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AI That Hunts Logic Bugs Before Attackers Do - Taylor Luttrell-Williams, Sonar

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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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AI That Hunts Logic Bugs Before Attackers Do - Taylor Luttrell-Williams, Sonar

AI That Hunts Logic Bugs Before Attackers Do - Taylor Luttrell-Williams, Sonar

Sonar's Taylor Luttrell-Williams introduces SonarQube Hunter Agent, an AI security agent that finds intent-level flaws such as broken access control, business logic gaps, and authentication holes that pattern-based SAST cannot detect. The talk covers its multi-agent pipeline with adversarial validation, Sonar's join to the OpenAI Daybreak Cyber Partner Program, and a live demo that surfaced 46 issues in a Python app, including a self-promotion to admin and an MFA bypass.

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.

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

🔬Bio-security is an AI Arms Race - Eric Nguyen (CEO, Radical Numerics)

🔬Bio-security is an AI Arms Race - Eric Nguyen (CEO, Radical Numerics)

Eric Nguyen, CEO of Radical Numerics, details the journey from early genome language models to Omni, a system that excels in DNA reading, writing, and reasoning. Omni outperforms specialized models in disease-variant prediction, particularly in previously challenging non-coding regions. The discussion also covers the critical need for AI-native biosecurity defenses, addressing how models can design biological sequences that evade current detection systems, and the broader vision for General Biological Intelligence.

Skill issue: stop deploying vision language models, use them with Skills — Merve Noyan, Hugging Face

Skill issue: stop deploying vision language models, use them with Skills — Merve Noyan, Hugging Face

Merve Noyan discusses the pitfalls of directly using large Vision Language Models (VLMs) at runtime due to performance limitations and restrictive licensing. She introduces "Web Vision," a toolkit that enables efficient training of smaller, task-specific computer vision models using a novel "vibe training" methodology. This approach leverages VLMs for initial labeling and judgment, followed by training efficient models like RF-DETR, all while adhering to Apache 2.0 licenses and costing only a few dollars.

Are AI labs ignoring cybersecurity experts?

Are AI labs ignoring cybersecurity experts?

This podcast explores the friction between frontier AI labs and cybersecurity experts, who disagree on AI safety priorities (alignment vs. traditional controls). It discusses the dual risks of open-weight AI models enabling sophisticated hacks like the TikTok camera exploit, and the challenges of CISA's call for transparent breach disclosures amidst corporate self-interest and the complexities of global AI regulation.

Thinking in Platforms • Kasper von Grünberg & Luca Galante • GOTO 2026

Thinking in Platforms • Kasper von Grünberg & Luca Galante • GOTO 2026

Kaspar von Grünberg and Luca Galante discuss their book "Thinking in Platforms," tracing platform engineering's origins from addressing key person dependencies to its critical role as an "operating model" for AI-first organizations. They highlight how AI agents necessitate standardized, productized internal platforms for effective deployment, emphasizing that platform efforts often fail due to social rather than technical challenges.

100x More Reliable Voice Agents

100x More Reliable Voice Agents

SLNG.ai introduces Unmute, an open declarative standard for voice agents, addressing platform lock-in and the limitations of current agent architectures. It proposes a shift from LLM-centric, sequential pipelines to declared execution with structural guarantees, enabling portable, cost-effective, and robust voice agents by breaking down complex interactions into modular, context-aware steps. This approach minimizes token usage, enhances determinism, and improves agent reliability compared to traditional single-prompt designs.

Debating RSI, the US-China Gap, and Jaggedness of Frontier AI

Debating RSI, the US-China Gap, and Jaggedness of Frontier AI

Jean-Stanislas Denain of Epoch AI and Nathan Lambert debate the nuanced trajectory of AI. They discuss the current state of RSI, the US-China AI capabilities gap (estimated 6-8 months), and the role of distillation and compute in closing it. The conversation also covers the challenges and differing paces of AI in robotics, insights from Chinese AI job postings, and the complex trade-offs between open and closed models regarding safety and misuse. They touch on Epoch AI's research philosophy and speculate on the intricate, evolving post-training recipes at frontier AI labs.

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