I've been impressed by ollama running locally for my work, involving grouping short text snippets by semantic meaning, using embeddings, as well as summarization tasks. Depending on your needs, a local GPU can sometimes beat the cloud. (I get no failures and consistent response times with no extra bill.) Obviously YMMV, and not ideal for scaling up unless you love hardware.
The trick is to already know how to use regexes to make searching the manpages easier! But you really have to nail down the rules for escaping when you want to search for perl's gnarliest sigil magic.
Clearly the US needs a constitutional amendment to preserve the right to keep and bear AI tools. Then we can arm the victims of AI tools with their own AI tools, for self-defense. If we're lucky, AI will send its AI thoughts and AI prayers in carefully calculated quantities.
The article is well-written and I even learned a few things. I'm glad for Nikhil's persistence troubleshooting it and fixing the bug upstream.
Thanks, Nikhil!
If only they passed the inverse law requiring gas and coal plants to buy renewable power to reduce their pollution impact. This raises the question, why should a power generator be required to purchase external power? Isn't that the job of the grid operator, not the generation companies?
It sounds like the state grid operator is trying to put their own burden onto renewable generators, rather than manage their portfolio directly.
Who actually is responsible for balancing the grid? The state? ERCOT? Individual generators? Nobody?
How does this compare to other grids?
> If only they passed the inverse law requiring gas and coal plants to buy renewable power to reduce their pollution impact.
Why? The goal of this law is a stable grid, it's not an environmental law. And your law makes no sense, they should buy renewable power in order to sell it? Why do I need an extra middleman?
The actual purpose of this law is that if you are putting unable power on the grid it's your job to make it stable.
The grid operator is responsible for the stability of the entire thing, but this law is saying that each individual supplier must be responsible for the stability of their personal part.
I suspect as the proportion of renewables increases more and more grids will require something like this.
What is the minimum resident RAM size per individual active unique series? Or what's a typical RSS RAM size for 10 or 100 million unique active series? How does unlimited cardinality avoid RAM exhaustion in this version?
Core doesn't index the metadata so it uses less RAM for higher cardinality data. However, if you have 100M series and you're writing to all of them at the same time, you're going to need some amount of RAM just to buffer it all up and then ship it off to storage as Parquet. The Enterprise product has a compactor that creates indexes as it goes, but those indexes are lighter weight than those in v1 and v2. Also, users can specify which columns they want to appear in those indexes, so they can leave out high cardinality ones if they want to save on RAM. In v3 you can brute force the query against high cardinality data, unlike v1 & v2, which would eat up a ton of RAM to do so.
absolutely true. imagine porting a decade or more of code for only the promised benefit of a more "pure" language. asyncio is nice, but excluding it and enhanced generator syntax from 2.7+ is >policy<, not engineering. python 3 is bootheel style top-down engineering >management<, not good engineering. The BFDL is fallible. Placeholder looks like a great Python 2.8+ to me. Runs all my old code and gives me new syntax, without rejiggering the stdlib for purity's sake? Twist my arm.
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