Month: August 2025

Asia Morning Briefing: Bitcoin’s ETFs Kill the Transaction Fees, Punishing the Miners More

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Good Morning, Asia. Here’s what’s making news in the markets: Welcome to Asia Morning Briefing, a daily summary of top stories during U.S. hours and an overview of market moves and analysis. For a detailed overview of U.S. markets, see CoinDesk’s Crypto Daybook Americas. Bitcoin’s price is holding near records, but the chain itself is … Read more

The Future of Tractable Deep Generative Models

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Table of Links Abstract and 1. Introduction Preliminaries and Related Work Key Bottlenecks in PC Parallelization Harnessing Block-Based PC Parallelization 4.1. Fully Connected Sum Layers 4.2. Generalizing To Practical Sum Layers 4.3. Efficient Implementations by Compiling PC Layers 4.4. Analysis: IO and Computation Overhead Optimizing Backpropagation with PC Flows Experiments 6.1. Faster Models with PyJuice … Read more

PyJuice Pushes HMMs and Image Models Beyond State-of-the-Art

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Table of Links Abstract and 1. Introduction Preliminaries and Related Work Key Bottlenecks in PC Parallelization Harnessing Block-Based PC Parallelization 4.1. Fully Connected Sum Layers 4.2. Generalizing To Practical Sum Layers 4.3. Efficient Implementations by Compiling PC Layers 4.4. Analysis: IO and Computation Overhead Optimizing Backpropagation with PC Flows Experiments 6.1. Faster Models with PyJuice … Read more

Optimizing Backpropagation with PC Flows

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Table of Links Abstract and 1. Introduction Preliminaries and Related Work Key Bottlenecks in PC Parallelization Harnessing Block-Based PC Parallelization 4.1. Fully Connected Sum Layers 4.2. Generalizing To Practical Sum Layers 4.3. Efficient Implementations by Compiling PC Layers 4.4. Analysis: IO and Computation Overhead Optimizing Backpropagation with PC Flows Experiments 6.1. Faster Models with PyJuice … Read more

How Block-Based Parallelization Cuts IO and Computation Overhead

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Table of Links Abstract and 1. Introduction Preliminaries and Related Work Key Bottlenecks in PC Parallelization Harnessing Block-Based PC Parallelization 4.1. Fully Connected Sum Layers 4.2. Generalizing To Practical Sum Layers 4.3. Efficient Implementations by Compiling PC Layers 4.4. Analysis: IO and Computation Overhead Optimizing Backpropagation with PC Flows Experiments 6.1. Faster Models with PyJuice … Read more

Why Researchers Are Betting on PCs to Power the Next Wave of AI

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Table of Links Abstract and 1. Introduction Preliminaries and Related Work Key Bottlenecks in PC Parallelization Harnessing Block-Based PC Parallelization 4.1. Fully Connected Sum Layers 4.2. Generalizing To Practical Sum Layers 4.3. Efficient Implementations by Compiling PC Layers 4.4. Analysis: IO and Computation Overhead Optimizing Backpropagation with PC Flows Experiments 6.1. Faster Models with PyJuice … Read more

Key Bottlenecks in PC Parallelization

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Table of Links Abstract and 1. Introduction Preliminaries and Related Work Key Bottlenecks in PC Parallelization Harnessing Block-Based PC Parallelization 4.1. Fully Connected Sum Layers 4.2. Generalizing To Practical Sum Layers 4.3. Efficient Implementations by Compiling PC Layers 4.4. Analysis: IO and Computation Overhead Optimizing Backpropagation with PC Flows Experiments 6.1. Faster Models with PyJuice … Read more