Chat GPT-4
04.25.23

What Does ChatGPT-4 Mean for Enterprise Organizations?

Summary: 

  • What are ChatGPT-4’s key updates?
  • What do these updates mean for enterprise businesses?
  • How can Veritone help businesses integrate ChatGPT-4 into their practices?

We’re a month into the release of ChatGPT-4, which is a new large language model (LLM) that evolves some of the capabilities seen with the previous release, ChatGPT-3. It also improves some of the early issues that users uncovered using the previous model. Now that we’ve had a chance to digest the updates and play around with it, we’ve put some thought into what these updates mean for enterprise organizations, and how you can take advantage of them. We’ll first go through the key updates made with the release of ChatGPT-4, then discuss how an enterprise should approach this new release.


Key updates for ChatGPT-4 

One of the first things to mention is that ChatGPT-4 requires a subscription, which, depending on how you’re going about using this tool, may be worth considering. The free version of ChatGPT is still accessible but is currently running on the 3.5 model.

ChatGPT-4 addresses quite a few of the issues and bugs that have cropped up in its previous iterations, encouraging more businesses to adopt its usage.

Here are some of the most notable updates:

1. Fewer mistakes and hallucinations

With this update comes improved responsiveness, reliability, and safety. According to OpenAI, ChatGPT-4 is 60% less likely to make reasoning mistakes or offer hallucinated facts has been lowered, but still not entirely resolved. Fortunately, this can be easily addressed with automated processes to validate responses that seek to reduce the human-in-the-loop review, which is a best practice.

2. Increased token allotment for longer text

Large language models such as ChatGPT have a restricted context window, but with the ChatGPT-4 model, users can utilize a long-form mode that can handle up to 32,000 tokens, which comes out to over 25,000 words or approximately 52 pages of text—an amount that’s nearly eight times greater than ChatGPT-3.  This provides additional room for prompt context from AI metadata in your workflow and potentially more sophisticated results. 

3. Image processing

The newest ChatGPT model—unlike previous models—now accepts images alongside text instructions. If a user inputs a handmade sketch into the AI chatbot, ChatGPT can transform that sketch into a functional web page. Image processing can benefit businesses by:

  • Adding media-based inputs to chatbot engagement for better customer service
  • Automating accessibility by creating captions and alt text for images
  • Optimizing or flagging content to ensure moderation and brand safety standards are met

4. Other updates worth mentioning include:

  • Improved memory for complex workflows and prompting
  • More training parameters to provide better depth
  • Better contextual understanding for response accuracy and clarity
  • Safer responses when bad behavior is detected 

In summary, while ChatGPT-4 offers significant improvements in functionality, responsiveness, and safety than its predecessors, it’s more of an incremental improvement to an already very compelling tool, that has made it even more ready for enterprise uses. 

Applying best practices for ChatGPT in the enterprise 

Reduced hallucinations, token increase, and improved content moderation make ChatGPT safer and easier for enterprise use, but it’s still important to have a human in the loop to manage and review the content creation process.

Prioritize user experience (UX)

Though you may have complex workflows and sophisticated models running behind the scenes, UX is paramount so keep all user interfaces clear and simple to use, and leverage customer feedback when possible and appropriate.  It may be a good idea to wrap user inputs with additional contexts or instructions behind the scenes. 

Optimizing the outcomes

For the foreseeable future, it’s still a best practice to have humans involved in the generative content process.  To add further efficiencies, there are ways to combine additional AI models in the process to review the LLMs’ output, which allows employees to focus on creating strong content parameters up front and reviewing or editing outputs before going through the next stage in the workflow.  

Stay up to date with best practices and top tech

Like with any new tech, it’s always a good idea for businesses to keep tabs on updates, new capabilities, potential issues, etc. We also recommend experimenting and playing around with new features to find what works best for your specific needs and can enhance overall performance. It’s important to use the right LLM for each stage in the workflow, to ensure the best responses along the way.

Partner up

For the highest success rate, it’s important to work with a provider that can help you integrate generative AI with your current practices and workflows. For example, Veritone Generative AI, which is deployed on a user-friendly enterprise platform called aiWARE™, can help regulated and commercial organizations across industries seamlessly integrate ChatGPT and other generative AI models with existing business protocols. 

Don’t wait!

The generative AI market is predicted to be $118B by 2032, according to IDC. On a more practical level, now is the time to test the waters. The beauty of ChatGPT and generative AI as a whole is not about ripping and replacing existing workflows and infrastructure but automating and augmenting certain tasks that free up employees to focus on more strategic activities. The companies that dig into this now are the ones that will gain the most. Developing a strategy, running tests, and iterating over time will help companies drive new ideas around improved productivity, creativity, audience experiences, and revenue opportunities.

To learn more about ChatGPT, Generative AI, and Veritone’s solutions approach, contact one of our team members for a demo or read more on our blog.

 

Reference:

Precedence Research