A new generative AI model from a leading financial services company gives us a glimpse of the future of artificial intelligence in business.
Bloomberg announced the development of a new large-scale generative AI model specifically trained on a wide range of financial data, including the vast trove of proprietary data the company has amassed over more than 40 years in business.
The model, called BloombergGPT, is a “domain-specific” model built on the specific complexities and terminologies of the financial services industry.
The model will enable Bloomberg to perform stronger sentiment analysis, organization recognition, news ranking and question answering. It will also enable entirely new use cases as it layers ChatGPT’s capabilities on top of one of the world’s most robust financial data sets.
But even if you don’t work in financial services, this model is important…
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 Retzer explained to me why every marketer and business leader should be paying attention.
- Bloomberg’s take on the future of AI in business. “Customized, personalized models are where all of this is going to go,” Roetzer says. If you have proprietary data, you have the option to create a custom model on that data. As powerful as GPT-4, ChatGPT, etc. are, they are still general models built on a general body of knowledge. Training models on your business’s custom data is the next frontier, allowing companies to get better, more specialized work from these systems.
- This is because there are so many possible use cases. Based on your own data, you can arm everyone in your company with a powerful AI assistant like ChatGPT that can access and use all of your organization’s information. This can act as the perfect knowledge base that any company, from sales to service, marketing to operations, can query to be more efficient and effective.
- And custom data provides a huge competitive advantage. Anyone can use powerful generic models to drive results in their business, including your competitors. When everyone has access to the same models, personalized data becomes a unique competitive advantage. No one else can access and train a model on your internal private data.
- You should act now if you have special, proprietary data. “If you work for an organization that has unique and valuable data sets, you should be scrambling to explore that,” Roetzer says. Insurance and healthcare companies are a no-brainer, but every business and/or vertical with useful private data should pay attention. Start talking to your CIO or relevant technical teams about what you are doing in this area. Start engaging companies like Cohere that can help train specific models.
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