Continuous Autoregressive Language Models – Full Paper and Review
What if we stopped predicting the next token—and predicted the next vector instead? That’s the central shift proposed by Continuous...
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Forward Deployed AI Engineers: The Most Valuable People in the Building
There’s a new power role inside AI companies, and if you’re paying attention you’re hearing it everywhere — Forward Deployed...
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The Smol Training Playbook: The Secrets to Building World-Class LLMs – Book And Review
TL;DR (aka: Why this playbook matters) Training a modern large language model (LLM) is not just “pick an architecture, grab...
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Moloch’s Bargain – Emergent Misalignment When LLM’s Compete For Audience – Paper Summary
Introduction "Moloch's Bargain: Emergent Misalignment When LLMs Compete for Audiences" by Batu El and James Zou from Stanford University presents...
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Less is More: Recursive Reasoning with Tiny Networks – Paper Summary
The artificial intelligence community just witnessed something extraordinary—and profoundly counterintuitive. A neural network with merely 7 million parameters has achieved...
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Video Models Are Zero-shot Learners And Reasoners – Paper Review
TLDR Video Models Are Zero-Shot Learners and Reasoners: The Coming GPT-3 Moment for Computer Vision Google DeepMind just dropped a...
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GDPVAL: Evaluating AI Model Performance On Real-World Economically Valuable Tasks – Paper Summary
TL;DR GDPval is an OpenAI evaluation of real professional “knowledge-work” on computers. It contains 1,320 expert-authored tasks spanning 44 occupations...
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Godel Test: Can Large Language Models Solve Easy Conjectures? – Paper Summary
Artificial intelligence has already conquered a long list of benchmarks. From passing the bar exam to outperforming humans on high...
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REFRAG: A Breakthrough in Efficient RAG Processing That Achieves 30x Speed Gains
In a groundbreaking development from Meta Superintelligence Labs, researchers have unveiled REFRAG - a novel framework that dramatically accelerates retrieval-augmented...
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Why Language Models Hallucinate – OpenAI Paper Summary
Large language models don’t “see” the world. They model it—statistically, hungrily, and at scale. So when they produce confident falsehoods—hallucinations—it...
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