ChatGPT fires up everyone around the globe. You can read and hear about it from different sources. Most likely, you have tried it for curiosity or to discover how it might help you with #SolvingRealLifeProblems. Some of our employees are still studying. They had college exams, and ChatGPT knew all the answers.

Here are some 2 cents on ChatGPT and its impact from my side. I will do my best not to repeat all the stuff already said about the subject, with some minor exceptions.

Suppose you need more time to go through the full article. Then, here is the summary of the post provided by the AI hero for the last few weeks.

The article discusses the potential impact of ChatGPT and other advanced technologies, such as AI and blockchain, on various industries. While these technologies offer tremendous potential, many businesses struggle to adopt them and realize their benefits fully. The article emphasizes the need for better collaboration between technical experts and domain specialists to bridge this gap and enable these technologies to be adopted more effectively. The article concludes with examples of use cases for ChatGPT and encourages readers to learn more about these technologies at an upcoming event.

The Technology.

I’ll keep my promise and skip that part intentionally, as you can easily find it everywhere, including ChatGPT.

ChatGPT is based on cutting-edge technology in the field of artificial intelligence called deep learning, specifically a type of deep learning model known as a transformer. The transformer architecture was introduced in 2017 by Google researchers and has since become a popular choice for natural language processing tasks, such as language translation and text generation.

ChatGPT was specifically developed by OpenAI, a leading research organization in the field of artificial intelligence, using a large-scale neural network with billions of parameters. The neural network was trained on vast amounts of text data from the internet, allowing it to learn to generate human-like responses to a wide range of prompts and questions.

Overall, ChatGPT is a powerful example of the potential of deep learning and natural language processing to create intelligent conversational agents that can engage with people in a human-like way.

ChatGPT didn’t show up all of a sudden. There were plenty of technologies that could revolutionize many industries. Some already did, like Blockchain, 3d printing, and AI in many ways. However, some are still waiting to participate in larger or smaller revolutions.

Thx to ChatGPT; this chance is now. Why?

The chance.

ChatGPT is a giant gate for new solutions in multiple domains. Thanks to the user-friendly interface and human-like interactions, non-technical people noticed opportunities almost out of current times. However, a massive part of the business is not ready to cover even part of the power delivered by ChatGPT. From our discussion with potential clients, it’s evident that most would like to use new technologies like AI, Blockchain, or now ChatGPT. They heard or learned that data is a bar of gold, AI is impressive, and Blockchain is decentralized, so it’s cool, and now ChatGPT is just a game changer. However, there is a vast “but” here. Many businesses don’t know how to make value from all those techs. Moreover, a big part of the business still needs to adopt technologies that, for the IT industry, are already a well-suited standard for years.

I remember one of the Legal conferences where using SharePoint as a cloud storage for documents was introduced as a tech innovation by a well-known worldwide brand. And it’s like, yes, that is a good tool for that, but that could have been an innovation 10+ years ago (for IT).

The chance exposed here is to make a smaller gap between engineers and multiple domain specialists so that all this tech can be adopted and bring value to the businesses sooner, as some of the domain knowledge people dream might turn out to be a day-to-day code for some of our devs.

As a BlueRider.Software, we prioritize projects with clear value propositions rather than solely relying on the most advanced technology to achieve the best possible outcomes. What is also extra vital is that either engineers could get into the domain deeply or experts from those fields were technical enough to communicate with the dev team to pass exact value.

Here is a quick example of two such cases.

Unique technology with a need for clear value for the end user.

A project that we have been working on for at least three years. We had to scrap many news articles (terabytes of data) and provide insights based on the selected content. Insight is prominent events or opinions around selected categories and time caps. From a tech point of view, that was an impressive work developed in 2016. We also built a chat and connected those insights with major communication platforms like slack.

But, even if we had feedback that our insights were correct and that they showed the real things within seconds, the end client needed to figure out what to do with that, how to create value with such information, and turn it into a profit — so impressive technology in 2016 but no clear vision and direction.

Well-established technology with an evident value add.

A project where we had to analyze legal documents, most of the same type and similar schema, to find out potential outliers or incorrect data. Technology-wise — well, not rocket science up now. If you did that once, you could handle that again straightforwardly. Business-wise — you have thousands of similar documents that you need to review repeatedly, paying a human to go through them. Instead, you can do that automatically in seconds. The case is so simple and brings immense value to the organization. Look at the use-case presentation to get through it more deeply.

The ChatGPT use cases

It’s a treasure chest of potential business use cases. From regular jobs automation to personal 24/7 assistance that provides you with general knowledge and your pre-trained data using, for example, your organization process and policies, to content creation to support authors and so many others. The number of potential cases is impressive, even if we would base it only on other available models. Take a look at the examples of what can be done with very few lines of code on the Open.ai page:

How I use ChatGPT so far?

Here are a few examples of how I use ChatGPT so far (more to come) in personal and business use cases.

Copywriter assistance.

ChatGPT helps me write this article. I’ve asked to rewrite some of the sentences more positively or use a bit different, more meaningful words. I’ve asked for a summary of the article, as well. It showed me that the output of the article was exactly what I counted to pass, and it provided an excellent shortener to use in the beginning. It also can help with grammar fixes — like the well-known Grammarly but with the difference that it’s one of many capabilities it provides.

Search engine on steroids.

That is one of the most outstanding achievements of ChatGPT, to become a new, faster, and more direct search engine. Two examples of that:

We are hiring on many possessions, such as Software Engineer in Test. I was about to interview a candidate with a unique set of technical skills that I’m not an expert. Before the new area, I would have to google most of that and try to look for some of the possible questions. So, with ChatGPT, I’ve asked: Can you provide me a list of 10 questions for an interview where the candidate has listed cypress, javascript, the postman, and ISTQB certificate for Software Engineer in Test position? That’s it, and a list of questions is there, with Answers !!! Within a second. Way faster than it usually would take.

My 15’th year’s old son, Mateusz, is now learning Python. I’m helping him on weekends to provide guidelines, review merge requests, or introduce new capabilities. He just finished his first console script and would like to transfer that to the window app. A few years ago, I was using PyQT for that, but maybe there is something new. So instead of doing regular searches, we asked ChatGPT.
What python library would you recommend for creating a Window application using Python for a junior developer?

So yes, PyQt was a good choice. Moreover, we asked, for example, “hello world” application so we can start with something more than an empty .py file.

Notes cleanup.

During the meetings, no matter what type it is, whenever I take notes, I do it in “draft” mode. So I can polish them later on and send them out. It typically takes a couple of minutes. Multiple that by 4–5 meetings, and you quickly spend an hour doing that. Here is an example of my short 15-minute notes from the meeting with one of the developers and how ChatGPT transferred it:

ChatGPT and other technologies, such as DaVinci-003, GPT-3, Bert, and many others, are intelligent technologies that can solve many issues of the current world. But now, humans need to connect to understand real-life problems and how technology works and solves them.

Thankfully some professionals make precisely such things. Connect ideas with engineering teams, and understand business and technology well enough to see the opportunities. We are lucky to have such team members on the board, like TGV partners Andrzej Rusewicz and Sebastian Burzynski, and gr8 connections in our network.

You can hear more about ChatGPT and other impressive technologies for upcoming years at the forthcoming TGV 64 Event !!!