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Understanding Generalization and Forgetting in In-Context Continual Learning

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In-context learning (ICL) derives its power from enabling Large Language Models to adapt to new tasks via prompt-based reasoning alone, entirely bypassing the need for parameter updates. Existing theories primarily study ICL in single-task settings, while real-world prompts often contain sequences of heterogeneous tasks, leaving a gap in understanding whether Large Language Models implicitly perform continual learning during inference. To bridge this gap, we propose the first theoretical framework for in-context continual learning, modeling how a pretrained Transformer […]

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Optimal Data Acquisition for Reinforcement Learning: A Large Deviations Perspective

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Data acquisition efficiency is a central challenge in deploying reinforcement learning in business and healthcare operations, where interactions are costly, slow, and often involve humans in the loop. This paper develops a unified large deviations framework for data acquisition in infinite-horizon reinforcement learning. We introduce the exponential decay rate of the policy-selection error probability as a principled efficiency metric and derive a variational characterization of this rate via large deviations theory for Markov chains, yielding a nested optimization […]

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Sending Emails With Python

Sending Emails With Python

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You probably found this tutorial because you want to send emails with Python to automate confirmation messages, password resets, or scheduled notifications. Python’s standard library covers the whole pipeline, from making a server connection to building the message and sending it to one or many recipients. This tutorial walks through every step in working code. By the end of this tutorial, you’ll understand that: A safe testing setup uses a throwaway Gmail account with an app password, a […]

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RoPE Demystified: How Rotary Position Embeddings Actually Work (With GPU optimized PyTorch Code)

RoPE Demystified: How Rotary Position Embeddings Actually Work (With GPU optimized PyTorch Code)

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Introduction Imagine trying to read a book where all the words are written on separate pieces of paper, thrown into a hat, and mixed together. To understand the story, you would have to pull out each word, guess where it belongs, and mentally reconstruct the sentences. This is exactly how a vanilla Transformer model views human language. When the landmark paper “Attention Is All You Need” dropped in 2017, it fundamentally shifted the AI landscape by introducing Self-Attention. […]

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Google folds Display Ads into AI-first Demand Gen platform

Google folds Display Ads into AI-first Demand Gen platform

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Google is folding Display Ads into its AI-powered Demand Gen platform, marking the end of a long-standing digital advertising model. The Google Display Network (GDN) has been a staple of the open internet for almost twenty years. Marketers previously relied on its predictable framework to target placements, bid on audiences, and A/B test static creative across news sites and blogs. That familiar setup is changing and requires marketing teams to move away from manual campaign controls and rely […]

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Exploring the Benefits of AI Bots for Forex Trading in Forex Markets

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The foreign exchange market is really moving away from pure intuition and toward a space shaped by speed, data and precision. By using automated systems in your routine, you can approach volatility with a level of discipline that manual trading often struggles to maintain. Every entry and exit can be based on clear rules, not the emotional swings that frequently influence human decisions. Currency markets really move quickly, often faster than any person can react. With advanced digital […]

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