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

Marktechpost

Multilingual natural language processing (NLP) is a rapidly advancing field that aims to develop language models capable of understanding & generating text in multiple languages. These models facilitate effective communication and information access across diverse linguistic backgrounds.

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Innovations in Analytics: Elevating Data Quality with GenAI

Towards AI

GenAI can help by automatically clustering similar data points and inferring labels from unlabeled data, obtaining valuable insights from previously unusable sources. Natural Language Processing (NLP) is an example of where traditional methods can struggle with complex text data. GPT-4o mini response use case #2.

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Award-Winning Breakthroughs at NeurIPS 2023: A Focus on Language Model Innovations

Topbots

The findings indicate that alleged emergent abilities might evaporate under different metrics or more robust statistical methods, suggesting that such abilities may not be fundamental properties of scaling AI models. The paper also explores alternative strategies to mitigate data scarcity.

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Unlocking Deep Learning’s Potential with Multi-Task Learning

Pickl AI

Also read: What is Information Retrieval in NLP? What is Tokenization in NLP? Instead of training separate models for each task, we can train a single model for multiple tasks, leading to significant time, memory, and energy savings. By simultaneously tackling multiple related tasks, MTL offers a myriad of benefits.

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What is Transfer Learning in Deep Learning? [Examples & Application]

Pickl AI

Transfer Learning is a technique in Machine Learning where a model is pre-trained on a large and general task. Since this technology operates in transferring weights from AI models, it eventually makes the training process for newer models faster and easier. Thus it reduces the amount of data and computational need.

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How Fastweb fine-tuned the Mistral model using Amazon SageMaker HyperPod as a first step to build an Italian large language model

AWS Machine Learning Blog

Overcoming data scarcity with translation and synthetic data generation When fine-tuning a custom version of the Mistral 7B LLM for the Italian language, Fastweb faced a major obstacle: high-quality Italian datasets were extremely limited or unavailable. In his free time, Giuseppe enjoys playing football.

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Innovations in AI: How Small Language Models are Shaping the Future

Pickl AI

This blog explores the innovations in AI driven by SLMs, their applications, advantages, challenges, and future potential. What Are Small Language Models (SLMs)? Small Language Models (SLMs) are a subset of AI models specifically tailored for Natural Language Processing (NLP) tasks.