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AI Shorts

AI21 Labs presents a new version of their Hybrid SSM-Transformer Jamba Model, meticulously tuned for instructions and dubbed Jamba-Instruct Model.

AI21 Labs has unveiled its Jamba-Instruct model, a solution designed to tackle the challenge of using large context windows in natural language processing for business applications. Traditional models usually have constraints in their context capabilities, impacting their effectiveness in tasks such as summarising lengthy documents or continuing conversations. In contrast, Jamba-Instruct overcomes these barriers by…

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What are the measurements needed for constructing Retrieval Augmented Generation (RAG) workflows?

In the rapidly evolving domain of Artificial Intelligence, Natural Language Processing (NLP), and Information Retrieval, the advent of advanced models like Retrieval Augmented Generation (RAG) has stirred considerable interest. Despite this, many data science experts advise against jumping into complex RAG models until the evaluation pipeline is fully reliable and robust. Performing comprehensive assessments of RAG…

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What are the specifications required for developing Retrieval Augmented Generation (RAG) pipelines?

Retrieval Augmented Generation (RAG) models have become increasingly important in the fields of Artificial Intelligence, Natural Language Processing (NLP), and Information Retrieval. Despite this, there's a cautionary note from data science experts advising against a rush into using sophisticated RAG models until the evaluation pipeline is reliable and robust. Emphasising the importance of examining RAG…

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Utilizing Bayesian Optimization for Gathering Preferences from Broad Language Models

The challenge of efficiently determining a user's preferences through natural language dialogues, specifically in the context of conversational recommender systems, is a focus of recent research. Traditional methods require users to rate or compare options, but this approach fails when the user is unfamiliar with the majority of potential choices. Solving this problem through Large…

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Improving Ongoing Education through IMEX-Reg: A Sturdy Strategy to Reduce Severe Memory Loss

Continual learning (CL), the capability of systems to adapt over time without losing prior knowledge, presents a significant challenge. Neural networks, while adept at processing large amounts of data, can often suffer from catastrophic forgetting, when learning new information may erase what was previously learned. This becomes extremely problematic in scenarios with limited data retention…

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Understanding Physics Better through Intuitive Visualizations

Physics, often perceived as an abstract and challenging field, covers fundamental aspects of the universe which can intimidate learners due to intricate mathematical formulations. To make physics more relatable, the field of Visual Intuitive Physics seeks to transform these complexities into accessible visual experiences through the use of visual aids and intuitive methodologies. Visualization in physics…

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E2B Unveils SDK for Code Interpretation: Allowing AI Applications to Possess Code Parsing Features

Code interpreters have become important tools in the rapidly developing field of Artificial Intelligence (AI) as they enable AI models to execute code designed for specific problems, thus unlocking more advanced problem-solving capabilities. Enabling AI agents to run AI-generated code safely without compromising security and data integrity is one of the key challenges faced by…

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