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NVIDIA advances AI frontiers with CES 2025 announcements

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Pras Velagapudi, CTO at Agility, comments: Data scarcity and variability are key challenges to successful learning in robot environments. Explore other upcoming enterprise technology events and webinars powered by TechForge here. The post NVIDIA advances AI frontiers with CES 2025 announcements appeared first on AI News.

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Google DeepMind Researchers Introduce Diffusion Augmented Agents: A Machine Learning Framework for Efficient Exploration and Transfer Learning

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A major issue in RL is the data scarcity in embodied AI, where agents must interact with physical environments. This problem is exacerbated by the need for substantial reward-labeled data to train agents effectively. Also, don’t forget to follow us on Twitter and join our Telegram Channel and LinkedIn Gr oup.

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CMU Researchers Release Pangea-7B: A Fully Open Multimodal Large Language Models MLLMs for 39 Languages

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The dataset was designed to address the major challenges of multilingual multimodal learning: data scarcity, cultural nuances, catastrophic forgetting, and evaluation complexity. Moreover, PANGEA matches or even outperforms proprietary models like Gemini-1.5-Pro If you like our work, you will love our newsletter.

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Open Artificial Knowledge (OAK) Dataset: A Large-Scale Resource for AI Research Derived from Wikipedia’s Main Categories

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However, acquiring such datasets presents significant challenges, including data scarcity, privacy concerns, and high data collection and annotation costs. Artificial (synthetic) data has emerged as a promising solution to these challenges, offering a way to generate data that mimics real-world patterns and characteristics.

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VulScribeR: A Large Language Model-Based Approach for Generating Diverse and Realistic Vulnerable Code Samples

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The success of VulScribeR highlights the importance of large-scale data augmentation in the field of vulnerability detection. By generating diverse and realistic vulnerable code samples, this approach provides a practical solution to the data scarcity problem that has long hindered the development of effective DLVD models.

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MMS Zero-shot Released: A New AI Model to Transcribe the Speech of Almost Any Language Using Only a Small Amount of Unlabeled Text in the New Language

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With its extensive language training and romanization technique, the MMS Zero-shot method offers a promising solution to the data scarcity challenge, advancing the field towards more inclusive and universal speech recognition systems. Also, don’t forget to follow us on Twitter and join our Telegram Channel and LinkedIn Gr oup.

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Meta AI Researchers Introduce Token-Level Detective Reward Model (TLDR) to Provide Fine-Grained Annotations for Large Vision Language Models

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To address data scarcity and granularity issues, the system employs sophisticated synthetic data generation techniques, particularly focusing on dense captioning and visual question-answering tasks. Also, don’t forget to follow us on Twitter and join our Telegram Channel and LinkedIn Gr oup.