Vypno

Gartner predicts that by 2030, machine learning models will use synthetic data exclusively, making real data unnecessary. Here are 10 companies you can use to generate synthetic data: Gretel.ai: Offers data anonymization solutions with APIs and machine learning models for data integration and analysis. MOSTLY AI: Specializes in generating high-quality synthetic data for various industries, focusing on privacy and diverse applications. Hazy: Focuses on synthetic data generation emphasizing data privacy and compliance across healthcare, banking, and technology. Tonic.ai: Provides automated synthetic data creation for testing and development, ensuring privacy and compliance. Datagen: AI-based platform for generating synthetic data, particularly for training computer vision models. Synthesis: Offers a data generation platform for computer vision, with an API for programmatic image generation. Betterdata: Cloud-based data security management platform offering AI-based solutions for data protection and anonymization. Rendered.ai: Provides AI and cloud-based tools for producing synthetic datasets, with applications in various industries. GenGenAI: AI-based platform for data preparation, specializing in generating and transforming image and video data. Vypno: Offers AI-based synthetic data for object recognition in images from various sources. To further explore the topic, use our article: https://lnkd.in/eF84_WH6

Really interesting piece here on the use of synthetic data in LLM's. Using synthetic data could well have positive implications around data protection and copyright. Yina Moe-Lange makes a really interesting point that synthetic data could be used for smaller models in specific use cases instead of a one size fits all approach. I touched on reinforcement learning from human feedback in a previous post and how this skillset is becoming more prevalent in open vacancies right now. Researchers at Google have seen comparable results using reinforcement learning from AI feedback. https://lnkd.in/ecGvmnSN Will RLAIF be the next in demand skillset? The corner of the market where #syntheticdata is concerned is busy. $290m of VC funding in 2022 - projected to hit well over $2b by 2030. This growth is fuelled by the increase of LLM usage across practically every sector and the notable, audible push on ethical and responsible AI which synthetic data will play a massive part. Using synthetic data in LLM's allows privacy and sensitive data, corporate and personal to be protected, is cost effective in model training, can be customised for ultra specific model training situations and can be reused for repeated experiments. Notable players in the space are Gretel.ai, Datagen, Betterdata, Rendered.ai, Vypno, FiddleCube, brudata Technologies, Datomize, IBM, K2view, MOSTLY AI, Redgate Software, Tonic.ai. Let me know who I have missed in the comments. Subscribe to The Big Y. #syntheticdata #machinelearning #LLM #reinforcementlearning #responsibleai #ethicalai CSG Talent