Copyleaks Blog·
A Unified Experience With this launch, Copyleaks is delivering a unified detection suite that allows consumer users to verify the authenticity of text and images in a single, seamless view. It is now easier than ever to check for AI-generated text, identify synthetic images, and scan for plagiarism simultaneously. Whether it’s for verifying an essay, […] The post Clarity in the Age of AI: Copyleaks Launches the AI Image Detector for Consumers appeared first on Copyleaks.
Read full articleInsider Brief PRESS RELEASE — Text, the company behind LiveChat, ChatBot and HelpDesk, is revealing details of its strategic shift aimed at turning customer service into a profit engine with the help of new features powered by AI Agents. Text announces the release of Shopify-native AI selling agents, designed to move customer service teams beyond answering questions to actively […]
As AI images flood the media, publishers must rebuild reader trust. Learn how Copyleaks AI detection automates image validation and scales transparency. The post Rebuilding Reader Trust: Transparent Disclosure and Image Validation appeared first on Copyleaks.
Is your next hire a deepfake? Discover why interview fraud is rising and how HR teams can protect company security using Copyleaks' AI content detection. The post Deepfake Candidates: Why Interview Fraud Is on the Rise appeared first on Copyleaks.
Google's Gemini Omni is a new multimodal model that reasons across text, images, audio, and video to generate and edit videos through simple conversation — starting with Omni Flash.
Insider Brief Researchers at Northwestern University and the National Institutes of Health suggest that the rise of generative AI should force a rethink of how plagiarism and research misconduct are defined in scientific writing. In a commentary published in Nature Machine Intelligence, Northwestern’s Mohammad Hosseini and NIH bioethicist David Resnick write that traditional definitions of […]
Thinking Machines Lab has introduced a research preview of TML-Interaction-Small, a 276B parameter Mixture-of-Experts model with 12B active parameters, built around a multi-stream, time-aligned micro-turn architecture that processes 200ms chunks of audio, video, and text simultaneously — eliminating the need for external voice-activity detection harnesses. Unlike standard turn-based models that freeze perception during generation, the system runs two components in parallel: a real-time interaction model that maintains continuous full-duplex exchange with the user, and an asynchronous background model that handles sustained reasoning and tool use while sharing the full conversation context throughout. The post Mira Murati’s Thinking Machines Lab Introduces Interaction Models: A Native Multimodal Architecture for Real-Time Human-AI Collaboration appeared first on MarkTechPost.
Thinking Machines, the AI company founded by former OpenAI CTO Mira Murati, announced Monday that it's working on something called "interaction models." The idea behind interaction models, according to Thinking Machines, is that they will let people "collaborate with AI the way we naturally collaborate with each other - they continuously take in audio, video, and text, and think, respond, and act in real time." As explained by Thinking Machines: Today's models experience reality in a single thread. Until the user finishes typing or speaking, the model waits with no perception of what the user is doing or how the user is doing it. Until th … Read the full story at The Verge.
We used the Copyleaks AI detector as a lab instrument to find which model is more likely to be flagged. The post Claude vs Grok Which is Easier To Detect? appeared first on Copyleaks.
