Although ChatGPT appears to be quite remarkable, it still has limitations, find these out!
In the Machine Learning method, you first research the issue before using your data to train the Machine Learning algorithm. The solutions are then assessed, and if there is a problem, the errors are examined before starting over. Once it functions, you launch. The specific procedures needed to solve a problem are written down in traditional programming, but with a subset of Artificial Intelligence (AI), Machine Learning is motivated by human learning behaviour which it follows.
Although ChatGPT appears to be quite remarkable, it still has limitations. These restrictions include the inability to respond to questions that are phrased in a particular way since it necessitates rephrasing in order to comprehend the input question. A more significant drawback is the poor quality of the responses it provides, which occasionally sound reasonable but are overly vague or lengthy. When the model assumes what your confusing inquiry implies rather than seeking clarification it can lead to unintentional responses. As a result, ChatGPT-generated answers to questions have already been temporarily banned on the developer question-and-answer website StackOverflow.
Chat GPT can help with time-consuming and repetitive software development activities, saving developers time. Although it is unlikely to replace software engineers, it has the power to drastically alter how developers create software and utilize their time.
Though Chat GPT will be a wonderful aid to developers, don't expect it to take the position of developers just yet. For it to understand and create whole applications while keeping context, design, and business strategy in mind, there is still a long way to go!
We may therefore draw the conclusion that it is cool and that it will undoubtedly disrupt several sectors, but for now it will most likely just change the way we design software. When developers are stuck on a problem or need to start a project but are unsure about how to go about it, developers today visit sites like Stack Overflow, Google, etc. This trend can switch to just chatting with OpenAI.
Hopefully the goal is that the use of tools and technologies like Chat GPT will increase people's productivity and not just for developers, but many others like copywriters, webmasters, lawyers, doctors.
Stack Overflow moderators wrote that "the main issue is that while the answers that ChatGPT produces have a high likelihood of being inaccurate, they often look like they might be decent and the solutions are relatively easy to produce."
Critics claim that these tools are simply very effective at arranging words in a way that makes sense statistically, but they are unable to comprehend the meaning or determine whether the claims they make are true. Another major limitation is that ChatGPT's data is limited to 2021. The chatbot does not have an awareness of events or news that have occurred since then. Therefore, some prompts you ask will render no results such as "Who won the Super Bowl 2023?"
However, ChatGPT might open the door for brand-new positions. For instance, prompt engineering would become a sought-after skill set in the AI era. To acquire the greatest outcomes from chatbots, prompt engineers should be aware of the rules and procedures for developing model inputs. According to GlobalData's Dunlap, the rise of AI programmers like ChatGPT will also result in a spike in the need for software engineers knowledgeable in data science techniques. engineers, for instance, who can create, develop, and test apps employing platforms for data science.
Even though ChatGPT can't currently create complex code, such as that needed for banking apps, it will master coding within the next couple of years.
ChatGPT4 is set to be released by OpenAI somewhere in the Q1 of 2023.
GPT-4, is said by some to be “next-level” and disruptive, but what will the reality be? Hints that GPT-4 Will Be Multimodal AI?
Sam Altman in a late interview said that a multimodal model was in the near future. Multimodal means the ability to function in multiple modes, such as text, images, and sounds. OpenAI interacts with humans through text inputs. Whether it’s Dall-E or ChatGPT, it’s strictly a textual interaction. An AI with multimodal capabilities can interact through speech. It can listen to commands and provide information or perform a task.
Altman offered these details about what to expect soon:
“I think we’ll get multimodal models is not that much longer, and that’ll open up new things.
I think people are doing amazing work with agents that can use computers to do things for you, use programs, and this idea of a language interface where you say a natural language – what you want in this kind of dialogue back and forth. You can iterate and refine it, and the computer just does it for you. You see some of this with DALL-E and CoPilot in very early ways.”
Altman didn’t specifically say that GPT-4 will be multimodal. But he did hint that it was coming within a short time frame. Of particular interest is that he envisions multimodal AI as a platform for building new business models that aren’t possible today. He compared multimodal AI to the mobile platform and how that opened opportunities for thousands of new ventures and jobs.
One unconfirmed rumour on Twitter is that it will have 100 trillion parameters (compared to GPT-3’s 175 billion parameters). That rumour was debunked by Sam Altman.
OpenAI already has a ChatGPT model designed for translating natural language into code, called Codex.
We’ve created an improved version of OpenAI Codex, our AI system that translates natural language to code, and we are releasing it through our API in private beta starting today. Codex is the model that powers GitHub Copilot, which we built and launched in partnership with GitHub a month ago. Proficient in more than a dozen programming languages, Codex can now interpret simple commands in natural language and execute them on the user’s behalf—making it possible to build a natural language interface to existing applications. We are now inviting businesses and developers to build on top of OpenAI Codex through our API.
However, recent research shows that coding might be improved even more by utilizing ChatGPT's unique potential for human interaction. It is hardly unexpected that OpenAI is using more contractors while investing in this area. Despite this, ChatGPT-generated replies have been prohibited on the programmers' Q&A website Stack Overflow because even its mediocre solutions might seem plausible.
Yann LeCun, the chief AI scientist for Meta, stated that researchers would need to develop "a system that is capable of anticipating the effect of its own actions" in addition to having "some sort of internal world model, a mental model of how the world is going to change as a consequence of its own actions."
More on the topic:
ChatGPT3 is a huge milestone but not yet an imminent threat, we will see what the ChatGPT4 release brings, but taking into account the time to teach the model a new programming language we would probably wait a bit more.
But overall in the end we can confidently say that we will end in a place and time where AI writes code in multiple languages disrupting the huge tech industry and putting almost all of the repetitive FE and BE developers' jobs out of work.
GPT itself is not new, it started in 2018 and had multiple released versions and editions. Link to ChatGPT space on hugging face:
To understand more about it ChatGPT please check out Andrej Karpathy’s Let's build GPT: from scratch, in code, spelled out.
Interesting link about increasing developer’s productivity using ChatGPT from Programming with Mosh: https://www.youtube.com/watch?v=sTeoEFzVNSc
Another interesting example - creating a TO-DO app with ChatGPT https://blog.bitsrc.io/i-asked-chat-gpt-to-build-a-to-do-app-have-we-finally-met-our-replacement-ad347ad74c51