The University of Chicago is hiring its first AI Librarian to lead innovative research support, ethics guidance & digital literacy initiatives in artificial intelligence. Apply by April 28, 2025.
Salary: $75–95k/year
More info: https://www.lib.uchicago.edu/about/thelibrary/employment/librarian-staff-opportunities/artificial_intel_lib/
#AI #DigitalScholarship #Librarianship #ML #AIethics #AcademicJobs #DataScience #ArtificialIntelligence
Welp, I caught the BIML Bibliography up to 2024. LOL. A labor of love, that's for sure. Only three more months of papers to enter...
We keep track of the #MLsec field by reading the science so you don't have to.
See our "top 5 papers" list to get started.
Taming the Wild West of #ML: Practical Model Signing with #Sigstore
https://security.googleblog.com/2025/04/taming-wild-west-of-ml-practical-model.html
Meta released Llama4. Llama-4-Scout-17B and Llama-4-Maverick-17B #Llama #LLM #AI #ML https://huggingface.co/meta-llama?sort_models=created#models
R in Maine: Connecting Ecologists, Medical Researchers, and Data Scientists
Donald Szlosek, the MaineR Users Group organizer, recently spoke with the R Consortium about the group’s transition from a city-based meetup to a statewide community and its efforts to engage a diverse audience. He highlighted his work in real-world evidence studies, where R is critical in causal inference and machine learning validation.
Making OCaml Safe for Performance Engineering https://lobste.rs/s/ujvpdn #slides #video #compilers #ml #performance
https://youtube.com/watch?v=g3qd4zpm1LA
We're pleased to announce that you can now host and share your Gradio applications on Posit Connect!
Gradio is an open-source Python package that allows you to quickly build a demo or web application for your #ML model, #API, or #Python function.
Learn more in the blog post: https://posit.co/blog/posit-connect-gradio-support/
Roguetype: The first ever roguelike written in the OCaml type system https://lobste.rs/s/abunxs #ml #plt
https://github.com/Octachron/roguetype
Hot-reloading in Python can be slow since the entire server process must be restarted from scratch. The Tach package speeds this up by building a dependency map. Evan Doyle explained how it works with an interesting example.
https://www.gauge.sh/blog/how-to-build-hot-module-replacement-in-python
ICYMI: I'll be talking at the Melbourne #ML and #AI Meetup in a couple weeks' time about the #TokenWars - the conflict for data to train LLMs and the fight by IP rights holders to protect their data from scrapers.
Come learn about how #LLMs are trained on huge volumes of tokens with transformers, why those tokens are becoming more economically valuable, and what you can do to protect your token treasure.
You'll never look at ChatGPT or data the same way again.
Huge thanks to @jonoxer for the recommend, and to Lizzie Silver for the behind the scenes wrangling.
https://www.meetup.com/machine-learning-ai-meetup/events/306548300
GenAI is so expensive that some (foundation model building) companies will not survive. This is a major cause of technical lock in...scientific exploration of the space is incredibly expensive.
Who can do A/B testing when it is that expensive?
https://www.theregister.com/2025/03/31/llm_providers_extinction/
Basics of Mathematical Notation for #MachineLearning https://machinelearningmastery.com/basics-mathematical-notation-machine-learning/ #ML #AI
Using LLMs does not make one an expert in ML. Ask about how does a model actually work, step by step and I can guarantee the answer is be hallucinatory.
Same devs that were laid off because “vibe coding” is here, will be rehired because of the 100x tech debt that is too great without the fundamentals of software engineering and critical thinking when thinking long term, scalability and ease of maintenance.
LLM is great for a Proof of Concept, not production code. Host your own git server, keep it away from LLM training and let’s see the shitshow and AI bubble burst into oblivion.
My new favorite pasttime is reimplementing ML algorithms from scratch. I am currently working on a JS implementation of tSNE for embeedding visualization. Can be useful for https://embeddings.svana.name.
There are some existing alternatives out there, but they are almost 10 years old. My goal is to create an implementation that works well with the modern JS stack and doesn't use any external dependencies.
As usual, @dangoodin has written an excellent security explainer article. This one is about prompt injection...but not the usual trial and error whack-a-mole prompt manipulation by pizza guy...instead, automated manipulation by search in gradient space.
This technique is new enough that we're discussing the original paper only today at BIML. It makes the whole boring front door malicious input thing much more interesting.
𝗪𝗲𝗹𝗰𝗼𝗺𝗲 𝘁𝗼 𝘁𝗵𝗲 𝘀𝗲𝗺𝗮𝗻𝘁𝗶𝗰 𝗮𝗽𝗼𝗰𝗮𝗹𝘆𝗽𝘀𝗲
𝘚𝘵𝘶𝘥𝘪𝘰 𝘎𝘩𝘪𝘣𝘭𝘪 𝘴𝘵𝘺𝘭𝘦 𝘢𝘯𝘥 𝘵𝘩𝘦 𝘥𝘳𝘢𝘪𝘯𝘪𝘯𝘨 𝘰𝘧 𝘮𝘦𝘢𝘯𝘪𝘯𝘨
https://www.theintrinsicperspective.com/p/welcome-to-the-semantic-apocalypse
Big update to my Embeddings Playground. I added support for the first free-to-use embedding model: "all-MiniLM-L6-v2" from Sentence transformers (https://www.sbert.net/).
Try the Embeddings playground here: https://embeddings.svana.name
This week newsletter will be out tomorrow. Interesting stuff by Tanner Young, Max Gabrielsson, Tom Nijhof-Verhees, Charles de Villiers & Lee Vaughan covered
https://newsletter.piptrends.com/p/async-agnostic-decorators-vector
