Deepfake Detection Challenge Dataset
Detecting Deepfakes for a Safer Online Environment
The Deepfake Detection Challenge Dataset is a project initiated by Facebook AI to accelerate the development of new ways to detect deepfake videos. The dataset consists of over 100,000 videos and was created in collaboration with industry leaders and academic experts. It includes two versions: a preview dataset with 5k videos and a full dataset with 124k videos, each featuring facial modification algorithms. The dataset was used in a Kaggle competition to create better models for detecting manipulated media. The top-performing models achieved high accuracy on the public dataset but faced challenges when tested against the black box dataset, highlighting the importance of generalization in deepfake detection. The project aims to encourage the research community to continue advancing in detecting harmful manipulated media.
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Deepfake Detection Challenge Dataset
The Deepfake Detection Challenge Dataset is a project initiated by Facebook AI to accelerate the development of new ways to detect deepfake videos. The dataset consists of over 100,000 videos and was created in collaboration with industry leaders and academic experts. It includes two versions: a preview dataset with 5k videos and a full dataset with 124k videos, each featuring facial modification algorithms. The dataset was used in a Kaggle competition to create better models for detecting manipulated media. The top-performing models achieved high accuracy on the public dataset but faced challenges when tested against the black box dataset, highlighting the importance of generalization in deepfake detection. The project aims to encourage the research community to continue advancing in detecting harmful manipulated media.
Cartesia Sonic Team Blog Research Playground
Cartesia Sonic Team Blog Research Playground is an AI application that offers real-time multimodal intelligence for every device. The application aims to build the next generation of AI by providing ubiquitous, interactive intelligence that can run on any device. It features the fastest, ultra-realistic generative voice API and is backed by research on simple linear attention language models and state-space models. The founding team, who met at the Stanford AI Lab, has invented State Space Models (SSMs) and scaled it up to achieve state-of-the-art results in various modalities such as text, audio, video, images, and time-series data.
Claude 3
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DagsHub is an open source data science collaboration platform that helps AI teams build better models and manage data projects. It provides a central location for data, code, experiments, and models, making it easy for teams to collaborate and track their progress. DagsHub also integrates with a variety of popular data science tools and frameworks, making it a powerful tool for data scientists and machine learning engineers.
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Grok-1.5 Vision (Grok-1.5V) is a groundbreaking multimodal AI model developed by Elon Musk's research lab, x.AI. This advanced model has the potential to revolutionize the field of artificial intelligence and shape the future of various industries. Grok-1.5V combines the capabilities of computer vision, natural language processing, and other AI techniques to provide a comprehensive understanding of the world around us. With its ability to analyze and interpret visual data, Grok-1.5V can assist in tasks such as object recognition, image classification, and scene understanding. Additionally, its natural language processing capabilities enable it to comprehend and generate human language, making it a powerful tool for communication and information retrieval. Grok-1.5V's multimodal nature sets it apart from traditional AI models, allowing it to handle complex tasks that require a combination of visual and linguistic understanding. This makes it a valuable asset for applications in fields such as healthcare, manufacturing, and customer service.
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syntheticAIdata
syntheticAIdata is a platform that provides synthetic data for training vision AI models. Synthetic data is generated artificially, and it can be used to augment existing real-world datasets or to create new datasets from scratch. syntheticAIdata's platform is easy to use, and it can be integrated with leading cloud platforms. The company's mission is to make synthetic data accessible to everyone, and to help businesses overcome the challenges of acquiring high-quality data for training their vision AI models.
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OpenAI01.net is an AI tool that offers free usage with some limitations. It provides a new series of AI models designed to spend more time thinking before responding, capable of reasoning through complex tasks and solving harder problems in science, coding, and math. Users can ask questions and get answers for free, with the option to select different models based on credits. The tool excels in complex reasoning tasks and has shown impressive performance in various benchmarks.
Dreamervision.ai
Dreamervision.ai is an innovative AI tool that utilizes advanced machine learning algorithms to analyze and interpret images and videos. The tool is designed to provide users with valuable insights and information based on visual content, enabling them to make informed decisions and enhance their understanding of the world around them. With its cutting-edge technology, Dreamervision.ai offers a seamless and efficient way to extract meaningful data from visual media, making it a valuable asset for professionals in various industries.
Camel AGI
Camel AGI is a groundbreaking platform that revolutionizes the way artificial intelligence is utilized to solve complex tasks by employing a unique role-playing method inspired by loop architecture, similar to that of BabyAGI and AutoGPT. At its core, CamelAGI facilitates the collaboration between two autonomous AI agents, each assigned specific roles, to work synergistically towards accomplishing a designated task. This innovative approach allows users to observe as the agents, equipped with distinct capabilities and perspectives, engage in a dynamic and context-aware dialogue, effectively mirroring the collaborative efforts seen in human interactions.
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Weavel is an AI tool designed to revolutionize prompt engineering for large language models (LLMs). It offers features such as tracing, dataset curation, batch testing, and evaluations to enhance the performance of LLM applications. Weavel enables users to continuously optimize prompts using real-world data, prevent performance regression with CI/CD integration, and engage in human-in-the-loop interactions for scoring and feedback. Ape, the AI prompt engineer, outperforms competitors on benchmark tests and ensures seamless integration and continuous improvement specific to each user's use case. With Weavel, users can effortlessly evaluate LLM applications without the need for pre-existing datasets, streamlining the assessment process and enhancing overall performance.
Grok-1.5
The website features Grok-1.5, an AI application that bridges the gap between the digital and physical worlds through its multimodal model. Grok-1.5 boasts enhanced reasoning capabilities and a context length of 128,000 tokens. Additionally, the platform offers PromptIDE, an IDE for prompt engineering and interpretability research, allowing users to create and share complex prompts in Python. Grok, an AI modeled after the Hitchhiker’s Guide to the Galaxy, is also available on the site, providing answers to a wide range of questions and even suggesting relevant queries. The platform aims to facilitate knowledge sharing and exploration through advanced AI technologies.
Sacred
Sacred is a tool to configure, organize, log and reproduce computational experiments. It is designed to introduce only minimal overhead, while encouraging modularity and configurability of experiments. The ability to conveniently make experiments configurable is at the heart of Sacred. If the parameters of an experiment are exposed in this way, it will help you to: keep track of all the parameters of your experiment easily run your experiment for different settings save configurations for individual runs in files or a database reproduce your results In Sacred we achieve this through the following main mechanisms: Config Scopes are functions with a @ex.config decorator, that turn all local variables into configuration entries. This helps to set up your configuration really easily. Those entries can then be used in captured functions via dependency injection. That way the system takes care of passing parameters around for you, which makes using your config values really easy. The command-line interface can be used to change the parameters, which makes it really easy to run your experiment with modified parameters. Observers log every information about your experiment and the configuration you used, and saves them for example to a Database. This helps to keep track of all your experiments. Automatic seeding helps controlling the randomness in your experiments, such that they stay reproducible.
Tableau
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Deepfake Detection Challenge Dataset
The Deepfake Detection Challenge Dataset is a project initiated by Facebook AI to accelerate the development of new ways to detect deepfake videos. The dataset consists of over 100,000 videos and was created in collaboration with industry leaders and academic experts. It includes two versions: a preview dataset with 5k videos and a full dataset with 124k videos, each featuring facial modification algorithms. The dataset was used in a Kaggle competition to create better models for detecting manipulated media. The top-performing models achieved high accuracy on the public dataset but faced challenges when tested against the black box dataset, highlighting the importance of generalization in deepfake detection. The project aims to encourage the research community to continue advancing in detecting harmful manipulated media.
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My Voice AI is an advanced voice identity security infrastructure that provides privacy-preserving, real-time voice authentication and deepfake protection. It is designed to reduce fraud, impersonation, and identity risk in voice-based interactions by offering speaker verification, anti-spoofing, and deepfake detection capabilities. The platform operates as a voice identity layer integrated into existing infrastructure, offering enterprise-grade latency, privacy-first architecture, and deterministic behavior suitable for audits. My Voice AI is purpose-built for regulated environments, such as financial institutions, critical services, and governments, where identity assurance is crucial to mitigate operational risks.
Resemble AI
Resemble AI is an advanced AI tool offering a range of features such as AI Voice Generator, Deepfake Detection, Voice Cloning, Text-to-Speech, Speech-to-Speech, Multilingual support, Audio Editing, and more. It provides state-of-the-art AI models for voice generation and detection, helping users create realistic voices and detect deepfakes across various media types. The platform is trusted by millions of users worldwide, including Fortune 500 companies and government agencies, for its innovative solutions in generative AI and security.
Facia.ai
Facia.ai is an AI-powered platform that specializes in liveness detection and deepfake detection solutions for businesses and governments. It offers cutting-edge technology to prevent identity fraud, verify authenticity, and enhance security measures. The platform provides accurate face matching, facial recognition, and age verification services, along with customizable integration options and reliable support. Facia.ai aims to combat misinformation, identity fraud, and evolving threats in various industries by leveraging AI algorithms and real-time detection capabilities.
Resemble AI
Resemble AI is a cutting-edge generative voice AI platform that empowers enterprises with advanced voice cloning, deepfake detection, and AI watermarking capabilities. Our suite of tools enables the creation of realistic synthetic voices, detection of AI-generated content, and protection of intellectual property. With Resemble AI, businesses can enhance customer service, elevate gaming experiences, revolutionize entertainment, and safeguard their digital assets.
TrueMedia.org
TrueMedia.org is a non-profit, non-partisan organization that fights political deepfakes. They offer a free AI-enabled deepfake detector to help newsrooms and the public identify and combat AI-manipulated content.
Attestiv
Attestiv is an AI-powered digital content analysis and forensics platform that offers solutions to prevent fraud, losses, and cyber threats from deepfakes. The platform helps in reducing costs through automated photo, video, and document inspection and analysis, protecting company reputation, and monetizing trust in secure systems. Attestiv's technology provides validation and authenticity for all digital assets, safeguarding against altered photos, videos, and documents that are increasingly easy to create but difficult to detect. The platform uses patented AI technology to ensure the authenticity of uploaded media and offers sector-agnostic solutions for various industries.
FaceSeek
FaceSeek is an advanced identity search tool that utilizes AI technology to search faces across the internet and social media. It offers features such as reverse face search, AI video generation, OSINT investigation, and AI image generation. FaceSeek provides a private and secure search process, allowing users to verify identity, detect deepfakes, and uncover impersonation. With a focus on privacy and creativity, FaceSeek is a versatile platform for visual investigation and creative content generation.
FaceFinder
FaceFinder is the #1 Reverse Face Search Engine, offering the most advanced AI face search and reverse image lookup tool. It allows users to instantly find social media profiles, check for catfish, and uncover online presence with just one photo. The application scans millions of websites, social media platforms, and public records to provide accurate facial recognition search results. FaceFinder prioritizes privacy by deleting uploaded photos immediately after the search completes, ensuring secure and anonymous face search experience.
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The Deepfake Detection Challenge Dataset is a project initiated by Facebook AI to accelerate the development of new ways to detect deepfake videos. The dataset consists of over 100,000 videos and was created in collaboration with industry leaders and academic experts. It includes two versions: a preview dataset with 5k videos and a full dataset with 124k videos, each featuring facial modification algorithms. The dataset was used in a Kaggle competition to create better models for detecting manipulated media. The top-performing models achieved high accuracy on the public dataset but faced challenges when tested against the black box dataset, highlighting the importance of generalization in deepfake detection. The project aims to encourage the research community to continue advancing in detecting harmful manipulated media.
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