Skip to content Skip to sidebar Skip to footer
Only AI Stuff
Only AI Stuff

Language Model

Close

Representative Ability of Transformer Language Models Compared to n-gram Language Models: Harnessing the Parallel Processing Potential of n-gram Models

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Staff, Tech News, Technology, UncategorizedApril 28, 202433Views0Likes0Comments
Neural language models (LMs), particularly those based on transformer architecture, have gained prominence due to their theoretical basis and their impact on various Natural Language Processing (NLP) tasks. These models are often evaluated within the context of binary language recognition, but this approach may create a disconnect between a language model as a distribution over…

Read More

Improving Biomedical Named Entity Recognition through Dynamic Definition Augmentation: A Unique AI Method to Enhance Precision in Large Language Models

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Staff, Tech News, Technology, UncategorizedApril 27, 202434Views0Likes0Comments
The practice of biomedical research extensively depends on the accurate identification and classification of specialized terms from a vast array of textual data. This process, termed Named Entity Recognition (NER), is crucial for organizing and utilizing information found within medical literature. The proficient extraction of these entities from texts assists researchers and healthcare professionals in…

Read More

Scientists at DeepMind have proposed an innovative self-training machine learning technique known as Naturalized Execution Tuning (NExT). It significantly enhances the ability of Language Models (LLMs) to infer about program execution.

AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Machine learning, Staff, Tech News, Technology, UncategorizedApril 27, 202431Views0Likes0Comments
Coding execution is a crucial skill for developers and is often a struggle for existing large language models in AI software development. A team from Google DeepMind, Yale University, and the University of Illinois has proposed a novel approach to enhancing the ability of these models to reason about code execution. The method, called "Naturalized…

Read More

Transforming Web Automation: AUTOCRAWLER’s Novel Structure Boosts Effectiveness and Versatility in Changing Web Scenarios

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Staff, Tech News, Technology, UncategorizedApril 27, 202433Views0Likes0Comments
Web automation technologies play a pivotal role in enhancing efficiency and scalability across various digital operations by automating complex tasks that usually require human attention. However, the effectiveness of traditional web automation tools, largely based on static rules or wrapper software, is compromised in today's rapidly evolving and unpredictable web environments, resulting in inefficient web…

Read More

Investigating Machine Learning Model Training: A Comparative Study of Cloud, Centralized, Federated Learning, On-Device Machine Learning and Other Methods

AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Machine learning, Staff, Tech News, Technology, UncategorizedApril 27, 202432Views0Likes0Comments
Machine learning (ML) is a rapidly growing field which has led to the emergence of a variety of training platforms, each tailored to cater to different requirements and restrictions. These platforms comprise Cloud, Centralized Learning, Federated Learning, On-Device ML, and numerous other emerging models. Cloud and Centralized learning uses remote servers for heavy computations, making…

Read More

Improving the Scalability and Efficiency of AI Models: Research on the Multi-Head Mixture-of-Experts Approach

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Staff, Tech News, Technology, UncategorizedApril 26, 202435Views0Likes0Comments
Large Language Models (LLMs) and Large Multi-modal Models (LMMs) are effective across various domains and tasks, but scaling up these models comes with significant computational costs and inference speed limitations. Sparse Mixtures of Experts (SMoE) can help to overcome these challenges by enabling model scalability while reducing computational costs. However, SMoE struggles with low expert…

Read More

CATS (Contextually Aware Thresholding for Sparsity): An Innovative Machine Learning Structure for Triggering and Utilizing Activation Sparsity in LLMs.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Machine learning, Staff, Tech News, Technology, UncategorizedApril 26, 202437Views0Likes0Comments
Large Language Models (LLMs), while transformative for many AI applications, necessitate high computational power, especially during inference phases. This poses significant operational costs and efficiency challenges as the models become bigger and more intricate. Particularly, the computational expenses incurred when running these models at the inference stage can be intensive due to their dense activation…

Read More

+60 12-462 2768
hello@goacademyai.com