Reinforcement Learning from Human Feedback (RLHF) is currently the main method for aligning LLMs with human values and preferences. RLHF is also used for further tuning a base LLM to align with values and preferences that are specific to your use case.
@avikumart_
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Aligning Large Language Models with Human Values via RLHF
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Large language models (LLMs) are trained on human-generated text, but additional methods are needed to align an LLM with human values and preferences. To align models with human values and individual RLHF is a highly recommended solution
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Distance-Based Methods: Supervised vs Unsupervised Learning
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Both are based on distance based methods but one is supervised while the other is unsupervised algorithm
Well explained -
India’s Growth Trajectory: A Different Path Forward
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We very well put
And completely agree with china Vs India growth trajectory
India will be totally different in its way forward
It's a long way to go but surely we will get there -
Git and GitHub Essential Skills for Tech Professionals
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Git and GitHub are absolutely necessary to learn for anyone in tech domain
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Essential Learning Resources for Data Science and Machine Learning
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End of this thread! If you are looking to learn more about
Data Science
ML/DL/AI
Analytics
Math & Statistics
Resources
LLMs
MLOps Then, Don't forget to follow me at @avikumart_ for upcoming posts -
Real-time AI Models in Business Decision-Making Processes
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It often involves applying live models within an organization’s decision-making processes-for example, real-time personalization web page, product recommender system, or scoring of marketing leads.
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Model Deployment: From Creation to Practical Implementation
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6. Deployment The creation of the model is generally not the end of the project. Even if the purpose of the model is to analyze the data and increase the understanding of the data, the knowledge or insight gained from the modeling needs to…
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Presenting AI Models to End Users Across Business Levels
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…be presented so that the end users of the model can use it. End users could be operational-level staff, business executives, or customers as well.