14 min listen
Allyson Ettinger on GPT-3
FromCarry the Two
ratings:
Length:
41 minutes
Released:
Jan 31, 2023
Format:
Podcast episode
Description
How can a teacher know if a student actually wrote their book report, or if a computer did it? Are AI writers coming for journalists’ jobs? What does it mean when a language processing model can write its own computer code upon request? These are all questions currently sparked by GPT-3, a free online natural language processing artificial intelligence by Open AI.
This isn’t your dimestore chatbot. GPT-3 takes advantage of a whole new method of artificial intelligence research, called neural nets, to create plays, write code, and even roleplay as a historical figure. But what are the limitations to this kind of AI? In this episode of Carry the Two, University of Chicago professor Allyson Ettinger walks us through how GPT-3 manages to sound so human and where and how it fails in interesting ways.
Find our transcript here: LINK
Curious to learn more? Check out these additional links:
Use natural language processing to talk with a TV character or historical figure: https://beta.character.ai/
Chat bot using GPT-3.5: https://chat.openai.com/chat
Find out how you can chat with GPT-3: https://lifearchitect.ai/how-do-i-talk-to-gpt/
When GPT-3 accidentally lies: https://www.technologyreview.com/2022/11/18/1063487/meta-large-language-model-ai-only-survived-three-days-gpt-3-science/
Microsoft’s chatbot that went racist: https://www.theverge.com/2016/3/24/11297050/tay-microsoft-chatbot-racist
Is GPT-3 a replacement or tool for journalists: https://contently.net/2022/12/15/trends/chatgpt/
Undark’s interview with GPT-3 on truth & journalism: https://undark.org/2023/01/07/interview-a-conversation-on-truth-and-fiction-with-chatgpt/
Previous Carry the Two episode on statistical language learning with Ben Reuveni: https://podcasts.apple.com/us/podcast/ben-reuveni-on-statistical-learning/id1629115184?i=1000577827727
Follow more of IMSI’s work: www.IMSI.institute, (twitter) @IMSI_institute, (mastodon) https://sciencemastodon.com/@IMSI, (instagram) IMSI.institute
Follow Allyson Ettinger: https://linguistics.uchicago.edu/people/allyson-ettinger, @AllysonEttinger
This episode was audio engineered by Tyler Damme.
Music by Blue Dot Sessions.
Sound effects from pixabay.
The Institute for Mathematical and Statistical Innovation (IMSI) is funded by NSF grant DMS-1929348.
This isn’t your dimestore chatbot. GPT-3 takes advantage of a whole new method of artificial intelligence research, called neural nets, to create plays, write code, and even roleplay as a historical figure. But what are the limitations to this kind of AI? In this episode of Carry the Two, University of Chicago professor Allyson Ettinger walks us through how GPT-3 manages to sound so human and where and how it fails in interesting ways.
Find our transcript here: LINK
Curious to learn more? Check out these additional links:
Use natural language processing to talk with a TV character or historical figure: https://beta.character.ai/
Chat bot using GPT-3.5: https://chat.openai.com/chat
Find out how you can chat with GPT-3: https://lifearchitect.ai/how-do-i-talk-to-gpt/
When GPT-3 accidentally lies: https://www.technologyreview.com/2022/11/18/1063487/meta-large-language-model-ai-only-survived-three-days-gpt-3-science/
Microsoft’s chatbot that went racist: https://www.theverge.com/2016/3/24/11297050/tay-microsoft-chatbot-racist
Is GPT-3 a replacement or tool for journalists: https://contently.net/2022/12/15/trends/chatgpt/
Undark’s interview with GPT-3 on truth & journalism: https://undark.org/2023/01/07/interview-a-conversation-on-truth-and-fiction-with-chatgpt/
Previous Carry the Two episode on statistical language learning with Ben Reuveni: https://podcasts.apple.com/us/podcast/ben-reuveni-on-statistical-learning/id1629115184?i=1000577827727
Follow more of IMSI’s work: www.IMSI.institute, (twitter) @IMSI_institute, (mastodon) https://sciencemastodon.com/@IMSI, (instagram) IMSI.institute
Follow Allyson Ettinger: https://linguistics.uchicago.edu/people/allyson-ettinger, @AllysonEttinger
This episode was audio engineered by Tyler Damme.
Music by Blue Dot Sessions.
Sound effects from pixabay.
The Institute for Mathematical and Statistical Innovation (IMSI) is funded by NSF grant DMS-1929348.
Released:
Jan 31, 2023
Format:
Podcast episode
Titles in the series (26)
Tiffany Christian on City-Friendly Animal Species: Our last episode featuring Statistician-in-Residence Tiffany Christian (at least for now), dives into sampling methods. How can we track animal populations, especially those who share our urban environment with us? Ecologists and statisticians have found methods to track everything from coyotes to Canadian geese and can see how their populations are changing over time. Find our transcript here: LINK Curious to learn more? Check out these additional links: Video explaining the statistics of capture mark recapture: https://www.youtube.com/watch?v=240806aPHVg Collection of examples using capture mark recapture: https://www.usgs.gov/centers/eesc/science/capture-mark-recapture-science?qt-science_center_objects=0 Urban coyote research: https://urbancoyoteresearch.com/coyote-info/basics-studying-coyotes Sampling methodology: https://www.khanacademy.org/math/statistics-probability/designing-studies/sampling-methods-stats/a/sampling-methods-rev by Carry the Two