Cool that they did this on top of Qwen3.6-35B-A3B. If they have their own collection of valuable data this is the only way to make sure it doesn’t end up in general purpose models. That’s probably enough justification for the $40m spend - continued control of your destiny as an information provider.
cootsnuck 2 hours ago [-]
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. All you need is time to figure out how to make it useful for yourself and then eventually sell access to it however you want.
Think of all the data that big orgs have that isn't accessible to all the AI labs to suck up.
johnnypangs 34 minutes ago [-]
Here is some more technical information on how this was trained, as well as a download link.
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 inefficient compared to using an API. Idk how Reuters will manage to solve this fundamental problem.
Arcuru 2 hours ago [-]
> starting from a strong open-source foundation and investing $40 million to train Thomson
Sounds like they spent $40 million finetuning an open weight model on their own data? I wonder what they built on.
postalcoder 30 minutes ago [-]
From the HF link posted above it's Qwen3.6-35B-A3B.
> Our evaluation found Thomson’s citation quality generally competitive with leading frontier models, even when tested on Canadian employment-law questions without a Canada-specific setting.
That’s it? It was generally competitive with leading frontier models? Neat, but why would someone pay for frontier models and also a generally competitive additional product?
granzymes 1 hours ago [-]
It’s a cost-saving measure and a marketing story.
peddling-brink 2 hours ago [-]
> Thomson Reuters is also making a “small” version of Thomson available as an open-weight model on Hugging Face for academic and non-commercial use to further aid in this validation.
Looking forward to the ERP fine-tune.
dash2 2 hours ago [-]
Has anyone found a link to the technical report? They don’t seem very keen to publicise their performance on evals…
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 narrative affront to OpenAI and Anthropic, maybe, but this is Reuters, not a deeply political organization seeking to land gotchas against big tech.
judge2020 2 hours ago [-]
Reuters, the news agency, is only roughly 10% of TR's revenue. They're still a pretty big player in Legal and Tax.
CircuitSeuss 60 minutes ago [-]
Keep in mind line items can be deceptive. e.g. “Corporates” can mean “money we make from selling access to individual’s biometric data to the government.”
1. Marketing and expressing to their customers that they are not falling behind, and
2. Insulating themselves from frontier labs jacking up prices, nerfing the models they depend on, or otherwise unexpected changes in behavior.
I think the main goal is #2. Thomson Reuters might be a $40B company, but.... at this point it's not clear that that holds any weight in terms of not being fucked over by 2 companies aiming for $2t+ IPO valuations.
Edit: On second thought, there is probably a #3 too. They can serve inference for their own models significantly cheaper than frontier lab rates (assuming they're capturing continuous use of their hardware). I still think #2 is the primary goal.
blooalien 12 minutes ago [-]
> I think the main goal is #2. Thomson Reuters might be a $40B company, but.... at this point it's not clear that that holds any weight in terms of not being fucked over by 2 companies aiming for $2t+ IPO valuations.
It's exactly the same sorta thinking re; Microsoft potentially fucking over the PC videogames industry that Valve used to justify the zillions of dollars and countless man-hours put into their big push for Linux gaming rather than tie themselves to a single proprietary company that could try to kick them out of the gaming industry. So far it's going pretty well for them. Depending on how they play their cards, this could also work out really well for Thomson Reuters as well.
colechristensen 2 hours ago [-]
No it's just a value add to their existing data products and a moat against the big n LLM companies. The "news" part of the business is relatively small compared to everything else the do.
Like how Bloomberg does news but its far from their only or primary product. TR covers a different surface of data products than Bloomberg but it's a decent comparison.
fenestella 2 hours ago [-]
[flagged]
Rendered at 05:22:37 GMT+0000 (Coordinated Universal Time) with Vercel.
It's going to become another way to monetize your informational assets if you're a big older enterprise with troves of data. All you need is time to figure out how to make it useful for yourself and then eventually sell access to it however you want.
Think of all the data that big orgs have that isn't accessible to all the AI labs to suck up.
https://huggingface.co/thomsonreuters/Thomson-1.0-Small
(Full disclosure I’m a TR employee, although I had nothing to do with making this)
It eventually stopped making sense because of inference costs. Running something internal with 30% GPU utilization is just too cost inefficient compared to using an API. Idk how Reuters will manage to solve this fundamental problem.
Sounds like they spent $40 million finetuning an open weight model on their own data? I wonder what they built on.
https://huggingface.co/thomsonreuters/Thomson-1.0-Small
[1] https://www.businessinsider.com/thomson-reuters-builds-ai-mo...
That’s it? It was generally competitive with leading frontier models? Neat, but why would someone pay for frontier models and also a generally competitive additional product?
Looking forward to the ERP fine-tune.
https://huggingface.co/thomsonreuters/Thomson-1.0-Small
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 narrative affront to OpenAI and Anthropic, maybe, but this is Reuters, not a deeply political organization seeking to land gotchas against big tech.
https://ir.thomsonreuters.com/news-releases/news-release-det...
It's likely split between two goals:
1. Marketing and expressing to their customers that they are not falling behind, and
2. Insulating themselves from frontier labs jacking up prices, nerfing the models they depend on, or otherwise unexpected changes in behavior.
I think the main goal is #2. Thomson Reuters might be a $40B company, but.... at this point it's not clear that that holds any weight in terms of not being fucked over by 2 companies aiming for $2t+ IPO valuations.
Edit: On second thought, there is probably a #3 too. They can serve inference for their own models significantly cheaper than frontier lab rates (assuming they're capturing continuous use of their hardware). I still think #2 is the primary goal.
It's exactly the same sorta thinking re; Microsoft potentially fucking over the PC videogames industry that Valve used to justify the zillions of dollars and countless man-hours put into their big push for Linux gaming rather than tie themselves to a single proprietary company that could try to kick them out of the gaming industry. So far it's going pretty well for them. Depending on how they play their cards, this could also work out really well for Thomson Reuters as well.
Like how Bloomberg does news but its far from their only or primary product. TR covers a different surface of data products than Bloomberg but it's a decent comparison.