United States
I'm a technical writer, editor, and journalist covering AI and machine learning, with a focus on real-world applications, business use cases, and technical deep dives. If you're looking for technical projects, check out my GitHub at the link below.
News story covering the conference AI in Finance, where industry leaders discussed technical, security, and compliance challenges related to generative AI in fintech and banking.
Feature spotlighting the individuals who build and maintain open source software and the challenges they face amid rising enterprise FOSS adoption. Received a Regional Gold award from ASBPE, which recognizes outstanding business journalism.
Interview with a longtime trust and safety leader on generative AI's impacts on the internet landscape. Received National and Regional Gold awards from ASBPE, which recognizes outstanding business journalism.
Feature on industry trends in AI/ML for 2025, including multimodality, agentic AI, and major shifts in the AI model and vendor landscapes.
Documentation I wrote for PromptKeep, a Python-based CLI tool I built. PromptKeep stores prompts as Markdown files with YAML metadata, making them easy to manage and version control, and lets you quickly find and edit stored prompts and copy them to your clipboard via the command line.
Documentation I wrote for Birdwatch, a Python-based CLI tool I built. Birdwatch lets you log bird sightings via the command line, including species, location, count, and notes, and export your locally stored JSON data to CSV for analysis.
Feature exploring how the legal sector is approaching generative AI tools, with a focus on early use cases, potential risks, and best practices.
Case study showcasing how a fashion brand found creative ways to use hallucinations to its advantage when building an internal generative AI tool, reported from the AI Summit conference.
Coverage of a report produced by in-house industry analysts, who surveyed IT and business decision-makers about the state of the generative AI market.
Technical explainer on the mixture-of-experts model architecture in machine learning.
Deep dive into the differences between OpenAI's GPT-4 and GPT-4o models, covering aspects like capabilities, performance, and pricing.