sisyphean

The original thread is on the devil’s website and I don’t want to direct traffic to it, so here’s a link to the tweet instead:

https://twitter.com/davidfowl/status/1671351948640129024?s=46&t=OEG0fcSTxko2ppiL47BW1Q

Quote:

In this work, we introduce TinyStories, a synthetic dataset of short stories that only contain words that a typical 3 to 4-year-olds usually understand, generated by GPT-3.5 and GPT-4. We show that TinyStories can be used to train and evaluate LMs that are much smaller than the state-of-the-art models (below 10 million total parameters), or have much simpler architectures (with only one transformer block), yet still produce fluent and consistent stories with several paragraphs that are diverse and have almost perfect grammar, and demonstrate reasoning capabilities.

Related:

• Models (you can try them online):
  • TinyStories-1M
  • TinyStories-33M
• An interview with the authors (highly recommended): The Tiny Model Revolution with Ronen Eldan and Yuanzhi Li of Microsoft Research

cross-posted from: https://programming.dev/post/120039

HN discussion: https://news.ycombinator.com/item?id=36400053

HN discussion: https://news.ycombinator.com/item?id=36400053

cross-posted from: https://programming.dev/post/119195

AI isn’t magic, of course, but what this weirdness practically means is that these new tools, which are trained on vast swathes of humanity’s cultural heritage, can often best be wielded by people who have a knowledge of that heritage. To get the AI to do unique things, you need to understand parts of culture more deeply than everyone else using the same AI systems.

AI isn’t magic, of course, but what this weirdness practically means is that these new tools, which are trained on vast swathes of humanity’s cultural heritage, can often best be wielded by people who have a knowledge of that heritage. To get the AI to do unique things, you need to understand parts of culture more deeply than everyone else using the same AI systems.

Prompt:

open source, federated software connecting free people across the globe, without commercial interest --q 2 --v 5.1

TL;DR (by GPT-4 🤖):

• The author reminisces about life before the ubiquity of cellphones and the internet, particularly focusing on the after-work hours.
• The concept of being unreachable after work hours is alien to younger generations who are constantly connected and expected to be available at all times.
• The author and his peers recall the days when work emails didn't exist, and work communication was restricted to work hours only.
• The article highlights how the growth of remote work and the pandemic have blurred the boundaries between work and personal time, with a survey suggesting that U.S. workers were logged into their employers' networks 11 hours a day in 2021, up from 8 hours pre-pandemic.
• The author interviews people of his age group about their experiences around 2002, when they were about 27 years old. They recall waking up just in time for work, commuting with newspapers or books, and using work phones for personal calls.
• After work, they would engage in activities like swing dancing, improv classes, or simply visiting friends. Plans were made over the phone or via work email, and people were less likely to flake as there was no option to send a last-minute text.
• They recall the days of watching whatever was on TV, renting movies from Blockbuster, and playing games on their desktop computers.
• The article concludes with a reflection on how different life was before the internet and cellphones became a constant presence in our lives.

cross-posted from: https://programming.dev/post/115656

Quote from the article:

And the terrible, horrible thing about it is THIS IS A GOOD LETTER. It is better than most letters of recommendation that I receive. This means that not only is the quality of the letter no longer a signal of the professor’s interest, but also that you may actually be hurting people by not writing a letter of recommendation by AI, especially if you are not a particularly strong writer. So people now have to consider that the goal of the letter (getting a student a job) is in contrast with the morally-correct method of accomplishing the goal (the professor spending a lot of time writing the letter). I am still doing all my letters the old-fashioned way, but I wonder whether that will ultimately do my student’s a disservice.

cross-posted from: https://programming.dev/post/85783

OP actually went to the café as a joke but GPT-4 didn’t show up.

Original tweet by @emollick: https://twitter.com/emollick/status/1669939043243622402

Tweet text: One reason AI is hard to "get" is that LLMs are bad at tasks you would expect an AI to be good at (citations, facts, quotes, manipulating and counting words or letters) but surprisingly good at things you expect it to be bad at (generating creative ideas, writing with "empathy").