I'm hiring, anti-hype crash course in AI, and a remnant of the old Internet 🔍🌐💾
tech and data person #4
Howdy 🤠
I’m on the search for the perfect red lipstick. It’s part of my “newly 30, new me” glow-up, where I’m seeking to wear brighter, bolder colors and fashions, nurture a culture of self-care through meditation and physical movement, and generally commit to being a happier person. Much like this Pittsburgh weather, I’ve been a little grey. I want to change that.
If you have lipstick recommendations, holler💄
I’m hiring 🔍
I am hiring for an ✨Analytics Director✨ to lead and execute the vision for how the Working Families Party can leverage data analytics to build governing power for the multi-racial working class. This job is perfect for you if you
resonated with last week’s post about SQL style guides and being “opinionated af”,
are passionate about your BI/dashboarding tool of choice,
will defend your stance on pie charts to the death,
have been personally victimized by stripped zeroes in spreadsheets,
find joy in managing and motivating technical teams,
believe in movement-owned infrastructure,
and want to elect Working Families champions to all levels of office!
Please submit your application here with either answers to the listed questions or a cover letter (no need to do both). The deadline to apply is Friday, April 26th. I encourage you to apply even if you do not meet all the requirements. This was almost verbatim the job I applied to when I joined WFP, and I did not meet every listed requirement (and I think I did the job pretty well). And, if this job isn’t a match for you, I would appreciate the boost!
AI round up 🌐
I have updated the resources section of my website with the AI tools and materials that were most beneficial to me throughout my learning journey. My goal is to curate an "anti-hype" crash course that demystifies AI, providing a realistic and accessible introduction others can follow to enhance their understanding. This work is inspired by Vicky Boykis’ Anti-Hype LLM reading list but with an intention to be more accessible to the average political data practitioner. I am starting with a focus on a deep dive into the math and science of transformer architecture and AI safety and getting hands-on experience playing with LLMs through APIs.
Speaking of resources, I found my holy grail resource, Levelling Up in AI Safety Research Engineering. This self-study guide contains every resource imaginable on becoming a borderline expert on AI safety, including the math behind deep learning, software engineering principles, Python tutorials, a whole course dedicated to machine learning and transformers, and ends with a lesson on how to read white papers to continue to stay on top of the research. The estimated time to complete this guide is roughly two years, but that hasn’t stopped me from diving in.
Right now, I am working through this course on AI alignment, which is the very first resource in the document above. It has already taken me a week to get through the first two modules. I highly recommend this free course—it covered a bit of the technical side of LLMs and introduced me to AI safety, which I am now obsessed with.
I experimented with prompt engineering this week to see if AI could replace me at my job. To that end, I built a GPT that acts as “grug brained” manager: it responds to concerns, questions, and frustrations from a hypothetical data team member with an empathetic response from a manager who is no longer a “big brain” and instead is a grug. You can try it out for yourself here.
a remnant of the old Internet 💾
This substack, my blog, and most of my personality were inspired by the Internet of my youth: an eclectic world of diverse blogs and forums, the lawless realm of music pirating platforms like Limewire, simple browser games such as Neopets and Club Penguin, and the vibrant subcultures that thrived across these digital spaces. I am doing my small part to preserve the innocence and eccentricity of this earlier Internet, and this past week, I discovered a digital community that embodies this culture: the r/CelebrityNumberSix subreddit.
r/CelebrityNumberSix is dedicated to the communal effort of identifying an unknown celebrity, affectionately dubbed "Celebrity Number Six," found on a piece of fabric owned by a user named TontsaH (see the image above). The fabric features images of various celebrities, all of whom, except for number six, have been successfully identified by TontsaH. The subreddit is an online community where Redditors share clues, discuss theories, and leverage collective knowledge in hopes of finally discovering the identity of this elusive celebrity, completing the list of known figures on TontsaH's fabric.
I am obsessed with Celebrity Number Six. The effort to identify this unknown celeb has spanned years, and this community is still active nearly every day, posting new ideas as to the identity of the fabric. They have tried everything. They contacted the designers. They contacted the suppliers. ChatGPT and other AI tools have been of no help. People have manually combed through celebrity photo datasets. And yet Celebrity Number Six remains elusive.
Remarkably, I derive a strange sense of comfort from the fact that in our hyper-connected world, where personal data is so readily accessible, an image of a celebrity still manages to defy identification through reverse image searches, databases, and cutting-edge AI software. It kindles hope that some semblance of privacy may still be attainable and that an air of mystery can endure amidst the deluge of publicly available information.
bye bye 👋
That’s all for this week. I hope to hear from you, especially if you can tell me what to buy with my Sephora gift card.
Thank you,
brittany bennett, tech and data person