Yes. I think the main benefit is that it comes in a more structured or refined format compared to raw data. But the knowledge is the same as in the raw data (and may even be more hallucinated), considering that raw data was used to generate the synthetic data through a model.
MACHINE LEARNING
-
Mastering RAG: Vector Databases and Prompt Engineering for AI Professionals
By
–
This book is designed for AI researchers, data scientists, software developers, and business analysts looking to: Enhance data retrieval and AI accuracy using Retrieval-Augmented Generation (RAG). Master practical techniques like vector databases and prompt engineering.
-
Generative AI and RAG: Enhance LLMs with Internal Data Integration
By
–
Unlocking Data with #GenerativeAI and RAG — Enhance Generative #AI systems by integrating internal data with large language models using RAG: https://
amzn.to/3PtFHdv v/ @PacktPublishing —————
#GenAI #LLMs #MachineLearning #KnowledgeGraph #DataScience #DataScientist #ad -
Synthetic Data from High-Quality Models as Transfer Learning Jumpstart
By
–
Yeah, I see it as some flavor of transfer learning (i.e., not starting from raw data). Synthetic data generated by a high-quality model (such as GPT-4o, which has already undergone extensive refinement) may serve as a kind of jumpstart to the model you are trying to train.
-
Building ClaireBot: AI Personal Stylist Chatbot Application
By
–
Building ClaireBot, an AI Personal Stylist Chatbot https://
bit.ly/3BGrwys
#AI #MachineLearning #DeepLearning #LLMs #DataScience -
AI Development Breakthroughs Across Industries in 2024
By
–
Last year proved to be another gear shift in AI development across many industries. Here’s a look back from @CNN at what became possible in 2024 through strides in artificial intelligence:
-
Preventing Hallucinations in Synthetic Data Generation Models
By
–
Since the model can't really explicitly distinguish between synthetic and non-synthetic data during training, the best way would tackle the problem at the root: ensuring that the synthetic data-generating model does not produce hallucinated contents.
-
DataRobot Named Gartner Customers’ Choice in Data Science
By
–
DataRobot customers maximize impact, innovate faster, and minimize risks. Don't just take our word for it — hear from our customers! We’re proud to be named a Customers’ Choice in the November 2024 Gartner Peer Insights “Voice of the Customer”: Data Science and Machine Learning
-
Abacus AI Deep Learning Anomaly Detection for Data Analysis
By
–
#AnomalyDetection by @AbacusAI uses leading-edge #DeepLearning models to spot anomalies in your data and to enable fast informed response: https://
abacus.ai/anomalydetecti
on
…
—————
#AI #MachineLearning #ML #BigData #Analytics #DataQuality #DataScience #CDO #CMO #DataScientist #DataAnalyst -
Building LLMs from Scratch: Is It Really Necessary?
By
–
We’d all love to build a model from scratch like Llama, but how realistic is that? The computing, architecture, and training data they have access to are so vast that it’s fair to say most of us wouldn’t be able to replicate it. But is it really necessary to train such large