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The investment in AI Search Engine by Jeff Bezos is predicted to double in the upcoming months.

Perplexity AI, a startup launched in August 2022, is aspiring to compete with Google in the search engine sector. The company's technology merges the capabilities of a chatbot and a traditional search engine, and its innovation is gaining investment from figures including Amazon founder, Jeff Bezos. In the first few months of 2024, Perplexity AI…

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Revealing the Simplicity in Complexity: The Straightforward Depiction of Ideas in Extensive Language Models

In the ever-evolving sphere of artificial intelligence, the study of large language models (LLMs) and how they interpret and process human language has provided valuable insights. Contrary to expectation, these innovative models represent concepts in a simple and linear manner. To demystify the basis of linear representations in LLMs, researchers from the University of Chicago…

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Transforming Text into Imagery: The Game-Changing Collaboration between AWS AI Labs and the University of Waterloo through MAGID.

A new multimodal system, created by scientists from the University of Waterloo and AWS AI Labs, uses text and images to create a more engaging and interactive user experience. The system, known as Multimodal Augmented Generative Images Dialogues (MAGID), improves upon traditional methods that have used static image databases or real-world sources, which can pose…

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Introducing Modeling Collaborator: A Revolutionary Artificial Intelligence system enabling anyone to train vision models through straightforward language interactions and less effort.

Computer vision traditionally concentrates on acknowledging universally agreed concepts like animals, vehicles, or specific objects. However, real-world applications often need to identify variable subjective concepts like predicting emotions, determining aesthetic appeal, or regulating content. What is considered "unsafe" content or "gourmet" food differs greatly among individuals, hence the increasing demand for user-centric training frameworks that…

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“Thought Enhancement via Retrieval (TER): An AI Instruction Approach that Unifies Thought Sequence (TS) Instructions and Retrieval Enhanced Generation (REG) to Resolve the Difficulties Associated with Long-Term Reasoning and Generation Tasks.”

Artificial Intelligence researchers are continuously striving to create models that can think, reason, and generate outputs similar to the way humans solve complex problems. However, Large Language Models (LLMs), the current best attempt at such a feat, often struggle to maintain factual accuracy, especially in tasks that require a series of logical steps. This lack…

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Pioneering Advances in AI: The Role of Multimodal Large Language Models in Transforming Age and Gender Prediction

The evolution of Multimodal Large Language Models (MLLMs) has been significant, particularly those models that blend language and vision modalities (LVMs). There has been growing interest in applying MLLMs in various fields like computer vision tasks and integrating them into complex pipelines. Despite some models like ShareGPTV performing well in data annotation tasks, their practical…

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This Chinese AI research showcases MathScale: an expandable machine learning approach for generating superior mathematical reasoning data with cutting-edge language models.

Large language models (LLMs) like GPT-3 have proven to be powerful tools in solving various problems, but their capacity for complex mathematical reasoning remains limited. This limitation is partially due to the lack of extensive math-related problem sets in the training data. As a result, techniques like Instruction Tuning, which is designed to enhance the…

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Researchers from UNC-Chapel Hill have developed a new AI method known as Contrastive Region Guidance (CRG), which doesn’t require training, and provides open-source vision-language models (VLMs) the ability to respond to visual cues.

Modern vision-language models (VLMs) have made significant progress in providing solutions for multimodal tasks by merging the reasoning abilities of large language models (LLMs) and visual encoders like ViT. Nevertheless, despite their impressive performance in tasks involving entire images, these models often struggle with the fine-grained region grounding, inter-object spatial relations, and compositional reasoning. They…

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An introductory manual for developing a Retrieval Augmented Generation (RAG) application from the ground up | Authored by Bill Chambers.

Retrieval Augmented Generation (RAG) has recently been gaining attention as it provides new possibilities for large language models like OpenAI's GPT-4 to use and leverage their own data. This technique essentially involves adding one's own data (via a retrieval tool) to the prompt that is passed into a language model which then generates an output.…

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5 Complimentary University Courses for Computer Science Education

If you're interested in transitioning into a tech career, it's important to start by learning the fundamentals of computer science. Here are some of the best university computer science courses that will help cover the basics, including programming with Python, data structures and algorithms, and essential tools for software engineering. Stanford University's Computer Science 101 course…

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