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Over 300,000 photos in earlier massive datasets like COCO have over 3 million annotations. Models may now be trained on datasets with a 1000x increase in scale, such as FLD-5B, which contains over 126 million photos annotated with five billion+ words. Annotation speed can be increased by a factor of 100 with synthetic annotation pipelines,…
Natural Language Processing (NLP), despite its progress, faces the persistent challenge of hallucination, where models generate incorrect or nonsensical information. Researchers have introduced Retrieval-Augmented Generation (RAG) systems to mitigate this issue by incorporating external information retrieval to enhance the accuracy of generated responses. The problem, however, is the reliability and effectiveness of RAG systems in…
LG AI Research has recently announced the release of EXAONE 3.0. This latest third version in the series upgrades EXAONE’s already impressive capabilities. The release as an open-source large language model is unique to the current version with great results and 7.8B parameters. With the introduction of EXAONE 3.0, LG AI Research is driving a…
Calendars, specifically Google Calendars, have both positive and negative aspects. For example, they can help plan gatherings, track time spent on individual tasks, and even keep in touch with pals. However, our schedule has the potential to balloon out of control quickly. Having nothing to go on but a sea of blue checkboxes on your…
Large Language Models (LLMs) are advancing rapidly resulting in more complex architecture. The high cost of LLMs has been a major barrier to their widespread adoption in various industries. Businesses and developers have been hesitant to invest in these models due to the substantial operational expenses. A significant portion of these costs arises from the…
Visual representation learning using large models and self-supervised techniques has shown remarkable success in various visual tasks. However, deploying these models in real-world applications is challenging due to multiple resource constraints such as computation, storage, and power consumption. Adapting large pre-trained models for different scenarios with varying resource limitations involves weight pruning, knowledge distillation, or…
Recent advances in segmentation foundation models like the Segment Anything Model (SAM) have shown impressive performance on natural images and videos. Still, their application to medical data remains to be determined. SAM, trained on a vast dataset of natural images, struggles with medical images due to domain differences like lower resolution and unique image challenges.…
Artificial intelligence, particularly AI chatbots like ChatGPT, has ushered in a new era of technological interaction. These intelligent systems, capable of understanding and generating human-like text, are not just prevalent across various applications but are also transforming the way we communicate, work, and learn. The rapid adoption of AI chatbots, particularly ChatGPT, across different domains…
One of the primary challenges in AI research is verifying the correctness of language models (LMs) outputs, especially in contexts requiring complex reasoning. As LMs are increasingly used for intricate queries that demand multiple reasoning steps, domain expertise, and quantitative analysis, ensuring the accuracy and reliability of these models is crucial. This task is particularly…
IncarnaMind is leading the way in Artificial Intelligence by enabling users to engage with their personal papers, whether they are in PDF or TXT format. The necessity of being able to query documents in natural language has increased with the introduction of AI-driven solutions. However, problems still exist, especially when it comes to accuracy and…