Data Collection
Data collection involves gathering and preparing information from various sources for analysis. We provide reviews and comparisons of data collection tools, explore common challenges, and cover approaches like AI data collection and data crowdsourcing.
Innodata Review & Top 3 Alternatives in August
Technologies such as natural language processing (NLP), computer vision (CV), or generative AI are all fueled by data. Businesses are increasingly relying on AI data collection services to obtain this data. Innodata Inc. is an AI data service provider that claims to help companies fulfill their AI data needs.
Telus International Review & Alternatives
As AI-powered solutions become increasingly abundant, many businesses rely on AI data services to acquire the necessary data to fuel their AI projects, such as large language models (LLMs) or natural language processing (NLP) systems. Telus International is one such service that helps businesses with their AI data needs.
10+ Image Data Collection Services in August
As artificial intelligence (AI) and machine learning-powered solutions grow, the demand for comprehensive image datasets has never increased. The foundation of a successful AI model, especially in computer vision (CV) projects, is reliant upon high-quality data. Image data collection services play an instrumental role in gathering this crucial data.
Top 10 Data Crowdsourcing Platforms in August
With the spread of AI tools like generative AI and chatbots, the demand for AI data services has also increased. One such service is data crowdsourcing platforms, which leverage large groups to gather data, enhancing collection efforts with fast, detailed insights.
AI Data Collection: Risks, Challenges & Tools
AI builders need fresh, high quality data: However, data collection comes with its risks. For example, enterprises need to avoid unethical data collection practices and ensure that data is collected ethically to minimize reputational risk.
Top 3 Prolific Alternatives in August
Prolific is a popular AI data collection service that offers a crowdsourcing platform for AI data seekers. Our research identified some drawbacks of working with Prolific from the perspectives of its customers and workers.
5 Steps to OCR Training Data
The interest in optical character recognition (OCR) and intelligent character recognition (ICR) technology is falling as companies switch to more automated solutions, such as machine learning-enabled data extraction. However, due to its various benefits, many companies still use1 or plan to use tools powered by OCR technology in their paper-based operations.
7 Best Data Pipeline Tools With Key Capabilities
Businesses use a variety of data sources, including internal sources (e.g., CRM, ERP), external sources (e.g., social media platforms), and third-party web analytics services ( e.g., Google Analytics). Through the diversity of data sources, businesses use different technologies to capture data from their sources such as web scraping tools and browser fingerprinting technologies.
Human Generated Data with Methods
Despite the rise of generative AI tools like ChatGPT and Gemini, human-generated data remains crucial for AI developers. Companies like OpenAI invest heavily in obtaining human-generated data to train their large language models (LLMs). Whether through data collection services or in-house efforts, AI developers require a steady stream of human-generated data.
Top 4 Facial Recognition Data Collection Methods
Despite the controversies surrounding this technology, the facial recognition systems (FRS) market continues to grow. Facial recognition applications are everywhere, from helping improve mental disorder diagnoses to finding fugitives. Developing and improving these systems requires facial data, which sometimes can be challenging to obtain due to security and privacy-related concerns of people.