Creating engaging videos is complex, involving tasks like scripting, filming, and editing. However, AI tools have simplified content generation, making it easier to produce videos for platforms like social media and YouTube. The article identifies 11 top AI video generators, emphasizing key features to consider: real AI functionalities, high-quality output, customization options, user-friendly interfaces, and unique creative features. Among the highlighted tools are Sora, Runway, Descript, and Wondershare Filmora, each with distinct pros and cons tailored for various needs. For instance, Sora excels in scene control and customization, while Descript allows edits via transcripts, streamlining the editing process. There’s also mention of tools like Peech, Synthesia, and Vyond, which cater to unique production contexts (marketing, training, etc.). The article reinforces the vast potential of AI in video creation, making high-quality production more accessible to creators of all levels.
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The Top AI Video Generators for Crafting Captivating Content in Minutes
Cybercriminals Outsmart Human Intelligence Using Phony AI Installers • The Register
Criminals are capitalizing on interest in artificial intelligence (AI) by distributing malware through fake software installers that mimic legitimate AI products. Research by Cisco Talos identified threats including CyberLock ransomware and a new malware called “Numero,” both of which are spread through impersonated websites. The attackers create websites that closely resemble those of actual AI vendors, enticing users to download compromised files. CyberLock encrypts sensitive documents and demands a $50,000 ransom in cryptocurrency, while also claiming the funds will support humanitarian efforts—though this is likely a manipulation tactic. Another scam involves Yashma ransomware disguised as a ChatGPT installer, which can bypass security measures. The “Numero” malware corrupts Windows systems in an endless loop. Talos warns individuals and small businesses against downloading AI tools from unverified sources to avoid these growing cyber threats. The malicious activities highlight a troubling trend of exploiting AI’s popularity for cybercrime.
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Stability AI Lawsuit Fails to Address Widespread Industry Theft
Getty Images is pursuing legal action against Stability AI, alleging the U.K.-based startup illegally used 12 million copyrighted images to train its text-to-image model, Stable Diffusion, for commercial purposes. Getty’s CEO, Craig Peters, criticized the AI industry’s claims that requiring payment for creative works stifles innovation, arguing that this notion equates to theft and unfair competition. The lawsuit, filed in both the U.K. and U.S., underscores the broader issue of copyright infringement involving AI firms using large datasets, raising concerns among content creators. Stability AI contests the allegations, claiming its use of copyrighted material falls under “fair use.” Intellectual property expert Sukanya Wadhwa highlighted that the legal landscape around such cases is complex, especially concerning international jurisdiction. While Peters believes his case is strong, he notes the challenges of navigating costly legal battles against well-funded tech entities. An initial trial is scheduled for June 9.
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EMAQI App Officially Launches: A New Era for AI-Powered Manga Start-Up
Orange Inc. has launched its new manga app, emaqi, on May 28, 2025, targeting readers in the U.S. and Canada. The app features over 13,000 volumes from major publishers, including VIZ Media and Kodansha, alongside nearly 50 exclusive titles. Emaqi operates as a digital manga bookstore, selling complete volumes à la carte instead of using a subscription model. The app is designed to enhance discovery and personalization through intuitive search tools, marking a unique experience for manga fans.
Backed by ¥2.92 billion (~$20 million) in funding, Orange aims to significantly increase manga localization efforts, claiming that over 95% of Japanese works are unavailable in English. While the company integrates AI in its localization process, it insists that human involvement is critical to maintaining quality. However, the use of AI has sparked controversy among creators and professionals concerned about its impact on traditional translation methods. Despite criticism, Orange remains committed to expanding manga access globally.
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Google Unveils LMEval: An Open-Source Tool for Evaluating Cross-Provider LLMs
LMEval is a tool designed to help AI researchers and developers compare the performance of various large language models (LLMs) efficiently and accurately. Given the rapid development of new models, LMEval facilitates quick evaluations for safety and security. Its key features include compatibility with numerous LLM providers, incremental benchmark execution to enhance efficiency, and support for multimodal evaluations involving text, images, and code. Utilizing the LiteLLM framework, LMEval allows for consistent benchmarking across different APIs. Written in Python and available on GitHub, users define benchmarks and tasks, such as identifying eye colors in images, before evaluating selected models. The tool also enables result storage in SQLite databases, with encrypted security measures. LMEval includes a dashboard for performance analysis and has been pivotal in creating the Phare LLM Benchmark, assessing LLM safety and reliability. Other frameworks like Harbor Bench and EleutherAI’s LM Evaluation Harness also exist for similar purposes.
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IndiaAI Mission Chooses Soket AI Labs, Gnani.ai, and Gan.ai for Next-Gen LLM Development
Dr. Anjali Sharma, an AI policy analyst, highlighted India’s strategic move towards technological sovereignty and inclusive growth by supporting startups such as Soket AI Labs, Gnani.ai, and Gan.ai. She emphasized that these innovative models will not only drive the development of new applications but also foster opportunities for research and entrepreneurship. Additionally, they are expected to facilitate global collaboration, further enhancing India’s status in the technology landscape. This approach reflects a commitment to nurturing a robust ecosystem that empowers emerging companies, ultimately contributing to broader economic and technological advancement.
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Unexpected Gmail Update by Google: Implications for Your Privacy
Gmail has introduced automatic AI summaries for Workspace customers, aimed at enhancing user experience as Gmail evolves. This update, accessible on Android and iOS, utilizes Google’s Gemini AI to automatically generate summaries for relevant email threads, synthesizing key points and keeping summaries up to date with new replies. While privacy concerns have been raised, Google assures that this feature adheres to its strong data protection policies, indicating that interactions are confined within the organization and not shared externally without consent. The update is specifically designed for Google Workspace users, including business and education clients, and allows administrators to adjust settings. Users must enable smart features and personalization in Gmail to utilize this new function. With nearly 2 billion users, Gmail continues to innovate through AI technology to maintain its leading position in the email market while ensuring user privacy and security remain priorities.
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Do AI Tools Undermine Developer Skills? Exploring the Impact of AI Applications
Artificial intelligence (AI) is swiftly transforming the software industry, with tools like ChatGPT and GitHub Copilot aiding developers in coding, debugging, and offering suggestions. Although these AI applications boost productivity and expedite software development, companies express concern over their impact on developer skills. Despite the advantages of AI, employers expect developers to possess strong foundational knowledge, including proficiency in data structures, system design, independent debugging, and effective communication. Many candidates, however, struggle with articulating their coding logic and effectively collaborating in teams, leading to a skills gap that concerns employers. Companies also recognize the risks associated with AI, such as potential bugs in AI-generated code and reduced creativity. To thrive, developers should focus on deepening their technical expertise, reviewing AI-generated code critically, and using AI as a supportive tool rather than a substitute for critical thinking. Balancing AI integration with core skills will drive future innovation in software development.
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Google Unveils New App for Downloading and Running AI Models Locally
Google has launched the Google AI Edge Gallery app, enabling users to run various AI models from Hugging Face on Android devices, with an iOS version to follow. This app allows for offline access to capabilities like image generation, question answering, and code editing, utilizing users’ phone processors. While cloud-based AI models are typically more powerful, the app addresses data privacy concerns by enabling offline use. The experimental app features a user-friendly interface with shortcuts for tasks such as “Ask Image” and “AI Chat” and includes a “Prompt Lab” for single-turn tasks, offering templates and settings for customization. Performance may vary based on device hardware and model size, with larger models requiring more processing time. Google encourages developer feedback, and the app is available under an Apache 2.0 license, allowing broad usage without restrictions.
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Google Unveils New App for Local Download and Execution of AI Models
Google recently launched the Google AI Edge Gallery app, allowing users to run various AI models from Hugging Face on their Android devices, with an iOS version forthcoming. This app enables offline functionality for tasks like image generation, question-answering, and code writing, tapping into smartphone processors. While cloud-based AI models are often more robust, they raise concerns about data privacy and internet dependency. The app features a user-friendly interface, showcasing shortcuts to tasks such as “Ask Image” and “AI Chat.” Users can explore different models suited for each capability, including Google’s Gemma 3n, and utilize a “Prompt Lab” to initiate tasks like summarizing text. Performance varies based on device hardware and model size. Google invites developer feedback on this experimental Alpha release, which is available on GitHub under an Apache 2.0 license, permitting broad usage.
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