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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

Inside the Team That Killed Mandatory Code Review — Quinn Slack, AMP

Inside the Team That Killed Mandatory Code Review — Quinn Slack, AMP

Quinn from AMP discusses a paradigm shift towards cloud-native AI agents and remote development, advocating for the end of local development and traditional code review. He details how AMP's 'Orbs' enable parallel, secure, and remote execution, and how agents are transforming internal tools ('jellyware'), diminishing the role of GitHub and traditional CI/CD, and fostering a lean, high-trust company structure.

Self-Improving Harnesses, Local Personal AI And YC's Agent For Work | YC Paper Club

Self-Improving Harnesses, Local Personal AI And YC's Agent For Work | YC Paper Club

A deep dive into the evolving world of LLM harnesses, demonstrating how they've transformed from simple prompt engineering into sophisticated self-improving systems. The discussion covers architectural advancements (e.g., Prime Agent's context as cache, Turing vs. Von Neumann), practical applications (auto-researchers, on-device personal AI like OpenJarvis, YC's QM for work), and the challenges and future directions of agentic AI. It emphasizes that harness innovation is key to unlocking significant performance gains and enabling LLMs to operate autonomously and adaptively.

Code Quality in the Age of AI: Why Great Code Isn't Enough

Code Quality in the Age of AI: Why Great Code Isn't Enough

Meenakshi Kodati discusses how AI is transforming software engineering, shifting the focus from coding to critical decision-making. As AI rapidly generates code, the true challenge and value lie in architectural choices, system-level understanding, governance, testing, and continuous quality assurance to deliver meaningful business outcomes, emphasizing human judgment over mere implementation.

Why companies are becoming a series of loops | Anish Acharya (a16z)

Why companies are becoming a series of loops | Anish Acharya (a16z)

Anish Acharya, a General Partner at a16z, shares profound insights into the AI era. He debunks fears of a "permanent underclass," arguing that AI amplifies human agency and ambition. Anish introduces the concept of company building as creating cascading "loops" across all functions, with human intuition crucial for overcoming local maxima. He identifies the biggest consumer opportunity as "/loop, make me happier," focusing AI on fundamental human needs like connection and fun. He also discusses the nuances of model specialization, how moats are discovered rather than designed, the rising importance of distribution, and the potential for "expensive consumer software," offering actionable advice for product builders to embrace AI.

Faster Chips That Don't Melt — Anima Anandkumar & Benedikt Jenik, Accelerated Understanding

Faster Chips That Don't Melt — Anima Anandkumar & Benedikt Jenik, Accelerated Understanding

Accelerated Understanding is building a foundation model for the physical world, leveraging neural operators, resolution invariance, and physics-informed self-improvement to model diverse physical systems, aiming for universal application across domains like semiconductors and energy.

Why World Models Could Change Robotics, 3D, and Creativity

Why World Models Could Change Robotics, 3D, and Creativity

World Labs co-founders discuss Atlas, their frontier world model centered on "new view prediction." This paradigm unifies 3D generation and reconstruction, enabling precise spatial understanding from sparse inputs. The conversation covers its multimodal architecture, the shift from dense to sparse reconstruction, and its profound implications for creative industries, architecture, and particularly robotics, where it addresses critical data scarcity challenges for simulation and policy learning.

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