Hmm putting aside the specifics of 2030 etc, and just talking about "timeline compression", I think around the time of char-rnn (~2015), if someone said something like this to me, or if I read it anywhere: "It's quite possible that if you make char-rnn bigger and then finetune
MACHINE LEARNING
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Logic-of-Thought: Enhancing LLMs with Logic Programs for Puzzles
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Logic-of-Thought: Empowering Large Language Models with Logic Programs for Solving Puzzles in Natural Language
Paper: https://
arxiv.org/pdf/2505.16114
Code & data: https://
github.com/naiqili/Logic-
of-Thought
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Lost in Latent Space: Finding AI Models
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He got lost in latent space. Let me know if you find him!
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AI Scaling Laws and the Critical Value of Data Discussion
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This is a wonderful thread on AI scaling laws and the value of data
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Top 10 Machine Learning Algorithms for Digital Transformation
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New on the Blog: Top 10 Machine Learning Algorithms Stay ahead in the ever-evolving world of Digital Transformation. This article explores key insights into emerging technologies and their impact on today's business landscape. Discover how to leverage innovation to drive
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CPGD: Stabilizing Rule-Based Reinforcement Learning for Language Models
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CPGD: Toward Stable Rule-based Reinforcement Learning for Language Models CPGD introduces a novel reinforcement learning algorithm designed to stabilize policy updates for language models trained with rule-based rewards, addressing instability and training collapse issues found
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vec2vec: Unsupervised Text Embedding Translation Method
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Harnessing the Universal Geometry of Embeddings This work introduces vec2vec, the first unsupervised method to translate text embeddings between different vector spaces without any paired data, encoders, or predefined matches, by leveraging a universal latent semantic
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MAGI-1: Large-Scale Autoregressive Video Generation Model
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MAGI-1: Autoregressive Generation at Scale MAGI-1 is a large-scale autoregressive video generation model that produces videos by generating fixed-length chunks of consecutive frames with diffusion, enabling efficient, streaming-capable, and temporally consistent video
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Panda: Pretrained Model for Chaotic Dynamics Forecasting
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Panda: A pretrained forecast model for universal representation of chaotic dynamics Panda is a pretrained attention-based model trained solely on synthetic chaotic systems, capable of zero-shot forecasting across diverse, unseen real-world dynamical systems, including PDEs it
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Robin: Multi-Agent AI System Automates Scientific Discovery Loop
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Robin: A multi-agent system for automating scientific discovery Robin is the first multi-agent AI system to automate the entire scientific discovery loop—literature review, hypothesis generation, experiment design, data analysis, and hypothesis refinement—within a single