At MyQ, the core belief is that print solutions should be automated, personalized, and easy to use, allowing people to focus on what matters most in their daily work. This principle is reflected in MyQ’s approach to our product design, combining intuitive user experiences with strong data security and efficient document workflows.
MyQ’s print management solutions strengthen document security while helping organizations reduce costs, save time, and lower their environmental impact.
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TinyPNG (by Tinify) is a free image optimization service built for developers and designers. It utilizes smart lossy compression to reduce the file sizes of JPEG, PNG, WebP, and AVIF files by up to 80% with no visible quality loss. That means faster load times, better SEO, and lower bandwidth.
You can compress, convert, and resize images via a clean web interface or integrate it into your workflow with the API. The platform also provides an image CDN for fast global delivery of optimized assets. SDKs are available for Python, Node.js, PHP, Java, Ruby, and .NET. WordPress plugin included, plus plenty of community-driven integrations.
No tuning, no noise, Tinify just works. Whether you're optimizing a handful of images or processing millions, it scales effortlessly. All plans include a generous free tier, and support is quick when you need it.
George the panda 🐼 approves.
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ByteScout Text Recognition SDK
Text recognition involves the identification and transformation of images or documents, like PDFs, that feature typed or printed text into a format that can be processed by computers, utilizing the Optical Character Recognition (OCR) method that is enhanced by Machine Learning and Artificial Intelligence. This technology streamlines labor-intensive processes such as extracting data from various documents including driver licenses, passports, invoices, and bank statements. It allows users to define specific rectangular areas within an image that are to be analyzed, with options for rotating and flipping the image as needed. By integrating advanced technologies with accessible tools available on our website, we ensure that our SDKs are tailored to meet your specific requirements. For those interested in a deeper understanding, our comprehensive tutorials, source codes, and documentation are designed to provide clarity and insight into the underlying mechanisms of our solutions. We believe that empowering users with knowledge is as crucial as providing the tools themselves.
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DeepSeek-V2
DeepSeek-V2 is a cutting-edge Mixture-of-Experts (MoE) language model developed by DeepSeek-AI, noted for its cost-effective training and high-efficiency inference features. It boasts an impressive total of 236 billion parameters, with only 21 billion active for each token, and is capable of handling a context length of up to 128K tokens. The model utilizes advanced architectures such as Multi-head Latent Attention (MLA) to optimize inference by minimizing the Key-Value (KV) cache and DeepSeekMoE to enable economical training through sparse computations. Compared to its predecessor, DeepSeek 67B, this model shows remarkable improvements, achieving a 42.5% reduction in training expenses, a 93.3% decrease in KV cache size, and a 5.76-fold increase in generation throughput. Trained on an extensive corpus of 8.1 trillion tokens, DeepSeek-V2 demonstrates exceptional capabilities in language comprehension, programming, and reasoning tasks, positioning it as one of the leading open-source models available today. Its innovative approach not only elevates its performance but also sets new benchmarks within the field of artificial intelligence.
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