ChatGPT: Her History, Capabilities, and Competitors

ChatGPT was publicly released on November 30, 2022. It happened only a year ago, and this event is being very actively discussed all over the world and across many industries. Some people admire the newly gained technical capabilities and compare the introduction of ChatGPT with a new Google search or an iPhone. Others, to the contrary, discuss the risks and fears of this technology and one can find really horrifying titles in the media, like “Our way of making a living is suddenly destroyed”. What unites both groups is admitting a significant impact of this technology on our lives.

It looks like Artificial Intelligence (AI) has evolved so strongly as of today, that many of the science fiction ideas and technologies are becoming real in our eyes. For instance, creating a human-like intelligent robot who would be a close copy of a passed away relative is no longer a concept from sci-fi. And it is already the time when Azimov’s Laws of Robotics did become practical for our nowadays questions. And ChatGPT is only the first supernova of this AI generation on our skies while many technological companies such as Meta, Google, and others will release their next-gen AI in a very short timeframe.

ChatGPT history

Let’s look closely into what is ChatGPT and the new generation of AI in general. We will not limit only to ChatGPT but will take into account its analogs, competitors, and similar AI-based technologies as well.

The reasons for that:

  1. ChatGPT itself already has several versions and implementations – products built on top of it;
  2. ChatGPT is an AI model that can be trained differently; being a large corporation one can obtain an own copy of it and evolve this model. For instance, the newly released Bing AI by Microsoft is built using ChatGPT version 4 model, trained by Microsoft, and provides some different capabilities;
  3. Other technological companies strive to build their own AI models of similar complexity or higher;
  4. The social impact of such modern AI-based products is rather similar.

ChatGPT and Her History

So, how’s ChatGPT different from the AI-based solutions we have got used to?

ChatGPT (Generative Pre-trained Transformer) is a generative language AI model based on “transformer” architecture. These models are capable of processing large amounts of text and learning to perform natural language processing tasks very effectively.

ChatGPT is developed by OpenAI company, founded in December 2015 in San Francisco. The company is the author of several more famous AI products, such as DALL-E (the model which generates images) and Whisper (speech recognition model). OpenAI initially announced it would develop AI solutions with open-source code. However, the code of ChatGPT is not available to the public. While some make jokes that the company should rename itself into “ClosedAI”, the others criticize the not open-source approach – they state that humanity becomes dependent on a piece of software that only few people inside only one company know how it works. After the release of ChatGPT, capitalization of OpenAI reached 29 Bln dollars, which makes it an IT corporation with clear commercial interests.

OpenAI first pre-trained its GPT model in June 2018. It improved it to GPT-2 in February 2019, made it bigger, and still not available to the public due to ethical concerns. In May 2020 GPT-3, an even bigger version of GPT-2 was developed and able to perform well on a variety of tasks without the need for fine-tuning. So, the work on ChatGPT creation took years before we got the first possibility to try and use it.

Finally, the first publicly available version of ChatGPT was introduced on November 30, 2022 – it was version 3.5 which made an incredible hype and buzz in the media.

Since then, OpenAI has introduced a newer version, GPT 4, on March 14, 2023. Now it is available only to paid subscribers. The cost is 20 USD for private users (there is a limitation of the number of questions per time), while commercial use of this model is being billed per the number of prompts (questions/dialogues) and is significantly greater. GPT5 version 5 is now in training and expected to significantly improve in reasoning and problem-solving. We observe that OpenAI is progressing with ChatGPT maturity rather fast.

It is important to say that OpenAI was of course not the first company to propose AI chatbots. The topic of AI was raised in science in the 1940s. By the year 2022, thousands of AI-based IT solutions were present in the market. So, what made a difference?

Two factors that differ ChatGPT from what was present in the market:

  1. ChatGPT became the first to introduce a really large-scale and highly capable AI model which made a significant difference in comparison to the AI models we had previously;
  2. OpenAI and other companies made the topic of AI a prime marketing hype.

This could be compared to the introduction of an iPhone. There were smartphones before Apple’s presentation in late 2007, however, they were used and demanded just by few. The miracle of Apple Corporation was in making their product extremely popular and common. Something similar is happening with OpenAI and other companies in their competition in terms of adding complex AI solutions to our everyday life, business, and habits.

What ChatGPT Can Do and What She Can’t

ChatGPT differs from its predecessors in the size (complexity) of its AI model and in the intensity of its training. The complexity of large AI models is growing exponentially. For instance, the GPT-3 model, in particular, has 175 billion parameters in size, making it the largest language model ever trained.

Comparison of NLP models


To work, GPT needs to be “trained” on a large amount of text. For example, the GPT-3 model was trained on the text set that included over 8 million documents and over 10 billion words. Since then, OpenAI has already introduced GPT version 4 with 1 trillion parameters!

ChatGPT became the first publicly available AI model of such a size, which in turn gives her significantly greater capacity in language processing.

Because of this technical capacity, ChatGPT is capable of mimicking a human conversation so that sometimes it cannot be recognized as done by a machine. Even GPT-3.5, which I have access to, can do it in 35 human languages! Just a few years earlier, it would be seen as a miracle.

Besides the key function of mimicking human conversation, ChatGPT is also capable of performing several complex functions. First of all – to compile the output information in almost every possible style. From simple ones, like answering in a laconic Twitter style, the style of a business email, to the ability to copy the writing style of a specific person, or a format – teleplay scenarios, resumes, checklists, simple poems, fairy tales, essays, song lyrics, jokes, etc. And, completely deleting the edge between humans and robotics, she can write and interpret computer code in over 10 programming languages. We need to add that the computer language is just another language for ChatGPT, some say even an easier one due to its clearer and more defined structure.

On the other hand, there are limitations in the operations of ChatGPT:

  • Not real-time. Her knowledge is limited to the information she has been educated with, and this information is dated by years 2021-22. ChatGPT is not browsing the answers on the Internet. However, such implementations of GPT-4 as Bing and some others can do so.
  • No voice recognition and no ability to draw. However, these functions can be done by other products of OpenAI and other companies.
  • Cloud only. ChatGPT is technically complex, which means she needs huge resources of data centers to operate. This means that by giving her your data, you are actually sending it out. This is a ground for a huge privacy concern for companies and individuals. Would you want to upload your company’s confidential texts or personal know-hows somewhere outside of its resources?
  • Mistakes. ChatGPT can make mistakes, focus on the wrong solution to a problem, not account for multifactor influence for a certain situation (for example, several intersecting causes of a mistake in computer code to be fixed).

However, ChatGPT progresses very rapidly, and newer versions become more capable and proficient. And she also learns as she operates and interacts with users and their sources of information.

After defining do’s and don’ts, let’s identify some unique and sometimes untrivial benefits, which we could not get before ChatGPT entered our life. Some of them still can be not fully executable, but we are on the edge of making those possible.

  • Timely processing of large volumes of textual information. Imagine you need to read a large article or a book but have only several minutes to do it. For instance, you are preparing for a business meeting, but are very limited in time. Now you can upload the text to ChatGPT and ask to sum up the key takeaways. This task was not solvable before ChatGPT.
  • As a derivative from the above, imagine you need to have software code documentation that is not available – this is quite a common case in the IT industry. Or, you can have a code commented in a language, which you don’t know. ChatGPT can comprehend the code and write its overview very fast. Again, this is something that was not possible before. Of course, you could set up a team of software developers and technical writers – but statistics say this is something companies often don’t have time or resources for.
  • Getting external suggestions. Imagine you need help in preparation for a brainstorming. Just some ideas for your further discretion on whether to consider them or not. Traditional browsers provide sources, but it is for you to read them thorough and find the key points in each. Now ChatGPT can give some, although unverified, ideas.
  • ChatGPT can unify human knowledge regardless of the language. The knowledge of ChatGPT comes from different languages no matter which one you use to ask questions. Additionally, one can, for instance, upload a text in one language and ask to provide its key takeaways in another language.
  • Technical mentorship. Imagine you are an IT student studying a new technology and having a difficult technical question. Previously you would need to wait for your mentor to get advice. Now you can take away some burden from your mentor and consult about the task, like nonworking code, with ChatGPT.
  • Low code. For some easy IT tasks, ChatGPT can write pieces of software for you. This opens the way for some startups that need some simple software, for instance for proof-of-concept purposes, and don’t have software engineers on board. ChatGPT can help with some easy tasks, which in some cases can be sufficient to achieve a startup’s current goals.

New Generation of AI Technology

Let’s take a look at the mates of ChatGPT – other modern AI solutions available or being currently developed. We foresee a significant degree of competition in the AI sphere in the coming months (many would want to join the rising market) and years (as AI technology evolves).

Let’s divide ChatGPT’s mates into several categories:

  1. Solutions with ChatGPT. This is a class of solutions where one of the versions of ChatGPT is used as a language processing model and component. Overall, there are more than 10 implementations built with only GPT-4 model, including:
    1. Bing, Microsoft’s trained GPT-4 model, which is integrated in Microsoft browsers and Skype. It has access to internet, and, for instance, in Microsoft Edge browser, Bing bot can review and rephrase the contents of the currently visited web page. It was announced that Microsoft plans to add AI functionality to Office 365 suite as well.
    2. Chatsonic. It provides a more modern UX, offers the possibility to create digital artwork, and might be more accurate with facts and recent events. Furthermore, it offers pre-built templates to speed up writing processes. Chatsonic recognizes human voice commands.
    3. Replica. It is a personal companion able to hear and speak, having an animated avatar. Conversations with Replica grow together. In a certain sense, this product is close to Tamagotchi, but of a human kind and with a degree of growing relationships.
  2. Solutions that compete with ChatGPT. A set of technological companies work on their own language transformers. For instance, Google released its Bard chatbot on March 21, 2023, Meta corporation has its own Meta AI laboratory.
  3. AI models focused on other functionalities. There are AI-based solutions that convert text messages (tasks) into images, for instance, Midjourney and DELL-E. Other solutions focus on the conversion of speech to text and back.

All-in-all, there are more than 20 complex AI solutions available or under development.

Impact on the Workplace

As the AI models get more and more competent in solving specific tasks, this brings a noticeable impact on people’s day-to-day workplace. Certain professions have already been impacted by the use of modern chatbots and more consequences are expected to come. According to Bloomberg, over time AI technology will impact the daily work of nearly a quarter of all workers.

Here are some examples of human professions which already started to be replaced by ChatGPT and her mates.

  • Content creation. A set of professions connected with the creation of non-complicated written content can already be replaced with ChatGPT. For instance, the creation of articles for Search Engine Optimization (SEO), the creation of trivial posts in blogs, and creating content for email campaigns.
  • Text editorial. Chatbots have significantly increased their skills in editing texts, rephrasing, and optimizing the original author’s text. During the past months, a large number of authors named ChatGPT as a co-author of articles and books.
  • Game graphics. Chatbots like Midjourney and DELL-E become more and more actively used for the creation of graphical assets for the gaming industry.
  • Graphic visualization. An increasing number of visualizations for publications is being created by the chatbots, they already started to substitute professional graphic artists and photographers. When the requirements to design are not very complex, modern bots can create good enough images. There’s been much discussion of the potential harmful impact on the visual industry and substituting human has a large stake in it.
  • Scriptwriting. Chatbots start being used in writing scripts for plays and TV shows. Doing so, their capacity in text transformation can be considered good enough.
  • Basic level programming and debugging. ChatGPT can be applied to substitute some basic programming, thus substituting some of the tasks in the IT industry.

We can see that modern AI has already started to replace some of the professions and such a trend will likely accelerate. The result of such a replacement is in laying off some people from their workplace or forcing them to extend their current skills.

This brings us to an ethical problem of whether humanity should slow down the progress for the sake of keeping current employment. On the other hand, the replacement of some professions is what we typically observe together with the technical progress. This is quite wide, from cars replacing horse-driven carriages (and now going to driverless cars), moving a large number of previously paper-based pieces of information to digital format, introduction of cellular telephony, 3D printing, and other examples. Such inventions are helping humanity to increase its production capabilities, the quality and quantity of outputs, and consequently the quality of life. So, this ethical question is not new and rather it is not about substitution itself, but about the speed of the shift and the benefits we gain.

Read more about the Safety, Ethical, and Legal Aspects of ChatGPT.

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