News from the AI & ML world
DeeperML - #multiple
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@x.com
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IEEE Spectrum
The integration of Artificial Intelligence (AI) into coding practices is rapidly transforming software development, with engineers increasingly leveraging AI to generate code based on intuitive "vibes." Inspired by the approach of Andrej Karpathy, developers like Naik and Touleyrou are using AI to accelerate their projects, creating applications and prototypes with minimal prior programming knowledge. This emerging trend, known as "vibe coding," streamlines the development process and democratizes access to software creation.
Open-source AI is playing a crucial role in these advancements, particularly among younger developers who are quick to embrace new technologies. A recent Stack Overflow survey of over 1,000 developers and technologists reveals a strong preference for open-source AI, driven by a belief in transparency and community collaboration. While experienced developers recognize the benefits of open-source due to their existing knowledge, younger developers are leading the way in experimenting with these emerging technologies, fostering trust and accelerating the adoption of open-source AI tools. To further enhance the capabilities and reliability of AI models, particularly in complex reasoning tasks, Microsoft researchers have introduced inference-time scaling techniques. In addition, Amazon Bedrock Evaluations now offers enhanced capabilities to evaluate Retrieval Augmented Generation (RAG) systems and models, providing developers with tools to assess the performance of their AI applications. The introduction of "bring your own inference responses" allows for the evaluation of RAG systems and models regardless of their deployment environment, while new citation metrics offer deeper insights into the accuracy and relevance of retrieved information. Recommended read:
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@slashnext.com
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A new AI platform called Xanthorox AI has emerged in the cybercrime landscape, advertised as a full-spectrum hacking assistant and is circulating within cybercrime communities on darknet forums and encrypted channels. First spotted in late Q1 2025, this tool is marketed as the "killer of WormGPT and all EvilGPT variants," suggesting its creators intend to supplant earlier malicious AI models. Unlike previous malicious AI tools, Xanthorox AI boasts an independent, multi-model framework, operating on private servers and avoiding reliance on public cloud infrastructure or APIs, making it more difficult to trace and shut down.
Xanthorox AI provides a modular GenAI platform for offensive cyberattacks, offering a one-stop shop for developing a range of cybercriminal operations. This darknet-exclusive tool uses five custom models to launch advanced, autonomous cyberattacks, marking a new era in AI-driven threats. The toolkit includes Xanthorox Coder for automating code creation, script development, malware generation, and vulnerability exploitation. Xanthorox Vision adds visual intelligence by analyzing uploaded images or screenshots to extract data, while Reasoner Advanced mimics human logic to generate convincing social engineering outputs. Furthermore, Xanthorox AI supports voice-based interaction through real-time calls and asynchronous messaging, enabling hands-free command and control. The platform emphasizes data containment and operates offline, ensuring users can avoid third-party AI telemetry risks. SlashNext refers to it as “the next evolution of black-hat AI” because Xanthorox is not based on existing AI platforms like GPT. Instead, it uses five separate AI models, and everything runs on private servers controlled by the creators, meaning it has few ways for defenders to track or shut it down. Recommended read:
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@upwarddynamism.com
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The rise of AI agents is rapidly transforming various sectors, from online retail to enterprise applications. These intelligent software entities are designed to operate autonomously, achieving specific goals by formulating strategies, executing them, and adapting to changing circumstances. Companies are investing heavily in AI agents to automate tasks, streamline workflows, and unlock productivity gains, leading to a significant shift in how businesses operate and engage with customers. Experts predict that AI agents will soon augment a vast number of jobs, automating tasks and enhancing decision-making processes across industries.
AI agents are already making a significant impact on online shopping. Retailers are tapping into AI agents to deepen customer engagement, enhance offerings, and maintain a competitive edge. By leveraging customer data and generative AI tools, these agents provide personalized recommendations, enriching product catalogs with detailed information and offering omnichannel support. AI agents can act as virtual assistants, providing tailored product recommendations and boosting conversion rates, ultimately enhancing customer satisfaction. In the enterprise sector, AI agents are evolving from simple assistants to independent entities capable of perceiving, evaluating, and acting upon data. IDC estimates that over 50% of the enterprise application market is already AI assistant or AI advisor-enhanced, with 20% further supplemented by complete AI agents. Over the next few years, advancements in generative and agentic AI will push enterprise applications towards agent-led models, where agents replace entire functional areas. Eventually, companies may enlist entire fleets of AI agents to manage supply chains, customer relations, and other critical functions, signaling a major shift in the way businesses utilize software. Recommended read:
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Maximilian Schreiner@THE DECODER
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OpenAI has announced its support for Anthropic’s Model Context Protocol (MCP), an open-source standard. The move is designed to streamline the integration between AI assistants and various data systems. MCP is an open standard that facilitates connections between AI models and external repositories and business tools, eliminating the need for custom integrations.
The integration is already available in OpenAI's Agents SDK, with support coming soon to the ChatGPT desktop app and Responses API. The aim is to create a unified framework for AI applications to access and utilize external data sources effectively. This collaboration marks a pivotal step towards enhancing the relevance and accuracy of AI-generated responses by enabling real-time data retrieval and interaction. Anthropic’s Chief Product Officer Mike Krieger welcomed the development, noting MCP has become “a thriving open standard with thousands of integrations and growing.” Since Anthropic released MCP as open source, multiple companies have adopted the standard for their platforms. CEO Sam Altman confirmed on X that OpenAI will integrate MCP support into its Agents SDK immediately, with the ChatGPT desktop app and Responses API following soon. Recommended read:
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kevinokemwa@outlook.com (Kevin@windowscentral.com
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OpenAI and MIT Media Lab collaborated on studies revealing potential negative impacts of frequent ChatGPT use. The research indicates that power users, who engage with the chatbot most often, may experience increased loneliness, reduced socialization, and emotional dependence. One study analyzed nearly 40 million ChatGPT interactions, while another was a controlled experiment with nearly 1,000 participants tracked for a month.
The studies suggest that while ChatGPT can be helpful for various tasks, excessive reliance on the AI tool could lead to unhealthy habits, such as skipping real conversations and a loss of confidence in decision-making. Researchers found that some users develop an unhealthy emotional dependency, even befriending ChatGPT and sharing personal information with the false belief that the tool "cares." These findings raise concerns about the long-term impact of AI companions on mental health and social well-being, drawing parallels with the issues caused by excessive social media use. Recommended read:
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george.fitzmaurice@futurenet.com (George@Latest from ITPro
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www.itpro.com
, Databricks
The AI agent landscape is rapidly evolving, with major tech companies pushing 'do-it-yourself' agent platforms to drive AI adoption. Firms like Oracle, OpenAI, AWS, Salesforce, and Workday are releasing platforms that allow users to build custom agents, rather than offering pre-built solutions. This emphasis on customization stems from the understanding that AI agent use cases are often less deterministic and require tailoring to specific business contexts. Gartner analyst Pieter J. den Hamer highlights the need for customization, noting that end-users gain the most from agentic tools when they have full control over their functionality.
Dataiku offers a platform to build AI agents that optimize workflows, enhance productivity, and automate complex processes. They allow users to add tools that extend agent capabilities, allowing integration with external systems. China's Manus AI is emerging as a potential leader, moving beyond chatbots to autonomous agents capable of executing real-world tasks with minimal human oversight. Other offerings include Databricks Apps, which can be combined with React and Mosaic AI Agent Framework, to create enterprise chat solutions. Recommended read:
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Mandvi@Cyber Security News
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Cyber Security News
, gbhackers.com
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AI has become a powerful weapon for cybercriminals, enabling them to launch attacks with unprecedented speed and precision. A recent CrowdStrike report highlights the increasing sophistication and frequency of AI-driven cyberattacks. Cybercriminals are leveraging AI to automate attacks, allowing them to be launched with minimal human intervention, which leads to an increase of network penetrations and data theft.
AI's ability to analyze large datasets and identify patterns in user behavior allows cybercriminals to develop more effective methods of stealing credentials and committing fraud. For example, AI can predict common password patterns, making traditional authentication methods vulnerable. AI-powered tools can generate highly personalized phishing emails, making them almost indistinguishable from legitimate communications and greatly increasing the profitability of cyberattacks. Recommended read:
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@www.marktechpost.com
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Windows Copilot News
, www.marktechpost.com
A new wave of AI-powered browser-use agents is emerging, with companies like OpenAI, Convergence, Google, Anthropic, and Microsoft developing solutions. These agents aim to transform how enterprises interact with the web by autonomously navigating websites, retrieving information, and completing tasks. For example, OpenAI's Operator focuses on consumer-friendly web automation, while Convergence's Proxy offers free limited use and a paid unlimited access option.
However, early testing reveals significant gaps between promise and performance. While consumer-focused applications like ordering pizza or booking game tickets have garnered attention, the primary developer and enterprise use cases are still being determined. Experts suggest that these agents may find their niche in time-consuming web-based tasks like price comparisons and hotel booking or be used in combination with other tools like Deep Research, where companies can then do even more sophisticated research plus execution of tasks around the web. AI agents are autonomous software entities that perceive their surroundings, process data, and take action to achieve specified goals. They differ from traditional software by employing machine learning and natural language processing for decision-making, allowing them to evolve over time. Key characteristics include autonomy, adaptability, interactivity, and context awareness. The evolution of AI agents represents a shift from rule-based systems to systems that learn and adapt. Recommended read:
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@learn.aisingapore.org
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aithority.com
, AWS Machine Learning Blog
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Ikigai Labs has launched a new AI-powered Demand Forecasting and Planning solution aimed at revolutionizing how businesses predict demand. This cutting-edge technology utilizes patented Large Graphical Model (LGM) technology to provide more accurate predictions, even for new or unpredictable products. The solution is designed to help businesses in retail, manufacturing, and consumer goods reduce costs, improve forecasting accuracy, and make resilient decisions in volatile markets. Ikigai’s offering is specifically built to address the complexities of modern supply chains and allows companies to move beyond traditional, rigid forecasts, by simulating and planning for a range of real-world outcomes.
Amazon Web Services (AWS) is also addressing forecasting challenges, particularly in the retail and consumer packaged goods (CPG) sectors, through Amazon SageMaker Canvas. This no-code machine learning service enables business analysts and data professionals to build accurate forecasting models using a visual, point-and-click interface. SageMaker Canvas employs AutoML techniques, training several algorithms on historical time-series data and combines them to create an optimized forecasting model. This provides businesses with enhanced capabilities to anticipate demand shifts, manage inventory effectively, and make data-driven decisions. Recommended read:
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