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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

No Memory, No Harness: Why the Database Is the Last Line of Defense — Kay Malcolm, Oracle

No Memory, No Harness: Why the Database Is the Last Line of Defense — Kay Malcolm, Oracle

Kay Malcolm discusses how AI, while boosting individual performance, often hinders overall team productivity due to fragmented context. She introduces the concept of an "agent harness" with "memory" as its central nervous system, vital for sharing context. Drawing on personal experiences with database sprawl, she highlights the inefficiencies of storing diverse memory types across multiple data stores. Malcolm then presents Oracle's AI database (26AI) as a unified solution, capable of natively managing all memory types in a single platform, thereby enhancing team collaboration and solving the context problem for enterprise AI agents.

We let an AI agent execute Bash and lived to talk about it — Sarah Sanders, PostHog

We let an AI agent execute Bash and lived to talk about it — Sarah Sanders, PostHog

Sarah Sanders, a context engineer at PostHog, discusses the security implications of building an agentic CLI tool, "The Wizard," which automates developer workflows. She highlights the inherent risks of agents capable of executing commands, labeling it a "malware starter pack," and details how PostHog evolved its security posture from basic allow lists to a sophisticated "defense in depth." Key insights include the principle that "attacks compose, code review doesn't," the discovery of internal supply chain vulnerabilities through the "Context Mill," and the development of "The Warlock," a deterministic scanner using YARA rules. Sanders emphasizes the critical distinction between deterministic enforcement and probabilistic judgment, explaining how an LLM-powered "Triage" layer acts as an adviser (failing closed) rather than a bouncer, preserving the integrity of their security model.

Greg Brockman Says AGI Has Arrived

Greg Brockman Says AGI Has Arrived

OpenAI President Greg Brockman discusses the advent of the "AGI era" with models like Astra, highlighting the transformative power of AI agents capable of computer use and autonomous task execution. He delves into critical safety and security challenges, emphasizing the "defender's window" for proactive cybersecurity, and explores AI's evolving impact on employment, global sentiment, and the future of proactive AI assistants.

How Developers Secure AI-Generated Code: 5 Security Best Practices

How Developers Secure AI-Generated Code: 5 Security Best Practices

Discover five essential principles for implementing shift-left security in AI-assisted software development. Jeff Crume explains how to secure AI-generated code by focusing on outcome validation, integrating security early, scrutinizing dependencies, validating intent, and maintaining continuous security practices for more trustworthy AI-powered workflows.

Essential Skills for Becoming an AI Engineer: RAG, AI Agents, & More

Essential Skills for Becoming an AI Engineer: RAG, AI Agents, & More

Cedric Clyburn outlines the essential skills for AI engineering, distinguishing it from ML research. He details a three-tier skill stack covering foundational programming (Python, Git, APIs), AI-specific techniques (embeddings, RAG, AI agents), and deployment strategies (containerization, observability). The discussion emphasizes judgment over code generation and highlights key use cases like RAG systems and agent-based solutions.

Navier-Stokes and AI generated work: If You Can't Explain It, Did You Really Do It?

Navier-Stokes and AI generated work: If You Can't Explain It, Did You Really Do It?

Ben Lorica and Evangelos Simoudis discuss the profound impact of AI on knowledge work, examining the Navier-Stokes controversy as a case study for IP protection and the need for human validation of AI-generated output. They explore the Chinese concept of "involution" and its implications for global productivity and Western knowledge workers, contrast US and Chinese approaches to AI risk, and reflect on 9/11's role in accelerating the big data revolution.

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