Posts

Why Top Founders Are Racing Into AI Infrastructure

Why Top Founders Are Racing Into AI Infrastructure

a16z's new Machine Age Fund addresses the unprecedented demand for AI infrastructure, shifting the bottleneck from models to the foundational hardware. The discussion highlights surging Hyperscaler CapEx, component supply crunch extending to 2028, and the exponential compute needs driven by reasoning and agents. It explores how AI turns engineering problems into capital/compute challenges, identifying opportunities for new infrastructure companies in chips, power, and data center redesign, and the emergence of experienced "systems founders" to rebuild the computing stack for this new era.

CLAUDE.md, AGENTS.md, Skills, Hooks and Subagents: A Field Guide to Steering AI Agents (Ep. 1022)

CLAUDE.md, AGENTS.md, Skills, Hooks and Subagents: A Field Guide to Steering AI Agents (Ep. 1022)

Episode 1022 dissects the crucial aspect of effectively steering AI agents by determining the optimal placement of instructions to ensure reliability and cost-efficiency. It explores seven distinct methods for instruction delivery, contrasting instructions as probabilities with hooks as guarantees, and highlights the industry-wide adoption of standards like `agents.md` and the importance of human-crafted guidance for superior agent performance.

Analyzing Group Chat Encryption in Messaging Applications

Analyzing Group Chat Encryption in Messaging Applications

This talk details a formal security analysis of group chat encryption algorithms in popular messaging applications like MLS, Session, and Keybase. It introduces Symmetric Sign Encryption (SSE) to model these protocols, identifying critical vulnerabilities such as insider replay and reordering attacks in MLS and Session due to insufficient context binding. The analysis highlights the complexities of key-dependent messages and key reuse, demonstrating how formal methods can pinpoint subtle design flaws and suggest robust mitigations for real-world secure communication.

Invited Research Talk: Measuring Generalization in EEG Foundation Models

Invited Research Talk: Measuring Generalization in EEG Foundation Models

This talk presents a multi-dimensional evaluation and interpretability framework for EEG foundation models. It reveals that current models often fail to outperform supervised baselines for BCI tasks, lack robustness to sparse channels, and exhibit an aperiodic low-frequency bias, making them better at capturing subject-specific rather than task-specific information. The analysis highlights critical deficiencies and suggests future directions for pre-training objectives and data collection to improve generalization.

TruthTable: A Verifiable Query Engine

TruthTable: A Verifiable Query Engine

TruthTable is a verifiable database engine that produces succinct cryptographic proofs for SQL query execution. It supports a wide range of SQL queries by leveraging query plans, polynomial encoding, and operator-specific PIOPs. It features a query planner with proof-specific optimizations and a novel batch compilation engine (ARCPOP). Benchmarks on TPC-H show average proving times of 55 seconds, verification times of 32 milliseconds, and proof sizes of 24kB, significantly outperforming prior academic and industrial systems in speed and expressiveness.

AI, Radio Astronomy, and the Search for Life Beyond Earth

AI, Radio Astronomy, and the Search for Life Beyond Earth

Ramiro Caisse Saide presents a multimodal deep-learning approach for technosignature detection in radio astronomy, using observations from Breakthrough Listen at MeerKAT. He investigates combining spectrograms with I/Q signal representations to improve signal detection and classification, particularly in low signal-to-noise environments. The talk also covers his extensive background in AI education, software development, the motivations behind SETI, fundamental radio astronomy concepts, and studies on Earth's own radio leakage.