Dr Bhavin Parekh’s Post

Great article from Nature Portfolio regarding generative AI in Accessibility. It touches on the need for consideration of under-represented individuals when we look to regulate AI. While acknowledging the fears many schools in the US have around plagiarism and cheating, chatbots and other AI tools can be extremely helpful for neurodivergent students and the article provides instances where these tools can also assist those who are English-language learners find success in both sharing and understanding content. Thanks to Amanda Heidt for such an insightful read! https://lnkd.in/d8EVFfGz

"It has been astonishing how many facets of higher education are being transformed by generative AI. As the months unfolded, so did the ideas and explorations of how ChatGPT and subsequent AI tools will affect teaching, learning, and how universities are managed. Higher education expert Louise Nicol suggested in February this year that online education would continue to grow and there would be increased integration with AI for more personalised learning. Highlighting the remarkable potential of technology Dr Paul LeBlanc, president of Southern New Hampshire University, said AI is forcing a paradigm shift in higher education from ‘what you know’ to ‘how you will be’, with knowledge no longer the foundation it has been in the past." #highereducation #highered #education #onlineeducation #artificialintelligence #generativeai #ai #chatgpt #technology #studentlearning #continuouslearning #professionaldevelopment

Why do AI systems like Chat-GPT often get factual questions wrong? CSE:s Richard Johansson, who was promoted to professor in April, has set out to find the answer, together with PhD students Lovisa Hagström, Mehrad Farahani and Nicolas Audinet de Pieuchon. “Our goal is to find a method of understanding how the algorithm acts when it knows something compared to when it does not", says Richard Johansson. Read more about his work in the article 👇 https://lnkd.in/e4P5jjw6 #AI #LLM #chatgpt #research #naturallanguageprocessing

IS YOUR AI HALLUCINATING? NEW APPROACH CAN TELL WHEN CHATBOTS MAKE THINGS UP Discover how researchers are tackling AI hallucinations in large language models with new methods to detect false responses. Learn about the implications for AI applications in healthcare and education. https://lnkd.in/dgk6VcAW

Companies that build large language models typically use a process called red-teaming to prevent safety issues. Teams of human testers write prompts aimed at triggering unsafe text from the model being tested. These prompts are used to teach chatbots to avoid such responses. Learn more about this process in this article from MIT News. #AI #chatbots #safety #redteaming

Each week we find a new topic for our readers. This week in #AI Education we’re discussing Large Language Models https://bit.ly/3NsNNlG

Important overview of "Eight Things Students Should Know About AI", written for students by a current high school senior who is also researching and developing AI tools for learning. https://lnkd.in/gqzG7636

Is ChatGPT making scientists hyper-productive? The highs and lows of using AI. Democratization of GPT has catalysed the use of LLMs in research writing. In a 2023 Nature survey of more than 1,600 scientists, almost 30% said that they had used generative AI tools to help write manuscripts, and about 15% said they had used them to help write grant applications. A very interesting article in 'Nature'. Read more here: https://lnkd.in/diizk8rj #reasearch #nature #gpt #llm

"ChatGPT and the Future of AI" by Terry Sejnowski is an insightful book that delves into Large Language Models (LLMs) - what they are, how they work, and their potential impact on our future. The book is structured into three parts: 1. Living with Large Language Models: An introduction to AI technologies including ChatGPT (Chapters 1–5) 2. Transformers: Exploring the origins, workings, capabilities, and potential threats of LLMs (Chapters 6–10) 3. Back to the Future: Discussing the future of AI and its potential benefits (Chapters 11–14) Sejnowski adeptly balances technical depth with clear explanations, occasionally seeking ChatGPT's help to simplify complex concepts. His engaging writing style and use of stories make the content accessible and enjoyable. While acknowledging the challenges of predicting the future in a rapidly evolving field, the book offers valuable insights for those looking to grasp the nuances of AI. Whether you're tech-savvy or a newcomer, "ChatGPT and the Future of AI" provides practical value and is a highly recommended read, even if you have philosophical differences with the author. Read my detailed review here: [Link to review](https://lnkd.in/gS_ScDJT) #ai #llm #chatgpt

Pleased to share that a paper I have worked on for some time has finally been published. Those interested in AI and language co-development can give it a read :) https://lnkd.in/e-Yammbz