Design Patterns for LLM-Powered Software
Posted on May 15, 2023
If you aren’t too familiar with large language models or how we can use them to solve problems, check out this post. Generative large language models (LLMs) like ChatGPT possess extraordinary problem-solving abilities. However, they are difficult to use. One key challenge lies in their cost and latency. These models...
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Tags:
Machine Learning, Machine Learning Systems, ML, Large Language Models, GPT
Using Large Language Models to Solve your Problems
Posted on May 14, 2023
Generative large language models (LLMs) like ChatGPT will revolutionize the way we approach complex problems. Enormous amounts of custom labeled data are no longer required to train many specialized AI systems. LLMs make generalized problem-solving capabilities vastly more accessible. This has profound implications for software development, data science, and machine...
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Tags:
Machine Learning, Machine Learning Systems, ML, Large Language Models, GPT
One Quick Trick to Increase ML Engineer Productivity
Posted on February 26, 2023
ML models are collaboration bottlenecks. Suppose your team owns a binary classification model, and you have decided that increasing this model’s recall without reducing precision is very important for the business. You’ve put 5-10 engineers on the job. The Problem What should these engineers do? There are many ways to...
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Tags:
Machine Learning, Software Engineering, ML Engineering
How to Execute
Posted on November 26, 2022
One of the hallmarks of a great engineer is the ability to execute. An engineer who can execute gets things done. They crush tickets, pump out designs, spin up features, answer critical data questions, improve models, and prototype new ideas quicker than their peers. How to Execute Engineering projects are...
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Tags:
Software Engineering, Engineering Leadership
An Ensemble of Kan Extensions
Posted on August 14, 2022
A common problem in machine learning is “use this function defined over this small set to generate predictions over that larger set.” Extrapolation, interpolation, statistical inference and forecasting all reduce to this problem. The Kan extension is a powerful tool in category theory that generalizes this notion. In a recent...
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Tags:
Machine Learning, Category Theory