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3 天之前 — 40+ Cool AI Tools You Should Check Out (Oct 2024) AI Shorts October 11, 2024. DeepSwap DeepSwap is an AI-based tool for anyone who wants to create convincing deepfake videos and images. It is super easy to create your content by refacing videos, pictures, memes, old movies, GIFs…. You name it.
Google and Duke University's New Machine Learning
2024年3月2日 — The most compelling aspect of this research is its implications for the future of machine learning. The demonstrated capability of linear transformers to intuitively grasp and implement advanced optimization methods opens up new avenues for developing models that are more adaptable and more efficient in learning from complex data scenarios.
Microsoft and NVIDIA AI Introduces MT-NLG: The Largest and …
2021年10月13日 — Transformer-based language models have made rapid progress in many natural language processing (NLP) applications, thanks to the availability of large datasets, large computation at scale, and advanced algorithms and software to train these models. The high-performing language models need many parameters, a lot of data, and a lot of training time to develop a richer, more sophisticated ...
Meet Arch: The Intelligent Layer 7 Gateway for LLM Applications
5 天之前 — Meet Arch: An intelligent Layer 7 gateway designed to protect, observe, and personalize LLM applications (agents, assistants, co-pilots) with your APIs. Arch serves as the connective tissue that enhances the interaction between your LLM-based application and its users, providing vital layers of protection, observability, and personalization.
Meet PowerInfer: A Fast Large Language Model (LLM) on a
2023年12月23日 — Generative Large Language Models (LLMs) are well known for their remarkable performance in a variety of tasks, including complex Natural Language Processing (NLP), creative writing, question answering, and code generation. In recent times, LLMs have been run on approachable local systems, including home PCs with consumer-grade GPUs for improved data privacy, customizable models, and lower ...
LongRAG: A New Artificial Intelligence AI Framework that
2024年6月25日 — Retrieval-Augmented Generation (RAG) methods enhance the capabilities of large language models (LLMs) by incorporating external knowledge retrieved from vast corpora. This approach is particularly beneficial for open-domain question answering, where detailed and accurate responses are crucial. By leveraging external information, RAG systems can overcome the limitations of relying solely on the ...
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Marktechpost Media Inc. is a California-based Artificial Intelligence News Platform with a community of 1.5 Million+ AI Professionals/ Developers. Marktechpost brings AI research news that is much more technical than most resources but still digestible and applicable. Who is Marktechpost's Audience? Our audience consists of Data Engineers, MLOps Engineers, Data Scientists, ML Engineers, ML ...
Thinking LLMs: How Thought Preference Optimization Transforms …
4 天之前 — Large language models (LLMs) have evolved to become powerful tools capable of understanding and responding to user instructions. Based on the transformer architecture, these models predict the next word or token in a sentence, generating responses with remarkable fluency. However, they typically respond without engaging in internal thought processes that could help improve the accuracy of ...
CaLM: Bridging Large and Small Language Models for
2024年6月30日 — The paper addresses the challenge of ensuring that large language models (LLMs) generate accurate, credible, and verifiable responses by correctly citing reliable sources. Existing methods often need help with errors and hallucinations, leading to incorrect or misleading information in generated responses. This research aims to improve the accuracy and reliability of LLM outputs by introducing ...
Apple Announces MM1: A Family of Multimodal LLMs Up To 30B …
2024年3月16日 — Recent research has focused on crafting advanced Multimodal Large Language Models (MLLMs) that seamlessly integrate visual and textual data complexities. By delving into the minutiae of architectural design, data selection, and methodological transparency, research has pushed the boundaries of what MLLMs can achieve and support future explorations. Their work is particularly notable for its ...