Totally agree, one of the most interesting podcasts i have listened to in a while was a couple of years ago on the Tiny Stories paper and dataset (the author used that dataset) which focuses on stories that only contain simple words and concepts (like bedtime stories for a 3 year old), but which can be used to train smaller models to produce coherent english, both with grammar, diversity, and reasoning.
The podcast itself with one of the authors was fantastic for explaining and discussing the capabilities of LLMs more broadly, using this small controlled research example.
As an aside: i dont know what the dataset is in the biological analogy, maybe the agar plate. A super simple and controlled environment in which to study simple organisms.
I like the agar plate analogy. Of course, the yeast is the star of the show, but so much work goes into prepping the plate.
As someone in biotech, 90% of the complaints I hear over lunch are not about bad results, but about bad mistakes during the experiment. E.G. someone didn't cover their mouth while pipetting and the plates unusable now.
Ha! I remember where I was when I listened to that episode (Lakeshore Drive almost into Chicago for some event or other) — thanks for triggering that memory — super interesting stuff
The podcast itself with one of the authors was fantastic for explaining and discussing the capabilities of LLMs more broadly, using this small controlled research example.
As an aside: i dont know what the dataset is in the biological analogy, maybe the agar plate. A super simple and controlled environment in which to study simple organisms.
For ref: - Podcast ep https://www.cognitiverevolution.ai/the-tiny-model-revolution... - tinystories paper https://arxiv.org/abs/2305.07759