With all the hype surrounding Generative AI/LLM, and all the hallucinations mentioned in the news, what are these actually good for? As it turns out LLMs trained for code generation are helpful. But what if you don’t want your code going to some cloud provider? The following is a great solution for that. Here is … Read More
My prior posts used Lambda to do data transformation. But what if we could use a non-programmatic tool, in keeping with the Extract-Load-Transform mindset of the modern data pipeline. As it turns, we can: Amazon Athena can write data as well as query it. There are, of course, a few stumbles along the way. In this blog post I walk through the process of aggregating CloudTrail data using SQL.
In my previous post, Experiences in Fine-Tuning LLMs: Time + Power = Potato?, I covered my experiences around trying to fine-tune an LLM (large language model) with a dataset, which gave me less than stellar results. Ultimately, fine-tuning is best for a use-case where additional reasoning & logic needs to be added to an LLM, … Read More
In this final part of a three-part series, I add another aggregation step to combine a month’s worth of data and write it as Parquet.
If you’ve tried to use Ollama with Docker on an Apple GPU lately, you might find out that their GPU is not supported. But you can get Ollama to run with GPU support on a Mac. This article will explain the problem, how to detect it, and how to get your Ollama workflow running with all of your VRAM (which, on a Mac, is your DRAM too)!
So you want to execute some custom CUDA-based AI processing on a GPU, but don’t have the hardware? Have an AWS account? Try using the DLAMI machine instances. This article explains how to get started if you need OS-level access.
As I’ve written in the past, large numbers of small files make for an inefficient data lake. But sometimes, you can’t avoid small files. Our CloudTrail repository, for example, has 4,601,675 files as-of this morning, 44% of which are under 1,000 bytes long. In this post, I develop a Lambda-based data pipeline to aggregate these files, storing them in a new S3 location partitioned by date. Along the way I call out some of the challenges that face such a pipeline.
ViteJS (Vite) has rapidly emerged as one of the most exciting tools in the modern web development ecosystem. Vite offers developers a highly efficient and flexible build process with sane defaults to get a project up and running quickly. One of the many features that makes Vite truly stand out is its extensible Plugin API. … Read More
Earlier this year at PhillyETE, we had a great talk by Avdi Grimm and Jessica Kerr, REPLs All The Way Up: A Rubric For Virtuous Feedback Loops. In this talk, one of the key theses was to find ways to make exploring your code easier, via REPLs, scenario setups and other means. Many years ago … Read More
In this post I walk through several execution plans, explain what Redshift is doing in each, and highlight the parts of plans that indicate problems.
