nmwnmw

In particular, https://issuetracker.google.com/issues/35874988#comment258 > This issue was made when I was born. Amazing how this isn't and will not be fixed. Guess I'll just move cloud providers then.

- Llama 3.2 introduces small vision LLMs (11B and 90B parameters) and lightweight text-only models (1B and 3B) for edge/mobile devices, with the smaller models supporting 128K token context.

- The 11B and 90B vision models are competitive with leading closed models like Claude 3 Haiku on image understanding tasks, while being open and customizable.

- Llama 3.2 comes with official Llama Stack distributions to simplify deployment across environments (cloud, on-prem, edge), including support for RAG and safety features.

- The lightweight 1B and 3B models are optimized for on-device use cases like summarization and instruction following.

Walk starts at https://www.youtube.com/watch?v=ABQBEdOzrV0&t=6360s

Three astronauts died in 1967: Gus Grissom, Edward White II, Roger Chaffee.

Author is Shane Legg, cofounder of DeepMind.

Highly recommend The Man from the Future: The Visionary Life of John von Neumann by Ananyo Bhattacharya. Talks about this time plus many of his other contributions to e.g. game theory.

Also check out https://www.halfbakery.com/.

Isn't it sufficient to have another lab confirm that the existing sample is a super conductor? Then we can all sprint to replication.

Did this in north Alabama back in the mid 90s for a school fundraiser. They hired a surveyor to plot the squares on the football field. We discovered that the field was narrower on one end by about 7 feet! The cow plopped on a square boundary with an unsold square so the winner only got half. As I recall it was a whole lot of standing around and waiting. Funny for the first 20 minutes, then very, very boring.

This is the same Virgil of:

- Ethereum Proof of Stake [1]

- King of the Nerds TV Show

- Wikiscanner [2]

Source [3]

[1] https://arxiv.org/abs/1710.09437 [2] https://en.wikipedia.org/wiki/WikiScanner [3] https://en.wikipedia.org/wiki/Virgil_Griffith

Wikidata[0] is a freely available knowledge graph. You can even query it online [1]

[0] https://www.wikidata.org/wiki/Wikidata:Main_Page

[1] https://query.wikidata.org/

My personal favorite of these is the Splay Tree[1]. I've never used it in production, but it's really simple to implement and reason about. Though my main experience was trying (and failing) to prove amortized bounds on the operations.

[1] https://en.wikipedia.org/wiki/Splay_tree