bergenholtz.bsky.social
bergenholtz.bsky.social
@bergenholtz.bsky.social
Always good to read Brooks' annual prediction post - and be reminded that real world progress and implementation (be it AI, robots or self-driving cars), is usually slower than expected.
Every Jan 1 I post a scorecard on predictions I made, with dates, on Jan 1, 2018 on cars (self-driving), robots, AI, & ML, and on human spaceflight. Besides telling which turned out right and which wrong in the last year I also talk a lot of smack about these topics. rodneybrooks.com/predictions-...
Predictions Scorecard, 2025 January 01 – Rodney Brooks
rodneybrooks.com
January 1, 2025 at 10:17 AM
Interesting write up, and intriguing approach to comparing the different types of LLMs.
December 7, 2024 at 8:31 PM
Reposted by bergenholtz.bsky.social
The debate on AI in Denmark is too much risk and not enough value. By focusing on the risk of AI and not the possible value, we are starting to lag behind in AI adoption.

Piece in Børsen with a group of cool collaborators across academia, politics, and industry.

borsen.dk/nyheder/opin...
“Frygt får Danmark til at halte bagud i AI-kapløbet”
Debatten om AI handler meget om frygt og for lidt om innovation. Vi skal turde at investere i forskning og udvikling, der sikrer, at AI bruges til at forbedre samfundet For nylig holdt en af os oplæg
borsen.dk
November 11, 2024 at 11:47 AM
Excellent example of this quote: "Students who use LLMs...asking for explanations benefit from usage. However, learning is impaired for students who excessively rely on LLMs to solve practice exercises for them and thus do not invest sufficient own mental effort."
www.linkedin.com/posts/christ...
Christian Hendriksen on LinkedIn: I recently showed up to teach an exercise class where I had prepared for a…
I recently showed up to teach an exercise class where I had prepared for a different set of exercises than the students. You can imagine how I must have felt…
www.linkedin.com
November 29, 2024 at 8:14 AM
This is a great explainer (with examples and visuals) of correlation vs causation, confounders & selection biases. Also useful in more general philosophy of science classes - goes straight into my curriculum, at a business school.
I teach quant methods to psych students. I miss good algebra-free intro materials on causal inference. So I have decided to make some and post them on my blog. Here is the first, in which I explain *why* we warn that "correlation does not equal causation": pedermisager.org/blog/why_doe...
December 2, 2023 at 7:34 AM
Any future case study or analysis on the recent Open AI spectacle is incomplete if they don't refer to
MCHammer's take x.com/MCHammer/sta...
November 22, 2023 at 9:20 AM