Harnessing the power of GPT-4

The latest advancements in generative AI for your business

Bence Lukacs

Bence Lukacs

Experience Design Lead

ChatGPT Insurance AI Technology Free Download
18 April, 2023

In the rapidly evolving world of technology, it can be difficult to keep up with the latest developments. This is especially true in the field of generative AI, where breakthroughs seem to happen every day. 

In March 2023, OpenAI released GPT-4, the newest and most powerful generation of the GPT language model family which runs the premium version of ChatGPT and boasts an impressive range of new and improved features. 

We pride ourselves on being early at the party when it comes to new technologies, so we've updated our whitepaper, first published in February, with new insights on the latest GPT-4 version which is even more powerful and reliable than its predecessors. Read on to learn more about the latest developments in conversational AI and how they're shaping the future of the insurance industry. 

How does the new generation of GPT change the game?

With the release of GPT-4, the world of generative AI has taken another leap forward. This latest release introduces new and improved features that expand its capabilities, such as 

  • multi-modal: processes both text and images. Besides text and language understanding, GPT-4 can also interpret images, providing the insurance industry with new use cases, such as identifying damages from photos while processing insurance claims.
  • ability to handle longer text: GPT-4 can process much longer text simultaneously (up to 50 pages), making it ideal for text classification, generating larger pieces of text or summarizing longer documents.
  • improved capabilities and reliability: GPT-4 improved substantially in many aspects, including factual correctness and reasoning, and exceeds average human-level performance on several professional benchmarks.

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Cautions to keep in mind

Despite these impressive capabilities, it's important to remember that ChatGPT is still a prototype of natural language processing technology. In our whitepaper, we also provide an updated overview of these limitations, which you should keep in mind when considering immediate integration into business processes. 

  • factual mistakes and incorrect information: The original 3.5 version of ChatGPT had a flaw where it often produced responses that sounded plausible but were factually incorrect or illogical. Although GPT-4 has improved, this is still a significant shortcoming as it relies on statistical patterns rather than deep semantic understanding. 
  • unpredictability: Real-time text generation makes it difficult to anticipate its responses and errors, making it unsuitable for high-stakes applications such as making binding legal claims or critical business decisions.
  • sensitivity to tweaks on how questions are phrased: Answer quality is largely dependent on prompt quality, so the role of prompt engineering is increasingly important.
  • possible ‘hallucination’ of false statements: Large Language Models tend to “hallucinate”, make up false facts, or mix up words that result in false statements.
download our ChatGPT whitepaper updated with the latest advancements of GPT-4

Preparing for the future with GPT

As generative AI continues to evolve at such a rapid speed, the technology may overcome the limitations mentioned above sooner than most insurance carriers can even adapt to the new possibilities it offers. Thus there are plenty of reasons to stay excited and up-to-date with the latest developments that can give your business a significant edge in the marketplace.

Do you want to dig deeper?

Our updated whitepaper offers a comprehensive guide for insurance companies looking to prepare for the forthcoming transformation brought on by this evolution. It provides a visionary outlook on the technology's potential, practical use cases, and necessary precautions.

Moreover, it answers some technical questions about how businesses might integrate ChatGPT into their systems via APIs and how they can train and fine-tune the model for their specific needs, in particular in the insurance industry. 

check out our updated whitepaper

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