Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
License information was derived automatically
This is an instruction dataset fine for the purpose of efficient answering to row completion prompts. See https://github.com/mostly-ai/datallm for more.
Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
License information was derived automatically
MOSTLY AI Prize Dataset
This repository contains the dataset used in the MOSTLY AI Prize competition.
About the Competition
Generate the BEST tabular synthetic data and win 100,000 USD in cash. Competition runs for 50 days: May 14 - July 3, 2025. This competition features two independent synthetic data challenges that you can join separately:
The FLAT DATA Challenge The SEQUENTIAL DATA Challenge
For each challenge, generate a dataset with the same size and structure as… See the full description on the dataset page: https://huggingface.co/datasets/mostlyai/mostlyaiprize.
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BASE YEAR | 2024 |
HISTORICAL DATA | 2019 - 2024 |
REPORT COVERAGE | Revenue Forecast, Competitive Landscape, Growth Factors, and Trends |
MARKET SIZE 2023 | 7.98(USD Billion) |
MARKET SIZE 2024 | 9.55(USD Billion) |
MARKET SIZE 2032 | 40.0(USD Billion) |
SEGMENTS COVERED | Type ,Application ,Deployment Mode ,Organization Size ,Regional |
COUNTRIES COVERED | North America, Europe, APAC, South America, MEA |
KEY MARKET DYNAMICS | Growing Demand for Data Privacy and Security Advancement in Artificial Intelligence AI and Machine Learning ML Increasing Need for Faster and More Efficient Data Generation Growing Adoption of Synthetic Data in Various Industries Government Regulations and Compliance |
MARKET FORECAST UNITS | USD Billion |
KEY COMPANIES PROFILED | MostlyAI ,Gretel.ai ,H2O.ai ,Scale AI ,UNchart ,Anomali ,Replica ,Big Syntho ,Owkin ,DataGenix ,Synthesized ,Verisart ,Datumize ,Deci ,Datasaur |
MARKET FORECAST PERIOD | 2025 - 2032 |
KEY MARKET OPPORTUNITIES | Data privacy compliance Improved data availability Enhanced data quality Reduced data bias Costeffective |
COMPOUND ANNUAL GROWTH RATE (CAGR) | 19.61% (2025 - 2032) |
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The Generative AI Market size was valued at USD 16.88 billion in 2023 and is projected to reach USD 149.04 billion by 2032, exhibiting a CAGR of 36.5 % during the forecasts period. The generative AI market specifically means the segment of a market that sells products based on the AI technologies for creating content that includes text, images, audio content, and videos. While generative AI models are mainly based on machine learning, especially neural networks, it synthesises new content that is similar to human-generated data. Some of them are as follows- Creation of contents and designs, more specifically in discovery of any drug and through customized marketing strategies. It is applied to areas including, but not limited to entertainment, health care, and finances. Modern developments indicate the emergence of AI-art, AI-music, and AI-writings, the usage of generative AI for automated communication with customers, and the enhancement of AI-ethics and -regulations. Challenges are defined by the constant enhancements in AI algorithms and the rising need for automation and inventiveness in various fields. Recent developments include: In April 2023, Microsoft Corp. collaborated with Epic Systems, an American healthcare software company, to incorporate large language model tools and AI into Epic’s electronic health record software. This partnership aims to use generative AI to help healthcare providers increase productivity while reducing administrative burden , In March 2021, MOSTLY AI Inc. announced its partnership with Erste Group, an Australian bank to provide its AI-based synthetic data solution. Using synthetic data, Erste Group aims to boost its digital banking innovation and enable data-based development .
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
CAI-Synthetic Model
Overview
The CAI-Synthetic Model is a large language model designed to understand and respond to complex questions. This model has been fine-tuned on a synthetic dataset from Mostly AI, allowing it to engage in a variety of contexts with reliable responses. It is designed to perform well in diverse scenarios.
Base Model and Fine-Tuning
Base Model: Google/Gemma-7b
Fine-Tuning Adapter: LoRA Adapter
Synthetic Dataset: Mostly AI Synthetic… See the full description on the dataset page: https://huggingface.co/datasets/InnerI/CAI-synthetic-10k.
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Market Analysis for Synthetic Data Software The global synthetic data software market is projected to reach a value of 168.5 million by 2033, expanding at a CAGR of 14.2% from 2025 to 2033. The growth is attributed to the increasing adoption of synthetic data in various industries, such as healthcare, retail, and finance, to improve data privacy, reduce data preparation time, and enhance model accuracy. The cloud-based deployment model and applications in government, retail, and research and development drive market expansion. Market Trends and Competitive Landscape Key trends shaping the market include the rising demand for synthetic data in artificial intelligence training, the proliferation of cloud-based solutions, and the growing emphasis on data privacy. Several notable companies operate in the market, including AI.Reverie, Deep Vision Data, Informatica, and MOSTLY AI. Strategic partnerships and acquisitions are common, with companies seeking to expand their capabilities and customer base. The competitive landscape is expected to remain fragmented as new entrants emerge and established players continue to innovate their offerings. As organizations strive to leverage data for transformative insights, the demand for synthetic data software is on the rise. This report provides an in-depth analysis of the synthetic data software landscape, shedding light on market trends, key players, and industry dynamics.
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Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
License information was derived automatically
This is an instruction dataset fine for the purpose of efficient answering to row completion prompts. See https://github.com/mostly-ai/datallm for more.