ChatGPT Doesn’t Exist Where Real Generative AI Innovations Lies

ChatGPT is now both a blessing and curse for tech leaders and entrepreneurs.

Generative AI Vs ChatGPT
Source: | Generative AI Vs ChatGPT

For tech executives and leaders, ChatGPT’s success has been both a boon and a curse. On the one hand, it has raised investment in underfunded R&D teams, made generative AI appear like it has limitless promise, and elevated technology to the top of the boardroom agenda. However, it has also diverted attention from other significant AI and tech initiatives, syphoned funds from other programmes to fund a desperate attempt by competitors to catch up, and maybe set off a big compliance timebomb that might blow at any moment.

Precisely, ChatGPT has turned into a distraction. The majority of forward-thinking and creative companies have previously experimented with or successfully implemented AI. The problem is that not all AI advancement is immediately apparent or visually appealing. While automating and streamlining a necessary but tedious procedure could increase productivity and boost profits, it is unlikely to make as much news as a language model that can pass a challenging test.

Every company seemed to be rushing to release their generative AI news ahead of the competition as ChatGPT fever spread. And for good reason: research indicates that the S&P 500 companies’ share prices outperformed those of the companies that did not discuss artificial intelligence during earnings calls. It’s likely that increased timetables, a few all-nighters, and—most importantly—redirected energies that had been occupied elsewhere were the driving forces behind these firms’ AI announcements.

Good news for the value of the stock. Not ideal for innovation plans, which now require more examination.

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Disadvantage in the marketplace

Ironically, not everyone has realised the importance of generative AI or the best method to use it, despite the fact that in principle anybody may access it with only a credit card information, a chat interface, or a basic API. Businesses are missing out on opportunities because, although knowing they must employ GenAI to stay competitive, they don’t really do it well enough.

One may argue that the companies investing thousands of hours in strategy, R&D, and product development time on these platforms are essentially depleting their teams’ valuable innovation resources, especially in the absence of strong governance and learning-sharing procedures.

Please understand that ChatGPT is a very helpful tool that may increase productivity and efficiency in a number of ways. It may be used as a lightning-fast research helper, to speed up the generation of content, or to improve customer service, among many other tasks. Additionally, all businesses have to be using it or a different type of generative AI as a “starter for 10.” However, it loses its competitive edge and becomes the same as utilising a search engine in the late 1990s when everyone has access to the same resources. Being an early adopter may give you an advantage, but those benefits quickly spread and become commonplace.

Generative AI’s full potential can only be realised by applying it to strengthen and expedite each company’s unique skills. You are the expert on your own company, and no off-the-shelf generative AI tool can compare to the exclusive intelligence contained in your organization’s data. Businesses may benefit from hyper-relevant industry information that is specifically contextualised and in line with their company strategy and goals by including industry-specific data into custom LLMs and applications.

This is already occurring in the wild.

Customised Made to Guage vs. Off-the-Shelf

Harvey is a generative AI platform that law and accounting firms use globally for contract analysis, due diligence, litigation, and regulatory compliance. Going one step further, PwC said in March that it will be collaborating with Harvey to build its own exclusive AI models that separate data unique to each organisation. Similar to this, Mondelez International, the company that owns Cadbury and Oreos, developed a generative AI software that allows researchers to find and improve new recipes in an effort to find consumer-friendly new items.

Of course, creating or implementing a bespoke LLM is motivated in part by distinction, but security and intellectual property protection are considerably more essential considerations. Samsung disclosed earlier this year that workers supplying corporate data via ChatGPT had exposed private information, including source code and meeting minutes. Any company employing ChatGPT runs the risk of unintentionally disclosing confidential information to other users because the application keeps all inputs as training data. Generally speaking, people should be aware that free programmes provide inadequate levels of data protection.

Since then, OpenAI has introduced ChatGPT Enterprise in an effort to make its main product more appealing to companies in an effort to solve these problems. Although it makes the claim to provide greater privacy safeguards, there is still the additional problem that the data is managed and kept in the US, which might present problems for organisations in the UK and Europe.

Using responsible experimentation

But while ChatGPT is readily available now, pragmatics will understand that training a custom LLM and putting AI technologies into practice require time. They will also be aware that it is pointless to try to police personnel who are already utilising some form of Generative AI in their job.

“Responsible experimentation” should be your approach rather than sticking your head in the sand and opening yourself up to hazards of reckless use or being leapfrogged by rivals. Allowing a few carefully selected applications is a smart place to start in order to reduce the majority of user-associated dangers, while a complete ban on generative AI tools is unlikely to be beneficial.

In order to provide explicit staff rules, responsible experimentation also necessitates close collaboration with legal and data protection departments. When it comes to AI governance and supervision, don’t cut corners now. You can always apply your bespoke solutions later. It is difficult to break bad habits, thus it is important to build behaviours that encourage employees to use AI technologies responsibly and place responsibility on them as soon as feasible.

Businesses in every industry area are expected to undergo a significant transformation in the next years. Businesses that proactively invest in data and AI to generate long-term value and growth will outperform those who focus just on making quick profits.

Nevertheless, investigating off-the-shelf generative artificial intelligence technologies is worthwhile, especially if they have the potential to significantly increase production and efficiency.

The difficulty is in striking the correct balance for your company; you won’t succeed if you wait for the answer to present itself. Asking the appropriate inquiry is the only way to receive the right answer from any chatbot or search engine. And it takes asking a few incorrect questions before you can arrive at the right one.