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Everyone Has the Same AI Models. Here's What Sets Agents Apart - Richmond Alake, Oracle

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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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Everyone Has the Same AI Models. Here's What Sets Agents Apart - Richmond Alake, Oracle

Everyone Has the Same AI Models. Here's What Sets Agents Apart - Richmond Alake, Oracle

Richmond Alake argues that after the control plane, agent architectures need an intelligence plane covering what an agent knows, remembers, is allowed to see, and how it improves. He draws on the WWII Midway codebreaking story to separate information from intelligence, then demos a governed agent using an ontology and semantic layer that answers correctly about 99% of the time with far fewer tokens than a naive agent. The talk also covers Oracle's agent memory package, deep data security, private inference, and fine-tuned decision models for memory routing.

Using Agents for Long-Horizon Financial Work — Aman Singh, Arca

Using Agents for Long-Horizon Financial Work — Aman Singh, Arca

Aman Singh, head of AI at Arca, explains how the firm is building an AI-native wealth management business in which agents run back-office work, monitor clients proactively, and coordinate multi-day workflows, while humans retain advisory relationships and trade execution. The discussion covers model selection through internal benchmarks, a model-agnostic custom harness with tiered routing, persistent memory for long-running tasks, deterministic and LLM-based guardrails, auditability by default, decision models for financial accuracy, and feedback loops that turn staff edits into evals.

THE $800B COMPUTE TRAP

THE $800B COMPUTE TRAP

Ben Lorica and Evangelos Simoudis work through Anthropic's S-1 filing, weighing its striking growth and improving unit economics against compute commitments, falling prices from open-weight models, and dependence on coding. They then examine SpaceX's emerging neocloud business and close with a debate over proposed frontier AI regulation, from self-improvement limits to independent testing and incident disclosure.

Technology

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Why Founders Are Betting Big on Factories, Mines, and Energy

Why Founders Are Betting Big on Factories, Mines, and Energy

Erin Price-Wright and Connor Love unpack the AD50 and the rebuilding of America's industrial base, covering how defense demand is financing manufacturing capacity for commercial markets, how AI is reshaping factory economics, how a new generation of founders applies lessons from SpaceX, Tesla, Anduril, and Palantir to mining, energy, and manufacturing, and why private capital is now willing to fund physical infrastructure before government demand is guaranteed.

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.

Recent Post

Have we finally solved social engineering? Plus: World Cup fraud, AI IDs and an IBM/OpenAI collab

Have we finally solved social engineering? Plus: World Cup fraud, AI IDs and an IBM/OpenAI collab

This podcast episode explores the intersection of AI and cybersecurity, discussing whether AI-native operating systems can curb social engineering, the impact of AI agents on identity and security, and the ongoing threat of cybercrime exploiting major events. It also highlights IBM's new partnership with OpenAI to enhance application security using advanced AI models.

⚡️Every product of the future will be a living system — Ronak Malde, Trajectory.ai

⚡️Every product of the future will be a living system — Ronak Malde, Trajectory.ai

Ronuk Malde, CEO of Trajectory.ai, discusses his journey from building AI coding agents at Windsurf to his current focus on continual learning for enterprise AI. He shares insights on leveraging real-world user data, the unique challenges of model acquisition, and how Trajectory.ai's platform, powered by innovations like scaled SDPO and a novel training stack, enables dynamic, always-learning AI models for diverse industries from legal to finance.

3‑2‑1 Backup Rule Explained: Protect Your Data from Disaster

3‑2‑1 Backup Rule Explained: Protect Your Data from Disaster

Jeff Crume outlines essential data resiliency strategies, starting with the 3-2-1 backup rule—three copies, two media types, one offsite—and expanding to include immutable or air-gapped backups, rigorous testing, and encryption. He emphasizes these principles for robust disaster recovery, ransomware protection, and minimizing costly downtime, highlighting the trade-offs in achieving high availability.

6 Things to Know about AIE World's Fair 2026

6 Things to Know about AIE World's Fair 2026

Discover the AI Engineering World's Fair 2026, the largest iteration yet, offering an unparalleled deep dive into AI engineering with expanded tracks on auto research, GPU specialization, and new verticals like finance and healthcare. Highlights include an innovative expo experience, exclusive leadership initiatives like the "Token Billionaires Program," and unique side events fostering community, including "Posters on AI" where attendees can defend their tweets. This event is designed to be a curated hub for practical, cutting-edge insights and networking in the AI/ML professional landscape.

The data black hole at the center of AI

The data black hole at the center of AI

AI progress is fundamentally driven by vast amounts of data and compute, rather than improvements in sample efficiency, creating a stark contrast with human learning. This essay explores the "black hole of data" powering AIs, quantifies the massive sample-efficiency gap between humans and machines, counters common objections, and discusses the implications for white-collar automation and future AI research.

The Media Game Has Changed

The Media Game Has Changed

The conversation explores the shift from legacy media to creator-led platforms, why authenticity has become a competitive advantage, and how founders can build audiences by communicating directly with customers, employees, and the public. They discuss podcasts, social media, storytelling, corporate communications, and the changing relationship between companies, journalists, and audiences. Along the way, they examine how founders can develop a public voice, why some leaders become influential communicators, and what it means to build a brand in a world where distribution is increasingly decentralized.

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