amazing ability OpenAI’s ChatGPT wouldn’t be possible without a large language model. These models are trained on billions, sometimes trillions, of text examples. The idea behind ChatGPT is that it understands the language so well that it can predict the next word in an instant. Achieving this requires a tremendous amount of training, computing resources, and developer knowledge.
But the future of these models may be more focused than boil-the-ocean approaches such as OpenAI, which wants to be able to answer all questions under the sun. What if each industry, and even each company, had its own model trained to understand the jargon, language, and approach of individual entities? Perhaps the answer is more limited words and phrases. There will be fewer answers that are completely hoaxes because they come from the world of
In an AI-driven future, each company’s unique data may be its most valuable asset. An insurance company has a very different lexicon than a hospital, auto company, or law firm, and when you combine that with customer data and overall content across your organization, you have a language model. Perhaps it’s not massive, but in the sense of a truly massive language model, it’s exactly the model you need, a model made for one of him, not for the masses.
This also requires a set of tools to collect, aggregate, and continuously update enterprise datasets so that they can be ingested into these small and large language models (sLLMs).
Building these models can be challenging. They will likely take existing LLMs, such as open source or private companies, and fine-tune them to industry and company data to provide a more focused environment in a more secure environment than the typical LLM variety. increase.
This is a huge opportunity for the startup community and many companies are getting a head start on this idea.
