ChatGPT Celebrates Its First Anniversary: Achievements and Limitations

ChatGPT Celebrates Its First Anniversary: Achievements and Limitations

When San Francisco startup OpenAI launched ChatGPT on Nov. ⁣30, 2022, the technology landscape was shaken to its core —‍ and artificial intelligence (AI) rapidly moved from being a fringe idea to mainstream ​adoption.

“We ⁢spent a couple ⁢of​ decades learning how to talk to machines. What changed in November ‌2022‍ is that ⁣machines learned how to talk to us,” said Cisco CIO Fletcher Previn. “By​ December, it was clear [ChatGPT] would have a significant‌ impact, and for something that’s been around a year, ‍it continues to amaze and terrorize.”

Like other‍ enterprises, Cisco believes generative ⁣AI (gen AI) tools such as ChatGPT will eventually be embedded⁤ into every ‍back-end IT system and external product.

“ChatGPT’s explosive global popularity has‌ given us AI’s first true⁢ inflection point in public adoption,” said Ritu Jyoti, group vice president of ⁣Worldwide Artificial Intelligence and Automation Market Research ⁣at ⁤IDC.⁣ “As AI ​and automation investments ⁣grow, focus on outcomes, governance, and risk management is paramount.”

AI itself is not new. Companies have been investing heavily in predictive and interpretive AI for‍ years; consider Microsoft Outlook and⁢ its AutoComplete feature. But the release of GPT-3.5 captured the world’s attention ⁤and ⁣triggered a surge of investment in genAI generally ⁢and on the large language models ‍(LLMs) ‌that underpin the various tools.

In the simplest ​of terms, LLMs are next-word, image or code prediction engines. For example, ChatGPT ⁤(which stands for “chatbot⁢ generative pre-trained transformer“) is built‌ atop the GPT LLM, a computer algorithm that processes natural language ⁢inputs and predicts the next word ⁢based on⁢ what it’s already seen. Then it predicts the next word,⁣ and the next word, and so on until its answer is ‌complete.

AI’s adoption journey is not unique. ‍Technologists​ such as Previn liken it to the⁢ early days of‍ cloud computing, which spurred similar ​discussions ‍and debates ​about security, privacy, data‍ ownership, and liability.

“People⁣ were saying no bank will ever ⁤put their data on⁣ a public⁤ cloud, and ‌no enterprise will ever ⁢host their email on the Internet,” Previn⁣ said. “I think there ‌was a lot of similar angst around what it means to put​ your crown-jewel data assets in someone else’s data center.”

Full speed ahead,​ with problems

Most​ enterprises are still experimenting with ChatGPT‌ and other​ genAI tools, trying ⁣to figure out where their ‌return on⁤ investment will be. ⁣And⁢ most remain uncertain about how​ to use it and how to benefit from⁣ it, according to Avivah Litan, a⁣ distinguished vice​ president analyst with Gartner Research.

“They are seriously worried that ⁤they will fall behind if they don’t adopt these new technologies, but are not adequately prepared to adopt it,” Litan said.⁣ “Organizational ‌readiness is severely lacking in terms of skills, risk and security management,⁢ and⁤ overall strategy.”

Along⁢ with the promise of automating…

2023-11-22 02:41:02
Original ⁣from www.computerworld.com rnrn

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