Fast Data Science

https://fastdatascience.com/generative-ai/openai-vs-claude-vs-qwen/

How well do the newest large language models perform? How do they compare to 2025's offerings?

We evaluated the newest large language models on a law test prepared by Eugenio Vaccari. The Chinese entrants DeepSeek and Qwen have challenged the dominance of GPT, although most UK users use GPT, Gemini, and Claude. Over time we are heading towards an 80% score on the law test when the bots are combined with a RAG system (a database of English insolvency statutes and case law), when two years ago we were only around 30%. What is fascinating is that the Chinese models are delivering a similar performance to the American juggernauts, for a fraction of the cost.

We've plotted the AI models' performance on the law exam with model release date on the x-axis, so you can see at a glance how rapidly the field is advancing. I posted an earlier version of this graph a year ago, but now we have data going back to 2024 and the early days of GPT 3.5, which is very exciting.

Meanwhile, the House of Lords has put out a report recommending that the UK government implements some protections for creative industries and to force AI companies to be transparent about where their training data came from. https://fastdatascience.com/legal-ai/ai-copyright/

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https://fastdatascience.com/ai-in-research/jicl-paper/

Publication Announcement: A Generative AI-Based Legal Advice Tool for Small Businesses in Distress

We are thrilled to announce the publication of our latest paper in the Journal of International and Comparative Law (JICL):

Marton Ribary, Thomas Wood, Miklos Orban, Eugenio Vaccari, Paul Krause, A Generative AI-Based Legal Advice Tool for Small Businesses in Distress. Journal of International and Comparative Law, Vol 12.2, 2025.

Small business owners often face a "justice gap" when dealing with the complexities of corporate insolvency. To address this, our team developed the Insolvency Bot, a Retrieval-Augmented Generation (RAG) system specifically designed to provide information about English and Welsh insolvency law.

In head-to-head testing against unmodified models like GPT-4, the Insolvency Bot significantly outperformed them in legal accuracy and reliability. The system leverages a curated database of 6,000 legal texts, including statutes, case law, and HMRC forms.

What's next? We are currently working with partners around the world to develop equivalents in
* Bhutan
* India
* Eight European jurisdictions



🌐 https://fastdatascience.com

https://youtu.be/QRfeUD2Y5Is

This new video explains natural language processing: what it is, how it works, and what can it do for your organisation. Natural Language Processing (NLP) is a branch of Artificial Intelligence (AI) that focuses on giving computers the ability to understand human language, combining disciplines like linguistics, computer science, and engineering.

Companies need NLP because much of their crucial data, especially in industries like insurance, healthcare, and pharmaceuticals, exists as unstructured text in formats like PDFs, scanned documents, or audio, which computers struggle to process compared to clean numerical data.

The most effectve way a business can get value out of NLP is by implementing it as part of a wider strategic initiative, such as the development of a predictive risk model or cost model, as in our example of clinical trials. This allows the company's C-level to turn unstructured text documents into a quantifiable risk or cost estimate for the next quarter or year, delivering a phenomenal return on investment and a competitive advantage, especially in traditionally conservative industries. While lower-impact initiatives can save staffing costs (e.g., by triaging customer support), the highest impact comes from these larger strategic projects that provide predictive business insights.

🌐 https://fastdatascience.com