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Improving Maritime Safety and Efficiency through Vision AI in Marine Navigation

Maritime transport has a key role in worldwide trade and travel, but the unpredictability of global waters presents various difficulties. However, the inception of autonomous ships could revolutionise maritime navigation. These ships, also known as Maritime Autonomous Surface Ships (MASS), combine advanced sensors and Artificial Intelligence (AI) to improve situational awareness and ensure safer navigation.…

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THRONE: Progress in Assessing Hallucinations in Vision-Language Models

The rapidly evolving field of research addressing hallucinations in vision-language models (VLVMs), or artificially intelligent (AI) systems that generate coherent but factually incorrect responses, is increasingly gaining attention. Especially important when applied in crucial domains like medical diagnostics or autonomous driving, the accuracy of the outputs from VLVMs, which combine text and visual inputs, is…

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THRONE: Progressing the Assessment of Visual-Language Models’ Hallucinations

Artificial Intelligence (AI) systems, such as Vision-Language Models (VLVMs), are becoming increasingly advanced, integrating text and visual inputs to generate responses. These models are being used in critical contexts, such as medical diagnostics and autonomous driving, where accuracy is paramount. However, researchers have identified a significant issue in these models, which they refer to as…

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Scientists from Princeton University and Meta AI have unveiled ‘Lory’, a completely differentiable MoE model which has been exclusively designed for pre-training of autoregressive language models.

Mixture-of-experts (MoE) architectures, designed for better scaling of model sizes and more efficient inference and training, present a challenge to optimize due to their non-differentiable, discrete nature. Traditional MoEs use a router network which directs input data to expert modules, a process that is complex and can lead to inefficiencies and under-specialization of expert modules.…

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QoQ and QServe: Pioneering Model Quantization for Effective Large Language Model Distribution

Large Language Models (LLMs) play a crucial role in computational linguistics. However, their enormous size and the massive computational demands they require make deploying them very challenging. To faciliate simpler computations and boost model performance, a process of "quantization" is used, which simplifies the data involved. Traditional quantization techniques convert high-precision numbers into lower-precision integers,…

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Physicians face more challenges in identifying illnesses when examining pictures of darker skin tones.

A study led by researchers at the Massachusetts Institute of Technology (MIT) has revealed that physicians' success at diagnosing skin diseases using images is lower when the subject has darker skin. The study documented the accuracy of over 1,000 dermatologists and general practitioners at diagnosing diseases based on images, and found that while dermatologists correctly…

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Enhanced safety in the sky through autonomous helicopters.

After enduring a few frightening experiences while learning to fly helicopters, aerospace engineering PhD student, Haofeng Xu, was motivated to improve helicopter flight safety. In 2021, Xu founded Rotor Technologies, targeting the dangers prevalent in small private aircraft flights which lead to fatal accidents every year across the U.S. Rotor Technologies aims to retrofit existing…

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Utilizing AI in Healthcare: 3 Practical Instances

Artificial Intelligence (AI) is currently experiencing a surge in popularity and is gaining recognition for its impact on numerous industries. One of the areas where AI has been less highlighted but is increasingly being leveraged is in healthcare. Contrary to common misconceptions of AI as robotic physicians, AI in healthcare is more accurately described as…

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ChuXin: A Completely Open Source Language Model Containing 1.6 Billion Parameters

The recent development of large language models (LLMs), which can generate high-quality content across various domains, has revolutionized the field of natural language creation. These models are fundamentally of two types: those with open-source model weights and data sources, and those for which all model-related information, including training data, data sampling ratios, logs, checkpoints, and…

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Comprehensive Review of GPT’s Innovative Contributions to Game Design

Generative Pre-trained Transformers (GPT) have significantly transformed the gaming industry, from game development to gameplay experiences. This is according to a comprehensive review that draws from 55 research articles published between 2020 and 2023, as well as other papers. GPT's application in Procedural Content Generation (PCG) allows for increased creativity and efficiency in game development. For…

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Aloe: An Assemblage of Precision-Enhanced Open Healthcare LLMs that Delivers Superior Outcomes using Model Integration and Prompting Techniques

In the world of medical technology, the use of large language models (LLMs) is becoming instrumental, largely due to their ability to analyse and discern copious amounts of medical text, providing insight that would typically require extensive human expertise. The evolution of such technology could lead to substantial reductions in healthcare costs and broaden access…

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Researchers from the University of California, Berkeley have unveiled a new AI strategy named Learnable Latent Codes as Bridges (LCB). This innovative approach merges the abstract thinking abilities of large language models with low-level action strategies.

Robotics traditionally operates within two dominant architectures: modular hierarchical policies and end-to-end policies. The former uses rigid layers like symbolic planning, trajectory generation, and tracking, whereas the latter uses high-capacity neural networks to directly connect sensory input to actions. Large language models (LLMs) have rejuvenated the interest in hierarchical control architectures, with researchers using LLMs…

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