Neal Lathia is a machine learning practitioner and writer exploring how AI is built, evaluated, and adopted in the real world. His blog focuses on AI progress, responsible deployment, and the human impact of machine learning systems.
10 articles from this blog
A call to critically review and update your core assumptions about AI's capabilities, risks, and applications in development and strategy.
Analysis of a realistic AI voice agent demo, highlighting key design principles for bridging the gap between demos and real-world systems.
Argues that reading raw AI input/output data is essential for developing true intuition about system behavior, beyond just metrics.
Critiques the limited scope of current customer support automation and argues for more ambitious AI solutions across industries.
A developer shares talks on building safe AI agents for high-stakes industries using Go and durable execution, and announces an upcoming meetup.
A guide on transitioning into AI careers, distinguishing between working 'on' AI models and 'in' AI infrastructure, products, and engineering processes.
Author announces moving their technical blog to a new platform focused on AI agent systems and Gradient Labs' work.
A developer shares insights from building an AI audit prototype, discussing the importance of defensibility and lessons from banking model audits.
Analyzes common pitfalls in AI adoption, arguing that technical and product maturity models can hinder practical implementation.
An update on how Monzo integrated machine learning across its organization in 2022, covering team structure, growth, and new initiatives.
