author
AI Advocate
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Snorkel AI
Jonathan Schlosser is an AI Advocate at Snorkel.ai. He has previously worked as an AI Engineer, an Educator, and Founder. He has taught graduate-level AI and Data Science courses at UNC Chapel Hill for the last few years, and has taught hundreds of data science professionals through programs with Correlation One, Amazon, Google, and others. With 10+ years across the data and AI spectrum, from data science roles to building AI-driven applications, he writes about deep learning, LLMs, and AI agents with a direct and simplified instructional approach.
The latest from Jonathan Schlosser
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From Foundational Competency to Expert Performance: A Curriculum Approach to Model Development
Mengqi Yuan (XLANG Lab, University of Hong Kong) presents OSWorld 2.0, a benchmark of 108 long-horizon, real-world computer-use workflows where even frontier AI agents complete only 20.6% of tasks outright after 300+ steps each.
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Fable 5.1 on Frontier Coding Tasks: Efficient Successes, Distinct Failure Modes
We evaluated Fable 5.1 on a series of frontier coding tasks from our proprietary Terminal-Bench+ dataset and compared the results against Opus 5. Fable remained competitive across most categories and was materially more efficient on successful runs, while its gap was concentrated in a small set of terminal-heavy and build/dependency tasks. Because category sizes are small and uneven, we treat…
