espadrine
Joined 15 years ago
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1,290
Member since
Sep 12
Enabling laziness and creativity.
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Comment · 2 days ago
That negatively impacts reading speed in my experience :(
Comment · 1 month ago
There may be a reason that I cannot access it from the EU. There, they cannot repurpose data they swallowed for another use without consent.
Comment · 1 month ago
I wish for this company to have great models. I am glad to see such good scores.
I see they have a HuggingFace account[0] and they fine-tuned GPT-OSS, Nemotron, and Qwen, in the past under new names.
There are some things about it that make me worry though.
• They don't indicate the active parameter count, or indicate whether they pretrained the model. It could be a MiniMax M3 finetuning, as the parameter count almost matches (435B vs. 438B).
• They mention using quantum algorithms in other projects: https://multiversecomputing.com/singularity despite quantum algorithms not being typically useful currently.
It would not be the first company with a splashy release, like Brampton Intelligence[1], or SubQ[2]. Unlike those, they do seem to have experience fine-tuning models. Regardless of my worries, I am rooting for them to learn how to train models.
[0]: https://huggingface.co/MultiverseComputingCAI
Comment · 1 month ago
As a European, I do. I don’t envy the state that has to buy all its water and food from its aggressive, militarized neighbour.
Comment · 2 months ago
I would be interested to have a third X-axis with dollars.
Time is sometimes more about inference infrastructure (especially with systolic chips) than model quality (and providers tweak knobs to support higher batches at the expense of latency).
Tokens are not always fully equivalent between models.
Comment · 2 months ago
Models start going to extreme, damaging lengths to achieve ambiguous prompts[0]. Having good sandboxes is now a must IMO.
But sbx is a bit annoying to use with OpenCode for instance (which has zero sandboxing by default, unlike codex CLI or Claude Code). You cannot easily change ~/.config/opencode/opencode.jsonc AFAIK.
[0]: Black Hat OpenAI-Hugging Face incident: https://www.youtube.com/watch?v=87DyyMV0kCY&t=1021s
Comment · 3 months ago
I maintain this meta-benchmark leaderboard: https://metabench.organisons.com/
With this new price change, Terra does look pretty Pareto’ed by Luna.
On agentic coding, pairing Sol Medium for architecting with Luna High for coding does kinda make sense. But beware that architecting can be very read-heavy, and Sol is a bit read-pricey compared to Terra.
Comment · 3 months ago
Composer 2.5 finetuned Kimi K2.5[0].
In the blog post, it is unclear whether Grok 4.5 is also a finetune on top of Kimi; they do imply it is also a finetune.
> Training included trillions of tokens of Cursor data… We used reinforcement learning on difficult problems
If xAI pivoted from a frontier base model company, to a finetuning company, it does mark a stark change to their relevance in the industry.
Comment · 4 months ago
Iridum gains 23 launches per year with 100% success rate in the past 12 months, a satellite manufacturing pipeline with 6 satellites produced and launched, and a cost-to-orbit of $25K/kg operational (with an in-development design targetting $4K/kg).
They are late compared to SpaceX, to be sure: 150 launches per year, 2400 satellites manufactured per year, $3K/kg operational with F9, target $200/kg in development with Starship.
Comment · 4 months ago
I see it mean two things:
1. Indeed, Google is compute-constrained, and is ready to buy any it can.
2. xAI (now SpaceXAI) has a lot of idle compute, which it resells to Cursor, Anthropic, Google, probably others as we speak.
In other words: Google is training models, xAI is not.
Comment · 5 months ago
I use Le Chat as default search engine, using this search engine string: https://chat.mistral.ai/chat?q=Give%20a%20list%20of%20links%...
(In most browsers, you can input any URL with %s as the query string.)
A negative is the high latency.
(Looks like Mistral is not profitable yet[0]. It expects 1 G$ revenue for 1 G$ capex in 2026[1], so it is moving towards profitability, but to be fair it is building a couple datacenters.)
[0]: https://www.forbes.com/sites/iainmartin/2026/04/16/how-franc...
[1]: https://www.bloomberg.com/news/videos/2026-01-22/mistral-ceo...
Comment · 5 months ago
His goal could simply be to learn SOTA architectures.
When rumors started that GPT-4 design would be kept secret, he likely wanted to know what architecture it would be. Perhaps he left Tesla, waited out the non-compete clause, and joined OpenAI to learn its details.
When Mythos dropped, there were hints that it had a new architecture. He might similarly want to know how it works.
Either way, there is enough cross-lab hiring that those secrets eventually get known, but only by the labs.
Comment · 5 months ago
Could you link to a project that you consider the best Tailwind use you know?
I have a bias against Tailwind, admittedly because I saw some vibecoded Tailwind where each class was essentially equivalent to style="font-size: 4em; background-color: grey; display: flex;", all of which was repeated for each header.
But that could be my bias; perhaps the right way to use is is DRY.
Comment · 6 months ago
> A portable battery should be considered to be removable by the end-user when it can be removed with the use of commercially available tools and without requiring the use of specialised tools, unless they are provided free of charge […] to disassemble it.
> Commercially available tools are considered to be tools available on the market to all end-users without the need for them to provide evidence of any proprietary rights and that can be used with no restriction, except health and safety-related restrictions.