Friday, June 24, 2022

6/24/22: Read a bit on explainable AI

 

Agenda & Minutes

  • Welcome to the 20th meeting, June 24, 2022.
  • Updates/news/inputs/comments
    • VK paper status? No report.
  • Readings, viewings, etc. 
  • Potential future readings that we have assessed in earlier meetings.
    • 2021 Turing Award lecture paper: https://dl.acm.org/doi/pdf/10.1145/3448250. We read the first two paragraphs. Vote was 4.5 to read more.
    • Vote on: Dalle-E 2 - how it works: https://www.youtube.com/watch?v=F1X4fHzF4mQ. Should we read/view more of this? Vote was 4.
    • Explainable AI as a reading/discussion topic: https://en.wikipedia.org/wiki/Explainable_artificial_intelligence. 6/24/22: vote was 4.0 based on up to but not including the last paragraph of the Goals section.
    • 6/10/22: vote was 4.0 on the following article coauthored by Timnit Gebru. https://dl.acm.org/doi/pdf/10.1145/3442188.3445922
    • Ni et al., Learning Good State and Action Representations via Tensor Decomposition, https://arxiv.org/abs/2105.01136. We read the title and 1st sentence. Vote to read more was 4 out of 5.
    • We have read through the fifth paragraph of  https://www.marktechpost.com/2022/03/07/an-introduction-to-saliency-maps-in-deep-learning, then voted on the priority for reading more of it. Vote: 3.67 out of 5.
    • CNN basics: https://towardsdatascience.com/the-most-intuitive-and-easiest-guide-for-convolutional-neural-network-3607be47480. We previously read 2 paragraphs. Read more? Vote was 3.6 out of 5.
    • https://www.youtube.com/watch?v=BolevVGJk18. This introduces Jonschkowski, Brock, Learning State Representations with Robotic Priors. Should we try the first paragraph(s) of the paper? Vote was 3.6 out of 5.
    • https://en.wikipedia.org/wiki/Markov_decision_process. Should we read/view more of this? Vote was 3 1/5.  
    • 6/10/22: vote was 3.0 on the following article. https://www.technologyreview.com/2020/12/04/1013294/google-ai-ethics-research-paper-forced-out-timnit-gebru/.
    • Brooks, R., 2017, Seven Deadly Sins of AI Prediction, in serveinfo\AIstudyGroup. Vote was 2.6 out of 5.

 

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Friday, June 17, 2022

6/17/22: Read about masking and how it connects back to attention

Agenda & Minutes

  • Welcome to the 19th meeting, June 17, 2022.
  • Any updates/news/inputs/comments?
    • (none)
  • Readings, viewings, etc. 
    • Source to read/view in more depth. 
      • https://e2eml.school/transformers.html: "Transformers From Scratch." We read up to "Rest Stop and an Off Ramp" and will start there next week. The vote was 4 3/8 out of 5 for this document, though we can always revote as we progress through it.
    • Sources to scan to see if we want to read more. Please send in more suggestions for readings. We can read/view the first paragraph/minute or so of each, assessing each. Should we read it in more depth? 5=strongly agree, 4=agree, 3=neutral, 2=disagree, 1=strongly disagree. 
  • Potential future readings that we have assessed in earlier meetings.
    • 2021 Turing Award lecture paper: https://dl.acm.org/doi/pdf/10.1145/3448250. We read the first two paragraphs. Vote was 4.5 to read more.
    • Vote on: Dalle-E 2 - how it works: https://www.youtube.com/watch?v=F1X4fHzF4mQ. Should we read/view more of this? Vote was 4.
    • 6/10/22: vote was 4.0 on the following article coauthored by Timnit Gebru. https://dl.acm.org/doi/pdf/10.1145/3442188.3445922
    • Ni et al., Learning Good State and Action Representations via Tensor Decomposition, https://arxiv.org/abs/2105.01136. We read the title and 1st sentence. Vote to read more was 4 out of 5.
    • We have read through the fifth paragraph of  https://www.marktechpost.com/2022/03/07/an-introduction-to-saliency-maps-in-deep-learning, then voted on the priority for reading more of it. Vote: 3.67 out of 5.
    • CNN basics: https://towardsdatascience.com/the-most-intuitive-and-easiest-guide-for-convolutional-neural-network-3607be47480. We previously read 2 paragraphs. Read more? Vote was 3.6 out of 5.
    • https://www.youtube.com/watch?v=BolevVGJk18. This introduces Jonschkowski, Brock, Learning State Representations with Robotic Priors. Should we try the first paragraph(s) of the paper? Vote was 3.6 out of 5.
    • https://en.wikipedia.org/wiki/Markov_decision_process. Should we read/view more of this? Vote was 3 1/5.  
    • 6/10/22: vote was 3.0 on the following article. https://www.technologyreview.com/2020/12/04/1013294/google-ai-ethics-research-paper-forced-out-timnit-gebru/.
    • Brooks, R., 2017, Seven Deadly Sins of AI Prediction, in serveinfo\AIstudyGroup. Vote was 2.6 out of 5.

 

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Friday, June 10, 2022

6/10/22: Back from break - continue readings

 

Agenda & Minutes

  • Welcome to the 18th meeting, June 10, 2022.
  • Any updates/news/inputs/comments?
    • VK's paper - recap
    • The last two meetings were cancelled and that may be why so few people are here for this meeting. Or maybe people are just in Summer mode. In any case DB will send a specific email for next week letting people know we are back to regular meetings.
  • Readings, viewings, etc. 
    • Source to read/view in more depth. 
      • https://e2eml.school/transformers.html: "Transformers From Scratch." We read part of "Second order sequence model with skips" but plan to reread starting from that section next week when there will hopefully be more attendees. The vote was 4 3/8 out of 5 for this document, though we can always revote as we progress through it.
    • Sources to scan to see if we want to read more. Please send in more suggestions for readings. We can read/view the first paragraph/minute or so of each, assessing each. Should we read it in more depth? 5=strongly agree, 4=agree, 3=neutral, 2=disagree, 1=strongly disagree. 
  • Potential future readings that we have assessed in earlier meetings.
    • 2021 Turing Award lecture paper: https://dl.acm.org/doi/pdf/10.1145/3448250. We read the first two paragraphs. Vote was 4.5 to read more.
    • Vote on: Dalle-E 2 - how it works: https://www.youtube.com/watch?v=F1X4fHzF4mQ. Should we read/view more of this? Vote was 4.
    • 6/10/22: vote was 4.0 on the following article coauthored by Timnit Gebru. https://dl.acm.org/doi/pdf/10.1145/3442188.3445922
    • Ni et al., Learning Good State and Action Representations via Tensor Decomposition, https://arxiv.org/abs/2105.01136. We read the title and 1st sentence. Vote to read more was 4 out of 5.
    • We have read through the fifth paragraph of  https://www.marktechpost.com/2022/03/07/an-introduction-to-saliency-maps-in-deep-learning, then voted on the priority for reading more of it. Vote: 3.67 out of 5.
    • CNN basics: https://towardsdatascience.com/the-most-intuitive-and-easiest-guide-for-convolutional-neural-network-3607be47480. We previously read 2 paragraphs. Read more? Vote was 3.6 out of 5.
    • https://www.youtube.com/watch?v=BolevVGJk18. This introduces Jonschkowski, Brock, Learning State Representations with Robotic Priors. Should we try the first paragraph(s) of the paper? Vote was 3.6 out of 5.
    • https://en.wikipedia.org/wiki/Markov_decision_process. Should we read/view more of this? Vote was 3 1/5.  
    • 6/10/22: vote was 3.0 on the following article. https://www.technologyreview.com/2020/12/04/1013294/google-ai-ethics-research-paper-forced-out-timnit-gebru/.
    • Brooks, R., 2017, Seven Deadly Sins of AI Prediction, in serveinfo\AIstudyGroup. Vote was 2.6 out of 5.

 

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Friday, May 20, 2022

5/20/22: Readings; also, we will skip the next two Friday meeting times

  Agenda & Minutes

  • Welcome to the 17th meeting.
  • Any updates/news/inputs/comments?
    • Next two weeks: this group will not meet.
    • JS's ML study group: many people did not get the email DB sent to ifsc-gradstudents@ualr.edu, so JS will contact Dr. P. to get his message out more effectively.
    • VK's paper was presented this morning in Minnesota!
  • Readings, viewings, etc. 
    • Source to read/view in more depth. 
      • Scan and vote on: 2021 Turing Award lecture paper: https://dl.acm.org/doi/pdf/10.1145/3448250. We read the first two paragraphs. Should we read/view more of this? (5=strongly agree, 4=agree, 3=neutral, 2=disagree, 1=strongly disagree.) Vote was 4.5.
      • https://e2eml.school/transformers.html: "Transformers From Scratch." We read up to: "Second order sequence model with skips". So we can start there next time we meet. The vote was 4 3/8 out of 5 for this document, though we can always revote as we progress through it.
We ended the meeting here.
  • Potential future readings that we have assessed in earlier meetings.
    • Vote on: Dalle-E 2 - how it works: https://www.youtube.com/watch?v=F1X4fHzF4mQ. Should we read/view more of this? Vote was 4.
    • Ni et al., Learning Good State and Action Representations via Tensor Decomposition, https://arxiv.org/abs/2105.01136. We read the title and 1st sentence. Vote to read more was 4 out of 5.
    • We have read through the fifth paragraph of  https://www.marktechpost.com/2022/03/07/an-introduction-to-saliency-maps-in-deep-learning, then voted on the priority for reading more of it. Vote: 3.67 out of 5.
    • CNN basics: https://towardsdatascience.com/the-most-intuitive-and-easiest-guide-for-convolutional-neural-network-3607be47480. We previously read 2 paragraphs. Read more? Vote was 3.6 out of 5.
    • https://www.youtube.com/watch?v=BolevVGJk18. This introduces Jonschkowski, Brock, Learning State Representations with Robotic Priors. Should we try the first paragraph(s) of the paper? Vote was 3.6 out of 5.
    • https://en.wikipedia.org/wiki/Markov_decision_process. Should we read/view more of this? Vote was 3 1/5.
    • Brooks, R., 2017, Seven Deadly Sins of AI Prediction, in serveinfo\AIstudyGroup. Vote was 2.6 out of 5.
  • Please send in more suggestions for readings. We can read/view the first paragraph/minute or so of each, assessing each whether to go over it in more depth. To assess each one, vote: Should we read/view more of this? 5=strongly agree, 4=agree, 3=neutral, 2=disagree, 1=strongly disagree.

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      Friday, May 13, 2022

      5/13/22: Presentation rehearsal; reading & discussion

       Agenda & Minutes

      • Welcome to the 16th meeting.
      • Any updates/news/inputs/comments?
        • VK's paper: rehearsal
        • No other reports.
      • Readings, viewings, etc. 
        • Source to read/view in more depth. 
          • https://e2eml.school/transformers.html: "Transformers From Scratch." We read through the sentence "A Markov chain illustrates a first order model for this." So we can start there next time. The vote was 4 3/8 out of 5 for this document, though we can always revote as we progress through it.
      We ended here.
      • Potential future readings that we have assessed in earlier meetings.
        • Vote on: Dalle-E 2 - how it works: https://www.youtube.com/watch?v=F1X4fHzF4mQ. Should we read/view more of this? Vote was 4.
        • Ni et al., Learning Good State and Action Representations via Tensor Decomposition, https://arxiv.org/abs/2105.01136. We read the title and 1st sentence. Vote to read more was 4 out of 5.
        • We have read through the fifth paragraph of  https://www.marktechpost.com/2022/03/07/an-introduction-to-saliency-maps-in-deep-learning, then voted on the priority for reading more of it. Vote: 3.67 out of 5.
        • CNN basics: https://towardsdatascience.com/the-most-intuitive-and-easiest-guide-for-convolutional-neural-network-3607be47480. We previously read 2 paragraphs. Read more? Vote was 3.6 out of 5.
        • https://www.youtube.com/watch?v=BolevVGJk18. This introduces Jonschkowski, Brock, Learning State Representations with Robotic Priors. Should we try the first paragraph(s) of the paper? Vote was 3.6 out of 5.
        • https://en.wikipedia.org/wiki/Markov_decision_process. Should we read/view more of this? Vote was 3 1/5.
        • Brooks, R., 2017, Seven Deadly Sins of AI Prediction, in serveinfo\AIstudyGroup. Vote was 2.6 out of 5.
      • Please send in more suggestions for readings. We can read/view the first paragraph/minute or so of each, assessing each whether to go over it in more depth. To assess each one, vote: Should we read/view more of this? 5=strongly agree, 4=agree, 3=neutral, 2=disagree, 1=strongly disagree.

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          Monday, May 2, 2022

          5/6/22: Reading and discussion (with co-host)

          Agenda & Minutes

          • Welcome to the 15th meeting.
          • Any updates/news/inputs/comments?
            • VK's paper 😲. 
            • ??
          • Readings, viewings, etc. (co-host: JS)
            • Source to read/view in more depth. 
              • https://e2eml.school/transformers.html: "Transformers From Scratch." We read up to the sentence "Because probabilities always sum to one, the values in each row will always add up to one." and were looking at the matrix after it, so next time we can finish the diagram and continue. The vote was 4 3/8 out of 5 for this document, though we can always revote as we progress through it.
          • Potential future readings that we have assessed in earlier meetings.
            • Vote on: Dalle-E 2 - how it works: https://www.youtube.com/watch?v=F1X4fHzF4mQ. Should we read/view more of this? Vote was 4.
            • Ni et al., Learning Good State and Action Representations via Tensor Decomposition, https://arxiv.org/abs/2105.01136. We read the title and 1st sentence. Vote to read more was 4 out of 5.
            • In a previous meeting we read through the fourth paragraph of  https://www.marktechpost.com/2022/03/07/an-introduction-to-saliency-maps-in-deep-learning/. Previously we read the fifth paragraph, then voted on the priority for reading more of it. Vote: 3.67 out of 5.
            • CNN basics: https://towardsdatascience.com/the-most-intuitive-and-easiest-guide-for-convolutional-neural-network-3607be47480. We previously read 2 paragraphs. Read more? Vote was 3.6 out of 5.
            • https://www.youtube.com/watch?v=BolevVGJk18. This introduces Jonschkowski, Brock, Learning State Representations with Robotic Priors. Should we try the first paragraph(s) of the paper? Vote was 3.6 out of 5.
            • https://en.wikipedia.org/wiki/Markov_decision_process. Should we read/view more of this? Vote was 3 1/5.
            • Brooks, R., 2017, Seven Deadly Sins of AI Prediction, in serveinfo\AIstudyGroup. Vote was 2.6 out of 5.
          • Please send in more suggestions for readings. We can read/view the first paragraph/minute or so of each, assessing each whether to go over it in more depth. To assess each one, vote: Should we read/view more of this? 5=strongly agree, 4=agree, 3=neutral, 2=disagree, 1=strongly disagree.

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              Friday, April 29, 2022

              4/29/22: More reading

                       Agenda & Minutes

              • Welcome to the 14th meeting.
              • Any updates/news/inputs/comments?
              • Readings, viewings, etc.: 
                • Sources to read/view in more depth.
                  • https://e2eml.school/transformers.html: "Transformers From Scratch." We read up to "First order sequence model" so next time we will start there.
                    • Remember that the vote was 4 3/8 out of 5 for this document, which can always be updated as we progress through it.
              The meeting ended here.
              • Potential future readings that we have assessed in earlier meetings.
                • In a previous meeting we read through the fourth paragraph of  https://www.marktechpost.com/2022/03/07/an-introduction-to-saliency-maps-in-deep-learning/. Previously we read the fifth paragraph, then voted on the priority for reading more of it. Vote: 3.67 out of 5.
                • CNN basics: https://towardsdatascience.com/the-most-intuitive-and-easiest-guide-for-convolutional-neural-network-3607be47480. We previously read 2 paragraphs. Read more? Vote was 3.6 out of 5.
                • https://www.youtube.com/watch?v=BolevVGJk18. This introduces Jonschkowski, Brock, Learning State Representations with Robotic Priors. Should we try the first paragraph(s) of the paper? Vote was 3.6 out of 5.
                • Ni et al., Learning Good State and Action Representations via Tensor Decomposition, https://arxiv.org/abs/2105.01136. We read the title and 1st sentence. Vote to read more was 4 out of 5.
                • Brooks, R., 2017, Seven Deadly Sins of AI Prediction, in serveinfo\AIstudyGroup. Vote was 2.6 out of 5.
              • We can read/view the first paragraph/minute or so of different sources, assessing each whether to go over it in more depth. To assess each one, vote: Should we read/view more of this? 5=strongly agree, 4=agree, 3=neutral, 2=disagree, 1=strongly disagree.
                    • https://en.wikipedia.org/wiki/Markov_decision_process. 
                    • MM suggests explainable AI as a reading/discussion topic. 

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