Andrej Karpathy cautions against the over-excitement surrounding AI, particularly in deploying unsupervised agents. Speaking at a Y Combinator event, he emphasized the need to “keep AI on the leash,” highlighting the persistent mistakes made by large language models (LLMs), which can inaccurately claim facts or make basic errors. Even though LLMs can generate substantial amounts of code rapidly, Karpathy insists that developers must not relinquish control, as they remain the essential quality check. He advocates for a cautious approach, emphasizing the importance of concrete prompts to ensure accurate outputs. This sentiment is echoed by other experts, including Bob McGrew and Kent Beck, who stress the indispensable role of human engineers in managing AI complexities and preventing unpredictable outcomes. Despite AI’s potential, tech companies are increasingly integrating it into coding processes, with Alphabet reporting that AI is responsible for over 30% of their new code.
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OpenAI Co-Founder Andrej Karpathy: ‘Rein in AI for Safety’
Fast Feedback Secures SHINE Trust Funding for AI Assessment Tool
Fast Feedback, an open-source AI-driven platform created by Tom Rye, Vice Principal at Ark Bolingbroke, has received £20,000 in funding from the SHINE Trust to automate written assessments and reduce teacher workload in UK classrooms. This funding, part of the Let Teachers SHINE initiative, will support development and a pilot program in North East England over the next 12 months. Fast Feedback automates grading and generates high-quality feedback, allowing teachers to upload question banks and model answers to quickly score student responses and identify trends. This tool aims to enhance the efficiency of assessments, allowing educators to devote more time to instruction. Rye, who started through Teach First, emphasizes the importance of timely feedback for student progress and the need to alleviate marking burdens that impact teacher retention and wellbeing. The platform will remain open-source to ensure affordability and accessibility for all schools, especially those serving disadvantaged students.
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AI-Powered User Research Platform
UXArmy AI streamlines the user research process, enabling teams to obtain insights more rapidly. Key features include instant summaries and sentiment analysis, which help condense findings effectively. Additionally, the platform offers video playback for easier review of recorded sessions and AI-generated follow-up questions to deepen participant engagement. A conversational test assistant enhances the research experience for participants by guiding them through the process. Overall, UXArmy AI aims to make user research more efficient and insightful, fostering a quicker path from data collection to actionable insights.
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Transforming Overwhelming Support Ticket Volume: How We Developed an AI to Manage 80% of Inquiries
I’m unable to access external URLs directly. However, you can provide me with key points or excerpts from the article, and I’d be happy to help you summarize that content!
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Ask HN: What AI Code Editor Are You Using Right Now?
I’ve been using Cursor and recently had to reinstall it. I almost agreed to mandatory data sharing, which I found concerning since I prefer keeping my code private. Although I’m okay with sharing usage data, my code must remain confidential. The agent mode is not very effective, often missing context, and sometimes it inadvertently deletes helpful comments I add for guidance. However, I appreciate its chat feature, which significantly sped up my troubleshooting process and justifies its cost. The latest models in Cursor are notably better for novel code compared to previous versions. I also tried Copilot on VS Code but eventually stopped using it after discovering Cursor. While Copilot’s earlier autocomplete features were good for boilerplate code, they seem inadequate now compared to the newer Cursor models like deepseek and gemini 2.5, which excel in handling novel code.
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Adobe Firefly Unveils Mobile App Featuring AI Video Tools, Collaborative Models, and Live Moodboarding – Business Today
Adobe Firefly has launched a new mobile app featuring AI-powered video tools, innovative partner models, and real-time moodboarding capabilities. This app is designed to facilitate creative processes, allowing users to easily generate and edit video content using AI technology. The integration of partner models enhances collaboration among creators, enabling them to work together seamlessly. Real-time moodboarding offers users a dynamic way to collect and visualize their ideas, enhancing the brainstorming process. This development aligns with Adobe’s commitment to improving user experiences in creative endeavors, making advanced tools more accessible to a wider audience. Overall, the Adobe Firefly mobile app represents a significant leap in mobile creativity, empowering users with sophisticated resources for visual storytelling and content creation.
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Unveiling AI Clothing Removal Apps: How They Function and Where to Discover Them
In today’s digital age, social media users often share photos without considering the implications of privacy. Advanced artificial intelligence technologies can analyze these images and generate hyper-realistic representations of individuals without clothing, using only publicly available photographs. Originally intended for academic and medical purposes, these tools are now exploited for malicious uses, creating unauthorized intimate images and leading to new forms of digital harassment. Experts in cybersecurity highlight the rising risks associated with these technologies, emphasizing that the real concern lies in their accessibility. While some platforms are implementing automated detection systems to curb misuse, legislation is struggling to keep pace with rapid technological development. Experts advise caution when sharing personal images, as what may seem innocent today could lead to significant privacy violations tomorrow. Users are encouraged to think critically about their online presence and the potential for AI to reveal more than intended.
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A Comprehensive Developer’s Guide to AI Protocols
The article “A Developer’s Guide to AI Protocols: MCP, A2A, and ACP” explains three significant protocols in the realm of artificial intelligence. It highlights the Model Control Protocol (MCP), which manages interaction between AI models and applications. The Application-to-Application Protocol (A2A) facilitates communication between different applications using AI, ensuring seamless data exchange. Finally, the Application Control Protocol (ACP) focuses on governing the operations and behavior of AI applications. The article emphasizes the importance of these protocols for improving efficiency and interoperability in AI systems, providing developers with frameworks to navigate the complexities of AI development. By understanding these protocols, developers can better integrate AI into their projects, leading to more robust and intelligent applications. The discussion also touches on the evolving nature of AI protocols, underscoring the necessity for ongoing learning and adaptation in the fast-paced tech landscape.
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How Hearst Developed an AI Voice Assistant for Delish
Hearst’s Delish has launched the “Cooking Coach,” a voice assistant designed to help home cooks follow recipes hands-free. Initiated by Alexandria Redmon, the assistant uses OpenAI’s GPT model and was developed in collaboration with Delish editors over five months. It manages cooking tasks like setting timers, suggesting ingredient swaps, and answering culinary questions, all based on Delish’s extensive recipe database. This innovation comes as lifestyle publishers face challenges from AI-generated content from search engines, which impact website traffic. Delish aims to enhance user engagement by incorporating interactive AI tools. Redmon sees the value in mobile accessibility, while the team plans to refine features based on user interaction. Future developments might include improved search functionalities and personalized cooking assistance. Experts suggest that for publishers to remain competitive, they must focus on delivering unique and user-friendly AI experiences that differentiate them from generic platforms like ChatGPT.
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Midjourney Launches AI Video Generation Model ‘V1’—Discover the Pricing Details!
Midjourney has launched its new AI video generator, “V1,” allowing users to create short videos, incorporating animations, dialogue, and sound from uploaded images or generated visuals. Currently, the tool can produce clips under 30 seconds, accessible via a paid subscription costing $10 per month. Users can create five-second videos, extendable to a maximum of 21 seconds across multiple clips. Midjourney emphasizes real-time imagery, with an ongoing commitment to enhancing the technology, particularly in developing 3D and video models. The company has a history of pushing AI capabilities, as seen with its image generator, which allows for almost realistic creations. However, Midjourney faces legal challenges, including lawsuits from Disney and Universal for alleged copyright infringement involving their intellectual property, particularly animated characters. The platform previously operated through Discord, where users submitted prompts and received outputs, marking its evolution in the AI landscape.
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