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Synthetic Data for Machine Learning

It’s no secret that supervised machine learning models need to be trained on high-quality labeled datasets. However, collecting enough high-quality labeled data can be a significant challenge, especially in situations where privacy and data availability are major concerns. Fortunately, this problem can be mitigated with synthetic data. Synthetic data is data that is artificially generated…

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Advancing Vision-Language Models: A Survey by Huawei Technologies Researchers in Overcoming Hallucination Challenges

The emergence of Large Vision-Language Models (LVLMs) characterizes the intersection of visual perception and language processing. These models, which interpret visual data and generate corresponding textual descriptions, represent a significant leap towards enabling machines to see and describe the world around us with nuanced understanding akin to human perception. A notable challenge that impedes their…

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Pinterest Researchers Present an Effective Scalable Algorithm to Improve Diffusion Models Using Reinforcement Learning (RL)

Diffusion models are a set of generative models that work by adding noise to the training data and then learn to recover the same by reversing the noising process. This process allows these models to achieve state-of-the-art image quality, making them one of the most significant developments in Machine Learning (ML) in the past few…

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Speech to Text to Speech with AI Using Python — a How-To Guide | by Naomi Kriger | Feb, 2024

How to Create a Speech-to-Text-to-Speech Program Image by Mariia Shalabaieva from unsplashIt’s been exactly a decade since I started attending GeekCon (yes, a geeks’ conference 🙂) — a weekend-long hackathon-makeathon in which all projects must be useless and just-for-fun, and this year there was an exciting twist: all projects were required to incorporate some form…

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