Unite.AI

JULY 5, 2024

In this comprehensive guide, we'll explore LLM-driven synthetic data generation, diving deep into its methods, applications, and best practices. Introduction to Synthetic Data Generation with LLMs Synthetic data generation using LLMs involves leveraging these advanced AI models to create artificial datasets that mimic real-world data.

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Unite.AI

SEPTEMBER 12, 2024

Over the past decade, Artificial Intelligence (AI) has made significant advancements, leading to transformative changes across various industries, including healthcare and finance. The principle behind this is straightforward: better data results in better models. Data scarcity is another significant issue.

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Marktechpost

DECEMBER 31, 2023

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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Topbots

DECEMBER 19, 2023

Generated with Midjourney The NeurIPS 2023 conference showcased a range of significant advancements in AI, with a particular focus on large language models (LLMs), reflecting current trends in AI research. These awards highlight the latest achievements and novel approaches in AI research. Enjoy this article?

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Viso.ai

DECEMBER 18, 2023

Instead of relying on organic events, we generate this data through computer simulations or generative models. Synthetic data can augment existing datasets, create new datasets, or simulate unique scenarios. Specifically, it solves two key problems: data scarcity and privacy concerns.

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Computer Vision Neural Network Auto-complete Data Scarcity 52

Pickl AI

OCTOBER 9, 2024

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.

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AWS Machine Learning Blog

MARCH 14, 2024

Launched in 2017, Amazon SageMaker is a fully managed service that makes it straightforward to build, train, and deploy ML models. More and more customers are building their own FMs using SageMaker, including Stability AI, AI21 Labs, Hugging Face, Perplexity AI, Hippocratic AI, LG AI Research, and Technology Innovation Institute.

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