- Last 7 days
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matthew-van-der-hoorn.notion.site matthew-van-der-hoorn.notion.site
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https://matthew-van-der-hoorn.notion.site/matthew-van-der-hoorn/Book-Reading-bc745728387b4369b5b63739292c9ce7
van der Hoorn's suggestions for reading
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en.wikipedia.org en.wikipedia.org
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The Glass Bead Game is "a kind of synthesis of human learning"[11] in which themes, such as a musical phrase or a philosophical thought, are stated. As the Game progresses, associations between the themes become deeper and more varied.[11] Although the Glass Bead Game is described lucidly, the rules and mechanics are not explained in detail.
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docdrop.org docdrop.org
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Wonder is the beginning of wisdom in learning from books as well as from nature.
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- Sep 2023
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theinformed.life theinformed.life
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31:00 Zettelkasten as system for ongoing learning (not bound to an outcome)
- see zk on process vs outcomes
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framework.thoughtvectors.net framework.thoughtvectors.net
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This activity is an invitation to thinkers of all levels of experience, knowledge, and vocation.
People like me that have learned about this way for thinking and the challenge that is finding alike minds that want to explore and build this for the next generation. Sometimes the difference between a blue thought and a revolution is having who to talk to about it. How can we connect people working on the same problem how do you put in the same metaphorical room the people trying to push the envolope
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www.gardnercampbell.net www.gardnercampbell.net
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Art is the hook that engages students…. The subjects are familiar so that students have much to recognize but they also contain elements of mystery so students have observations, ideas, and emotions to puzzle over [my emphasis]. (p. 24)
Right, so the modern equivalent would be to design a game or an 3d animation in an intuitive way, yet the integration of pipeline in this systems makes it so that not even experienced professionals in the area cn develop a short film or an interactive experience through art that eases people into coding.
I think we need to do a better job at this. If the system that allowed us to design the processes also taught it to people then we wouldn't have to chose between improving the learning curve and the system there should all be one. why did we stop shipping manuals with our tech..? ahh it was because we stopped caring about what the people that designed the tool thought.
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how do you ever migrate from a tricycle to a bicycle because a bicycle is very unnatural and very hard to learn compared to a tricycle, and yet in society it has superseded all the tricycles for people over five years old.
The simple idea that new systems are harder than old even if they're better because they are new and people have to put more effort into using them.
What I feel it's really important is the idea that the measure of a good system isn't only how easy it is to learn, if we only evaluate systems by their learning curve we'll be face with only being able to advance society at the speed of the slower adopter. Therefore we need to * Segment and dream about the future * Be mindful of the gap between where we are and where the vision is pushing towards since there has to be a common point that collectively moves us forwards
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arxiv.org arxiv.org
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Adaptive Stress Testing with Reward Augmentation for Autonomous Vehicle Validation
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arxiv.org arxiv.org
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"SPRING: GPT-4 Out-performs RL Algorithms byStudying Papers and Reasoning"
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Quantitatively, SPRING with GPT-4 outperforms all state-of-the-art RLbaselines, trained for 1M steps, without any training.
Them's fighten' words!
I haven't read it yet, but we're putting it on the list for this fall's reading group. Seriously, a strong result with a very strong implied claim. they are careful to say it's from their empirical results, very worth a look. I suspect that amount of implicit knowledge in the papers, text and DAG are helping to do this.
The Big Question: is their comparison to RL baselines fair, are they being trained from scratch? What does a fair comparison of any from-scratch model (RL or supervised) mean when compared to an LLM approach (or any approach using a foundation model), when that model is not really from scratch.
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bryanmmathers.com bryanmmathers.com
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This is an idea I created a few years ago using the Visual Thinkery process with Educators.Coop and their collaborators focusing on the world of work.
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During the discussion, Musk latched on to a key fact the team had discovered: The neural network did not work well until it had been trained on at least a million video clips.
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By early 2023, the neural network planner project had analyzed 10 million clips of video collected from the cars of Tesla customers. Did that mean it would merely be as good as the average of human drivers? “No, because we only use data from humans when they handled a situation well,” Shroff explained. Human labelers, many of them based in Buffalo, New York, assessed the videos and gave them grades. Musk told them to look for things “a five-star Uber driver would do,” and those were the videos used to train the computer.
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The “neural network planner” that Shroff and others were working on took a different approach. “Instead of determining the proper path of the car based on rules,” Shroff says, “we determine the car’s proper path by relying on a neural network that learns from millions of examples of what humans have done.” In other words, it’s human imitation. Faced with a situation, the neural network chooses a path based on what humans have done in thousands of similar situations. It’s like the way humans learn to speak and drive and play chess and eat spaghetti and do almost everything else; we might be given a set of rules to follow, but mainly we pick up the skills by observing how other people do them.
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www.nature.com www.nature.com
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Wang et. al. "Scientific discovery in the age of artificial intelligence", Nature, 2023.
A paper about the current state of using AI/ML for scientific discovery, connected with the AI4Science workshops at major conferences.
(NOTE: since Springer/Nature don't allow public pdfs to be linked without a paywall, we can't use hypothesis directly on the pdf of the paper, this link is to the website version of it.)
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www.techlearning.com www.techlearning.com
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QR Codes can be a great way for teachers to distribute class material. Here are free sites you can use to generate QR codes
Free QR code sites
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giansegato.com giansegato.com
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When I create I learn. When I consume I just relax
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We all know the old saying practice makes perfect. The more we use a certain region of our brain, the more our brain "prioritizes" and "hones" it. That is what leads to myelin: activity induces myelination, which leads to increased strength of connectivity and efficiency along those very neurons. It’s a self-reinforcing process.
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The fact of the matter is that digital products make it uniquely easy to trick yourself into thinking that you’re learning when you are actually being entertained.
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learning must be effortful in order for it to happen
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www.ncbi.nlm.nih.gov www.ncbi.nlm.nih.gov
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Recent work has revealed several new and significant aspects of the dynamics of theory change. First, statistical information, information about the probabilistic contingencies between events, plays a particularly important role in theory-formation both in science and in childhood. In the last fifteen years we’ve discovered the power of early statistical learning.
The data of the past is congruent with the current psychological trends that face the education system of today. Developmentalists have charted how children construct and revise intuitive theories. In turn, a variety of theories have developed because of the greater use of statistical information that supports probabilistic contingencies that help to better inform us of causal models and their distinctive cognitive functions. These studies investigate the physical, psychological, and social domains. In the case of intuitive psychology, or "theory of mind," developmentalism has traced a progression from an early understanding of emotion and action to an understanding of intentions and simple aspects of perception, to an understanding of knowledge vs. ignorance, and finally to a representational and then an interpretive theory of mind.
The mechanisms by which life evolved—from chemical beginnings to cognizing human beings—are central to understanding the psychological basis of learning. We are the product of an evolutionary process and it is the mechanisms inherent in this process that offer the most probable explanations to how we think and learn.
Bada, & Olusegun, S. (2015). Constructivism Learning Theory : A Paradigm for Teaching and Learning.
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arxiv.org arxiv.org
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"Are Pre-trained Convolutions Better than Pre-trained Transformers?"
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d4mucfpksywv.cloudfront.net d4mucfpksywv.cloudfront.net
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GPT-2 Introduction paper
Language Models are Unsupervised Multitask Learners A. Radford, J. Wu, R. Child, D. Luan, D. Amodei, and I. Sutskever, (2019).
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GPT-3 introduction paper
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norabateson.wordpress.com norabateson.wordpress.com
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- for: symmathesy, mutual learning, mutual transcontextual learning, individual collective entanglement, Indyweb, Indraweb, Indynet, Indranet
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definition: symmathesy
- mutual transcontextual learning in living systems
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comment
- symmathesy lay at the heart of the Indyweb and Indraweb
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norabateson.medium.com norabateson.medium.com
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- for: symmathesy, mutual learning, mutual transcontextual learning, individual collective entanglement, Indyweb, Indraweb, Indynet, Indranet
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definition: symmathesy
- mutual transcontextual learning
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comment
- symmathesy lay at the heart of the Indyweb and Indraweb
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proof of effort: How can teachers know that students have done the work?
Hypothes.is is an example of a tool which shows reading effort.
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the brain evolved to be uncertainty-averse. When things become less predictable — and therefore less controllable — we experience a strong state of threat. You may already know that threat leads to “fight, freeze, or flight” responses in the brain. You may not know that it also leads to decreases in motivation, focus, agility, cooperative behavior, self-control, sense of purpose and meaning, and overall well-being. In addition, threat creates significant impairments in your working memory: You can’t hold as many ideas in your mind to solve problems, nor can you pull as much information from your long-term memory when you need it.
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github.com github.com
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I'd suggest that you play around a little bit with a vanilla app. Create a brand new app without any additional files, just what rails new generates. See how bin/rails runner Models raises an error because there is no models directory in autoload_paths. Now, put config.autoload_paths += %W(#{config.root}/app) in config/application.rb and observe how bin/rails runner Models just returns a prompt. With the confidence of having that running, then transalate to your app.
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- Aug 2023
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www.youtube.com www.youtube.com
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(~13:00) Koe argues for making information relevant (Dr. Sung always says you must make info relevant) through the learning for the solving of a particular problem, either for a client, your business, or your personal life. Your problem becomes the lense through which you learn.
For self-education this is ideal.
Dr. Sung's approach differs in that he advocates for the creation of relevancy through inquiry (the asking of relational questions) which is also incredibly powerful, however this is more suited to gaining more motivation for forced learning, i.e., in the formal education system.
In addition, Koe's lense is, I think, more of a high-level filter, whereas Sung's questioning is applicable on the content level. Therefore, both approaches could be, and should be, combined into the same overall (self-)educational system.
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(~10:20) Koe makes a very, very, very valid point about education:
I quote: "There is one thing that the school system did get right which is consistent, daily education in hopes for a better future. But, schools don't prioritize curiosity, so most people hate learning by the time they graduate." (emphasis added by me)
The larger point that Koe is making is that if we own anything in life, it is our mind; for everything else can be taken away from us; as such, we must spend a significant amount of effort to cultivate it, grow it, care for it, and make it unique.
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(~6:07) Koe argues that specializing, or focusing on one aspect only, limits your potential in every conceivable way.
I think I agree, yet I do also think there is a place for that... It depends on the person and what they enjoy. However, I might still be mistaken.
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Dan Koe seems to argue against a specialistic education based on the argument that it is nigh-impossible for a teenager to decide what they want (to be) for the rest of their lives. He also gives the argument that it results in a lack of creativity and underlying knowledge (that which connects the dots, instead of compartmentalization) which would result in abnormal performance.
I can bypass the limitation of the first point by giving the counter-point that when one has an insane amount of metacognition, which can be trained, it does not matter if one changes path later; why? Because one can easily learn the new subject matter and skills.
However, the second point is interesting and I think I agree with it. That said, I think there is a continuum, instead of only two points, between super-specialists and super-generalists. I myself enjoy specializing. And I believe a team of specialists (that can also work together) can accomplish much more than one (or even multiple) generalist.
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example.com example.com
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https://web.hypothes.is/help/annotating-youtube-videos-with-the-hypothesis-lms-app/
Walkthrough for how to add YouTube Videos into LMS assignments for annotation with H.
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the ability to annotate YouTube videos directly within your Learning Management System (LMS)!
https://web.hypothes.is/blog/exciting-new-feature-annotate-youtube-videos-with-hypothesis/
Wishing this was easier within YouTube directly instead of hidden within the LMS. Of course, there's always still https://docdrop.org/ for this instead.
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What is done right before and right after sleep sets the stage for literally everything.
How you do anything is how you do everything.
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arxiv.org arxiv.org
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Title: Delays, Detours, and Forks in the Road: Latent State Models of Training Dynamics Authors: Michael Y. Hu1 Angelica Chen1 Naomi Saphra1 Kyunghyun Cho Note: This paper seems cool, using older interpretable machine learning models, graphical models to understand what is going on inside a deep neural network
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www.youtube.com www.youtube.com
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Ideally in the evening, before sleep, do some activity or activities that turn off the mind. You want to relax and stop thinking so much.
Interestingly enough, forgiveness, or the act of forgiving makes relaxing easy. So, if you have someone, or even yourself, to forgive... Do this right before going to sleep :)
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Apparently, cold shower for roughly 3-4 minutes (rather than a hot shower) before sleep are helpful for sleep, as it decreases the core body temperature.
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When you wake up, get sunlight in. Andrew Huberman also advocates for that. It tells the brain and body to wake up. It creates cortisol.
Can be combined with movement/exercise as well which also increases sleep quality. (Movement should not to be too late, however.)
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www.youtube.com www.youtube.com
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Consistency is key when it comes to sleep.
Always go to bed at the same time and wake up at the same time.
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www.youtube.com www.youtube.com
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Apparently, some Magnesiums can help with deep sleep.
Author takes 400mg.
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It is important to block blue light in the evening. Blue light sends signals to your body to be awake.
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One of the things to optimize sleep is to take care of meal timing. Author eats: - Breakfast at 8 - Lunch at noon (12) - Dinner between 5 and 6.30
Discipline and consistency is important here.
Essential is to eat dinner 3+ hours before you go to sleep.
Food increases core body temperature which negatively impacts sleep.
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www.youtube.com www.youtube.comYouTube1
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Sleep is the absolute foundation for top-performance.
Measure it. Track it. Optimize it.
After that, results WILL go into the sky.
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www.youtube.com www.youtube.com
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The sixth step, most essential as well, is to Accept the Wins
Owning the losses means also owning the wins.
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The fifth step is to have Selective Memory only choose to remember the events that serve the future. Things that help to improve in the future.
It's like Marcus Aurelius wrote (in a slightly different way): "Ask yourself at any moment, is this essential?" In this way it would become: "Ask yourself at any moment, does this help me?"
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The fourth step is to Apply the Reflection. Adjust behavior based on reflection. We improve not for validation, we improve for ourselves (stoic philosophy)
Document the journey in for example a journal. Make a comparison between what would be done in the past and what will be done in the future.
Data collection. Measurement.
Marginal Gains. It's sort of a daily continous Kolb's cycle but in a more lightweight form. I can already see the power in this. Absolute gem.
Could also be overwhelming if applied to a lot. therefore, use the power law and focus on what is essential to life change. (thanks Dr. Benjamin Hardy.)
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The third step is to Reflect and think into the future. Extract meaning and lessons from the failure. Think about opportunities.
Reflection increases confidence. Kolb's can help with this a lot.
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The second step is Sit with the loss in order to find the (root) cause of the loss or pain. Do not avoid the pain, don't distract oneself, instead embrace it and feel it.
Endurance can be trained. Comfort with uncomfortability can be trained in the same way.
Accept and sit in the fire. Embrace the turmoil.
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The first step to deal with loss of any kind, be it a girlfriend, love, job, purpose, etc. Is to ACCEPT YOU LOST
Failure = Failure.
Failure is inevitable, and will be part of any learning process. Therefore it should not be avoided at all costs. It should be used to learn from. However; there is also no point in seeking failure, for if failure is not something negative, there is no point to improve (says the author at least)
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docdrop.org docdrop.org
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to live for the common good is a very good purpose but purpose is a gift and the purpose of our life here on Earth is to change the environment which we met for something better because there is 00:21:54 always an opportunity for something better [Music] or to be in a learning mode and we when we know things to be in a teaching mode 00:22:11 also that is propagating what we know sharing it with others and making this knowledge open source for the world and especially to help train a young 00:22:24 generation of new leaders who are going to be the ones that grapple with these problems
- for: open source, indyweb, open learning commons, radical collaboration, individual / collective entanglement
- paraphrase
- quote
- to live for the common good is a very good purpose but
- purpose is a gift and the purpose of our life here on Earth is to change the environment which we met for something better because there is always an opportunity for something better
- author
- Obiora Ike
- quote
- I would urge us all to be in a learning mode and
- we when we know things to be in a teaching mode also
- that is propagating what we know
- sharing it with others and
- making this knowledge open source for the world and
- especially to help train a young generation of new leaders who are going to be the ones that grapple with these problems
- author
- Jeffrey Sachs
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www.youtube.com www.youtube.com
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The essence for this video is correct; active learning, progressive summarization, deep processing, relational analytical thinking, even evaluative.
Yet, the implementation is severely lacking; marginalia, text writing, etc.
Better would be the use of mindmaps or GRINDEmaps. I personally would combine it with the Antinet of course.
I do like this guy's teaching style though 😂
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unesdoc.unesco.org unesdoc.unesco.org
- Jul 2023
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www.reddit.com www.reddit.com
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Hello! I've recently encountered the Zettelkasten system and adore the emphasis on connecting ideas. However, I don't want to use the traditional index card way, seeing as I have a ring binder with 90 empty pages thus I don't want it to go to waste. I've researched a lot of methods using a notebook, where some organize their zettels by page number, while others write as usual and connect and index the ideas for every 30 pages or so. But considering that the loose-leaf paper can be in any order I chose, I think there can be a better workaround there. Any suggestions? Thanks in advance!
reply to u/SnooPandas3432 at https://www.reddit.com/r/Zettelkasten/comments/158tzk7/zettelkasten_on_a_ring_binder_with_looseleaf_paper/
She didn't specify a particular dimension, but I recall that Beatrice Webb used larger sheets of paper than traditional index-card sized slips in her practice and likely filed them into something akin to hanging files in a filing cabinet.
For students, I might suggest using the larger sheets/3-ring binder to make Cornell notes for coursework and then later distilling down one or two of the best ideas from a lecture or related readings into index card form for filing away over time. You could then have a repository of bigger formatted literature notes from books/lectures with more space and still have all the benefits of a more traditional card-based zettelkasten for creativity and writing. You could then have the benefit of questions for spaced repetition for quizzes/tests, while still keeping bigger ideas for writing papers or future research needs.
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openreview.net openreview.net
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Shayan Shirahmad Gale Bagi, Zahra Gharaee, Oliver Schulte, and Mark Crowley Generative Causal Representation Learning for Out-of-Distribution Motion Forecasting In International Conference on Machine Learning (ICML). Honolulu, Hawaii, USA. Jul, 2023.
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Both the cult of learning around Dante and the cult ofignorance around Newton are phenomena of the vicious spe-cialization of scholarship.
p. xxiv
Hutchins seems to indicate that the "vicious specialization of scholarship" is in part to blame for the emergence of the "two cultures" delineated by C. P. Snow later in the decade.
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docdrop.org docdrop.org
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alphago
- Alphago
- first version took months of Google UK software developers to program. It won the world Go championship.
- Alphago Master played itself without ever watching a human player. It beat the first Alphago version after 3 days of playing itself.
- In 21 days, it beat Alphago version one a thousand to zero.
- Alphago
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proceedings.mlr.press proceedings.mlr.press
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IMPALA: Scalable Distributed Deep-RL with Importance WeightedActor-Learner Architectures
(Espeholt, ICML, 2018) "IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures"
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proceedings.mlr.press proceedings.mlr.press
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This paper introduced the DPG Algorithm
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openreview.net openreview.net
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Link to page with information about the paper: https://openreview.net/forum?id=rJeXCo0cYX
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openreview.net openreview.net
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Yann LeCun released his vision for the future of Artificial Intelligence research in 2022, and it sounds a lot like Reinforcement Learning.
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www.cs.toronto.edu www.cs.toronto.edudqn.pdf1
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The paper that introduced the DQN algorithm for using Deep Learning with Reinforcement Learning to play Atari game.
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arxiv.org arxiv.org
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Paper that evaluated the existing Double Q-Learning algorithm on the new DQN approach and validated that it is very effective in the Deep RL realm.
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arxiv.org arxiv.org
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This paper introduces the DDPG algorithm which builds on the existing DPG algorithm from classic RL theory. The main idea is to define a deterministic policy, or nearly deterministic, for situations where the environment is very sensitive to suboptimal actions, and one action setting usually dominates in each state. This showed good performance, but could not beat algorithms such as PPO until the additions of SAC were added. SAC adds an entropy penalty which essentially penalizes uncertainty in any states. Using this, the deterministic policy gradient approach performs well.
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arxiv.org arxiv.org
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This famous paper gives a great review of the DQN algorithm a couple years after it changed everything in Deep RL. It compares six different extensions to DQN for Deep Reinforcement Learning, many of which have now become standard additions to DQN and other Deep RL algorithms. It also combines all of them together to produce the "rainbow" algorithm, which outperformed many other models for a while.
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arxiv.org arxiv.org
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Arxiv paper from 2021 on reinforcement learning in a scenario where your aim is to learn a workable POMDP policy, but you start with a fully observable MDP and adjust it over time towards a POMDP.
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arxiv.org arxiv.org
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Paper that introduced the PPO algorithm. PPO is, in a way, a response to the TRPO algorithm, trying to use the core idea but implement a more efficient and simpler algorithm.
TRPO defines the problem as a straight optimization problem, no learning is actually involved.
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arxiv.org arxiv.org
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Bowen Baker et. al. (Open AI) "Video PreTraining (VPT): Learning to Act by Watching Unlabeled Online Videos" Arkiv, June 2022.
Introduction of VPT : New semi-supervied pre-trained model for sequential decision making on Minecraft. Data are from human video playthroughs but are unlabelled.
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arxiv.org arxiv.org
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Liang, Machado, Talvite, Bowling - AAMAS 2016 "State of the Art Control of Atari Games Using Shallow Reinforcement Learning"
Response paper to DQN showing that well designed Value Function Approximations can also do well at these complex tasks without the use of Deep Learning
A great paper showing how to think differently about the latest advances in Deep RL. All is not always what it seems!
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arxiv.org arxiv.org
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Tom Schaul, John Quan, Ioannis Antonoglou and David Silver. "PRIORITIZED EXPERIENCE REPLAY", ICLR, 2016.
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openaccess.thecvf.com openaccess.thecvf.com
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Xu, ICCV, 2019 "Temporal Recurrent Networks for Online Action Detection"
arxiv: https://arxiv.org/abs/1811.07391 hypothesis: https://hyp.is/go?url=https%3A%2F%2Fopenaccess.thecvf.com%2Fcontent_ICCV_2019%2Fpapers%2FXu_Temporal_Recurrent_Networks_for_Online_Action_Detection_ICCV_2019_paper.pdf&group=world
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www.notion.so www.notion.so
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You can tell people just like I have you to focus their attention, choose a target. Imagine there's a spotlight shining just on it. Don't pay much attention to what's in your periphery almost as if you have like blinders on, right? So don't pay attention to those distractors. People can do that. We have them talk to us about like, well, what is it that you're focused on? What's catching your attention right now? Those are easy instructions to understand and it's easy to make your eyes do it. What's important though is that that's not what their eyes do naturally. When they're walking or when they're running, people do take a sort of wider perspective. They broaden their scope of attention relative to what these instructions are having them do. And when we taught people that narrowed style of attention, what we found is that they moved 23% faster in this course that we had set up. From the start line to the finish line, it was always exactly the same distance. And we were using our stop watches to see how fast did they move. They moved 23% faster and they said it hurt 17% less. Right? So exactly the same actual experience, but subjectively it was easier and they performed better. They increase the efficiency of this particular exercise.
(24:58) In order to perform significantly better, you need to FOCUS your attention on a single thing only. Multitasking won't work, and thinking about different things at once also doesn't work. Set up your environment to foster this insane level of focus.
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Those distances literally look farther to people that for whom it might be harder to make it to that finish line, to navigate that space. We also found that that's the case with motivation, that when people are more motivated to exercise or to make it to that finish line, that motivation can in a sense compensate for that effect of their body on their perception of distance. So that even highly motivated people, people who are highly motivated, even if they have a higher waist to hip ratio might see the distance in a way that suggests it's just as short as people who have a lower waist to hip ratio. So motivation can change our visual experience and align people to experience a world that looks more like a person who'd have an easier time navigating it. So those were two initial findings, sets of findings, that suggested our visual experiences are not just reflective of the world that's out there. But instead it has to do with what is our body capable of doing and what is our brain capable of supplementing, our own motivational states and physical states of our body are working together to shift what it is that we're seeing in the world out there.
(21:47) There is a clear relation between the body and the brain and they influence each other, at least in terms of perception with regards to motivation.
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We prioritize what we see versus what we hear, why is that? Now, what comes to mind when I say that is when, somebody is saying no, but shaking their head yes. And so we have this disconnect, but we tend to prioritize what the action and not what we're hearing. So something that we visually see instead of what we hear.Speaker 1There isn't a definitive answer on that, but one source of insight on why do we do that, it could be related to the neurological real estate that's taken up by our visual experience. There's far more of our cortex, the outer layer of our brain that responds to visual information than any other form of information
(13:36) Perhaps this is also why visual information is so useful for learning and cognition (see GRINDE)... Maybe the visual medium should be used more in instruction instead of primarily auditory lectures (do take into account redundancy and other medium effects from CLT though)
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www.youtube.com www.youtube.com
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GRINDE mapping: 1. Grouped: grouping knowledge together 2. Reflective: reflective of your (non-linear) thinking 3. Interconnected: making more & distant connections (stronger than the groups) 4. Non-verbal (visuals) 5. Directional: which relations are the strongest, in which order can you sequence them? 6. Emphasise (visually) the most important things (see directional as well)
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blogs.nvidia.com blogs.nvidia.com
Tags
- wikipedia:en=BERT_(language_model)
- wikipedia:en=Self-supervised_learning
- wikipedia:en=Attention_(machine_learning)
- wikipedia:en=Transformer_(machine_learning_model)
- ai
- wikipedia:en=Artificial_neural_network
- cito:cites=doi:10.48550/arXiv.1706.03762
- cito:cites=doi:10.48550/arXiv.2108.07258
- machine learning
- neural networks
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intentionalcollegeteaching.org intentionalcollegeteaching.org
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In their article, Scientist Spotlight Homework Assignments Shift Students’ Stereotypes of Scientists and Enhance Science Identity in a Diverse Introductory Science Class,” Jeffrey Schinske, Heather Perkins, Amanda Snyder, and Mary Wyer created a “scientist spotlight” weekly homework assignment to introduce counter stereotypical examples of scientists and provide a diverse representation of contributions to science. Each week, students reviewed a resource regarding these scientists’ research and personal history in lieu of other textbook readings. Through their analysis, the scholars were able to study and detect shifts in both scientist stereotypes and the students’ ability to see their possible selves in science.
This same sort of structure could be useful for introducing students to fellow college students and also professionals who eschew a hyper-connected, frenetic, algorithmic, hustle mindset.
A way to normalize digital minimalism and slow productivity
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www.sciencedirect.com www.sciencedirect.com
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Measuring social presence in online-based learning: An exploratory path analysis using log data and social network analysis
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- Jun 2023
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twitter.com twitter.com
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To be processed
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interblah.net interblah.net
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I think we have a responsibility not only to ourselves, but also to each other, to our community, not to use Ruby only in the ways that are either implicitly or explicitly promoted to us, but to explore the fringes, and wrestle with new and experimental features and techniques, so that as many different perspectives as possible inform on the question of “is this good or not”.
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www.youtube.com www.youtube.com
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The author, Rediscovering Analog, reads a book at least twice, usually. He first reads it mainly for pleasure, just to enjoy it and to see what's in it. During the second time, if applicable, he goes through the book using intellectual (or learning) systems and methodologies to extract value from the book.
The first pass, which the author terms Scouting, is thus namely for enjoyment, but keeping in mind what might be valuable or interesting that will be valuable in the future, basically an unguided open ear. He has a list of scouted books in each section of the Zettelkasten that might be relevant to the section. What he does is have a stack of physical cards there with just the name of the book and the author, without anything else. Then when author proceeds to extract value from the book, he takes the card out and puts it in the respective book. Afterwards throwing this particular card into the trash. It's a form of the Anti-Library.
( Personally, I would include an appropriate reading cost and a level on Adler's hierarchy of books. In addition, I would make sure that my process of orientation, in the Inquiry-Based Learning framework, has been completed before I put it as a book within the Anti-Library. )
This may not be the most efficient for the purpose of acquiring value, but efficiency is not all there is. Enjoyment is a big part of intellectual work as well, as Antonin Sertillanges argues in his book The Intellectual Life: Its spirit, methods, conditions, as well as Mihaly Csikszentmihaliy in his book Flow.
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We use the same model and architecture as GPT-2
What do they mean by "model" here? If they have retrained on more data, with a slightly different architecture, then the model weights after training must be different.
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www.youtube.com www.youtube.com
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(14:20-19:00) Dopamine Prediction Error is explained by Andrew Huberman in the following way: When we anticipate something exciting dopamine levels rise and rise, but when we fail it drops below baseline, decreasing motivation and drive immensely, sometimes even causing us to get sad. However, when we succeed, dopamine rises even higher, increasing our drive and motivation significantly... This is the idea that successes build upon each other, and why celebrating the "marginal gains" is a very powerful tool to build momentum and actually make progress. Surprise increases this effect even more: big dopamine hit, when you don't anticipate it.
Social Media algorithms make heavy use of this principle, therefore enslaving its user, in particular infinite scrolling platforms such as TikTok... Your dopamine levels rise as you're looking for that one thing you like, but it drops because you don't always have that one golden nugget. Then it rises once in a while when you find it. This contrast creates an illusion of enjoyment and traps the user in an infinite search of great content, especially when it's shortform. It makes you waste time so effectively. This is related to getting the success mindset of preferring delayed gratification over instant gratification.
It would be useful to reflect and introspect on your dopaminic baseline, and see what actually increases and decreases your dopamine, in addition to whether or not these things help to achieve your ambitions. As a high dopaminic baseline (which means your dopamine circuit is getting used to high hits from things as playing games, watching shortform content, watching porn) decreases your ability to focus for long amounts of time (attention span), and by extent your ability to learn and eventually reach success. Studying and learning can actually be fun, if your dopamine levels are managed properly, meaning you don't often engage in very high-dopamine emitting activities. You want your brain to be used to the low amounts of dopamine that studying gives. A framework to help with this reflection would be Kolb's.
A short-term dopamine reset is to not use the tool or device for about half an hour to an hour (or do NSDR). However, this is not a long-term solution.
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Huberman states that doing these 4 things consistently and regularly, as a habit, might seem to take time, therefore decreasing performance. BUT, in reality they increase performance, as these things improve your health, focus, and awareness significantly.
Therefore they are so-called Performance Enablers
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The 4 (behavioral) keypoints for great physical and mental as well as cognitive health:
One) (2:00-4:05) View sunlight early in the day. The light needs to reach the eyes--increasing alertness, mood, and focus, through certain receptors. Also increases sleep quality at night, according to Huberman. Ideally five to ten minutes on a clear day, and ten to twenty minutes on an overcast day. No sunglasses, and certainly not through windows and windshields. If no sun is out yet, use artificial bright light. Do this daily.
Two) (4:05-6:10) Do physical exercise each and every day. Doesn't have to be super intense. Huberman recommends zone two cardiovascular exercise. Walking very fast, running, cycling, rowing, swimming are examples. He says to get at least between 150 and 200 minutes of this exercise per week. Some resistance training as well for longevity and wellbeing, increases metabolism as well. Do this at least every other day, according to Huberman. Huberman alternates each day between cardiovascular exercise and resistance training.
Three) (6:20-9:10) People should have access to a rapid de-stress protocol or tools. This should be able to do quickly and instantly, without friction. You can just do one breath for destress. ( Deep long breath through nose, one quick breath in nose to completely fill the longs, and then breathe out through mouth long.)
Four) (9:12-14:00) To have a deliberate rewiring nervous system protocol to use. A thing that can be done is NSDR (Non-Sleep Deep Rest protocol), this is specifically to increase energy.
Ideally the NSDR should be done after each learning session as well to imitate deep sleep (REM) and therefore accelerate neuroplasticity and thus rewire the nervous system; increasing the strength of connections between neurons and therefore increase retention significantly.
NSDR is also a process of autonomity and control, it allows one to find that they are in control of their body and brain. It makes one realize that external factors don't necessarily have influence. According to Huberman, NSDR even replenishes dopamine when it is depleted, making it also suitable for increasing motivation.
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twitter.com twitter.com
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The question is Do you know what your superpower is? The combination of skills and abilities that's unique to you
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d4mucfpksywv.cloudfront.net d4mucfpksywv.cloudfront.net
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Recent work in computer vision has shown that common im-age datasets contain a non-trivial amount of near-duplicateimages. For instance CIFAR-10 has 3.3% overlap betweentrain and test images (Barz & Denzler, 2019). This results inan over-reporting of the generalization performance of ma-chine learning systems.
CIFAR-10 performance results are overestimates since some of the training data is essentially in the test set.
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twitter.com twitter.com
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Deep focus is possible. Take care of the base (the body): • Nutrition • Sleep • Exercise Then train your focus by observing the mind. It gets easily distracted. You can be aware of this. And suddenly you are in flow, without the 'You' being there.
Test Twitter Two
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www.quora.com www.quora.com
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That’s easy. You can’t learn without thinking. Thinking is cognition. It’s the ability to recognize, and reason something out. It is observation with some understanding. Learning occurs when memory is added to thinking. The toddler touches hot stove. It thinks, “ouch, there’s pain.” That is observation, and is thinking. But you can’t say it learned, until the toddler remembers that the sensation of heat gradient when approaching a stove will end in a burn, when the stove is touched
Learning happens when we add memory to thinking. So, thinking precedes learning, and is fundamental to learning.
note to self: is thinking required for memory?
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twitter.com twitter.com
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Focus is a muscle. Start with 4 sets of 20 minutes. Rest between sets. Progressive overload still applies to mental lifting. When you get stronger, add more weight. Increase to 4 sets of 45 minutes. Train your focus to hit your ideal financial physique in record time.
Test Twitter Annotation
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marketshareassociates.com marketshareassociates.com
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www.youtube.com www.youtube.comYouTube1
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https://www.youtube.com/watch?v=TQXMl4GycD0
- (intro & title) Studying is not the same as learning
- Higher order learning is interweaving information (interconnecting, building knowledge in networks and graphs) [a zettelkasten and a commonplace book stimulate higher order learning]
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www.youtube.com www.youtube.com
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How to learn the art of memory (quick)
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www.youtube.com www.youtube.com
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Basically, you must be unique. You can't compete when you learn exactly the same as everyone else. The education system sets up to fail and makes you a modern slave.
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Local file Local file
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www.fandm.edu www.fandm.edu
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Liang, Machado, Talvite, Bowling - AAMAS 2016 "State of the Art Control of Atari Games Using Shallow Reinforcement Learning"
A great paper showing how to think differently about the latest advances in Deep RL. All is not always what it seems!
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assets.pubpub.org assets.pubpub.org
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LeBlanc, D. G., & Lee, G. (2021). General Deep Reinforcement Learning in NES Games. Canadian AI 2021. Canadian Artificial Intelligence Association (CAIAC). https://doi.org/10.21428/594757db.8472938b
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quoteinvestigator.com quoteinvestigator.com
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By the 1980s the adage had implausibly been reassigned to Benjamin Franklin. The 1986 book “Approaches and Methods in Language Teaching” by Jack C. Richards and Theodore S. Rodgers contained the following passage:[12]1986 (Seventh Printing 1991), Approaches and Methods in Language Teaching: A Description and Analysis by Jack C. Richards and Theodore S. Rodgers, Chapter 7: The Silent Way, Quote Page 100, Cambridge … Continue reading These premises are succinctly represented in the words of Benjamin Franklin: Tell me and I forget, teach me and I remember, involve me and I learn.
The misattribution of this quote often seen in educational settings likely stems from Richards & Rodgers from 1986.
See also: - https://hypothes.is/a/cKMkaAZQEe6dq0fkeyNabA - https://hypothes.is/a/YWrJKgZPEe6dy2sJU5KcSw
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Several English renderings have been published over the years. The following excerpt is from “Xunzi: The Complete Text” within chapter 8 titled “The Achievements of the Ru”. The translator was Eric L. Hutton, and the publisher was Princeton University Press in 2014. Emphasis added to excerpts:[1]2014 Copyright, Xunzi: The Complete Text, Translated by Eric L. Hutton, Chapter 8: The Achievements of the Ru, Quote Page 64, Princeton University Press, Princeton, New Jersey. (Verified with … Continue reading Not having heard of it is not as good as having heard of it. Having heard of it is not as good as having seen it. Having seen it is not as good as knowing it. Knowing it is not as good as putting it into practice. Learning arrives at putting it into practice and then stops . . .
The frequent educational quote "Tell me and I forget, teach me and I remember, involve me and I learn.", often misattributed to Benjamin Franklin, is most attributable to 3rd century Confucian philosopher Kunzi (Xun Kuang or 荀子) who wrote:
Not having heard of it is not as good as having heard of it. Having heard of it is not as good as having seen it. Having seen it is not as good as knowing it. Knowing it is not as good as putting it into practice. Learning arrives at putting it into practice and then stops . . .
The translation of which appears in Xunzi: The Complete Text, Translated by Eric L. Hutton, Chapter 8: The Achievements of the Ru, Quote Page 64, Princeton University Press, Princeton, New Jersey. 2014.
Variations of the sentiment and attributions have appeared frequently thereafter.
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www.sciencedirect.com www.sciencedirect.com
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the design and integration of new technologies in learning activities cannot be studied independently of the classroom environment, less attention has been paid in learning environments
Designing new learning technology is not always the best solution without paying attention to its learning environment.
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gist.github.com gist.github.com
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Blog post comparing ASG (Auto Segmentation Criterion - yes, the last letter doesn't match) to CTC (Connectionist Temporal Classification) for aligning speech recognition model outputs with a transcript.
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docdrop.org docdrop.org
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Learning does not happen in a vacuum. It is influenced by social dynamics, most notably between students and their peers.
this reminds me of the "whiteboard effect" and the concept of collaborative learning as described by cal newport in his book, deep work.
such dynamics cultivate a culture of fortuitous learning and the exchange of ideas. when another individual is present, it instills a sense of accountability and motivation to dive profoundly into a problem and the gaps of each other's knowledge than we might when woking in solitude.
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college students engage with and consume more content than at any time in history. It just so happens that this content is delivered by a streaming service, video game or social media platform, not by a college instructor.
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Student engagement is one of the strongest leading indicators we have of positive learning outcomes. Consequently, when students are disengaged, they are less likely to achieve their learning goals.
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- May 2023
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psychology.cornell.edu psychology.cornell.edu
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“Protracted immaturity and dependence on paternal care is not an unfortunate byproduct of our evolution but instead a highly adaptive trait of our species, which has enabled human infants to efficiently organize attention to social agents and learn efficiently from social output
- Quote worthy
- "“Protracted immaturity and dependence on paternal care
- is not an unfortunate byproduct of our evolution
- but instead a highly adaptive trait of our species,
- which has enabled human infants to
- efficiently organize attention to social agents and
- learn efficiently from social output,”
- “The evolutionary goal of altricial species is
- not to become highly competent as quickly as possible
- but rather to excel at learning over time.”
- "“Protracted immaturity and dependence on paternal care
- Authors
- Michael Goldstein,
- Katerina Faust,
- Samantha Carouso-Peck
- Mary R. Elson
- Quote worthy
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the beauty of perceptual immaturity in altricial species is that it makes learning easier by reducing the complexity of the world
- the beauty of perceptual immaturity in altricial species is that
- it makes learning easier by reducing the complexity of the world,” the researchers wrote.
- Parents are key to altricial learning, Goldstein said,
- forming a two-way system of feedback.
- Far from being passive recipients, he said,
- infants of many species can change the behavior of their parents
- in ways that actively shape their own developments.
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- Title
- The Origins of Social Knowledge in Altricial Species,
- Journal
- The Annual Review of Developmental Psychology, - -
- Publication Date
- Dec, 2021
- Authors
- Michael Goldstein,
- Katerina Faust,
- Samantha Carouso-Peck and
- Mary R. Elson
- Title
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Deep Learning (DL) A Technique for Implementing Machine LearningSubfield of ML that uses specialized techniques involving multi-layer (2+) artificial neural networksLayering allows cascaded learning and abstraction levels (e.g. line -> shape -> object -> scene)Computationally intensive enabled by clouds, GPUs, and specialized HW such as FPGAs, TPUs, etc.
[29] AI - Deep Learning
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https://pressbooks.pub/illuminated/
A booklet prepared for teachers that introduces key concepts from the Science of Learning (i.e. cognitive neuroscience). The digital booklet is the result of a European project. Its content have been compiled from continuing professional development workshops for teachers and features evidence-based teaching practices that align with our knowledge of the Science of Learning.
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bioschemas.org bioschemas.org
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bioschemas.org bioschemas.org
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bioschemas.org bioschemas.org
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www.youtube.com www.youtube.com
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More than just taking notes - Learning exhaust by Nicole van der Hoeven
https://www.youtube.com/watch?v=3L24rKggMX8
Nice framing to broadly define note taking as a form of learning exhaust, but broadly nothing new here for me.
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slides.lobid.org slides.lobid.org
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www.dublincore.org www.dublincore.org
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www.dublincore.org www.dublincore.org
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www.dublincore.org www.dublincore.org
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schema.org schema.org
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schema.org schema.org
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developers.google.com developers.google.com
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elijah.cs.cmu.edu elijah.cs.cmu.edu