Recent developments in Artificial Intelligence (AI), particularly in Generative AI, have proven the capacities of Large Language Models (LLMs) to generate human-like text in response to prompts. These models are proficient in tasks such as answering questions, summarizing long paragraphs, and more. However, even provided with reference materials, they can generate errors which could have…
Scaling laws in artificial intelligence are fundamental in the development of Large Language Models (LLMs). These laws play the role of a director, coordinating the growth of models while revealing patterns of development that go beyond mere computation. With every new step, the models become more nuanced, accurately deciphering the complexities of human expression. Scaling…
The Sparse Mixture of Experts (SMoEs) has become popular as a method of scaling models, particularly in memory-restricted environments. They are crucial to the Switch Transformer and Universal Transformers, providing efficient training and inference. However, some limitations exist with current implementations of SMoEs, such as a lack of GPU parallelism and complications related to tensor…
The intersection of Artificial Intelligence's (AI) language understanding and visual perception is evolving rapidly, pushing the boundaries of machine interpretation and interactivity. A group of researchers from the Korea Advanced Institute of Science and Technology (KAIST) has stepped forward with a significant contribution in this dynamic area, a model named MoAI.
MoAI represents a new…
The development of effective large language models (LLMs) remains a complex problem in the realm of artificial intelligence due to the challenge of balancing size and computational efficiency. Minimizing these issue, a strategy called Additive Quantization for Language Models (AQLM) has been introduced by researchers from institutions such as HSE University, Yandex Research, Skoltech, IST…
As you walk down a buzzing city street, the hum of a passing object draws your attention. It's a small, automated delivery robot navigating quickly and nimbly among pedestrians and urban obstacles. It's not a scene from a science fiction film, but a demonstration of the innovative technology called Generalizable Neural Feature Fields (GeFF). This…
Recent advancements in research have significantly built up the capabilities of Multimodal Large Language Models (MLLMs) to incorporate complex visual and textual data. Researchers are now providing detailed insights into the architectural design, data selection, and methodology transparency of MLLMs that offer heightened comprehension of how these models function. Highlighting the crucial tasks performed by…
Stanford University researchers are pushing the boundaries of artificial intelligence (AI) with the introduction of "pyvene," an innovative, open-source Python library designed to advance intervention-based research on machine learning models. As AI technology evolves, so does the need to refine and understand these advancement's underlying processes. Pyvene is an answer to this demand, propelling forward…
Text-to-video diffusion models are revolutionizing how individuals generate and interact with media. These advanced algorithms can produce engaging, high-definition videos just by using basic text descriptions, enabling the creation of scenes that vary from serene, picturesque landscapes to wild and imaginative scenarios. However, until now, the field's progress has been hindered by a lack of…
In the rapidly expanding world of generative artificial intelligence (AI), the importance of independent evaluation and 'red teaming' is crucial in order to reveal potential risks and ensure that these AI systems align with public safety and ethical standards. However, stringent terms of service and enforcement practices set by leading AI organisations disrupt this critical…
Machine learning (ML) workflows have become increasingly complex and extensive, prompting a need for innovative optimization approaches. These workflows, vital for many organizations, require vast resources and time, driving up operational costs as they adjust to various data infrastructures. Handling these workflows involved dealing with a multitude of different workflow engines, each with their own…
In the realm of artificial intelligence, notable advancements are being made in the development of language agents capable of understanding and navigating human social dynamics. These sophisticated agents are being designed to comprehend and react to cultural nuances, emotional expressions, and unspoken social norms. The ultimate objective is to establish interactive AI entities that are…