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Continual Adapter Tuning (CAT): A Parameter-Efficient Machine Learning Framework that Avoids Catastrophic Forgetting and Enables Knowledge Transfer from Learned ASC Tasks to New ASC Tasks

Marktechpost

Continual Learning (CL) poses a significant challenge for ASC models due to Catastrophic Forgetting (CF), wherein learning new tasks leads to a detrimental loss of previously acquired knowledge. These adapters allow BERT to be fine-tuned for specific downstream tasks while retaining most of its pre-trained parameters.

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Introduction to Large Language Models (LLMs): An Overview of BERT, GPT, and Other Popular Models

John Snow Labs

Are you curious about the groundbreaking advancements in Natural Language Processing (NLP)? Prepare to be amazed as we delve into the world of Large Language Models (LLMs) – the driving force behind NLP’s remarkable progress. and GPT-4, marked a significant advancement in the field of large language models.

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2024 Layoffs and LLMs: Pivoting for Success

The MLOps Blog

The rapid advancements of Large Language Models (LLMs) are changing the day-to-day work of ML practitioners and how company leadership thinks about AI. Are LLMs entirely overtaking AI and natural language processing (NLP)? Could this paradigm shift lead to widespread job reductions?

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Beyond ChatGPT; AI Agent: A New World of Workers

Unite.AI

With advancements in deep learning, natural language processing (NLP), and AI, we are in a time period where AI agents could form a significant portion of the global workforce. Deep learning techniques further enhanced this, enabling sophisticated image and speech recognition.

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How AI facilitates more fair and accurate credit scoring

Snorkel AI

Instead of the rule-based decision-making of traditional credit scoring, AI can continually learn and adapt, improving accuracy and efficiency. natural language processing, image classification, question answering). Data teams can fine-tune LLMs like BERT, GPT-3.5

AI 64
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How AI facilitates more fair and accurate credit scoring

Snorkel AI

Instead of the rule-based decision-making of traditional credit scoring, AI can continually learn and adapt, improving accuracy and efficiency. natural language processing, image classification, question answering). Data teams can fine-tune LLMs like BERT, GPT-3.5

AI 59
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Concept Drift vs Data Drift: How AI Can Beat the Change

Viso.ai

Continuous Learning and Adaptive Models: Online learning continuously updates the model as new data becomes available. On the other hand, transfer learning may help by adapting the model trained to do one task to do a related task. Versioning ensures that new updates can be tracked and managed.