halflings

> Youtube charges $10 per month and doesn't produce a single video

It is different from Netflix (that pays upfront for production costs), but there's of course a revenue share + the bulk of the revenue for creators is actually from sponsorships (which YT doesn't take a share of).

LLMs generate their output one token at a time. The first thought when you learn this is that this is a huge performance bottleneck, as we are used to highly parallelized systems.

However, a large part of what makes LLMs feel so magical comes from this bottleneck.

The main thing I noticed in the video is that they have heavily sped up all the code generation sections... seems to be on 5x speed or more. (because people got used to how fast and good Sonnet, and especially Gemini 3.0 Flash, are)

+1, reading through the post, the PR updating the documentation... thanks for being transparent, but also don't be so hard on yourself!

That was a very niche error, that you promptly corrected, no need to be so apologetic about it! And thanks for all the hard work making Python faster!

"The models perform differently when called via the API vs in the Gemini UI."

This shouldn't be surprised, e.g. the model != the product. The same way GPT4o behaves differently than the ChatGPT product when using GPT4o.

I would also add that search has already moved elsewhere.

Less and less people are using search engines to shop, ex:Amazon makes >$57B a year from search ads, but also look at Temu and Shein which are mostly glorified product search platforms.

No one is searching for "funny videos" when you can just open Instagram and Tiktok.

The only real unique thing that search engines can do is queries that are not directly commercial (e.g. education, information seeking, etc.) and competition is insanely intense (w/ ChatGPT, Perplexity, etc) there.

That's what the chart says yes. 14.1GB VRAM usage for the 27B model.

Training code is only useful to people in academia, and the closest thing to "code you can modify" are open weights.

People are framing this as if it was an open-source hierarchy, with "actual" open-source requiring all training code to be shared. This is not obvious to me, as I'm not asking people that share open-source libraries to also share the tools they used to develop them. I'm also not asking them to share all the design documents/architecture discussion behind this software. It's sufficient that I can take the end result and reshape it in any way I desire.

This is coming from an LLM practitioner that finetunes models for a living; and this constant debate about open-source vs open-weights seems like a huge distraction vs the impact open-sourcing something like Llama has... this is truly a Linux-like moment. (at a much smaller scale of course, for now at least)

> The world is teetering on the edge of world war

The world probably has never been as peaceful as in the last 50 years or so.

Same goes for access to drinkable water, food, decent shelter, gender equality, freedoms, technology, etc.

But I suppose your comment is a good illustration of the problem at hands (that so many people deeply believe that things are fucked)

Thanks for putting this together! Will give it a watch now