A new generative AI model from a top financial services company gives us a glimpse into the future of artificial intelligence in business.
Bloomberg announced the development of a new large-scale generative AI model that is specifically trained on a wide range of financial data, including the vast repository of proprietary data the company has collected over 40 years of being in business.
Called BloombergGPT, the model is a “domain-specific” model, one trained on the specific complexities and terminologies of the financial services industry.
The model will enable Bloomberg to perform much more robust sentiment analysis, entity recognition, news classification, and question answering. It will also enable entirely new use cases as it layers ChatGPT capabilities over one of the world’s most robust financial datasets.
But even if you don’t work in financial services, this model matters…
Because it shows us a sneak preview of the future of AI in business. In Episode 41 of the Marketing AI Show, Marketing AI Institute founder/CEO Paul Roetzer explained to me why every marketer and business leader should be paying attention.
- Bloomberg’s approach is the future of AI in business. “Customized, personalized models are where this is all going to go,” says Roetzer. If you have proprietary data, you have a chance to build a custom model on top of that data. As powerful as GPT-4, ChatGPT, etc. are, they’re still general models trained on a corpus of general knowledge. Training models on your business’ custom data is the next frontier, allowing companies to get even better, more specialized performance from these systems.
- That’s because there are so many possible use cases. By building on top of your own data, you can arm every person in your company with a powerful ChatGPT-like AI assistant that can access and use all the information within your organization. This can function like a perfect knowledge base that anyone at the company—from sales to service, to marketing to operations—can query at will to be more productive and effective.
- And custom data provides a massive competitive advantage. Everyone can use powerful general models to produce results in their business, including your competitors. When everyone has access to the same models, custom data becomes a unique competitive advantage. No one else can access and train a model on the private data you have internally.
- You need to act now if you have custom, proprietary data. “If you work at an organization that has unique and valuable data sets, you should be racing to explore this,” says Roetzer. Insurance and healthcare companies are no-brainers, but every business and/or vertical with useful private data should be paying attention. Start talking to your CIO or relevant technical teams internally about what you’re doing in this area. Start involving companies like Cohere that can help train custom models.
Don’t get left behind…
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