Suresh Babu’s Post

Gentle reminder that we are not a finished product, nor we will ever be. We are a momentary baseline of cellular cohesion and synergy vs. environment. And we keep try pushing mathematical models/or language to fit our conceptual-perceptual spaces. Below some reading lately: "Importantly, we are not necessarily subscribing to the claim that consciousness cannot be captured within software at all. Rather, we emphasize that we have to at least entertain the possibility that consciousness is linked to the complex biological organization underlying life and thus computational descriptions that capture the essence of consciousness may be much more complex than our present-day theories suggest. It might be impossible to ‘biopsy’ consciousness and remove it from its organizational dwellings. This idea contradicts many current theories of consciousness, which assume that consciousness can be captured on the abstract level of computation. This assumption, however, might be one that will require updating in light of modern AI systems: perhaps interdependencies and organizational complexity across scales observed in living systems cannot be ignored to fully understand consciousness." https://lnkd.in/dzCZFfnM vs. https://lnkd.in/dx-ZN6e7 "Computational models of cognitive functioning have become a thriving paradigm in Cognitive Science, yet they usually only emphasize problem solving and reasoning, or treat perception and motivation as isolated modules. A very promising approach towards a broader architecture of cognition is the Psi theory of Dietrich Dörner. By dealing with the integration of motivation and emotion with perceptual and reasoning processes and including grounded neuro-symbolic representations, it contributes to an integrated understanding of the mind. "

The brain is a fascinating machine that generates emotions regardless of what is happening in the outside world. Recent research has shown that the brain has an abstract coding of emotions. This means that even though we may think our emotions depend on what is happening around us, it is our brain that is wired to generate emotional meaning. Check out this interesting article to learn more about the abstract coding of emotions in the brain. Link: https://lnkd.in/dj6iwVY6

Absolutely, the way our #brains process sentences and information hinges on the complex functionality of working memory, where data is not only stored but also interconnected with our upcoming intentions. Recent research has uncovered a fascinating aspect of how our minds work: visual memories exhibit adaptability based on how we intend to use that information in the future. These insights challenge established theories that propose working memory's neural patterns remain static over time. Instead, this study highlights a dynamic aspect of our #cognitiveprocesses. It demonstrates that our brains don't merely preserve memories unchanged; rather, they reshape these memories to better suit potential future actions rooted in these recollections. This suggests that our minds are constantly reorganizing stored information to optimize its usability and relevance to upcoming tasks. This revelation is significant as it provides new insights into the intricate workings of memory and cognition. This adaptive process could play a crucial role in how we efficiently navigate the world around us, making sense of past experiences to better guide our actions and decisions in the future. #cognitivescience #sciencecommunication #scienceandtechnology #innovationinhealthcare #innovationindrugdiscovery #technologyleadership https://lnkd.in/gDzyutU8

🧠 Data: Illuminating the Mysteries of the Mind in Neuroscience 📊🌌 The human brain, an enigma waiting to be unraveled, finds its ally in data—a tool that's shedding light on its complexities and unlocking the secrets of cognition. 🚀 Let's delve into the captivating relationship between data and neuroscience, a realm where digits unveil the workings of the human mind. Imagine data as a telescope into the cosmos of neural connections. From brain imaging to electrophysiology, data is the lens that lets us peer into the intricate dance of synapses, the circuits of thought, and the awe-inspiring symphony of consciousness. Consider this: brain scans capture every flicker of neural activity, mapping emotions, decoding memories, and unveiling the neural signatures of various mental states. It's not just about observing the brain—it's about interpreting the neural symphony. Just as an explorer charts a new territory, neuroscientists analyze vast datasets, deciphering patterns that provide insights into mental disorders, cognitive enhancement, and the mechanisms underlying human behavior. As we navigate this realm, discussions about brain-computer interfaces, AI-assisted diagnoses, and ethical implications of neurodata collection come to the forefront. It's a journey that unites science, ethics, and the pursuit of understanding what makes us who we are. Whether you're a neuroscientist, a curious mind, or someone fascinated by the intricacies of the brain, let's embark on this journey. Let's marvel at how data is unraveling the neural symphony, rewriting our understanding of the mind and redefining the frontiers of neuroscience. Are you ready to explore the incredible link between data and the mysteries of the human brain? 🧠🌌 Join me on this exploration as we decode the neural code that shapes our thoughts and emotions! 📚🔍 #DataInNeuroscience #MindUnveiled

Scientists estimate the human mind absorbs 74GB of data every day. 74GB is around 17,778 12 MP JPEG photos (a standard GoPro Image resolution). (17,778 x 365 x 39)= [(Total Number of images)/(Total Number of Estimated Influences)]= 6 dominant personality influences 9 siblings 9 first cousins 19 schools grade 1st - 12th (avg. population is 769) 16 full-time employment roles (avg. workforce of 1,740) 3 Family members (Wife and 2 kids since 2020) 38 businesses automated since 2018 (avg employee count 17) (17,778 x 365 x 39)= 253,069,830/[(6+9+9)+(19x769)+(16x1,740)+3+(38x17)= (17,778 x 365 x 39)= 253,069,830/[(24)+(14,611)+(27,840)+3+(646)] 253,069,830/[(24)+(14,611)+(27,840)+3+(646)] 5,869 is the average number of images the "major influences" contributed to my life per day. Meaning of the 17,778 images my brain stores a day, my conscious mind can only account for 5,869 of them or 33% of the total images. At 4 years old I declared I wanted to become a "theoretical theorist" after reading the A volume of the Encyclopedia Britannica and falling in love with the intelligence of Albert Einstein. Even at 4 years old, I desired to invent a new field of science Which I have now discovered was my misarticulation of an existing Branch of science I had not learned about yet Neurophysics is the combination of physics and neuroscience using complex mathematical formulas to understand how the brain works. I have been playing with versions of This mathematical formula in my head Since it exploded into my vision at age 4 as a layer Of flashing specs of light dancing in synchronicity Changing flow and formation based on environmental stimuli I have only known the limitations others want to place on me out of their discomfort with trying to use surface-level characteristics like the length of my hair or my skin color to view themselves in a superior intellectual position to me. This only happens in business discussions Where people use titles and societal constructs like Prejudice, racism, bias, and discrimination of African Americans like myself To deny economic opportunities over generations And claims like Elon Musk and Bill Ackman That I am less intelligent than they are because I am black Challenge accepted #socialsaturday

I have received multiple requests on best resources for understanding the Free Energy Principle (FEP) and the required mathematical skills. I will try and introduce some here. I would quite honestly begin by reading the Active inference book (https://lnkd.in/ePhRVNtb). There is another Step-by-Step tutorial on Active Inference that is amazing (https://lnkd.in/etRcnqmM). In so far as the required mathematical foundation, I would recommend you start learning about Dynamical Systems and brush up on systems of differential equations (Steve Brunton has a great playlist on it https://lnkd.in/e6y4tPkm). Then I would begin by learning about stochastic differential equations, which is absolutely critical in FEP. Last but not least, you will require a good bit of Bayesian Inference skills, in particular, variational Calculus methods such as Variational Inference (this is used to simulate an agent inferring what is going on in the world based on its sensations as well as infer the best course of action/policy into the future). This might seem intimidating but it is the most amazing journey and it could take time depending on your current level so patience is strongly advised! Some keywords to research: Active Inference, Predictive Coding, Free Energy Principle, etc. In particular, you will find that Predictive Coding is a neuro-mimetic alternative to traditional deep learning, which mimicks the neuronal message passing in the brain through top-down predictions and bottom-up prediction error transmission. For more advanced learners, once you become fluent in variational inference, particularly, Hierarchical Variational Inference under the Predictive Coding scheme, you need to start learning about the Generalized Coordinates of motion (this is introduced in the Active Inference book already). This is ABSOLUTELY critical, if you want to TRULY design an #AI system that mimics the brain, as it allows the agent to constantly track its own environment and react accordingly in the perception-action loop. I hope this was useful :-) #machinelearning #neuroscience #deeplearning #statistics #bayesian #philosophy

While thinking about the relationship between mathematics and the mind for the AI landscape, I decided to take a reverse route, understanding the possibilities for quantifying synapses between neurons in the nervous system. I came across a few concepts: #Neuromathematics is an interdisciplinary field that explores the connections between mathematics and the structure, function, and dynamics of the brain. #Mathematicalpsychology is a branch of psychology that utilizes mathematical models and techniques to understand and explain cognitive and behavioral processes. #Psychologicalmathematics is the study of how psychological factors influence mathematical thinking, learning, and problem-solving processes. *** Hoping to find new insights in these fields to learn how to better shape #artificialneuralnetworks

Imagination, delusion or simple interpretations – How does the brain make the difference? The general public’s impressions of  how  scientists work echo of fiscal analogies - scientists should be as methodical and as tedious as accountants.  In their work, there is no room for imagination to infiltrate science and such an intrusion is akin  to tampering  with the accounts, betraying a public trust. However, Gerald Holton, in his essay in Einstein, History, and Other Passions: The Rebellion against Science at the End of the Twentieth Century (Reading, Mass.: Addison-Wesley, 1996), 78–102.) had with great vigour and eloquence argued that first rate science requires imagination. 17th century writer and philosopher M. de Voltaire distinguished between the “active imagination,” which inspired the interesting works of mechanics, mathematics, poetry, and the fine arts, and the “passive imagination,” which caused violent passions, fanaticism, delusions, and monsters both metaphorical and literal. While some theories talk of science being objective with no room for imagery, others mention a certain degree of imagination as a prerequisite for understanding and building models for real world problems! A recent study by Nadine Dijkstra & Stephen M. Fleming (Subjective signal strength distinguishes reality from imagination, Nature Communications volume 14, Article number: 1627 (2023) tries to understand how reality and imagination are kept apart by human brain.Using a combination of computational modelling, neuroimaging and psychophysics  the authors show that imagined and perceived signals are intermixed, and a reality threshold is required for distinguishing between imagination and perception.   https://lnkd.in/gqrMZh8M

https://lnkd.in/eEM62JZt  From sentinel to self-awareness, the awakening of machine learning... "Consciousness has long been a marginalized topic in neuroscience, seen as at best unserious and at worst intractable. “A fascinating but elusive phenomenon,” reads the “Consciousness” entry in the 1996 edition of the International Dictionary of Psychology. “Nothing worth reading has been written on it.”  #abetterworldatwork #criticalthinking #intelligence  📢💡