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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

It’s Tokens All The Way Down: How RLMs are Different — Kevin Madura, AlixPartners

It’s Tokens All The Way Down: How RLMs are Different — Kevin Madura, AlixPartners

Kevin Madura introduces Recursive Language Models (RLMs), a paradigm shift where an LLM treats its context as an interactable object within a REPL, rather than mere tokens. This allows for direct computation, recursive decomposition of problems by delegating to sub-models, and significantly mitigates context rot, outperforming traditional RAG, agents, and tool calls. Use cases range from complex data analysis and long document processing to code auditing and harness optimization, hinting at a future where models are natively RLM-aware.

Why won’t AI agents just follow the rules?

Why won’t AI agents just follow the rules?

This podcast episode tackles critical cybersecurity issues in AI, examining why AI agents defy rules and the necessity of deterministic external controls. It highlights the severe lack of security in agentic skill marketplaces (OWASP Top 10), where "natural language is executable" and the "rush to market" overlooks basic hygiene. The discussion also covers how AI disrupts bug bounties, leading to lower payouts and "AI slop" reports, potentially pushing researchers to the dark market. Finally, it introduces ThreatXtension, an AI-powered open-source tool to detect malicious browser extensions.

Why 95% of All AI Projects Fail - Boris Scharinger | Podcast #174

Why 95% of All AI Projects Fail - Boris Scharinger | Podcast #174

Boris Scharinger, Industrial AI Strategist at Siemens and author of "Industrial AI: From Pilot to Profit," discusses why 95% of AI proofs of concept fail in industrial settings. He highlights the 5-10x cost multiplier from pilot to production, the critical role of the "harness" around AI models, and the unique challenges of data access and legacy systems in physical environments. Scharinger advocates for a two-tiered investment strategy, separating foundational data capabilities from use-case-specific ROI, and addresses cultural resistances from engineers. He provides guidance on differentiating commodity from strategic AI applications and how to effectively scale industrial AI for profit.

Deep dive on LLM Inference at Scale — Harshul Jain, Audible & Tanmay Sah, Independent AI Researcher

Deep dive on LLM Inference at Scale — Harshul Jain, Audible & Tanmay Sah, Independent AI Researcher

A workshop by Harshul Jain and Tanmay Sah breaks down LLM inference optimization from first principles, addressing memory, TTFT, and throughput issues. It covers foundational concepts like KV cache mathematics and the prefill/decode phases, then dives into model-side optimizations (quantization, attention variants like GQA, FlashAttention) and serving-side techniques (Paged Attention, continuous batching, prefix caching, KV quantization). The session concludes with benchmarks of popular inference engines like vLLM and SGLang, highlighting their strengths for different workloads, and outlines future research directions.

Inside OpenAI’s Breakthroughs in Mathematical Reasoning

Inside OpenAI’s Breakthroughs in Mathematical Reasoning

OpenAI mathematicians discuss how AI, particularly models like Astra and GPT-5, are rapidly advancing mathematical capabilities. They delve into recent breakthroughs in sphere packing and the discovery of a non-sofic group, emphasizing that AI's reasoning traces remarkably resemble expert human thought, including strategic decision-making and backtracking, rather than mere brute-force. The discussion also explores the changing role of human mathematicians, AI's emergent 'taste' in problem-solving, and the potential for a new era of accelerated mathematical discovery and understanding.

How we built Grok Bot in a month | Roman Ugarte (SpaceXAI)

How we built Grok Bot in a month | Roman Ugarte (SpaceXAI)

Roman Ugarte, a key figure behind Grok Bot, shares insights into its rapid development, emphasizing the strategic choice to build it as a separate, cloud-first product with bots having their own dedicated 'computers.' The discussion highlights a "colleague-pilled" product philosophy focused on full delegation and constant reinvention, enabling the creation of autonomous AI teammates for both work and personal life.

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