[This is] based on lessons learned from researching and creating Large Language Model (LLM) prompts for production use cases. It covers the history around LLMs as well as strategies, guidelines, and safety recommendations for working with and building programmatic systems on top of large language models, like OpenAI’s GPT-4.
A collection of pure POSIX sh alternatives to external processes.
This ethical and repairable design proves Bluetooth headphones can be more sustainable
A compact cyberdeck, featuring a QAZ 35% keyboard, Banana Pi M2 Zero SBC and 7.9 inch monitor.
I quickly learned that writing one giant query with a bunch of joins or even bunch of Python helper functions could get me stuck. My transformation functions weren’t flexible enough, or my joins were too complicated to answer the endless variety of questions thrown my way while keeping the numbers correct.
Instead, the easiest way to be fast, nimble, and answer all the unexpected questions was to prepare a giant table or dataframe and limit myself to it. As long as I understood the table’s contents, it was harder to make mistakes. I could group by and aggregate on the fly with confidence.
Only as traffic approaches, Norway’s auto-dimming roads get brighter. New LED lights dim to 20 percent when no cars are in area. When a car drives by, the lights turn to 100 per cent. Thus it reduces the country’s carbon footprint.
Use and compare all the popular LLMs
Over the past six months, I have spent my spare time studying Capcom success stories and in particular the genesis of Street Fighter II. If discovering the engineering behind the CPS-1 was fascinating, I found the side story of how developers tracked ROM budget using paper and scissors equally interesting.
See current activity on Bluesky in realtime.
This week, a tale of two Shawns/Seans, their impossible dream, and the file sharing service that lived fast, died young, and helped create the internet as we know it. Plus, Metallica.
I wanted to explore the malicious, confusing, and deceitful things that occur after signing up for digital services, as well as how design can nudge us to forget about a free trial or accidentally sign up for things that we didn’t intend to.
Dark patterns are often most egregious with subscriptions and free trials, especially when attempting to cancel, so I focused on those.
Though it makes me feel like a grandmother on her deathbed to admit it, I remember the days when the internet was vast, when there seemed to be more places to go than anyone could ever visit and infinite things to read. What you saw was not determined by some highly protected coded algorithm that lives somewhere in the cloud. You could just go out and find it.
I have a rail line right under my apartment, so I built a small computer vision app running on a Rasperry Pi which records each train passing, and tries to stitch an image of it.
More information about this project can be found here.
