Alex K. Chen
84 followers · 10 following · 4619 views
on the atlas — 90
- Thousand-dimensional structure — Resolution3 savers
- We can create the future of science right now1 savers
- Prioritizing Fundamental Capabilities for the Intelligence Age1 savers
- Information to Atoms - Substrate1 savers
- All pages - CCRMA Wiki1 savers
- Dr. Wei Min Lab | Columbia University1 savers
- Workshop26 - CompuCell3D1 savers
- Whole World Holonomy | Galileo Unbound1 savers
- Shtetl-Optimized » Blog Archive » The First Law of Complexodynamics15 savers
- Accounts on various services1 savers
- Christina Lee | Co-design AI1 savers
- Gabriele Sarti on X: "Today in neuro: RoPE for brains? [R]otating waves, which propagate along a circular trajectory, were a prominent and frequently occurring feature [...] [T]hey may serve as a mechanism for coordinating information flow across sensory and motor systems. https://t.co/Ol8kNPDvib" / X1 savers
- Curius / Bookmarks for the extremely curious182 savers
- humans&1 savers
- God in the Knowledge Machine - by Sean Manion1 savers
- List of Biotechnology Companies to Watch – AI Expanded Version1 savers
- Ludovico Comito1 savers
- RL-Enhanced 6DOF Rocket Landing - Jaival Patel1 savers
- EveryInc/compound-engineering-plugin: Official Claude Code compound engineering plugin2 savers
- 50 years of MRI3 savers
- Crystals in NNs: Technical Companion Piece — LessWrong1 savers
- Have You Tried Thinking About It As Crystals? — LessWrong1 savers
- 2025 letter | Dan Wang62 savers
- A Guide to Claude Code 2.0 and getting better at using coding agents | sankalp's blog12 savers
- Reflections on 2025 - Samuel Albanie7 savers
- 2025 letter | Zhengdong33 savers
- Juergen Schmidhuber's home page - Universal Artificial Intelligence - New AI - Deep Learning - Recurrent Neural Networks - Computer Vision - Object Detection - Image segmentation - Goedel Machine - Theory of everything - Algorithmic theory of everything - Computable universe - Zuse's thesis - Universal learning algorithms - Universal search - Kolmogorov Complexity - Algorithmic information - Super Omega - Speed Prior - Independent component analysis - ICA - Financial forecasting - Evolution - Reinforcement learning - POMDPs - Reinforcement learning economy - Hierarchical learning - Metalearning - Learning to learn - Self-Improvement - Genetic programming - Attentive vision - Active exploration - Theory of beauty - Theory of creativity - Theory of Humor - Facial Attractiveness - Low-complexity Art - Lego Art4 savers
- Ergodicity economics – Formal economics without parallel universes3 savers
- What 2026 looks like - LessWrong8 savers
- The trouble in comparing different approaches to science funding3 savers
- Amazon.com. Spend less. Smile more.1 savers
- Highly optimized optimizers - by Ben Recht - arg min1 savers
- Reshelving generalization - by Ben Recht - arg min1 savers
- Fractastical - Joel Dietz | Computational Creativity & Digital Art1 savers
- Hamidreza Ramezanpour – visual attention, social interactions, autism spectrum disorders, gaze following, eye movements, social cognition, face processing1 savers
- InterPLM1 savers
- Commentary On The Turing Apocrypha2 savers
- PRISM: Capturing the Invisible Art of Scientific Practice1 savers
- diffuse.one2 savers
- joelsimon.net/about1 savers
- Cyborsophy2 savers
- /r/neoliberal elects the American Presidents - Part 57, Trump v Biden in 2020 : r/neoliberal1 savers
- The ultimate practical guide to Deep Research1 savers
- Democratizing Computer-Assisted Drug Design: How Are We Doing?1 savers
- Resipher Dynamic Oxygen Consumption Reader1 savers
- Contrite Strategies and the Need for Standards | Sarah Constantin2 savers
- geometricdeeplearning.com/book/graphs.html1 savers
- Extensions in Arc: How to Import, Add, & Open – Arc Help Center3 savers
- Simulators - LessWrong16 savers
- Notifications / Twitter3 savers
- We May be Surprised Again: Why I take LLMs seriously.2 savers
- New Report on How Much Computational Power It Takes to Match the Human Brain - Open Philanthropy2 savers
- 1.1 - Fermi estimate of future training runs3 savers
- Unlock new parts of the proteome with PROTAC, a promising emerging technology2 savers
- Is Science Stagnant? - The Atlantic7 savers
- The Business of Extracting Knowledge from Academic Publications5 savers
- The Truth of Fact, the Truth of Feeling by Ted Chiang — Subterranean Press | devonzuegel.com2 savers
- 6. System resilience — Computational aging book2 savers
- A Declaration of the Interdependence of Cyberspace4 savers
- Why we stopped making Einsteins - by Erik Hoel29 savers
- Antimortality4 savers
- MegaMap: Giving scientists superpowers in the battle against aging | Spring Discovery6 savers
- Future ML Systems Will Be Qualitatively Different10 savers
- A Mathematical Framework for Transformer Circuits39 savers
- A Brief History & Ethos of the Digital Garden31 savers
- Toy Models of Superposition30 savers
- Making Deep Learning Go Faster29 savers
- Dynamicland27 savers
- Marley Xiong24 savers
- Notes on Effective Altruism22 savers
- who do you admire? - by Nix 🕊 - starting from nix16 savers
- Scraping training data for your mind - by Henrik Karlsson15 savers
- Moth Minds: Fund individuals doing work you believe in14 savers
- A Vision of Metascience13 savers
- How Life Sciences Actually Work: Findings of a Year-Long Investigation - Alexey Guzey12 savers
- The hot mess theory of AI misalignment: More intelligent agents behave less coherently | Jascha’s blog8 savers
- Project Ideas – Future Fund7 savers
- Without specific countermeasures, the easiest path to transformative AI likely leads to AI takeover - LessWrong7 savers
- The Overedge Catalog: The Future of Research Organizations7 savers
- The Illustrated Stable Diffusion – Jay Alammar – Visualizing machine learning one concept at a time.6 savers
- We have AE at home6 savers
- Cyborgism Wiki5 savers
- Beyond Message Passing: a Physics-Inspired Paradigm for Graph Neural Networks4 savers
- Fernando Borretti4 savers
- Milan Cvitkovic4 savers
- Zvi’s Thoughts on the Survival and Flourishing Fund (SFF) - LessWrong4 savers
- How Much Computational Power Does It Take to Match the Human Brain? - Open Philanthropy4 savers
- Hack Club Workshops – Hack Club3 savers
- Milestones Archive - The History of the Web3 savers
- There’s no such thing as a tree (phylogenetically) | Eukaryote Writes Blog2 savers
highlights — 33
Current advanced semiconductor process nodes require multi-patterning4, a process where a single layer is exposed or processed multiple times to achieve finer feature pitches beyond the resolution of a lithography system. Template-based approaches work by defining an initial pattern and then using deposition and etching to multiply the number of lines, but because this process produces only parallel lines, it often restricts signal routing to a single direction (1D) per metal layer. This drives the need for more metal layers and connections (vias) between them, introducing higher resistive-cap…
Information to Atoms - SubstrateToday in neuro: RoPE for brains? [R]otating waves, which propagate along a circular trajectory, were a prominent and frequently occurring feature [...] [T]hey may serve as a mechanism for coordinating information flow across sensory and motor systems.
Gabriele Sarti on X: "Today in neuro: RoPE for brains? [R]otating waves, which propagate along a circular trajectory, were a prominent and frequently occurring feature [...] [T]hey may serve as a mechanism for coordinating information flow across sensory and motor systems. https://t.co/Ol8kNPDvib" / XThe Dirichlet energy: E D ( f ) = f T L f = ∑ ( i , j ) ∈ E w i j ( f i − f j ) 2 measures the "roughness" of a signal f on the graph—how much it varies across edges. Minimizing Dirichlet energy produces smooth functions that respect graph structure. This is precisely the discrete analog of Landau's gradient term
Crystals in NNs: Technical Companion Piece — LessWrongWill the US solve manufacturing with AI? Well, maybe, because superintelligence is supposed to solve everything. But there’s a risk that AI will destabilize society before it fixes the industrial base. When I walk around the library at Stanford, I see students plugging everything into AI tools; when they need a break, they’re watching short-form videos on their phones. These videos have been marvelously transformed by AI tools. Shortly after OpenAI released Sora 2, I had brunch with a friend who told me that he created an AI video of himself expertly breakdancing that fooled his five-year-old;…
2025 letter | Dan WangThe neural structures that shape electrical activity in the brain take a bit longer to degrade, on a time scale of minutes to hours, but they too begin to degrade quickly. One study found that structural changes to dendrites, which are membrane extensions of neurons, can begin to occur within three minutes of lack of blood flow (Murphy et al., 2008). However, as we will discuss later, some neural structures can take hours or even days to degrade.
Towards a more accurate definition of death2. Lipid composition could affect the capacitance properties of the membranes, which are based on membrane thickness and the dielectric constant (Niebur, 2008). For example, higher levels of cell membrane cholesterol are associated with thicker cell membranes (Postila et al., 2020). In addition to ion concentration gradients, the electrical gradient across the membrane affects how ions will flow into and out of the cell. However, evidence has suggested that capacitance varies only slightly across cell types and very little with different densities of proteins embedded in the membrane (Gentet e…
Biomolecules: the building blocks of engramsDuring the curing process, the glass transition temperature rises as the embedding agent polymerizes. Vitrification occurs when the glass transition temperature is equal to or greater than the temperature of the sample that is being cured. At this point, there is generally a dramatic slowing of the cure rate, as the viscosity of the material is so high that the polymerization reactions are very slow. This, in turn, slows the increase of the glass transition temperature. As a result, the glass transition temperature of the resulting polymerized resin is limited by the curing temperature.
Notes on embedding for brain preservationA major trade-off is that a higher crosslink density and glass transition temperature will tend to the material more brittle and fractures more likely at a given storage temperature (Utaloff et al., 2019). This is the same phenomenon as is seen in vitrification by cold temperatures, where storage further below the glass transition temperature tends to make fractures more common.
Notes on embedding for brain preservationDue to the stringent photon-count requirements of voltage imaging and the modest voltage sensitivity of existing reporters, 2P voltage imaging in vivo faces a stringent tradeoff between shot noise and tissue photodamage. 2P imaging of hundreds of neurons with high SNR at a depth of > 300 μ m > 300 𝜇 m will require either major improvements in 2P GEVIs or qualitatively new approaches to imaging.
Optical constraints on two-photon voltage imagingFoundation models have been proposed for data formats which have resisted conventional large-scale machine learning, e.g. graph data, spikes, transcriptomics, etc.
Foundation models for neuroscience - by Patrick MineaultFoundation models have been proposed for data formats which have resisted conventional large-scale machine learning, e.g. graph data, spikes, transcriptomics, etc.
Foundation models for neuroscience - by Patrick MineaultWhat we want is a flourishing ecosystem of people with wildly imaginative and insightful ideas for new social processes; and for those ideas to be tested and the best ideas scaled out
A Vision of Metascienceprobability of loss of function intolerance (pLI
Tissue-specific impacts of aging and genetics on gene expression patterns in humans | Nature CommunicationsEven a super powerful recursive self-optimizing machine initially starts with some seed utility/objective function at the very core. Unfortunately it increasingly looks like efficiency strongly demands some form of inherently unsafe self-motivation utility function, such as empowerment or creativity, and self-motivated agentic utility functions are the natural strong attractor[8].
DL towards the unaligned Recursive Self-Optimization attractor - LessWrongScience isn't laying pipe, either. And there's something surreal about the idea of doing RCTs (or RCT-likes) to compare quantitative valuations of different funding schemes. Can you imagine someone doing RCTs on poetry? On art schools? Shakespeare didn't learn to write using RCTs; nor did Picasso learn to paint that way. And Bauhaus wasn't the result of a series of carefully controlled methodological studies. Scientific institution building is, similarly, an act of imaginative creation. And given that, you might reasonably throw your hands up in the air and declare: "It's ridiculous to be comp…
The trouble in comparing different approaches to science fundingIt's tempting to just nod along at all this. But it violates much of our intuition from everyday life, and from much conventional training. If you're a careful, analytically trained thinker, it's tempting to think that you should analyze venture capital by building a large body of evidence, perhaps by sampling a large number of companies. But if you believe Thiel, then the things you learn may, if you're not careful, actually be to your disadvantage. Why? Because by definition you'll be learning about merely good or great companies. That's the part of the curve you're trying to get away from: …
The trouble in comparing different approaches to science fundingIt's tempting to just nod along at all this. But it violates much of our intuition from everyday life, and from much conventional training. If you're a careful, analytically trained thinker, it's tempting to think that you should analyze venture capital by building a large body of evidence, perhaps by sampling a large number of companies. But if you believe Thiel, then the things you learn may, if you're not careful, actually be to your disadvantage. Why? Because by definition you'll be learning about merely good or great companies. That's the part of the curve you're trying to get away from: …
The trouble in comparing different approaches to science fundingAlong with learning and growing, I think I was also optimizing for recognition and validation. I said things I didn’t 100% understand (ex. impact billions) just to sound smart, posted resources in slack with a question that I didn’t really care about what the answer was, to give off a facade that I was thoughtful. Whenever I talked about the projects I worked on, I always felt a mild pang of uneasiness because none of them really amounted to anything, they were like trial runs of a game where I played it for a bit but it never really got anywhere, nothing real, nothing I truly believed in. It …
Reflections on 2021 - by Amy Li - Amy's Monthly Updatese together and form inappropriate chemical bonds in a process called cross-linking. This makes the skin stiffen and lose elasticity, and we get wrinkles.
Six ways metabolic health affects longevity - Levelsthe L1 cache 100 times in a row. The L1 cache has a 1ns access latency and a 100 percent hit rate. It, therefore, takes our CPU 100 nanoseconds to perform this operation.
How L1 and L2 CPU Caches Work, and Why They're an Essential Part of Modern Chips - ExtremeTechich high resolution structural information was not available. We classified these models into groups based on their biological functions, and provide examples of complexes in each functional class in Figs. 2-4. A first set of complexes are involved in maintenance and processing of genetic information: DNA repair, mitosis and meiosis checkpoints, transcription, and translation (Fig. 2). A second set of complexes play roles in protein translocation, transport through the secretory pathway, the cytoskeleton and cell organelles (Fig. 3). A third set of complexes are involved in metabolism (Fig. 4)…
Computed structures of core eukaryotic protein complexesensated for the disruption. While voting records are protected with zero-knowledge proofs, decision outcomes and consensus statements are transparently recorded, so if you find a new construction site across the street, you know exactly
Turing-Complete Governance — MirrorDendrimers can be prepared with a level of control not attainable with most linear polymers, leading to nearly monodisperse, globular macromolecules with a large number of peripheral groups as seen in Figure 2
Dendrimers: synthesis, applications, and propertiesthe detection of localized mRNAs in dendrites, spines, axons, and growth cones of cultured neurons; or digoxigenin
Neuronal lineage marker[-]PhoenixFriend4d 89 I'm a present or past CFAR employee commenting anonymously to avoid retribution. I believe that the dynamics of the organization grew to be significantly more cult-like than the OP and readers realize. I say all this with the hope that future-CFAR will emerge like a phoenix, leaving these issues in the ashes. At least four people who did not listen to Michael's pitch about societal corruption and worked in some capacity with the CFAR/MIRI team had psychotic episodes. Psychedelic use was common among the leadership of CFAR and spread through imitation, if not actual instit…
My experience at and around MIRI and CFAR (inspired by Zoe Curzi's writeup of experiences at Leverage) - LessWrongFetal alcohol syndrome (FAS) may be due to persistent ethanol consumption by mother during pregnancy. Newborn with FAS have defective intelligence, motor function and hyperactivity. The mechanism of this brain damage remains elusive. Nonetheless, ethanol consumption is hypothesized to affect the accumulation of DHA in brain development in which this fatty acid is required for the synthesis of plasmalogens in peroxisomes. Another finding also revealed that developing and adult brains have lower DHA and plasmalogen levels in neural membranes with ethanol exposure (Wing D R et al., 1982; Hofteig …
About Plasmalogens - Scallop-derived PLASMALOGENguards against depletion and overproduction of HSCs. Disruption of these regulatory mechanisms can result in blood disease, such as BM failure or leukemia. Transforming growth factor-β (TGF-β) is the founding member of a large family of secreted polypeptide growth factors, consisting of over 30 members in humans, including activins, bone morphogenetic proteins (BMPs), and others.5 The TGF-β family constitutes a multifunctional set of cytokines that regulate a bewildering array of
TGF-β signaling in the control of hematopoietic stem cells | Blood | American Society of Hematologythe real argument for decentralization is not that centralized systems are broken. It’s that they are so functional that only a radical redistribution of control and ownership could wedge new opportunities to create more equity.
Tweets liked by Alex K. Chen (Longevity+Accelerando protagonist) (@InquilineKea) / TwitterAlastair @_AlastairX_ · Sep 26 - Charisma is easy to see - Humor in leaders is underrated - "an abundance of reputational short-sellers" - Sales output is very correlated with input, software output less so - Past a threshold of intelligence, energy becomes a better predictor of success
Tweets liked by Alex K. Chen (Longevity+Accelerando protagonist) (@InquilineKea) / TwitterAlastair @_AlastairX_ · Sep 26 - Charisma is easy to see - Humor in leaders is underrated - "an abundance of reputational short-sellers" - Sales output is very correlated with input, software output less so - Past a threshold of intelligence, energy becomes a better predictor of success
Tweets liked by Alex K. Chen (Longevity+Accelerando protagonist) (@InquilineKea) / TwitterI have this "feeling" that doing deep learning with classical/quantum chemical simulation is easier than experimental data since sim inputs are so sparse (coordinates/sim parameters). I just learned there is a way to quantify this: Kolmogorov complexity.
Tweets liked by Alex K. Chen (Longevity+Accelerando protagonist) (@InquilineKea) / Twitteryour page. Capture what you learn while you
Curius / Bookmarks for the extremely curiousNon-linear interactions means that results are often context-specific. A protein will kill one cell type and protect another. Nothing is "better" or "worse", but shift a system in a way that may be desired.
Marley's Bookshelf / Curius