The buzz around LLM machine learning, OpenAI, Bedrock, & ChatGPT: what does it all mean?

Man shows coworker how to use LLM Machine Learning AI

Generative AI. LLM machine mearning (Large Language Models). OpenAI. ChatGPT. Amazon Bedrock. Microsoft Copilot. The buzz out there right now is deafening. But what does it all mean?

I have been in technology sales for almost 30 years. In that time, I have witnessed amazing technological advancements. I experienced the dot.com bubble firsthand.   

Way before there was Windows 11, there was DOS. Who remembers DOS?  Before there was Google, there was Netscape. Before everyone started moving to the cloud, before we had VMs and compartments, enterprise organizations had massive server farms to manage. 

Since I started my software sales career in 1994, innovation upon innovation has dramatically changed the way the world works, leading to direct leaps in improved workforce productivity. These innovations are one reason why we can work remotely today (and be just as, if not more efficient, from the home office). 

Well, we have not seen anything yet. Buckle up. 

The Rise of AI and LLM Machine Learning: Quick Retrospective

In 2023 alone, I have seen more technological advancements than in the previous 30 years combined. Generative AI and LLM Machine Learning like OpenAI and Amazon Bedrock are changing the world at a lightning-fast pace. I have never seen anything like it. No one has.   

In some ways, the acceleration of these technologies is concerning. The adoption of AI raises moral, ethical, and societal questions. It will require a thoughtful and balanced approach. That is a subject for another blog by someone wiser than me. Tech-philosophy is above my pay grade. 

But what do services like OpenAI mean for search? How can we leverage it? 

The new Bing experience is amazing. When I asked Bing who was the best defensive shortstop in baseball in the history of the game, it got it right: Ozzie “The Wizard” Smith. (Full disclosure: I’m from St. Louis.) 

When I talk to my enterprise customers, they think Bing is pretty neat, but they want to see internal enterprise search solutions that use LLM Machine Learning on their data. It’s their IP. That’s the value, and that’s a huge win. This comes up in every conversation.  

The good news is Upland BA Insight can help deliver this functionality—today. 

How AI Powers BA Insight’s Enterprise Search 

By using Azure Cognitive Search or by pulling from one of BA Insight’s 90+ Connectors and AutoClassifier solutions to break up the data into defined chunks, plus leveraging SmartHub’s APIs for security trimming, the OpenAI or Bedrock service can now be run against the content. This is when the magic starts; pay no attention to the man behind the curtain! 

Once processed, traditional enterprise search can be augmented to support conversational bots, like ChatGPT. Just think of the potential. 

Common Use Cases for AI-powered Search 

Let’s do a little creative role-playing. A sales executive asks the following questions (and instantly gets answers): 

  • What was our best-selling product last quarter?
  • What vertical experienced the most growth last year? 
  • What is our average sales cycle? 
  • Who did we lose most to last year? 

This salesperson can also have AI generate a first draft of a brief or a sales proposal using the data found within their organization. Conversational search and generative answers mean no more drilling down into complex reports or sifting from data silo to data silo in hopes of finding information. No more bottlenecks waiting for teammates to reply to your email or IM. Now, you can just ask a question and receive an answer right away. It’s that easy. 

Here’s another example of a product manager for a medical device company: 

  • What are the most common design mistakes? 
  • What products have the highest failure rate and why? 
  • What was the root cause of X product failure last September? 
  • What are our most popular products for the Asia Market? 

Asking these questions can save an organization millions of dollars by avoiding costly design mistakes. They can speed up the process of fixing product issues and improve target marketing.  

Let’s look at one final example, this time a senior partner at a law firm: 

  • What associate billed the most tort liability hours last year? 
  • Is there a conflict if we represent XYZ Company? 
  • Who is the firm’s top SEC expert? 
  • Do we have a labor law expert in our London office? 

By quickly getting answers, the firm spends more time on billable activities. The firm can quickly identify potential conflicts of interest. A partner can find an expert to join his team for an important tort litigation involving one of the firm’s top clients.  

The prospect of improving your firm’s decision-making skills using AI-powered enterprise search is immeasurable.  

Wrap Up 

I have listed a few examples of the power of LLM machine learning like OpenAI & Bedrock on your content but there’s so much more on the horizon. This is the future, and the future is now. Every organization and every vertical will benefit from this revolutionary new AI-fueled frontier. 

Hang on for the ride. The buzz is not hype. It’s real.