Here is some more technical information on how this was trained, as well as a download link. https://huggingface.co/thomsonreuters/Thomson-1.0-Small (Full disclosure I’m a TR employee, although I had nothing to do with making this)
Full technical report PDF: https://huggingface.co/spaces/tri-fair-lab/publications/blob... > In this report, we argue that frontier performance can be achieved by a wide range of institutions through Continual Learning on readily available open-weight models. > As opposed to existing limited approaches such as small-scale fine-tuning, prompt engineering, or tool-augmentation with a frozen model, our Continual Learnin…
Thomson Reuters Launches Its Own Frontier Model
41–50 of 65 posts
Re: Thomson Reuters Launches Its Own Frontier Model
#42Earlier quoted context omitted.
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…
I don't see why you couldn't see improvements in self-hosted or hosting-as-a-service model throughput? Basically API-style support for a company's internal LLM system. Why not? Or secure infra offered by AWS to self-host your own models that get served to the company just like any other company internal service can be hosted on AWS or similar? It won't match Anthropic or OpenAI, but it could be economic?
There is no such thing as "secure infra" hosted by someone else.
This might still be fine, depending on your threat model, of course, but if your weights absolutely must never leave the confines of your org, you cannot use any shared hosting provider, because they just offer legal coverage of incidents. But if your moat is your knowledge, legal doesn't matter as much as the knowledge being suddenly unmoated.
Re: Thomson Reuters Launches Its Own Frontier Model
#43I don't trust that they'll be able to make back that $40M. This feels very much like a news agency getting into crypto or launching its own NFT line. Or IBM selling Watson. Or Mozilla chasing every which thing. They're not stakeholders in the future of work. They're just wanting to stay relevant and pattern matching against what they see. Reuters is too important for this. If they were trying to use this as a narrati…
I know you're being facetious, but I genuinely think Thomson Reuters should be investing in NFTs as much as it is in AI. NFTs (while some of the shine has admittedly worn off) are an emerging infrastructure for digitally native ownership, and that's precisely the sort of institutional problem Thomson Reuters is positioned to solve (think tax records, medical records, etc). People in tech suddenly tossing NFTs to the…
Re: Thomson Reuters Launches Its Own Frontier Model
#44Earlier quoted context omitted.
40M$ 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.
Reuters News is only slightly over 11% of their business. Legal and Accounting is closer to half.
on edit: just went and looked it up, adding in compliance offerings it is over 80% of their business.
Re: Thomson Reuters Launches Its Own Frontier Model
#45Earlier quoted context omitted.
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…
I don't see why you couldn't see improvements in self-hosted or hosting-as-a-service model throughput? Basically API-style support for a company's internal LLM system. Why not? Or secure infra offered by AWS to self-host your own models that get served to the company just like any other company internal service can be hosted on AWS or similar? It won't match Anthropic or OpenAI, but it could be economic?
Re: Thomson Reuters Launches Its Own Frontier Model
#46Earlier quoted context omitted.
Full technical report PDF: https://huggingface.co/spaces/tri-fair-lab/publications/blob... > In this report, we argue that frontier performance can be achieved by a wide range of institutions through Continual Learning on readily available open-weight models. > As opposed to existing limited approaches such as small-scale fine-tuning, prompt engineering, or tool-augmentation with a frozen model, our Continual Learnin…
I wonder where the other $39.5 million went?
Re: Thomson Reuters Launches Its Own Frontier Model
#47How I understand it, without really reading into it:
- Thomson Reuters did not "create" a frontier model, they gave some money, maybe a bit of their data to Imperial College London, and took Alibaba's Qwen 3.6 35B A3B Model for a basic fine tune.
- "They" (some undergrads at Imperial College London) used an existing ablation framework to undo some of the topic alignment of the original model.
- "They" fine tuned on some domain knowledge trying to preserve general knowledge - here maybe, just maybe some data came from Thomson Reuters.
As a result: one of 100's of Qwen 3.6 35B A3B sparse model fine tunes, just for publicity, to write overstating headlines like "X created their own frontier model"
Re: Thomson Reuters Launches Its Own Frontier Model
#48This is going to increasingly happen over the years to come. Big organizations will become more sophisticated with operationalizing their data, training and running LLMs will continue to be demystified and accessible, and over time we'll get more and more specialized / industry-specific models. It's going to become another way to monetize your informational assets if you're a big older enterprise with troves of data.…
40M$ to get a marginally better model is surprising, why not just use the free weight models
If you are a highly specialized professional intellectual property paralegal, a forensic tax investigator or a post-market pharmacovigilance analyst, you will need for-profit knowledge sources, and your answers will often require synthesizing and interpreting multiple sources.
Re: Thomson Reuters Launches Its Own Frontier Model
#49Please challenge me and explain why this is a break through worth the headline they use for their own work. How I understand it, without really reading into it: - Thomson Reuters did not "create" a frontier model, they gave some money, maybe a bit of their data to Imperial College London, and took Alibaba's Qwen 3.6 35B A3B Model for a basic fine tune. - "They" (some undergrads at Imperial College London) used an exi…
Re: Thomson Reuters Launches Its Own Frontier Model
#50Please challenge me and explain why this is a break through worth the headline they use for their own work. How I understand it, without really reading into it: - Thomson Reuters did not "create" a frontier model, they gave some money, maybe a bit of their data to Imperial College London, and took Alibaba's Qwen 3.6 35B A3B Model for a basic fine tune. - "They" (some undergrads at Imperial College London) used an exi…