It’s safe to say that we’re all seeing headlines about ChatGPT — it’s a trending technology that’s gone mainstream in a viral way. Not because it’s suddenly being used by everyone — it’s not the new TikTok or the next iPhone — but because of what it represents: this technology is a pivotal moment in the evolution of artificial intelligence (AI) software development. PCGuide writer Kevin Pocock explains, “The chatbot has a language-based model that the developer fine-tunes for human interaction in a conversational manner.” As an auto-generative system, the potential for this AI is considerable for technical advances, disruption of multiple industries, and the highly-speculated timeline of widespread robotic implementation.
In this blog, we discuss the following points about ChatGPT:
ChatGPT — full name Chat Generative Pre-trained Transformer — launched in late November 2022 falls in to the following category of artificial intelligence: “large language model tools”. According to the deployers of ChatGPT, OpenAI, the model interacts in a conversational way. Their official site outlines that, “The dialogue format makes it possible for ChatGPT to answer followup questions, admit its mistakes, challenge incorrect premises, and reject inappropriate requests.”
This language model was developed using a complex combination of Reinforcement Learning from Human Feedback (RLHF) that enabled the generative chatbot AI; OpenAI have previously launched a product called Generative Pre-Trained Transformer 3 (GPT-3) that is an “autoaggresive language model” that uses deep learning to output humanoid text. ChatGPT is a chatbot product powered by GPT-3 whereas GPT-3 uses initial text as a prompt for output.
The uses of it are already considerable — within five days of launch OpenAI’s President and Co-Founder Greg Brockman tweeted the product user count exceeded 1 million — and these are early days for a chatbot that is technically an AI prototype. ChatGPT is representative of what the AI-generated content and UX will look like in the future. It’s important to note that the free version of the product has experienced some trouble: firstly, on a technical level with site access which suggests that OpenAI’s servers are repeatedly overloaded with people trying to use the free technology, and, secondly, on an accuracy level as some users have reported the AI filling in ‘blanks’ with random facts while OpenAI also says that ChatGPT currently has “limited knowledge of world events after 2021”.
We would be remiss not to address the reality that in the brief period since launch, Chat-GPT has been met with and continues to be the focus of the aforementioned massive amounts of attention. This attention is wide-reaching beginning with enthusiasm from a technological innovation standpoint shifting to concern with questions about the ethics of this AI in educational settings (namely secondary schools and universities) that has already led to bans on the product in some Australian schools
This is where the machine learning and deep learning characteristics are relevant to what the impact of ChatGPT actually is. There are immediate benefits to ChatGPT and this kind of AI technology in general due to these capabilities and features:
These features can be incorporated into a range of high-level and low-level tasks including content production, customer service, administration, professional document-writing, and educational resources. In software development, the progression of this AI from basic functionalities to advanced operations that are humanoid and believable is genuinely a historic moment. ChatGPT is capable of writing code, identifying and fixing errors, and also can help eliminate tiresome and repetitive tasks software developers and engineers need to do.
Equally, we need to flag some of the shortcomings of the features. On a technical and user level, there is already considerable discourse about the AI’s performance record of accuracy vs inaccuracies or generalist responses that can be seen as inaccuracies as noted above. The extent of how powerful and reliable this AI is and whether we will opt to use it for tasks instead of — or in place of — human beings is dependent on how sophisticated we need it to be: the limitations with facts, understanding of philosophy and critical analysis, and, creativity remain.
Where ChatGPT technology and this type of AI fits with customized software development is a key discussion point in this explainer. As the technical AI consists of supervised learning and reinforcement learning, that built and trained ChatGPT on both the AI and user side, software developers can wield ChatGPT as a tool in their custom development process without replacing themselves. Stephen Shankland expands on this for CNET, “It’s an AI that’s trained to recognize patterns in vast swaths of text harvested from the internet, then further trained with human assistance to deliver more useful, better dialog.” During the development process, developers can implement this to build even better custom products that won’t necessarily add to development costs or diminish tailored solutions. ChatGPT can be used for strategic tasks in the development process that are easily checked by developers which enables reallocation of time spent on other aspects of building custom software; the actual tasks the program can complete are limited though this is a strength in an unexpected way — developers basically have an additional tool in their arsenal.
On the UX side of custom software development, ChatGPT has scope to elevate and diversify the conversational AI already in use. UX is central to the customer experience and customer service for most organizations now, across platforms including apps, websites, Internet of Things, and progressive web applications. If ChatGPT is accurate and robust enough to handle customer interactions is still being established though it has already been put to the test with Meta, Canva, and Shopify all using the AI for their customer service now. The leading features of ChatGPT with its lifelikeness, human engagement power, and machine learning mean it has significant promise for software developers thinking of using it in the UX development of custom solutions. That said, as we’ve already covered, the risk of inaccuracies or issues do mean any organizations using the AI are making themselves vulnerable — and possibly causing financial and brand damage with their customer experience on the line. If the ChatGPT AI will change UX design in totality is unclear though less bugs in the platform and the technology developing to a point where data input is always current makes the hypothetical standard of this kind of chatbot seemingly doable.
A final point to cover is if ChatGPT is worth the investment. We’ve already mentioned that the platform is free to everyone. There is however a waitlist sign-up process open for a paid ChatGPT Professional product though the exact features of this are unknown. The OpenAI proposition for the product lists benefits for “no blackout windows, no throttling, and as many messages as you need”. Techcrunch reports that the ChatGPT Professional is in pilot mode and price point preferences are being surveyed during sign-up; this is noteworthy as ChatGPT is reportedly expensive for OpenAI to run especially with the volume of user demand.
The actual return-on-investment for this technology area is hard to quantify though the quantitative value is apparent even after three months of public access. For organizations looking to integrate the features of ChatGPT into their products, this AI could dovetail in with the other aspects of a custom software development solution with favourable returns in profit and investment. Fortune Business Insights reported the AI market’s global worth as $387.45 billion USD in 2022 and is projected to reach a value of $1394.30 billion USD in 2029. Therefore with these developments and how nearly every industry has responded to this free ChatGPT prototype, we could wager that the niche will boom in time and have a diversified impact on custom software development.
From here, we can obviously acknowledge that the AI used in our apps and all technology will continually grow smarter, more effective, and more efficient. Beyond 2023, all technology including the phases of custom software development and deployment will incorporate, if they don’t already involve them, all kinds of AI-enabled automation features. Contrary to our early concepts of robotics, any form of AI or automated technology falls under the classification of robots and machines.
Despite it being an early stage of this technology, it’s worthwhile to look at ChatGPT in terms of an ergonomic tool rather than an all-in-one replacement solution for everything from customer service to knowledge work. Even so, there is already speculation as to if this spells the end for Google’s search engine and if this has the capacity to change education systems negatively while paradoxically also permanently revolutionizing learning in the years ahead. This remains a ‘watch-this-space’ area of technology however it is a compelling development in automation and it’s as certain as anything can be that the success of OpenAI’s launch of ChatGPT is synonymous with a market that’s ready and willing to embrace this kind of automation. Lastly, we should mention that Microsoft is now a major investor in ChatGPT and this will likely contribute to its prominence for the foreseeable future though comparable products like Google’s LaMDA are generating buzz, too. There is no doubt that this AI will be prominent in technology in the years ahead and understanding the dynamics and applications of the various niches of AI is a smart move for all businesses and non-commercial organizations everywhere.
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