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Researchers at DeepSeek AI have suggested implementing Expert-Specialized Fine-Tuning (ESFT) as a way to cut down memory usage by as much as 90% and reduce processing time by up to 30%.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Machine learning, Staff, Tech News, Technology, UncategorizedJuly 7, 202476Views0Likes0Comments
Natural language processing has been making significant headway recently, with a special focus on fine-tuning large language models (LLMs) for specified tasks. These models typically comprise billions of parameters, hence customization can be a challenge. The goal is to devise more efficient methods that customize these models to particular downstream tasks without overwhelming computational costs.…

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Researchers from DeepSeek AI have introduced ESFT, also known as Expert-Specialized Fine-Tuning, which is projected to decrease memory usage by up to 90% and save time by up to 30%.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Machine learning, Staff, Tech News, Technology, UncategorizedJuly 7, 202460Views0Likes0Comments
The rapid evolution of natural language processing (NLP) is currently focused on refining large language models (LLMs) for specific tasks, which often contain billions of parameters posing a significant challenge for customization. The primary goal is to devise better methods to fine-tune these models to particular downstream tasks with minimal computational costs, posing a need…

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Protecting HealthCare AI: Uncovering and Handling the Risks of LLM Manipulation

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Staff, Tech News, Technology, UncategorizedJuly 7, 202475Views0Likes0Comments
AI models like ChatGPT and GPT-4 have made significant strides in different sectors, including healthcare. Despite their success, these Large Language Models (LLMs) are vulnerable to malicious manipulation, leading to harmful outcomes, especially in contexts with high stakes like healthcare. Past research has evaluated the susceptibility of LLMs in general sectors; however, manipulation on such models…

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Examining and Improving Model Efficiency for Tabular Data with XGBoost and Ensembles: A Step Further than Deep Learning

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Deep Learning, Editors Pick, Machine learning, Staff, Tech News, Technology, UncategorizedJuly 6, 202472Views0Likes0Comments
Model selection is a critical part of addressing real-world data science problems. Traditionally, tree ensemble models such as XGBoost have been favored for tabular data analysis. However, deep learning models have been gaining traction, purporting to offer superior performance on certain tabular datasets. Recognising the potential inconsistency in benchmarking and evaluation methods, a team of…

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Princeton University scientists uncover concealed expenses linked with advanced AI Agents.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Machine learning, Staff, Tech News, Technology, UncategorizedJuly 6, 202478Views0Likes0Comments
Research out of Princeton University makes a critical commentary on the current practice of evaluating artificial intelligence (AI) agents predominantly based on accuracy. The researchers argue that this unidimensional evaluation method leads to unnecessarily complex and costly AI agent architectures, which can hinder practical implementations. The evaluation paradigms for AI agents have traditionally focused on…

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Salesforce AI Research introduces APIGen: An automatic framework for producing validated and varied function-calling data sets.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Staff, Tech News, Technology, UncategorizedJuly 6, 202482Views0Likes0Comments
Function-calling agent models are a critical advancement in large language models (LLMs). They interpret natural language instructions to execute API calls, facilitating real-time interactions with digital services, like retrieving market data or managing social media interactions. However, these models often face challenges as they require high-quality, diverse and verifiable datasets. Unfortunately, many existing datasets lack…

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Memory3: An Innovative Structure for LLMs Incorporating a Clear Memory Process for Enhanced Efficiency and Operation.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Staff, Tech News, Technology, UncategorizedJuly 6, 202479Views0Likes0Comments
Language modeling in the area of artificial intelligence is geared towards creating systems capable of understanding, interpreting, and generating human language. With its myriad applications, including machine translation, text summarization, and creation of conversational agents, the goal is to develop models that mimic human language abilities, thereby fostering seamless interaction between humans and machines. This…

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A Simultaneous Coding Structure for Assessing Efficiency Challenges in Handling Several Extended-Context Requests under Restricted GPU High-Speed Memory (HBM) Conditions

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Machine learning, Staff, Tech News, Technology, UncategorizedJuly 6, 202478Views0Likes0Comments
Large language models (LLMs) are becoming progressively more powerful, with recent models exhibiting GPT-4 level performance. Nevertheless, using these models for applications requiring extensive context, such as understanding long-duration videos or coding at repository-scale, presents significant hurdles. Typically, these tasks require input contexts ranging from 100K to 10M tokens — a great leap from the…

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This Stanford-authored paper discusses the introduction of a novel set of data scaling laws related to artificial intelligence and how AI capabilities increase with data size in the field of machine learning.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Machine learning, Staff, Tech News, Technology, UncategorizedJuly 6, 202470Views0Likes0Comments
Researchers from Stanford University have developed a new model to investigate the contributions of individual data points to machine learning processes. This allows an understanding of how the value of each data point changes as the scale of the dataset grows, illustrating that some points are more useful in smaller datasets, while others become more…

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Dropout: An Innovative Method for Minimizing Overfitting in Neural Networks

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Machine learning, Staff, Tech News, Technology, UncategorizedJuly 5, 202469Views0Likes0Comments
Overfitting is a prevalent problem when training large neural networks on limited data. It indicates a model's strong performance on the training data but its failure to perform comparably on unseen test data. This issue arises when the network’s feature detectors become overly specialized to the training data, building complex dependencies that do not apply…

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Researchers from Google Disclose Useful Understanding of Knowledge Distillation for Optimizing Models

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Computer vision, Editors Pick, Staff, Tech News, Technology, UncategorizedJuly 5, 202465Views0Likes0Comments
The computer vision sector is currently dominated by large-scale models that offer remarkable performance but demand high computational resources, making them impractical for real-world applications. To address this, the Google Research Team has opted to reduce these models into smaller, more efficient architectures via model pruning and knowledge distillation. The team's focus is on knowledge…

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Researchers from Carnegie Mellon University Suggest XEUS: A Universal Speech Encoder Cross-Linguistically Trained in Over 4000 Languages.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Staff, Tech News, Technology, UncategorizedJuly 5, 202469Views0Likes0Comments
Self-supervised learning (SSL) has broadened the application of speech technology by minimizing the requirement for labeled data. However, the current models only support approximately 100-150 of the over 7,000 languages in the world. This is primarily due to the lack of transcribed speech and the fact that only about half of these languages have formal…

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