31–40 of 65 posts
Afaik... Lord Jacob Rothschild is 30% owner of Woodbridge, which holds Reuters. I believe the Thomson family owns the rest... The richest family in Canada. Woodbridge owns large shares of textbook companies, radio stations, news services, wires, scientific journals past and present.
I don't trust that they'll be able to make back that $40M. This feels very much like a news agency getting into crypto or launching its own NFT line. Or IBM selling Watson. Or Mozilla chasing every which thing. They're not stakeholders in the future of work. They're just wanting to stay relevant and pattern matching against what they see. Reuters is too important for this. If they were trying to use this as a narrati…
I know you're being facetious, but I genuinely think Thomson Reuters should be investing in NFTs as much as it is in AI. NFTs (while some of the shine has admittedly worn off) are an emerging infrastructure for digitally native ownership, and that's precisely the sort of institutional problem Thomson Reuters is positioned to solve (think tax records, medical records, etc). People in tech suddenly tossing NFTs to the…
Pretty cool someone is still doing this. Training in house LLMs was extremely popular in 2023-2024, back when domain-specific LLMs could easily top GPT in their field. In my field alone (tax/HR tech) I remember that Intuit, Workday, Indeed, LinkedIn were all training internal models. It eventually stopped making sense because of inference costs. Running something internal with 30% GPU utilization is just too cost ine…
That's actually easy, because you can solve it through doing nothing and simply declaring that optimizing for lowest cost is not the main goal.
The fundamental-ness of that problem is entirely man-made and thus can easily be declared void as long as you have the cash to back that up.
Which might be a winning strategy in a world where everyone else is not doing that. Plus that your knowledge stays in-house, etc.
But this is qwen based.
But w/e I'm pro AI so more companies having more people with skills for more post training is cool
Earlier quoted context omitted.
So it's a qwen fine-tune? I mean that's a reasonable thing to do, but then the press release shouldn't be written the way it is written. They're not as detached from the rest as the industry as the writing suggests. __ > It is obtained by repurposing the open-weight Qwen3.6-35B-A3B model and substantially improving it on a wide range of performance domains. nice wording on the HF page tho. "Repurposing". Lmao
the press release says this explicitly
Which is the thing with press releases. Would've been nice to not do the bare legal minimum tho
This is going to increasingly happen over the years to come. Big organizations will become more sophisticated with operationalizing their data, training and running LLMs will continue to be demystified and accessible, and over time we'll get more and more specialized / industry-specific models. It's going to become another way to monetize your informational assets if you're a big older enterprise with troves of data.…
40M$ to get a marginally better model is surprising, why not just use the free weight models
I don't trust that they'll be able to make back that $40M. This feels very much like a news agency getting into crypto or launching its own NFT line. Or IBM selling Watson. Or Mozilla chasing every which thing. They're not stakeholders in the future of work. They're just wanting to stay relevant and pattern matching against what they see. Reuters is too important for this. If they were trying to use this as a narrati…
I also doubt that R&D spending having to "make back" directly is a winning strategy.
Pretty cool someone is still doing this. Training in house LLMs was extremely popular in 2023-2024, back when domain-specific LLMs could easily top GPT in their field. In my field alone (tax/HR tech) I remember that Intuit, Workday, Indeed, LinkedIn were all training internal models. It eventually stopped making sense because of inference costs. Running something internal with 30% GPU utilization is just too cost ine…
Yep, this is the fundamental issue. It's a 35BA3B model and they probably finetuned it and evalled it in one bursty week on an 8xH100 rental just fine. But long term inference is always going to be easier in an API. Unfortunately for reuters tho, they dont really have a choice. A lot of their data moat is not necessary live data as in linkedin, and the only way they can keep that moat is by doing this. I guess that j…
It won't match Anthropic or OpenAI, but it could be economic?
Earlier quoted context omitted.
40M$ to get a marginally better model is surprising, why not just use the free weight models
They're trying to find a moat in the AI era, for their relatively gigantic news business (and they're among the few still standing giants in news). Most of these organizations are very scared of what AI might do to them.