How advances in GPT-4 could revolutionize app development

Although public attention has recently centered on ChatGPT, the underlying GPT-3 and GPT-4 models could be even more transformative, particularly for application developers.

Earlier this year, I predicted that application development would start to include self-generating elements to enhance roadmaps, fix code and improve the overall customer experience. The exposure of ChatGPT introduced something very powerful to the market.

The ChatGPT chatbot application developed by OpenAI is built on a variant of the Generative Pre-trained Transformer (GPT) model called GPT-3. GPT is powerful -- far more powerful than ChatGPT alone. This technology can be integrated into many applications to introduce advancements, and this is where some say the future of software development could go.

When I asked about GPT at a recent developer conference, I found that many vendors are looking to incorporate GPT into their product offerings, but not the public version. Remember that OpenAI can see whatever input is provided to the public version of ChatGPT and use it to further refine the model. Be careful, as this has already caused companies to expose their intellectual property.

What differentiates GPT-4 from GPT-3?

First, it is important to clarify the difference between GPT-3 and GPT-4. As an AI language model, GPT-3 provided the industry with the ability to autogenerate stories, articles, code and more. And now its successor -- GPT-4, the next version of this language model -- is expected to go even further.

GPT-4 is an AI language model currently in limited release from OpenAI. It is a powerful natural language processing model that can interact with humans in a conversational manner by generating responses that are virtually indistinguishable from those of human beings. GPT-4 represents the most recent milestone in the rapidly progressing field of AI.

Advancements expected from GPT-4 include the following:

  • Better conversational abilities, providing improvements to conversational dynamics.
  • Cross-lingual learning, which could break down language barriers through the model's ability to generate coherent translations for languages with unaligned grammatical structures, according to an OpenAI technical report.
  • Enhanced natural language understanding, meaning the model can perceive not only input language's tone and dictionary definition but also its context.
  • Controllable text generation, which could improve model effectiveness by letting users direct the AI with natural language instructions while preserving coherence and human-like responses.

How GPT-4 could advance application development

These new enhancements in GPT-4 open many possibilities in the application development world.

Internationalization and localization difficulties could be minimized with the introduction of GPT into the software tech stack. The ability to provide enhanced customer support with a self-learning model is intriguing, as this could potentially provide future roadmap enhancements and harmonize inbound -- and often conflicting -- requests in the product development lifecycle.

GPT-4 also promises advancements in innovation of applications using AI. The increase in conversational abilities, natural language understanding and other improvements could lead to greater levels of human-machine collaboration and ultimately drive innovation in various corners of the industry.

For application developers, this might support shifting valuable staffing resources to higher-value initiatives. As those in technical roles are continuously tasked with doing more with fewer resources, AI and automation tools such as GPT might be the next generation to overcome the skills gap.

Next Steps

ChatGPT writes code, but won't replace developers

Dig Deeper on Systems automation and orchestration

Software Quality
App Architecture
Cloud Computing
Data Center