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| Name | Introduction to Prompt-Tuning Technique: The advent of Foundation Models Age |
| Video Uploader | Video From Danesh Academy |
| Upload Date | This Video Uploaded At 06-07-2024 12:10:18 |
| Video Discription | Let’s review the key aspects and definitions concerning prompting in Natural Language Processing and Computer Vision. Parts: 00:39 Overview 01:17 Deep Learning from Scratch 04:48 Age of Foundation Models 09:13 Fine Tuning Vs Prompting 11:38 Prompts in NLP 13:45 Soft Prompts in NLP 15:41 Soft Prompts in CV 16:06 Prompting Visual Language Models In this video, we explore the core concepts of prompt-tuning, starting with explaining the conventional paradigm in deep learning and inherent problems. We then move into motivations which led to the advent of foundation models. Next, the paradigm shifts from “pertaining then tuning” to “pertaining then prompting” procedures are discussed. Finally, we discuss the evolution of prompt methods from “Prompt engineering” to “prompt tuning”. Join us on this educational adventure as we unravel the science behind Prompt-Tuning technique and its broad applicability across various research projects. [K1r-e4B9dwU] |
| Category | Education |
| Tags | Danesh | Academy | Danesh Academy | PromptTuning | FoundationModels | AI | MachineLearning | DeepLearning | NaturalLanguageProcessing | NLP | GPT4 | BERT | AIResearch | TechTutorial | AIInnovation | FutureOfAI | AITrends | TechEducation | AIModels | TechInnovation | AIExplained | DataScience | AICommunity | TechTalk | AIApplications | AIResearchPapers | AIAlgorithms | TechInsights | AIForGood | AIRevolution | AIInEducation | AIInIndustry | AIUpdates | AIResearchCommunity | AIModelTraining | AIExploration | TechTrends | AIAdvancements | AIModeling | AIInTech | AIInsights |
