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Showing posts with the label AI

Claude 2: A New Member of the Growing Family of Large Language Models

AI has advanced rapidly in recent years, with large language models (LLMs) like ChatGPT creating enormous excitement. These models can generate remarkably human-like text albeit  with certain limitations. In this post, we'll look at a new member of the family of large language models, Anthropic's Claude 2 , and highlight some of its features. Claude 2 Overview Claude2 was released in February 2023.  Claude 2 utilizes a context window of approximately 4,000 tokens during conversations. This allows it to actively reference the last 1,000-2,000 words spoken in order to strengthen contextual awareness and continuity. The context window is dynamically managed, expanding or contracting slightly based on factors like conversation complexity. This context capacity exceeds ChatGPT's approximately 1,000 token window, enabling Claude 2 to sustain longer, more intricate dialogues while retaining appropriate context.  In addition to conversational context, Claude 2 can take in multiple

Reinforcement Learning with Human Feedback: A Powerful Approach to AI Training

The unprecedented capabilities exhibited by the large language models (LLMs) such as ChatGPT and GPT-4 have created enormous excitement as well as concerns about the impact of AI on the society in near and far future. Behind the success of LLMs and AI in general lies among other techniques a learning approach called Reinforcement Learning with Human Feedback (RLHF). In this blog post, we will try to understand what RLHF is and why it offers a powerful approach to training AI models. However, before we do that, let's try to understand the concept of reinforcement learning (RL). What is Reinforcement Learning (RL)? RL, inspired by the principles of behavioral psychology, is a machine learning technique wherein the learner, called an agent , learns decision making by exploring an environment through a trial-and-error process to achieve its goal. Each action by the agent results in feedback in the form of a reward or punishment . While performing actions and receiving feedback, the a