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> posting this sentence was part of the deal to get the compute

This 100%


Expressing an interest is presumably free... So anthropic might as well.


Source? I'd like to read more on Anthropic's views of space compute


> As part of this agreement, we have also expressed interest in


Which is now their official position I guess as this whole “AI space datacenter” stuff is a significant part of the whole SpaceX IPO.

I assume privately they may not share that opinion, but it’s not in Anthropic’s interest to talk about this (very little to gain, and may ruffle a lot of feathers if they say the wrong thing).


AI space datacenters only make sense from one perspective -- sovereignty.

If you're someone with a lot of money, who dislikes governments meddling in your business, and often pisses off governments...

... oh, I see why this is an Elon talking point now.


But also - anyone would be interested in purchasing orbital compute at the price Elon is quoting.


> but given that you can actually run the models yourself on AWS Bedrock

That's not exactly how it works. Anthropic are hosting their models in AWS Bedrock as a managed service. Customers call those LLMs just like calling any other API. There's no visibility into what kind of AWS infrastructure is serving that API request.


Fun that it has oscillated from instant boot then to minutes-long boot a decade later back to instant boot (or resume to be fair) today.


I had the same confusion and closed the tab, only to discover here on HN that there's more. Open by default sounds reasonable.


There is a surprising amount of code needed in each of the inference frameworks (LM Studio, llama.cpp, etc) to support each new model release. For example to format the input in the right way using a chat template, to parse the output properly with the model-specific tokens the model provider decided to standardize on for their model, and more.

This particular instance was a fix to the output parsing [1] in LM Studio, described like this:

"Adds value type parsers that use <|\"|> as string delimiters instead of JSON's double quotes, and disables json-to-schema conversion for these types."

[1]: https://github.com/ggml-org/llama.cpp/pull/21326/commits/a50...

edit: formatting


I think we lost that terminology war. Open source models mean open weight. There are only a couple examples of fully open source models with open data and code, and the labs are not incentivized to go that far.


Yes, retooling gas stations is the way to go. Already happening in Norway where stations now show the price of kWh in addition to gas and diesel prominently on signs by the road. Charging is just a different kind of pump.


Charging stations don't need all the environmental equipment that gas stations have to catch oil and gas run off. I guess we could convert old gas stations that don’t need extensive environmental cleanup, but building new ones just to charge EVs is huge overkill when you just need some space in a parking lot.


a key difference between a gas station and a parking lot is that people only park at a gas station to get gas (and have a rest, get dinner, bathroom break etc), so, assuming quick charging, you need less chargers as they will spend less time not charging a fully charged car left parked on them. Gas station staff can ensure charging spots are utilized correctly as they do now for the pumps.

Also everyone understands how gas stations work, so it is easier to slip EVs into the social fabric.


Those fast chargers rely on a buffer, so I’m not sure thy can be used continuously like a gas pump can.


That's a good point. Charging stations benefit from being a service station too though, with amenities and a cafe etc, since people want something to do while they charge. So a gas station is a better candidate than a parking lot when decisions are made for where to place the new charging infrastructure. Lots of other factors too of course.


I prefer grocery stores because I can run in and grab something quickly. The only problem is that charging is often too quick to do any real shopping, so a smaller convenience store makes sense also.


America certainly did not invent electric cars. Depending on which electric car you consider the first real one, the inventor was either French, British or German [1].

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


GP is talking about the current market and product class, not the drive train/mechanisms. There was ~a century where EVs were effectively nonexistent


If the GP was aware of the history of electric cars, they would have known how to word their comment to be factually accurate.


> "electric car industry. They invented it"

"Industry" is a keyword that your pedantry is overlooking. Unless you can edify us as to where there was an EV industry prior to Tesla? The existence or history of the tech is irrelevant in that comment.


Unsloth is providing the best and most reliable libraries for finetuning LLMs. We've used it for production use-cases where I work, definitely solid.


Glad it was helpful!


Also wrestling with this challenge at the moment and curious to hear experiences from others. Even though it requires human input, the capture and the way it's updated has to get automated.


Completely agree the manual capture is exactly where it breaks down every time. Curious, what's your current setup? GitHub + Slack or something different?


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