#active learning

-- study tips!

this'll be a bit of a longer post. during my time working at my learning center, we were taught to help students implement these strategies to have more effective study sessions. below the cut i explain all of them in a little bit more detail so hopefully you all will be able to try some of them out as the school year takes off!

An article by Richard James Rogers (Award-Winning Author of The Quick Guide to Classroom Management and The Power of Praise: Empowering Students Through Positive Feedback). This blog post is illustrated by Pop Sutthiya Lertyongphati. Success in high school is not just about hard work: it’s about working smart, using proven strategies that boost learning, memory, and motivation. Here are 10…

Bayesian Active Exploration: A New Frontier in Artificial Intelligence

The field of artificial intelligence has seen tremendous growth and advancements in recent years, with various techniques and paradigms emerging to tackle complex problems in the field of machine learning, computer vision, and natural language processing. Two of these concepts that have attracted a lot of attention are active inference and Bayesian mechanics. Although both techniques have been researched separately, their synergy has the potential to revolutionize AI by creating more efficient, accurate, and effective systems.

Traditional machine learning algorithms rely on a passive approach, where the system receives data and updates its parameters without actively influencing the data collection process. However, this approach can have limitations, especially in complex and dynamic environments. Active interference, on the other hand, allows AI systems to take an active role in selecting the most informative data points or actions to collect more relevant information. In this way, active inference allows systems to adapt to changing environments, reducing the need for labeled data and improving the efficiency of learning and decision-making.

One of the first milestones in active inference was the development of the "query by committee" algorithm by Freund et al. in 1997. This algorithm used a committee of models to determine the most meaningful data points to capture, laying the foundation for future active learning techniques. Another important milestone was the introduction of "uncertainty sampling" by Lewis and Gale in 1994, which selected data points with the highest uncertainty or ambiguity to capture more information.

Bayesian mechanics, on the other hand, provides a probabilistic framework for reasoning and decision-making under uncertainty. By modeling complex systems using probability distributions, Bayesian mechanics enables AI systems to quantify uncertainty and ambiguity, thereby making more informed decisions when faced with incomplete or noisy data. Bayesian inference, the process of updating the prior distribution using new data, is a powerful tool for learning and decision-making.

One of the first milestones in Bayesian mechanics was the development of Bayes' theorem by Thomas Bayes in 1763. This theorem provided a mathematical framework for updating the probability of a hypothesis based on new evidence. Another important milestone was the introduction of Bayesian networks by Pearl in 1988, which provided a structured approach to modeling complex systems using probability distributions.

While active inference and Bayesian mechanics each have their strengths, combining them has the potential to create a new generation of AI systems that can actively collect informative data and update their probabilistic models to make more informed decisions. The combination of active inference and Bayesian mechanics has numerous applications in AI, including robotics, computer vision, and natural language processing. In robotics, for example, active inference can be used to actively explore the environment, collect more informative data, and improve navigation and decision-making. In computer vision, active inference can be used to actively select the most informative images or viewpoints, improving object recognition or scene understanding.

Timeline:

1763: Bayes' theorem

1988: Bayesian networks

1994: Uncertainty Sampling

1997: Query by Committee algorithm

2017: Deep Bayesian Active Learning

2019: Bayesian Active Exploration

2020: Active Bayesian Inference for Deep Learning

2020: Bayesian Active Learning for Computer Vision

The synergy of active inference and Bayesian mechanics is expected to play a crucial role in shaping the next generation of AI systems. Some possible future developments in this area include:

- Combining active inference and Bayesian mechanics with other AI techniques, such as reinforcement learning and transfer learning, to create more powerful and flexible AI systems.

- Applying the synergy of active inference and Bayesian mechanics to new areas, such as healthcare, finance, and education, to improve decision-making and outcomes.

- Developing new algorithms and techniques that integrate active inference and Bayesian mechanics, such as Bayesian active learning for deep learning and Bayesian active exploration for robotics.

Dr. Sanjeev Namjosh: The Hidden Math Behind All Living Systems - On Active Inference, the Free Energy Principle, and Bayesian Mechanics (Machine Learning Street Talk, October 2024)

Fitblr or whatever.

This person's purview is marketing. She is doing this research to more effectively market to Gen Z. But I don't give a shit about that. I give a shit about the "Gen Z focus group participants don't want to read to find information" and the alarm bells that rings to me.

In general, reading on paper >>> reading on screens >>>> audio >>>>> video for comprehension and absorption. Why is this?

It doesn't appear to be necessarily inherent to the screen vs print experience (other than some findings about temporal/spatial placement of events in a book, which CAN help with retention). But screen reading on a device connected to the internet, or capable of doing other things, even offline? Distraction machine. You cannot learn anything if you don't focus on it.

Furthermore, books and reading themselves are only the gate to learning (see https://andymatuschak.org/books/ for an excellent overview). To facilitate learning, you must have active involvement with new ideas. That can come from asking questions about what you've read, taking notes, discussing what you've read, connecting it to other ideas, and learning the same thing from several sources.

But those things? Those are LEARNED AND PRACTICED SKILLS. They're not a given from passive consumption of material. (What Matuschak cites as "metacognition.") And you have to CHOOSE to do them. Every time. It's hard. You cannot learn anything if you don't focus on it.

It's not that video is inherently bad for learning. It's a combination of attitudes about video (they must be "entertaining", see the Big Think piece above), distraction/lack of focus, and lack of active engagement.

It's not like these issues are new. People have been refusing to use their brains because it's hard since, well, forever. (Although the tools we have available to completely turn off our brains and let other people think for us are so fucking sophisticated today I don't think we really comprehend it). But things like democracy and pluralism are incredibly fragile, and are dependent upon an educated populace that can think critically. A functioning society cannot continue when its members spend the vast majority of their time disengaged from reality, passively consuming ideas without thinking about them, and addicted to being entertained.

Again, this is not just a generational problem. This is a fundamental problem with humans, who evolved in very different circumstances than the ones we find ourselves in. Our big, complex frontal lobes are late entries. But we greatly enjoy all the things frontal lobes have created (all the luxuries of society we take for granted until a major natural disaster). And to maintain them, or come up with new ones, we HAVE to foster a society that celebrates intellectual work. This is not a value judgment of "kids today don't read, reading is a moral good, get off my lawn" it's "we cannot continue the things we want in civilization if active learning is not cultivated." This is an emergency.

Are you looking to improve your productivity in studies? In this article, we will share 10 study tips that will help you maximize your study sessions and achieve better results.

Are you looking to improve your productivity in studies? Whether you’re a student preparing for exams or someone seeking to enhance your learning skills, implementing effective study techniques can significantly improve your productivity and retention. In this article, we will share 10 study tips that will help you maximize your study sessions and achieve better results. #1 Create a Study…

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