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Orchestrating the Move from Generative AI to Synthesis AI

Written by
Amrish Singh
generative AI

Everyone’s talking about generative AI – but what comes next? Although generative AI is impressive, it’s just the tip of the iceberg of what AI will be able do. As technology continues to progress, AI is moving from generation to synthesis. This has major implications for insurance companies.

Understanding Generative AI

A lot of tools get lumped together under the umbrella of artificial intelligence. 

According to Investopedia, artificial intelligence refers to “the simulation of human intelligence by software-coded heuristics.” At its core, AI machines mimic human intelligence, but they do this differently depending on the type of AI. For example, reactive AI tools use algorithms to produce optimized outputs based on a set of inputs, but they can’t learn or adapt. Limited memory AI, on the other hand, can adapt to past experiences and new observations to a limited degree. Theory-of-mind AI tools go further still: they have an extensive ability to learn, which is paving the way for chatbots that are convincing enough to pass as humans.

That brings us to generative AI. According to IBM, generative AI refers to deep-learning AI models capable of generating text, images, and other types of content based on training data. TechTarget lists ChatGPT, Bard, and Dall-E as popular generative AI interfaces. Dall-E generates images, whereas ChatGPT and Bard generate text. 

These text-based generative AI tools are based on large language models (LLMs) and produce humanlike responses. In fact, ZDNet says ChatGPT performs like a nine-year-old in theory of mind tests, which gauge whether children can understand what is going on in other people’s minds. In other words, the technology is so advanced that, just like humans, it can put itself in the shoes of its audience. 

What Generative AI Means for Insurance

Generative AI is a huge breakthrough in the field of AI. It’s also a major advancement for the insurance sector.

When interacting with generative AI models, users can type questions or commands (called prompts) using natural language. The AI model then responds with the information requested, also in natural language. As a result, interacting with a text-based generative AI model is just like chatting with a fast, knowledgeable human. Tools like ChatGPT can even remember information from earlier in the conversation, which makes it possible to ask follow-up questions.

The applications seem endless. You can use generative AI to answer questions, generate ideas, explain complex topics, translate from one language to another, and write letters – all with no coding knowledge.

But That’s Just the Beginning

Generative AI tools are so impressive, they may seem like the culmination of AI development. In reality, these tools are only one phase in a much longer progression of AI capabilities.

Adreessen Horowitz calls generative AI wave one, whereas synthesis AI is wave two. In the generative wave, AI tools create new content based on instructions. In the synthesis wave, AI tools converge information to provide insights and support decision making. Whereas generative AI often impresses users with long outputs based on generic models, synthesis AI promises to produce shorter, higher-quality outputs based on models that have been trained on specific data sets. 

Synthesis AI is exactly what the insurance industry needs. Insurers can input their data to train AI models on their unique claims and underwriting protocols. The AI tool also has access to everything it needs to perform tasks, such as the core claims system, core policy system, rating engine, document management system, vector databases, and email infrastructure. This enables users to create prompts in natural language and request the AI tool to orchestrate a response that synthesizes all the insurer’s data and systems.

There are numerous use cases. For example, AI tools can help:

  • Underwriters summarize insurance applications, highlight missing information, and draft emails requesting the missing information.
  • Claims professionals with claims intake and triage to ensure policyholders always receive a fast response.
  • Insurance customers ask questions about their coverage and receive personalized recommendations.

Advanced Generative AI Tools Are Here

ChatGPT was released to the public one year ago. The advancements made since have been astounding. 

With Liberate’s Operator AI, the realization of generative AI capabilities has never been easier. Our platform translates natural language dialogue into complex process orchestration. Your team inputs simple prompts; our program draws on your systems and vendors to produce high-quality outputs. Learn more.