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.
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An API powered by Google's AI technology allows you to accurately convert speech into text. You can accurately caption your content, provide a better user experience with products using voice commands, and gain insight from customer interactions to improve your service. Google's deep learning neural network algorithms are the most advanced in automatic speech recognition (ASR). Speech-to-Text allows for experimentation, creation, management, and customization of custom resources. You can deploy speech recognition wherever you need it, whether it's in the cloud using the API or on-premises using Speech-to-Text O-Prem. You can customize speech recognition to translate domain-specific terms or rare words. Automated conversion of spoken numbers into addresses, years and currencies. Our user interface makes it easy to experiment with your speech audio.
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Chainer
Chainer is a robust, adaptable, and user-friendly framework designed for building neural networks. It facilitates CUDA computation, allowing developers to utilize a GPU with just a few lines of code. Additionally, it effortlessly scales across multiple GPUs. Chainer accommodates a wide array of network architectures, including feed-forward networks, convolutional networks, recurrent networks, and recursive networks, as well as supporting per-batch designs. The framework permits forward computations to incorporate any Python control flow statements without compromising backpropagation capabilities, resulting in more intuitive and easier-to-debug code. It also features ChainerRLA, a library that encompasses several advanced deep reinforcement learning algorithms. Furthermore, with ChainerCVA, users gain access to a suite of tools specifically tailored for training and executing neural networks in computer vision applications. The ease of use and flexibility of Chainer makes it a valuable asset for both researchers and practitioners in the field. Additionally, its support for various devices enhances its versatility in handling complex computational tasks.
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Threat Landscape
The Threat Landscape is an automated platform designed for security analysts and SOC teams, providing them with reliable and actionable intelligence while eliminating the need for manual triage. This system continuously gathers and analyzes global open-source intelligence (OSINT) and darknet data, efficiently extracting relevant structured information and minimizing irrelevant data before it reaches the analysts. All gathered intelligence is formatted into STIX 2.1, mapped to the MITRE ATT&CK framework, and cross-referenced with various elements such as threat actors, malware families, CVEs, TTPs, and IOCs, enabling teams to focus their efforts on utilizing intelligence rather than generating it.
Among its notable features are interactive dashboards, visual representations of STIX threat graphs, sophisticated search and filtering options, monitoring of the darknet for claims related to leak sites and criminal discussions, automated daily and weekly reports, as well as a RESTful API that allows seamless integration with SIEM, SOAR, and TIP platforms. This platform ultimately empowers security teams to respond swiftly and effectively to emerging threats, improving their overall cybersecurity posture.
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