Google Assistant’s Gemini has gained a new capability: identifying songs. Previously, only certain devices like Pixel phones had this feature, while users on other Android devices often had to rely on separate apps like Shazam. Recently, Google has integrated a “Search a song” button into the Gemini assistant, which allows it to listen to either a hummed tune or an audio track. When the button is tapped, a pulsating orb indicates that the app is listening, providing a ranked list of song matches based on similarity. Although this functionality mirrors what’s available in Google Search, it enhances the Gemini experience. While direct audio identification proved effective, humming yielded mixed results for some users. Additionally, there’s renewed voice prompt capability for searching songs, expanding the assistant’s functionality. Overall, these updates are aimed at simplifying how users identify songs using the Gemini assistant.
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Exciting Free Gemini Update for Music Lovers on Your Android Phone!
Why I Transitioned Away from AI as a Senior Software Engineer
I’m unable to directly access content from URLs or view videos. However, if you provide a brief summary or key points from the video, I can help you create a 150-word summary based on that information!
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Stack Overflow’s Decline Amid the Surge of AI Tools
Stack Overflow, once a pivotal resource for developers seeking coding solutions, is experiencing a decline in influence, according to recent analysis by RedMonk. This shift reflects broader changes in developer behavior, with alternative platforms and AI-driven tools like GitHub Copilot and ChatGPT emerging as faster, personalized options for knowledge sharing. While these tools offer convenience, they lack the nuanced insights that Stack Overflow provided. Additionally, communities on platforms like Discord and Reddit are reshaping developer collaboration, pushing Stack Overflow to adapt or face obsolescence. Despite its diminishing role, Stack Overflow’s data remains crucial for tracking programming language popularity, revealing that languages like Python and JavaScript still dominate, while engagement for newer languages like Rust is waning. RedMonk emphasizes that Stack Overflow’s future relevance hinges on its ability to integrate AI and enhance real-time collaboration, as it navigates a rapidly evolving technological landscape.
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Discover HN: Screenshock.me – Unleash Your Productivity with Browser AI!
I recently experimented with the Pavlok, a wrist-worn device that delivers shocks for negative reinforcement of behaviors. The unique feature is that users must manually trigger the shock. To enhance its functionality, I recorded my screen and utilized vision AI (via gemini-flash) to detect when I lost focus, automatically activating the Pavlok via its API. This entire setup is browser-based, making it easy for anyone to try. For those without the device, a loud beep option is available in the browser version. Additionally, the project is open-source, allowing others to explore it further: https://github.com/gr-b/screenshockme.
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The Executive’s Guide to AI Skill Development
Technological advancements often outpace organizational adaptation, as evidenced by the delayed adoption of tools like typewriters, fax machines, and spreadsheets. Currently, while 90% of executives believe AI can enhance revenue, only 1% have fully integrated it into workflows. Successful AI adoption hinges on thorough implementation and change management; leaders must invest in both technology and employee skill development. Engaging employees can drive effective AI use, yet success requires that they see tangible benefits and receive adequate training. Leadership plays a pivotal role in fostering a culture of trust and openness. CEOs must prioritize AI transformation, ensuring it aligns with business goals. Effective strategies include tailored training, transparent communication, and creating feedback loops. Throughout this AI adoption journey, leaders need to assess employee needs, involve teams in the process, and prioritize ethical implementation. Ultimately, organizations that place people at the forefront will leverage AI not just for operational efficiency, but for genuine innovation and growth.
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The Economist: Balancing Data, AI Personalization, and Editorial Integrity
The press industry is significantly affected by AI advancements, prompting concerns about job displacement and copyright issues. In an interview, Panagiotis Lazaridis from The Economist discusses how their data team leverages AI for various applications. They employ language models for content tagging, enhancing workflows, and delivering personalized reader experiences. AI is integrated into their platforms, like the Espresso app, to translate content and automate tasks, strictly maintaining user privacy and transparency. While audience data informs content recommendations, editorial integrity remains paramount, as decisions are solely made by journalistic teams. Lazaridis emphasizes responsible data usage, minimizing personally identifiable information (PII), and compliance with regulations. He acknowledges the challenges of AI training on public content and advocates for better IP protection. Looking ahead, The Economist plans to focus on delivering value through AI while remaining cognizant of its impact on journalism, including future applications of intelligent agents to enhance decision-making and user engagement.
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When Marketers Take the Reins: The Rise of Automation in Advertising – Adweek
“When Marketers Run the Machines,” an article from Adweek, discusses the evolving role of marketers in managing automated technologies and machine learning within advertising. As digital marketing becomes increasingly data-driven, the responsibility for harnessing these tools falls more heavily on marketers. The piece emphasizes the importance of blending creativity with technology to optimize campaigns effectively. It highlights that while automation can streamline processes and enhance targeting, human insight remains crucial for interpreting data trends and making strategic decisions. Additionally, the article addresses the need for continuous learning and adaptation among marketers to keep up with rapid technological advancements. Emphasizing a collaboration between creative expertise and machines, the article posits that successful marketing strategies will increasingly depend on this interplay, positioning marketers as essential operators within the technological landscape. Ultimately, the piece advocates for a balanced approach to harnessing both human creativity and machine efficiency in marketing.
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GitHub Repository: mosiara/chromacode
The article discusses a novel approach to creating interactive overlays from static images, co-authored by Edna Nyangau and AI. It addresses the challenges designers face when AI attempts to transform intricate designs into code, often leading to poor recreations. The breakthrough involves dividing images into a structured grid, extracting hex color data, and creating interactive zones that maintain the original aesthetic. This system preserves visual integrity and color harmony while allowing for scalable structures adaptable to various images.
The implementation steps include building a grid mapping tool, creating an interactive overlay system, incorporating smart color constraints, and establishing a task management layer. Real-world applications span architecture, education, product design, gaming, and marketing. The grid-based approach aims to bridge the gap between design and development, emphasizing a visual-first methodology. The project, titled Chromacode™, lays the groundwork for a new UI language where color integrates directly with code, promoting a balance between creativity and functionality.
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Transforming Workplace Frustrations: How AI Can Alleviate Tasks Employees Dread – Inc.com
Many employees express frustration with repetitive and mundane tasks at work, such as data entry, scheduling, and handling basic customer inquiries. These tasks are seen as time-consuming and detract from more engaging and creative responsibilities. Employees believe that integrating artificial intelligence (AI) can significantly alleviate these burdens by automating routine processes, increasing efficiency, and allowing them to focus on higher-value work. AI tools can streamline operations, reduce errors, and enhance productivity, making work more enjoyable and fulfilling. By adopting AI solutions, organizations can not only improve employee satisfaction but also boost overall performance. Embracing technology in the workplace can transform job roles and foster a more innovative environment. Therefore, companies are encouraged to explore AI applications as a way to enhance employee experiences and optimize workflows.
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A Comprehensive Analysis of AI 2027’s Flawed Timeline Models — LessWrong
The article critiques the AI 2027 forecast developed by the AI Futures team, specifically focusing on its modeling methods and assumptions about future AI capabilities. After a thorough review of the timeline forecast, the author expresses significant skepticism about the model’s structure, parameter estimates, and empirical validation. While acknowledging the efforts of the authors, including Eli Lifland, to address critiques, the article argues that both the “superexponential” and “exponential” models rely on problematic assumptions, lack empirical support, and produce unrealistic predictions. The critique details flaws in the methodology, estimations of doubling times, and questions the validity of their chosen parameters. The author emphasizes a broader issue of inherent uncertainty in AI projections and advocates for a more cautious approach, suggesting that reliance on forecasts like AI 2027 could be dangerous. The article concludes by stating that the complexities involved make accurate predictions extremely challenging, urging for models that can accommodate this uncertainty.
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