Tag: natural language processing
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Podcast | Lex Fridman interviews Sam Altman (OpenAI)
I really enjoyed this conversation between Lex Fridman and Sam Altman. Sam is the CEO of OpenAI, who developed the GPT large language model, and the ChatGPT interface. I thought that his responses were thoughtful and considered. The conversation veers toward the technical, but there’s enough at a high level for this to be useful…
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Generative AI in higher education – HELTASA conference
This is a recording of a presentation I gave at the HELTASA conference, on the topic of generative AI in higher education. The focus of the talk was on ChatGPT but I tried to think about generative AI more broadly, including image generators like Midjourney and Stable Diffusion. I also tried to avoid making this…
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Having a conversation with an article through natural language processing
Thanks to Ben Gordon for pointing me towards explainpaper. In How to read a book (1972), Mortimer Adler says that “Reading…should be a conversation between you and the author.” Which is why I don’t read without a figurative pen in my hand; As I’m reading I want to mark up the text with questions and…
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How to replace a physiotherapist (or any professional, really)
Rowe, M., Nicholls, D. A., & Shaw, J. (2021). How to replace a physiotherapist: Artificial intelligence and the redistribution of expertise. Physiotherapy Theory and Practice. I’m really excited to finally share this article that I’ve been working on for a couple of years with David Nicholls and Jay Shaw. I say a couple of years…
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Comment: AI applications taking over professional tasks
Among the many, many tasks required of grade school teachers is that of gauging each student’s reading level, usually by a time-consuming and high-pressure one-on-one examination. Microsoft’s new Reading Progress application takes some of the load off the teacher’s shoulders, allowing kids to do their reading at home and using natural language understanding to help…
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Comment: Amazon Transcribe Medical
The new machine learning-powered service, Amazon Transcribe Medical, will allow physicians to quickly dictate their clinical notes and speech into accurate text in real time, without any human intervention, Amazon claims. Perez, S. (2019). Amazon debuts automatic speech recognition service, Amazon Transcribe Medical. Techcrunch. I use voice recognition on my phone fairly often and am…
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Comment: How AI could become an extension of your mind.
AlterEgo has sensors, embedded in a thin plastic, flexible and transparent device that sits on your neck just like a sticker. These sensors pick up on these internal signals sourced deep within the mouth cavity, right from the surface of the skin. An AI program running in the background then tries to figure out what…
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Comment: Lessons learned building natural language processing systems in health care
Many people make the mistake of assuming that clinical notes are written in English. That happens because that’s how doctors will answer if you ask them what language they use. Talby, D. (2019). Lessons learned building natural language processing systems in health care. O’Reilly. This is an interesting post making the point that medical language…
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Comment: Training a single AI model can emit as much carbon as five cars in their lifetimes
The results underscore another growing problem in AI, too: the sheer intensity of resources now required to produce paper-worthy results has made it increasingly challenging for people working in academia to continue contributing to research. “This trend toward training huge models on tons of data is not feasible for academics…because we don’t have the computational…
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WCPT poster: Introduction to machine learning in healthcare
My poster and list of references for the WCPT 2019 conference in Geneva.
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Mozilla’s Common Voice project
Any high-quality speech-to-text engines require thousands of hours of voice data to train them, but publicly available voice data is very limited and the cost of commercial datasets is exorbitant. This prompted the question, how might we collect large quantities of voice data for Open Source machine learning? Source: Branson, M. (2018). We’re intentionally designing…
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Doctors are burning out because electronic medical records are broken
For all the promise that digital records hold for making the system more efficient—and the very real benefit these records have already brought in areas like preventing medication errors—EMRs aren’t working on the whole. They’re time consuming, prioritize billing codes over patient care, and too often force physicians to focus on digital recordkeeping rather than…