Over the past few months, there has been a huge amount of hype and speculation about the implications of large language models (LLMs) such as OpenAI’s ChatGPT, Google’s Bard, Anthropic’s Claude, Meta’s LLaMA, and, most recently, GPT4. ChatGPT, in particular, reached 100 million users in two months, making it the fastest growing consumer application of all time.
It isn’t clear yet just what kind of impact LLMs will have, and opinions vary hugely. Many experts argue that LLMs will have little impact at all (early academic research suggests that the capability of LLMs is restricted to formal linguistic competence) or that even a near-infinite volume of text-based training data is still severely limiting. Others, such as Ethan Mollick, argue the opposite: “The businesses that understand the significance of this change — and act on it first — will be at a considerable advantage.”
What we do know now is that generative AI has captured the imagination of the wider public and that it is able to produce first drafts and generate ideas virtually instantaneously. We also know that it can struggle with accuracy.
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Haissam Badih PhD, is the Researcher and Professor at the Department of Math and Computer Science at the Lawrence Technological University, Southfield, Michigan, USA. He earned His B.S. degree in Computer Science from the University of Windsor at Ontario Canada, his M.S. Degree from Lawrence Technological University, and a Ph.D. in Computer Science and Informatics from Oakland University in 2020. He will begin his academic career at Lawrence Technological University in 2021. He has worked in various software companies in software engineering and architecture.He authored numerous journal and conference papers that were peer-reviewed. His current research and development interests and activities in Project DIAMOnD for Automation Alley in blockchain for building a 3D printer marketplace for the supply chain to support all kinds of business, including 4.0 Industry. This work on blockchain for autonomous systems design, sensor fusion, intelligent agents, automation, human/machine interaction, robotic programming, and interfacing/coding. His research dissertation, entitled "Advance and specialize our application of blockchain for webcam/microphone access control" and "Add Blockchain in A.I. for communication," has worked within research on the Blockchain and Decoy deception research project. He worked on blockchain and decoy deception using smart contracts. This project utilized a Blockchain application that enforces limited access to webcam and microphone devices. We utilize Blockchain's Smart Contract to form a contract between the user's computer and another party connected via a network.
