|
Greetings from Cannes. It's Day 1 of Cannes Lions and the town is buzzing. Today is our AI for Brand Marketers Summit hosted by Mastercard, and I could not be more excited.
In the news: As you know, AI models rely on vast amounts of real-world data scraped from the web, often plagued by privacy issues and inherent biases, and there has been talk about the possibility of running out of new data to train on. Synthetic data, however, offers a compelling alternative, and NVIDIA just introduced a vast synthetic data set.
Nemotron-4 340B is a suite of open models designed for generating synthetic data to train large language models (LLMs) across various industries, including healthcare and finance. This family includes base, instruct, and reward models optimized for use with NVIDIA's NeMo and TensorRT-LLM frameworks. These models offer a scalable solution for creating high-quality training data, which is crucial for the performance and accuracy of LLMs. Available on platforms like Hugging Face, Nemotron-4 340B will facilitate efficient data generation and customization for specific applications.
It's okay if you didn't follow the previous paragraph. What's important is understanding that synthetic data is a thing. Developers are using it now. It is improving quickly, and (in some cases) it reduces the need for large (think large language models) amounts of human-created data.
As always your thoughts and comments are both welcome and encouraged. Just reply to this email. -s
|
