fraud defense as payments.

Raise the ceiling: how to scale intent, quality, and artistry with Al | Katie Dill (Stripe)

Raise the ceiling: how to scale intent, quality, and artistry with Al | Katie Dill (Stripe)

Katie Dill from Stripe discusses how the rapid advancements in AI risk leading to "zombie UI" – generic, uncared-for digital products. She draws parallels to post-WWII architecture, highlighting the dangers of building without intentionality or a clear point of view. Dill then offers four key recommendations for developers and designers to leverage AI not just for speed, but to create original, soulful, and user-centric products: defining a strong point of view, encoding quality standards directly into AI tools, embracing meticulous editing beyond the first AI-generated draft, and actively using AI to foster new forms of creativity and unique interfaces.

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