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The AI study by Cohere explores the assessment of models using a massive assembly of language model evaluators, also known as PoLL.

In the field of artificial intelligence, the evaluation of Large Language Models (LLMs) poses significant challenges; particularly with regard to data adequacy and the quality of a model’s free-text output. One common solution is to use a singular large LLM, like GPT-4, to evaluate the results of other LLMs. However, this methodology has drawbacks, including…

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The Benefits of Edge AI Compared to Conventional AI

Edge Artificial Intelligence (Edge AI) is a novel approach to implementing AI algorithms and models on local devices, such as sensors or IoT devices at the network's edge. The technology permits immediate data processing and analysis, reducing the reliance on cloud infrastructure. As a result, devices can make intelligent decisions autonomously and quickly, eliminating the…

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ScrapeGraphAI: This Python library utilizes machine learning models for web scraping and simplifies the process of building scraping pipelines for websites, documents, and XML files.

In an era dominated by data-driven decision-making, businesses, researchers, and developers constantly require specific information from various online sources. This information, used for tasks like analyzing trends and monitoring competitors, is traditionally collected using web scraping tools. The trouble is that these tools require a sound understanding of programming and web technologies, can deliver errors,…

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Investigating Efficient Parameter Adjustment Approaches for Comprehensive Language Models

Large Language Models (LLMs) represent a significant advancement across several application domains, delivering remarkable results in a variety of tasks. Despite these benefits, the massive size of LLMs renders substantial computational costs, making them challenging to adapt to specific downstream tasks, particularly on hardware systems with limited computational capabilities. With billions of parameters, these models…

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The AI research document from China unveiles a new tool known as TinyChart: a highly efficient large-scale multimodal language model for interpreting charts that operates on a mere 3 billion parameters.

In the age of rapidly growing data volume, charts have become vital tools for visualizing data in diverse fields ranging from business to academia. As a result, the need for automated chart comprehension has become increasingly important and received significant attention. While advancements in Multimodal Large Language Models (MLLMs) have shown promise in understanding images…

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Maintaining Equilibrium between Innovation and Rights: A Collaborative Game Theory Strategy for Copyright Handling in AI based Creative Technologies.

Generative artificial intelligence's (AI) ability to create new text, images, videos, and other media represents a huge technological advancement. However, there's a downside: generative AI may unwittingly infrive on copyrights by using existing creative works as raw material without the original author's consent. This poses serious economic and legal challenges for content creators and creative…

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Meta AI Presents CyberSecEval 2: A New Machine Learning Standard to Measure Security Threats and Abilities in LLM

Large language models (LLMs) are increasingly in use, which is leading to new cybersecurity risks. The risks stem from their main characteristics: enhanced capability for code creation, deployment for real-time code generation, automated execution within code interpreters, and integration into applications handling unprotected data. It brings about the need for a strong approach to cybersecurity…

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Introducing Electric Atlas: A Fresh Chapter in Robotics from Boston Dynamics.

Boston Dynamics, a pioneer in robotics innovation for several decades, has introduced its latest product – the fully electric Atlas robot. Marking the retirement of its hydraulic Atlas, the new electric version ushers in a fresh phase of transformative, realistic applications across different sectors. Boston Dynamics had begun Atlas's development over ten years ago, at a…

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Hippocrates: A Comprehensive Machine Learning Framework for Developing Advanced Language Models for Healthcare using Open-Source Technology

Artificial Intelligence (AI) is significantly transforming the healthcare industry, addressing challenges in areas such as diagnostics and treatment planning. Large Language Models (LLMs) are emerging as a revolutionary tool in this sector, capable of deciphering and understanding complex health data. However, the intricate nature of medical data and the need for accuracy and efficiency in…

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REBEL: An Algorithm for Reinforcement Learning (RL) Diminishes the Complexity of RL by Converting it into Successfully Tackling a Series of Relative Reward Regression Challenges on Sequentially Compiled Datasets.

Proximal Policy Optimization (PPO), initially designed for continuous control tasks, is widely used in reinforcement learning (RL) applications, like fine-tuning generative models. However, PPO's effectiveness is based on a series of heuristics for stable convergence, like value networks and clipping, adding complexities in its implementation. Adapting PPO to optimize complex modern generative models with billions of…

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