Generative AI: When to Go Wide and When to Go Deep

Generative AI: When to Go Wide and When to Go Deep

Generative AI is everywhere, and you might be feeling the pressure from your colleagues or managers to explore how to incorporate Generative AI into your role or business. I’ve been seeing a lot of speculation about ChatGPT’s capabilities and what it can and cannot do. As a research scientist with years of experience in academic and industrial research with large language models, I wanted to dig into some of these notions:

First, ChatGPT is not a product, it’s an engine – and a really good one. However, a valuable solution still needs more in order to make a difference and drive business value in almost every case. This includes the UX (UI, latency, runtime constraints) and critical ML capabilities like data collection, data processing and selection, continuous training frameworks, optimizing models for outcomes (beyond next word prediction) and deployment (measurement, A/B tests, telemetry).

Second, while GPT does amazing things like write poetry, pass medical exams or write code (just to name a few), in CX we need solutions that solve specific problems like improving automated dispositioning or real-time agent augmentation. GPT models can be impressive, but when it comes to user experience and business outcomes, Vertical generative AI models that are trained on human data in a dynamic environment specifically for the task at hand typically outperform larger generic algorithms. In ASAPP’s case, this means solving customer experience pain points and building technology to make agents more productive.

Lastly, while we don’t use ChatGPT at ASAPP, we do train large language models and have deployed them for years. We don’t pre-train them on the web, but we do pre-train them on our customer data, which is quite sizable. From there, we then train them to solve specific tasks optimizing the model for specific KPIs and business outcomes we care about and need to solve for our customers — not just general AI. This includes purpose-built vertical AI technology for contact centers and CX. Vertical AI allows enterprises to transform by automating workflows, multiplying agent productivity and generating customer intelligence to provide optimal CX.

Interested in learning more about ChatGPT or how large language models might benefit your business? Drop us a line.

Ryan McDonald

Ryan McDonald, PHD, is Chief Scientist at ASAPP

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Transform your enterprise with generative AI • Optimize and grow your CX •
Transform your enterprise with generative AI • Optimize and grow your CX •