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50 results for “Sunfishstanford”
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Case study for using the Icicle library from Ingonyama to enable acceleration of zero knowledge proof over both GPU and CPU: #ZeroKnowledgeProof
ICICLE Case Study: Accelerating ZK Proofs with Kroma Network https://medium.com/@ingonyama/icicle-case-study-accelerating-zk-proofs-with-kroma-network-eae1fa4c09cc
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Zero knowledge proof (zkp) technologies are quickly maturing, and zkp protocols are driving applications such as blockchain scaling, verifiable AI, and new game mechanics with cryptographic "fog of war".
Here is a blog post that explains a key element of the zkp stack, R1CS.👇
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To improve confidentiality, trust, and scalability via decentralized compute, hardware and software acceleration technologies for zkp (zero knowledge proof) are essential. The initial use cases are in blockchain, and the future use cases include AI and gaming.
https://www.ingonyama.com/blog/ingonyama-seed-funding-announcement
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To improve confidentiality, trust, and scalability via decentralized compute, hardware and software acceleration technologies for zkp (zero knowledge proof) are essential. The initial use cases are in blockchain, and the future use cases include AI and gaming.
https://www.ingonyama.com/blog/ingonyama-seed-funding-announcement
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To improve confidentiality, trust, and scalability via decentralized compute, hardware and software acceleration technologies for zkp (zero knowledge proof) are essential. The initial use cases are in blockchain, and the future use cases include AI and gaming.
https://www.ingonyama.com/blog/ingonyama-seed-funding-announcement
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To improve confidentiality, trust, and scalability via decentralized compute, hardware and software acceleration technologies for zkp (zero knowledge proof) are essential. The initial use cases are in blockchain, and the future use cases include AI and gaming.
https://www.ingonyama.com/blog/ingonyama-seed-funding-announcement
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To improve confidentiality, trust, and scalability via decentralized compute, hardware and software acceleration technologies for zkp (zero knowledge proof) are essential. The initial use cases are in blockchain, and the future use cases include AI and gaming.
https://www.ingonyama.com/blog/ingonyama-seed-funding-announcement
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Particles obeying stochastic process equations that evolve forward and backward in time! See this post:👇
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Here is a concrete visualization/example of a filtration for a stochastic process. Using the spreadsheet "filter" function makes it clear why we call it a filtration, because we are filtering out the outcomes that are no longer possible.
https://docs.google.com/spreadsheets/d/1UwKdcoTnfMDEeWOClWN9zuSwCDKrcmM7pVBlMvx0vgI/edit?usp=sharing
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My distance and number of steps for a walk are approximations of the variation over the interval of my location, AKA total variation.
https://en.wikipedia.org/wiki/Total_variation
They are finite because even though you may think it is so, I am not really doing a random walk (which would have infinite variation and finite quadratic variation). 😎
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Exciting new collaboration that brings together clinical expertise in prostate cancer (second leading cause of cancer death for men) with the latest advances in instruments and AI technologies for atomic resolution of molecular structure. From our portfolio company Peptone based in Switzerland and the UK.
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Exciting new collaboration that brings together clinical expertise in prostate cancer (second leading cause of cancer death for men) with the latest advances in instruments and AI technologies for atomic resolution of molecular structure. From our portfolio company Peptone based in Switzerland and the UK.
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Exciting new collaboration that brings together clinical expertise in prostate cancer (second leading cause of cancer death for men) with the latest advances in instruments and AI technologies for atomic resolution of molecular structure. From our portfolio company Peptone based in Switzerland and the UK.
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Exciting new collaboration that brings together clinical expertise in prostate cancer (second leading cause of cancer death for men) with the latest advances in instruments and AI technologies for atomic resolution of molecular structure. From our portfolio company Peptone based in Switzerland and the UK.
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Exciting new collaboration that brings together clinical expertise in prostate cancer (second leading cause of cancer death for men) with the latest advances in instruments and AI technologies for atomic resolution of molecular structure. From our portfolio company Peptone based in Switzerland and the UK.
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Why is free energy a valuable tool for thermodynamics? And how is it related to simulating molecules for drug discovery? 👇
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In a thermodynamic system, the Reservoir acts like the central bank in an economy. But Instead of regulating money, the Reservoir is regulating energy. It sets the rules of the game, such as what forms of energy are allowed to flow.
This post explains how that works, and how that leads to the concept of "free energy" in a battery that is not tied to the Reservoir and therefore available to be charged/discharged:👇
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Here is a post to help me keep track of different types of transformation of tensors (covariant vs. contravariant vs. invariant). The post begins by seeming to show an object that is all 3 simultaneously (obviously wrong), but it all makes sense by the end. See here:👇
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Here is a post that dives into how the R1CS protocol is used in a zksnark (a zero knowledge proof protocol). I had some fun with math animation using Manim.👇
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From your chemistry or physics classes, you probably learned about free energy. But you may not have double clicked into why the different types of free energy (e.g., Helmholtz vs. Gibbs) are constructed the way they are and the subtleties relating to regulating pressure vs. using pressure to perform useful work.
Here is a deep dive👇
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Batteries are really important as we transition to more sustainable energy. But batteries are not isolated from the environment, as they are at the same temperature as the environment, which means that energy must be free to flow between the battery and the environment. So how could we "store" the energy if energy is free to flow out of the battery? This is where the thermodynamics concept of "free energy" comes in: 👇
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Some problems are so important that we optimize not only the infrastructure, but also the infrastructure of the infrastructure!
Two very different examples:
1. MLIR enables higher quality infrastructure for compilers. Really important because this allows machine learning to run more efficiently.
2. Zero knowledge proof (ZKP) enables more efficient/secure rollup layers inside blockchains. Really important because this enables blockchains to scale.
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It's very interesting how watching a video lecture while on an exercise machine is sort of like "synchronous" learning because you're mostly watching the content in real time, versus "asynchronous" learning when you are mostly paused at various key parts of the video.
It's the difference between breadth-first search (BFS) and depth-first search (DFS), and both are needed for learning deep concepts.
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And it turns out that watching a video lecture while exercising (safely) on a rowing machine or a treadmill is a great way to learn, when combined with focused studying done separately. While you're on a rower, it's harder to keep up with the details of the derivation or the algebra, so you're naturally more focused on the big picture ideas while noting which details need to be filled in later.
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We're very fortunate to live in a time when there are so many freely available learning resources from so many experts willing to donate their time and expertise.
Teaching yourself a complex concept usually requires many re-reads of the text, re-watches of the lecture video, or doing the same but with different books or videos teaching the same topic. The latter is especially helpful due to the benefit of insights from different perspectives.
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Free energy is a universal concept in thermodynamics that governs how all things evolve in the universe. Whether you are developing better batteries, or simulating molecular structures to develop better drugs, you surely are using calculations or algorithm that rely on minimizing some type of free energy (most likely Gibbs). But why is it "free"? See this post: 👇
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Why AI + ZK lets us amplify our communications with the power of generative AI while maintaining trust/privacy/authenticity via the power of zero knowledge proofs. And more efficient ZK computation will be a foundational enabler.
Nicely meta in its use of AI to communicate this!
https://medium.com/@ingonyama/zk-movie-behind-the-scenes-faa5546caca7
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In thermodynamics, we have extensive and intensive state variables. This post explores some of the important scaling requirements when we compute the various thermodynamic partial derivatives.
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When we first started to study the subject and began with the basics, it was very disconcerting to not understand some of the details. But then as we learned the big picture and how the theories are applied, things began to make more sense, so we grew more comfortable.
But the true experts and greats are those who have a complete understanding of almost all of the "knowledge stack", to better enable them to tackle the unknown frontiers.
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I now realize: For us mere mortals, we "understand" a complex/difficult field (pick any area in physics, math, biology, economics, ...) when we begin to master the big picture concepts, which also causes us to conveniently forget the points of confusion we had about the basic, foundational elements when we first learned them. So this makes us more comfortable so that we feel like we "understand."