Good blog post, this helped clarify some things for me.

My concern is we don't have answers to many of the open questions or limitations even with vanilla LLMs, so throwing a bunch of them together in more complex ways seems... dumb?

LLMs struggle with perception, not reasoning, in ARC-AGI by Mikel Bober-Irizar

What made o3 so much better than previous models on this benchmark?

anokas.substack.com/p/llms-strug...

The article discusses how the AI ethics community's focus on "fairness" significantly limits how it approaches and addresses algorithmic harm, and proposes reframing harms in terms of domination and oppression per Iris Marion Young's framework.

firstmonday.org/ojs/index.ph...

I'm sorry, this has to be the dumbest study with the dumbest framing. This is an actual sentence from the summary:

'Moreover, as in humans, age is a key determinant of cognitive decline: “older” chatbots, like older patients, tend to perform worse on the MoCA test.'

goblin.tools/About is the one LLM "product" that really hits the sweet spot for me in terms of a useful and specific application of generative AI. Is there more stuff like this? I just love the idea of a collection of simple, task-specific tools with a basic interface.

In fact, @sayash.bsky.social and I have just published an essay with them, where we play our usual role of looking at the evidence and tamping down AI hype and fears instead of playing them up.
knightcolumbia.org/blog/we-look...

(Cross-posted to AI Snake Oil aisnakeoil.com/p/we-looked-...)

It's been interesting to witness in real-time how the usage of "algorithm" in many places has shifted from a neutral "sequence of instructions" to a negative "controlled ordering and boosting of information".

This Thanksgiving we pitted ChatGPT against Claude in battle of the side dishes.

Claude gave us Za'atar Roasted Cauliflower with Whipped Feta and ChatGPT gave us Stuffed Acorn Squash with Quinoa, Kale, and Goat Cheese. Which was better? 🧵

In August I had the pleasure of presenting a talk at posit::conf, called A Future of Data Science, in which I assert that data science exists because statistics missed the boat on computation.
The video is up now...
www.youtube.com/watch?v=YKMZ...

We're back!