ChatGPT will keep giving occasional wrong answers for a couple of years, according to Morgan Stanley.
The AI bot sometimes "hallucinates," meaning it generates responses that are seemingly convincing, but are actually wrong, according to the bank.
ChatGPT's and AI's way forward is to run the technology on edge devices, including mobile phones, Morgan Stanley said.
ChatGPT will continue to "hallucinate" wrong answers occasionally for years to come and won't take off until it's on your cellphone, according to Morgan Stanley.
In a note dated Wednesday, the US investment bank highlighted the AI chatbot's shortcomings, saying it occasionally makes up facts. "When we talk of high-accuracy task, it is worth mentioning that ChatGPT sometimes hallucinates and can generate answers that are seemingly convincing, but are actually wrong," Morgan Stanley analysts led by Shawn Kim wrote.
"At this stage, the best practice is for highly educated users to spot the mistakes and use Generative AI applications as an augmentation to existing labor rather than substitution," they added.
ChatGPT, developed by OpenAI, recently shot to fame after Microsoft injected $10 billion into the company. While its debut kicked off a sudden frenzy in AI stocks, it's also been met with judgement. Academics have warned that platforms like ChatGPT could print misinformation. For example, Insider's Samantha Delouya asked the language tool to write a news story – and it spat out fake quotes from Jeep-maker Stellantis' CEO Carlos Tavares.
"Accuracy will continue to be a challenge for the next couple of years," Morgan Stanley's Kim said about ChatGPT.
But there may be a solution to the inaccuracies of AI platforms. That's by connecting large language tools, such as ChatGPT, to specialized domains to verify certain information, the analysts said.
At the same time, tools like ChatGPT could significantly improve via edge computing, according to the bank. "However, to be able to scale AI to even more applications, they would need to run directly on edge devices, which usually do not have high-performance GPUs embedded," Kim said.
Edge computing is a model in which processing power is placed closer to where the data is being created in the physical world. Examples include, mobile phones, smart cameras, or in-car computers. Kim highlighted four reasons why running AI at the edge are beneficial. It minimizes lag times compared to cloud computing services, it's less costly, enables privacy and is more consumer-friendly.
"At the current stage, it is still mainly used for text/code writing. But, we are just at the beginning of the technology curve, and we expect to see exponential growth through different versions," Kim said in reference to ChatGPT.
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