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Mahesh

04/09/24 10:50 AM IST

OpenAI’s Project Strawberry

In News
  • The secretive project, on which OpenAI has been working for long, was earlier known as Project Q* (Q-star), and is now codenamed Project Strawberry.
  • It is expected to feature autonomous Internet research and dramatically improve AI reasoning capabilities, and has been billed as OpenAI’s push to create Artificial General Intelligence — AI with capabilities similar to that of the human brain.
About Project
  • Project Strawberry aims to raise more capital, which OpenAI needs for its next-frontier model, codenamed Orion.
  • The generation of high-quality training data for Orion is believed to be one of Project Strawberry’s key applications.
  • This is significant because most of the training data on the Internet has already been used, and there is now a dearth of information that is outside paywalls and authentication, and is free to access for the purpose of training AI models.
  • Indeed, OpenAI has been of late making deals with publications to use their content for training.
  • Project Orion, which is being designed to outperform GPT-4, could use a combination of Project Strawberry and high-quality synthetic data that would likely reduce errors and hallucinations compared to its predecessors and other AI models.
Significance
  • Generative AI models create synthetic data based on real-world data samples.
  • The algorithms learn patterns, correlations, and statistical properties of the sample data; after it is trained, the model can produce statistically identical synthetic data.
  • The large datasets that AI models rely on could be prone to biases and errors, or could have incomplete or inaccurate information — high-quality synthetic data produced by Project Strawberry can fill gaps in real-world data sets and provide a more wholesome, inclusive, and balanced training set
  • Many believe that the use of synthetic data can help make future AI models more neutral and fair, and reduce noise and irrelevant information — thereby improving both the efficiency of training and the accuracy of the model.
Source- Indian Express

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