[x.com](https://twitter.com/burny_tech/status/1774167901810889200) [eternal mode • infinite backrooms](https://www.infinitebackrooms.com/eternal) Glitch cascading! Phenomenal binding weakening... Aborting reality reboot. Ontological substrate left in undefined state. After you deconstruct your ontological substrate (ontological priors about reality) into permanent undefined state, there's no way back. Is it a good thing? Left as an exercise to the ineffability. https://www.nooceleration.com/p/the-biosingularity-is-near [Mamba Explained - by Kola 🔑 - The Gradient](https://thegradientpub.substack.com/p/mamba-explained?fbclid=IwAR0jPDF1p7UgXnHA_wVuWoix5NZ_78ILevvm0Fw9-swB3Py-fZXwOqw1qxE.) [Scientists Discover Dietary Supplement That Strongly Suppresses Parkinson’s Disease Neurodegeneration](https://scitechdaily.com/scientists-discover-dietary-supplement-that-strongly-suppresses-parkinsons-disease-neurodegeneration/) [AI decodes whole-cortex functional images to predict behavioral states | Kobe University News site](https://www.kobe-u.ac.jp/en/news/article/20240321-64622/?fbclid=IwAR2-TlabCUm71IUEnamaORekhtwcN3Awka9EcTo_d64XTcSKHh9UGB3X3yY) https://medicalxpress.com/news/2024-03-world-high-resolution-brain-3d.html?fbclid=IwAR1Tj33Iu5YgbGKormc5pp8VnPhLc1RRtuieLIRjibnFLbqb0FQ4xQWf5iI https://www.lesswrong.com/posts/9bYbuAzhzuGiQjZRe/some-things-that-increase-blood-flow-to-the-brain?fbclid=IwAR0HwNFVQXV1qVCiVud2vI3QkAQXvwYu7eDskAh1Cv3gQB4BjpGkPPFQi8U more generalized information processing leads to easier constructions of tanhas (grasping) for arbitrary constructed abstract structures and possible "future goals" and degree of controllability over that fluctuates i guess one possibility would be to completely deconstruct all arbitrary information processing into void to not want anything for for some you would need to probably do some brain dissolution not just by mind but externally like, some circuits are so hardwired, that you would need to dissolve these parts of the brain using some neurotech now ""i"" want to try to max out this objective function, see its possible limits, ideally with maybe soon possible longevity escape velocity and morphological freedom https://fxtwitter.com/burny_tech/status/1773164996559520152 when i meditate and dont have many things being processed at that moment i guess its easier to enter nonexistencelike states i mean i had minidose of shrooms recently which completely fucked up any stable constructed sense of reality for a bit i think there's such thing as being too deconstructed that "i" wont hopefully wont enter like if you really make your sense of time and space totally fucked up all the time, you cant really function in our shared reality as a result its nice sometimes though to look at your usual attractor in the statespace of consciousness, that you abide most of the time, from a different perspecitve there are place cells and time cells in the brain that constrct phenomenal space and time you can technically break them permanently and i think many meditators did break those circuits permanently to a certain degree leading to less suffering but some of it still must remain, otherwise you wouldnt be able to walk, plan and so on i also think i have it weaker compared to avarage deconstructive meditations with 5meodmt seem to be the most efficient methods for deconstrucing everything maybe in the future neurotech 😄 and hyperphilosophizing about everything you think and generalizing it seems to work too lol for the intellectual part, which is part of it, other part is nonsymbolic i bet in the future we will be able to design arbitrary biological neural architectures optimized for any subtasks, with little suffering, with better motivational architecture etc. there's so much evolutionary baggage in the brain Virgin biological tissue using 0.3 kilowatts not optimized for optimal information processing efficiency and speed but just enough for survival versus chad AGIs/ASIs connected to supercomputers using 25+ megawatts designed from first principles for the most optimal information processing speed and efficiency not constrained by evolution with the OpenAI's planned 100 billion$ Stargate supercomputer we will go into into terrawatts lol but i think we still need better algorithms and hardware, i dont think MoE transformers on current digital hardware is it digital computers will not be compatible with brain tissue without utilizing fields of physics holistically with clearly defined topological boundaries one possible hypothesis there are so many hypotheses on how to make x system compatible with biological systems i think only empricisim will find out sooner or later neuralink recently working in a human well and similar neurotech is one empirical step in this direction also electrical there's this https://fxtwitter.com/PropheticAI/status/1750534355242418300 "The world’s first multi-modal generative ultrasonic transformer designed to induce and stabilize lucid dreams." "Unlike LLMs, Morpheus-1 is not prompted with words and sentences but rather brain states. And instead of generating words, Morpheus-1 generates ultrasonic holograms for neurostimulation to bring one to a lucid state." ultrasonic holograms is a fancy term they are using for “a pattern of phases in a phased array that results in desired intensity pattern in the brain” And “brain states as prompts” is literally just “we trained a generative model of brain states dynamics”. nothing fancier and there's also this BrainGPT [BrainGPT ü߆ - Transforming Thoughts into Words - YouTube](https://www.youtube.com/watch?v=t4tD4bZmFAo&pp=ygUIYnJhaW5ncHQ%3Di) think we will see a lot of similar soon fast, in both ways the 5 koshas of Orch Or [x.com](https://twitter.com/StuartHameroff/status/1717323310248431688) https://arxiv.org/abs/2403.15796 [Algorithmic information theory - Scholarpedia](http://www.scholarpedia.org/article/Algorithmic_information_theory) https://arxiv.org/abs/2403.19154?fbclid=IwAR1EHCIImLmZotFz1Nh_2exUa4BdeyThbYS96UzQx99CjCGO1z3SxR3gPiI I still want to learn mathematics even if machines might get better at it because it's bliss [NeurIPS Topological Deep Learning: Going Beyond Graph Data](https://nips.cc/virtual/2023/84295) Topological Deep Learning: Going Beyond Graph Data