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Large Language Model

TII unveils Falcon 2-11B: The inaugural AI Model from the Falcon 2 series, developed with 5.5T tokens employing a Vision Language Model.

The Technology Innovation Institute (TII) in Abu Dhabi has launched "Falcon," a ground-breaking collection of language models. They're available under the Apache 2.0 license, with Falcon-40B being the first "fully open" model that's equivalent in capabilities to numerous proprietary alternatives. This innovation marks a significant step forward in the field, presenting a wealth of opportunities…

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FinTextQA: An Extensive LFQA Dataset Exclusively Created for the Finance Industry

The increasing demand for financial data analysis and management has propelled the expansion of question-answering (QA) systems powered by artificial intelligence (AI). These systems improve customer service, aid in risk management, and provide personalized stock recommendations, thus requiring a comprehensive understanding of financial data. This data's complexity, domain-specific terminology, market instability, and decision-making processes make…

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TRANSMI: A machine learning structure that creates standard models tailored for transliterated data, derived from existing multilingual pretrained language models mPLMs, and requires no additional training.

The rapid growth of digital text in different languages and scripts presents significant challenges for natural language processing (NLP), particularly with transliterated data where performance often degrades. Current methods, such as pre-trained models like XLM-R and Glot500, are capable of handling text in original scripts but struggle with transliterated versions. This not only impacts their…

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Introducing Verba 1.0: Operate Cutting-Edge RAG Locally with the Integration of Ollama and Access to Open Source Models.

Advances in artificial intelligence (AI) technology have led to the development of a pioneering methodology, known as retrieval-augmented generation (RAG), which fuses the capabilities of retrieval-based technology with generative modeling. This process allows computers to create relevant, high-quality responses by leveraging large datasets, thereby improving the performance of virtual assistants, chatbots, and search systems. One of…

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A comparative investigation of LoRA and Full Finetuning in large language models was carried out by researchers associated with Columbia University and Databricks.

Researchers from Columbia University and Databricks Mosaic AI have conducted a comparative study of full finetuning and Low-Rank Adaptation (LoRA), a parameter-efficient finetuning method, in large language models (LLMs). The efficient finetuning of LLMs, which can contain billions of parameters, is an ongoing challenge due to the substantial GPU memory required. This makes the process…

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This Artificial Intelligence research article from Stanford University assesses the effectiveness of multi-modal foundational models as they scale from limited-shot to extensive in-context learning (ICL).

Recent research suggests that incorporating demonstrating examples, or in-context learning (ICL), significantly enhances large language models' (LLM's) and large multimodal models' (LMM's) performance. Studies have shown improvements in LLM performance with increased in-context examples, particularly in out-of-domain tasks. These findings are driven by newer models such as GPT-4o and Gemini 1.5 Pro, which include longer…

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Comparing GPT-4 and GPT-4o: An Overview of Major Changes and Comparative Study

The world of artificial intelligence (AI) and machine learning continues to evolve at a rapid pace, with OpenAI leading the charge. Their latest development is the introduction of GPT-4o, an optimized version of the widely used GPT-4, part of the Generative Pre-trained Transformer model series renowned for its natural language processing capabilities. GPT-4 boasts enhanced contextual…

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01.AI has launched its improved model, Yi-1.5-34B, a more advanced version of the original Yi. It boasts a high-quality corpus with 500 billion tokens and has been meticulously adjusted using 3 million diverse fine-tuning samples.

The world of Artificial Intelligence (AI) has taken another step forward with the introduction of the recent Yi-1.5-34B model by 01.AI. This model is considered a significant upgrade over prior versions, providing a bridge between the capabilities of the Llama 3 8B and the 70B models. The distinguishing features of the Yi-1.5-34B include improvements in multimodal…

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SpeechVerse: An AI Framework Built with Multiple Modes allowing LLMs to Comprehend and Carry Out a Wide Range of Speech-processing Tasks via Natural Language Commands.

Large language models (LLMs) have been successful in areas like natural language tasks and following instructions, yet they have limitations when dealing with non-textual data such as images and audio. But presently, an approach integrating textual LLMs with speech encoders in one training setup could revolutionize this. One option is multimodal audio-language models, proving advantageous…

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Meta AI presents Chameleon: A novel range of preliminary fusion token-based foundational models that establish a fresh benchmark for multimodal machine learning.

Recent multimodal foundation models are often limited in their ability to fuse various modalities, as they typically utilize distinct encoders or decoders for each modality. This structure limits their capability to effectively integrate varied content types and create multimodal documents with interwoven sequences of images and text. Meta researchers, in response to this limitation, have…

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