Remove AI Modeling Remove Data Scarcity Remove ML
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The “Zero-Shot” Mirage: How Data Scarcity Limits Multimodal AI

Marktechpost

This is the enticing promise of “zero-shot” capabilities in AI. Major tech companies have released impressive multimodal AI models like CLIP for vision-language tasks and DALL-E for text-to-image generation. But how close are we to realizing this vision? If you like our work, you will love our newsletter.

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Poro 34B: A 34B Parameter AI Model Trained for 1T Tokens of Finnish, English, and Programming languages, Including 8B Tokens of Finnish-English Translation Pairs

Marktechpost

.” Despite some research exploring the benefits and drawbacks of multilingual training and efforts to enhance models for smaller languages, most cutting-edge models still need to be primarily trained in large languages like English. Join our Telegram Channel , Discord Channel , and LinkedIn Gr oup.

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This paper from Google DeepMind Provides an Overview of Synthetic Data Research, Discussing Its Applications, Challenges, and Future Directions

Marktechpost

In the rapidly evolving landscape of artificial intelligence (AI), the quest for large, diverse, and high-quality datasets represents a significant hurdle. For instance, in domains where authentic data is rare or sensitive, synthetic data emerges as a scalable and customizable alternative. Yet synthetic data has its challenges.

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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

Marktechpost

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. If you like our work, you will love our newsletter.

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CRoP: A Context-wise Static Personalization Method for Robust and Scalable Human-Sensing AI Models in Healthcare and Real-World Scenarios

Marktechpost

These applications can significantly impact health management by monitoring human behavior and providing critical data for health assessments. However, due to the variability in individual behaviors, environmental factors, and the physical placement of devices, the performance of generic AI models is often hindered.

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This Paper Explores AI-Driven Hedging Strategies in Finance: A Deep Dive into the Use of Recurrent Neural Networks and k-Armed Bandit Models for Efficient Market Simulation and Risk Management

Marktechpost

He highlighted the necessity for effective data use by stressing the significant amount of data many AI systems consume. Another researcher highlighted the challenge of considering AI model-free due to market data scarcity for training, particularly in realistic derivative markets.

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This AI Paper from Cohere for AI Presents a Comprehensive Study on Multilingual Preference Optimization

Marktechpost

Consequently, many languages still need to be represented, limiting AI technologies’ applicability and fairness. Addressing this disparity requires innovative approaches to enhance the quality and diversity of multilingual datasets, ensuring that AI models can perform effectively across a broad spectrum of languages.