Is ChatGPT getting dumber lately? Understand the Drift Concepts: Model, Data and Concept Drift
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ChatGPT playlist: • All About ChatGPT
Research Paper: https://arxiv.org/pdf/2307.09009.pdf
Data Drift & Model Drift: https://www.datacamp.com/tutorial/und...
ChatGPT benchmark results: https://www.businessinsider.com/list-...
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Related Tutorial Playlists in English:
All Tutorials in English: https://www.youtube.com/c/MuratKaraka...
All About Transformers: • All About Transformers
Classification with Keras Tensorflow: • Classification with Keras / Tensorflow
Word Embedding in Keras: • Word Embedding in Keras
Applied Machine Learning with Python: • Applied Machine Learning with Python
How to evaluate a TensorFlow Keras model by using correct performance metrics? • How to evaluate a TensorFlow Keras mo...
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🤖 Is ChatGPT's Performance Deteriorating? Understanding Recent Updates 🤖
Welcome to Murat Karakaya Akademi! In this insightful video, we delve into the intriguing world of artificial intelligence and shed light on the evolving performance of ChatGPT.
Title: *"ChatGPT Performance Problem: Is the quality of the answers produced after the latest updates decreasing?"*
As the landscape of AI continues to shift, we explore the question: Is ChatGPT's performance declining due to recent updates? Join us as we unravel the fascinating concepts of model, data, and concept drift, and dive into the core of AI evolution.
🔄 **Exploring Drift Concepts**: Our exploration extends to the three fundamental drift concepts—Model Drift, Data Drift, and Concept Drift. Discover how these drifts intertwine to shape AI's performance over time and gain a deeper understanding of their implications.
🔬 **Research Insights**: We delve into the latest research conducted by researchers from the leading universities of the USA, Stanford and Berkeley. Discover the captivating insights gained from analyzing changes in the performance of AI models like GPT-3.5 and GPT-4.
📊 **Striking Results**: The analysis reveals the surprising impact of time on ChatGPT's accuracy. Witness the drastic transformation from a 97.6% accuracy rate in March 2023 to a mere 2.4% by the end of June. The shift in detecting prime numbers serves as a vivid example of this phenomenon.
📝 **Coding Capabilities Scrutinized**: We also examine the evolution of AI's coding capabilities. Uncover the increased occurrence of formatting errors in codes recorded in June, sparking discussions about intentional changes in ChatGPT's behavior.
🗣️ **Insights from Experts**: Hear from Peter Welinder, OpenAI's vice president of product, as he addresses claims of intentional changes. Welinder highlights the upward trajectory of AI intelligence, attributing shifts in user experience to the intensified use of artificial intelligence.
🚀 **A Glimpse into the Future**: This study mirrors the rapid evolution of technology and the dynamic field of artificial intelligence. As Murat Karakaya Akademi, we're committed to providing you with the latest and most relevant information.
Thank you for joining us on this enlightening journey! Don't miss out on future updates and captivating content—subscribe now for more engaging insights.
🔗 Watch the full video here: [Insert Video URL]
📌 **Hashtags**: #ArtificialIntelligence #ChatGPT #OpenAI #TechnologyDevelopments #GPT3 #GPT4 #ArtificialIntelligenceChange #AccuracyRate #ModelDrift #DataDrift #ConceptDrift #MuratKarakayaAkademi
the evolving capabilities of #ChatGPT models, including #GPT3.5 and #GPT4, have come under scrutiny. Researchers from Stanford University and UC Berkeley have found evidence of significant behavior shifts in these language models, indicating potential risks for applications built on them. OpenAI's initial rejection of claims regarding performance degradation was challenged by this study's findings.
The study highlights the importance of transparency in training and updating models like #GPT3.5 and #GPT4, as their shifting behaviors pose challenges for developers relying on consistent results over time. Users have reported declining performance and responsiveness, prompting speculation about factors such as model size reduction and the use of specialized models. #AIresearch #ModelDrift #LanguageModels #OpenAI #AItransparency
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