NLWeb is an innovative AI assistant developed by RV Guha, a tech leader at Microsoft renowned for creating web standards like RSS, RDF, and Schema.org. NLWeb integrates these frameworks with website data and large language models (LLMs) to enhance digital interaction. RSS, or Really Simple Syndication, enables the sharing of website updates, while RDF (Resource Description Framework) serves as a standardized method for exchanging metadata across the web. Additionally, Schema.org is a community-driven initiative that supports the creation and maintenance of structured data schemas for various digital environments, including web pages and emails. By leveraging these established protocols, NLWeb aims to provide intelligent assistance, facilitating better user experiences on the internet.
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“Microsoft’s NLWeb: Transforming Websites into AI-Powered Applications” – Computerworld
AI Adoption Hits a Snag: Rising Inferencing Costs Challenge Cloud Users • The Register
Broader AI adoption in enterprises faces challenges due to concerns over forecasting inferencing costs, leading to fears of excessive cloud bills, according to Canalys. Global spending on infrastructure and platform-as-a-service reached $90.9 billion in Q1, marking a 21% year-on-year increase as businesses migrate workloads to the cloud and explore generative AI. However, uncertainty about recurring inferencing costs complicates AI commercialization. Unlike one-time training expenses, inferencing creates ongoing operational costs that businesses must manage. Many AI services follow volatile usage-based pricing, prompting enterprises to limit usage or deployment strategies. Recent cases, such as 37signals incurring over $3 million in annual cloud costs, underscore budgetary concerns. As alternatives to public cloud models gain traction, Canalys notes that AWS, Azure, and Google Cloud still dominate the market, though Microsoft and Google are growing faster due to AWS’s slowing growth rate.
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Introducing an AI Tool: Instantly Generate Your Backend in Just 60 Seconds—No Coding Required!
I can’t access external URLs directly. However, if you provide key details or excerpts from the article, I’d be happy to help you summarize the content!
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Google Begins Testing Gemini-Enhanced ‘Audio Overviews’ for Search Results
Google is testing a new feature called ‘Audio Overviews’ that provides AI-generated audio summaries for search results, currently available in English and limited to US users through Search Labs. This feature uses Google’s Gemini AI model to convert text-based information into brief audio snippets, typically lasting around four minutes. Users can generate these overviews by clicking a button labeled ‘Generate Audio Overview,’ which creates a summary in about 40 seconds, accompanied by links to the original sources. The audio is delivered in a conversational format between two AI voices, making it more engaging than standard robotic assistants. Users of the feature can control playback speed and rate the summaries to improve quality. Despite its innovative approach, Google faces challenges related to AI accuracy, with past issues causing suspensions of similar features. This initiative is part of Google’s broader push to enhance the search experience through interactive, multimedia content.
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Support Charity: Pay What You Wish for O’Reilly’s 2025 Edition on Machine Learning, AI, and Bots!
Since its inception in 2010, the Humble community has raised over $268 million for charity, significantly impacting various global causes. This impressive contribution reflects the community’s commitment to philanthropy. The funds have been utilized to support diverse initiatives, enhancing the lives of many around the world. Humble Bundle, a brand of IGN Entertainment, Inc., emphasizes its dedication to charitable giving through its platform, which combines gaming, literature, and other media while encouraging consumers to support important causes. The organization also holds trademarks with Ziff Davis LLC, ensuring its brand integrity and legal protections. Overall, Humble Bundle’s efforts showcase an innovative blend of entertainment and altruism, fostering a culture of generosity within gaming and beyond.
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Enhancing Cognitive Engineering Through Test Time Scaling
In the paper titled “Generative AI Act II: Test Time Scaling Drives Cognition Engineering,” authored by Shijie Xia et al., the focus is on the advancements in generative AI and its implications for cognition engineering. The authors discuss how scaling test time effectively enhances the performance and capabilities of generative models. This work contributes to the broader understanding of human-like cognitive processes in AI systems. By exploring novel methodologies and frameworks, the authors aim to bridge the gap between theoretical research and practical applications, highlighting the importance of robust testing in AI development. The research is presented in the context of ongoing developments in cognitive science and machine learning, offering insights into how generative AI can evolve. The paper is accessible on arXiv, and serves as a significant contribution to the fields of artificial intelligence and computational linguistics.
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Why Generative AI Coding Tools and Agents Fall Short for Me
In his blog post, Miguel Grinberg discusses his frustrations with generative AI coding tools and agents, explaining why they haven’t met his expectations. He emphasizes that while these tools can automate some tasks, they often lack the understanding necessary for complex coding situations. Grinberg highlights issues such as generated code being incorrect or inefficient, the tools failing to grasp context, and difficulties in debugging AI-generated solutions. He argues that the tools can be unintuitive, requiring more time to fix their mistakes than to code manually. Moreover, he believes that the dependency on AI may hinder learning opportunities for developers, as they might rely too heavily on AI instead of mastering the craft themselves. Overall, Grinberg expresses skepticism about the practicality of these tools in real-world coding scenarios, advocating for traditional coding methods over AI-generated solutions.
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Show HN: Introducing Hugo – Your AI Coding Assistant
Hugo distinguishes itself from typical AI coding tools by approaching coding with a thoughtful and inquisitive mindset. Unlike conventional tools that merely execute commands, Hugo engages with users by asking clarifying questions when requirements are vague, considering the overall project context, and maintaining continuity between sessions—eliminating the need for repetitive explanations. It utilizes a layered memory strategy, balancing short-term focus on individual tasks with a compressed long-term memory for overarching project continuity. Additionally, Hugo plans, observes, and reflects on solutions prior to coding, embodying the qualities of a curious and collaborative engineer. Built by a solo developer passionate about creating genuinely cooperative AI, Hugo aims to improve the coding process. An early access waitlist is available, inviting user feedback to further refine the tool.
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Side-Splitting AI-Generated Bigfoot Vlogs Showcase the Creative Power of Artificial Intelligence
With advancements in AI video technology, particularly with Google’s Veo 3, creating engaging content has become easier than ever. Whereas making a decent Bigfoot video once required crafting a suit and filming on-site, AI now allows for the creation of imaginative visuals and audio, including character voices. This has led to the rise of amusing Bigfoot vlogs, as creators experiment with the medium. Though generating these videos can be costly, the availability of tools like Veo 3 enables users to produce multiple videos daily and edit them seamlessly. While critics argue that AI videos lack genuine humor or creativity, some creators are finding ways to make them entertaining by leveraging clever editing and context. Notably, the Bigfoot vlog phenomenon showcases distinct character personalities, resonating with audiences. Although the influx of AI-generated content can lead to subpar output, successful creators are finding ways to make viewers laugh, marking a promising evolution in digital entertainment.
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Protecting Your AI Agents: Join Our Webinar on Securing Secret Accounts
AI is reshaping industries, but it also introduces significant security risks, particularly through non-human identities (NHIs) like API keys and OAuth tokens. These identities are powerful yet often unsecured, making them vulnerable to exploitation by attackers who can move laterally within cloud infrastructure, deploy malware, and exfiltrate data without detection. Traditional identity security measures focus on protecting human users, but as AI tools proliferate, it’s crucial to adapt security strategies to account for these invisible entities. A forthcoming webinar, hosted by Jonathan Sander from Astrix Security, will address this issue, highlighting the unseen risks associated with NHIs and the inadequacies of conventional IAM tools. Attendees will learn about real-world attacks, identity sprawl caused by AI, and practical solutions for monitoring and securing these identities. This session is vital for security leaders and AI teams to mitigate potential threats and enhance organizational security.
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