News from the AI & ML world
DeeperML - #automation
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Tris Warkentin@The Official Google Blog
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Google AI has released Gemma 3, a new family of open-source AI models designed for efficient and on-device AI applications. Gemma 3 models are built with technology similar to Gemini 2.0, intended to run efficiently on a single GPU or TPU. The models are available in various sizes: 1B, 4B, 12B, and 27B parameters, with options for both pre-trained and instruction-tuned variants, allowing users to select the model that best fits their hardware and specific application needs.
Gemma 3 offers practical advantages including efficiency and portability. For example, the 27B version has demonstrated robust performance in evaluations while still being capable of running on a single GPU. The 4B, 12B, and 27B models are capable of processing both text and images, and supports more than 140 languages. The models have a context window of 128,000 tokens, making them well suited for tasks that require processing large amounts of information. Google has built safety protocols into Gemma 3, including a safety checker for images called ShieldGemma 2. Recommended read:
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Vasu Jakkal@Microsoft Security Blog
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Microsoft has unveiled a significant expansion of its Security Copilot platform, integrating AI agents designed to automate security operations tasks and alleviate the workload on cybersecurity professionals. This move aims to address the increasing volume and complexity of cyberattacks, which are overwhelming security teams that rely on manual processes. The AI-powered agents will handle routine tasks, freeing up IT and security staff to tackle more complex issues and proactive security measures. Microsoft detected over 30 billion phishing emails targeting customers between January and December 2024 highlighting the urgent need for automated solutions.
The expansion includes eleven AI agents, six developed by Microsoft and five by security partners, set for preview in April 2025. Microsoft's agents include the Phishing Triage Agent in Microsoft Defender, Alert Triage Agents in Microsoft Purview, Conditional Access Optimization Agent in Microsoft Entra, Vulnerability Remediation Agent in Microsoft Intune, and Threat Intelligence Briefing Agent in Security Copilot. These agents are purpose-built for security, designed to learn from feedback, adapt to workflows, and operate securely within Microsoft’s Zero Trust framework, ensuring that security teams retain full control over their actions and responses. Recommended read:
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@Techmeme
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OpenAI has unveiled its first AI agent, named Operator, designed to autonomously handle tasks on the web. This innovative tool, currently in a research preview for ChatGPT Pro subscribers in the US, is powered by the Computer-Using Agent (CUA) model. CUA leverages GPT-4o's visual capabilities coupled with advanced reasoning to interact with websites like a human. Operator can navigate pages, input text, click buttons, and scroll to accomplish a variety of tasks, including making dinner reservations, filling out online forms, and ordering groceries.
Operator's functionality is not just limited to basic web interactions, it can also learn from its mistakes, "self-correcting" and giving users back control when needed. The AI agent operates through a dedicated web browser and keeps users updated on its actions through explanations. OpenAI plans to integrate Operator into all of its ChatGPT clients after this initial release, and hopes to make the CUA available for developers through its API. While still in early stages, Operator represents a significant stride towards more user-friendly and practical AI applications. Recommended read:
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Ken Yeung@Ken Yeung
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Microsoft is enhancing its Copilot Studio platform with new 'deep reasoning' capabilities, allowing AI agents to solve complex problems more effectively. This upgrade also includes 'agent flows' which blend AI's flexibility with structured business automation. The new Researcher and Analyst agents for Microsoft 365 Copilot represent a significant step forward in AI agent evolution, enabling them to handle sophisticated tasks requiring detailed analysis and methodical thinking.
Microsoft's Security Copilot service is also getting a boost with a set of AI agents designed to automate repetitive tasks, freeing up security professionals to focus on more critical threats. These AI agents are designed to assist with critical tasks such as phishing, data security, and identity management. These agents showcase the breadth of what can be created when combining enterprise business data, access to advanced reasoning models, and structured workflows. Recommended read:
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Thomas Claburn@The Register
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Opera has introduced "Browser Operator," a new native AI agent integrated directly into its browser. This AI agent is designed to automate repetitive tasks, enhancing user convenience by performing actions such as purchasing products, completing online forms, and gathering web content. Unlike separate tools like Google AI assistant or ChatGPT, Browser Operator is an extension of the browser itself, processing tasks locally to empower users and streamline their online activities.
Opera's AI agent utilizes natural language processing powered by Opera’s AI Composer Engine to interpret written instructions and execute corresponding tasks within the browser. It allows users to delegate tasks like buying socks, booking flights, or searching the web. Opera emphasized the privacy-focused architecture, claiming that the AI agent is faster and more secure than cloud-based alternatives because it does not take screenshots or capture videos of your screen. The tool is the latest in a long line of AI developments at the Norwegian company, which launched a fully AI-enabled browser in 2023. Recommended read:
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stclarke@Source
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Microsoft is enhancing its Copilot capabilities by introducing new sales agents designed to streamline the sales process. These agents, accessible through Microsoft 365 Copilot and Microsoft 365 Copilot Chat, aim to help sales teams close deals faster by providing assistance with lead qualification, meeting setup, and customer outreach. The Sales Agent can autonomously work around the clock to grow the sales pipeline, even completing sales for low-impact leads by leveraging CRM data, company information, and web resources.
Estée Lauder is using the Sales Agent to reimagine trend forecasting and consumer marketing. Estée Lauder is also building a generative AI ecosystem with Copilot Studio, Azure OpenAI Service and Azure AI Search to move product to market faster. Vodafone projects to double or triple the number of requests for proposals its sales team can respond to each week. Salesforce has also launched Agentforce 2dx, enabling AI agents to work proactively across enterprise systems without human prompting. This update allows companies to embed agentic AI into workflows, monitor data changes, and initiate processes autonomously. IT leaders at TDX 2025 discussed the impact of AI on their businesses, with some experiencing significant revenue increases with AI implementation. Recommended read:
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Alex Woodie@BigDATAwire
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AI agents are poised to revolutionize day-to-day life across various industries. Enterprises are increasingly adopting these agents to automate tasks, streamline operations, and enhance customer experiences. A recent Salesforce report highlights that 75% of retailers consider AI agents essential for staying competitive, underscoring the growing importance of these systems. The trend signifies a move towards more autonomous AI, capable of independent action to achieve specific goals, impacting sectors such as retail, logistics, and security.
Enterprising AI's agentic capabilities are also transforming how companies are handling fraud and maximizing returns on investment. AI tools are no longer limited to data scientists as enterprise leaders are enabling employees to use AI in new innovative ways. Browser Use, an AI startup, has recently secured $17 million in funding to further enhance the web's accessibility for AI agents, streamlining their interactions with online interfaces for faster and more precise browsing. Recommended read:
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@medium.com
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AI agents are rapidly transforming how businesses operate, offering potential for significant profit and efficiency gains. These intelligent computer programs can independently perform tasks such as customer service and financial analysis. Businesses can leverage various AI agents, including reactive, proactive, and collaborative agents, to address specific needs in areas like e-commerce, healthcare, and online shopping. Success hinges on identifying lucrative niches where AI agents can provide measurable value, such as automating repetitive processes, streamlining patient management, or optimizing pricing strategies.
By choosing the right AI tools and platforms such as OpenAI, TensorFlow, PyTorch and Rasa, businesses can tailor AI agents to maximize return on investment. The integration of Large Language Models (LLMs) and Large Multimodal Models (LMMs) further enhances these systems, enabling them to handle diverse tasks across various use cases. However, the focus now is shifting toward enterprise-grade capabilities to facilitate real-world production deployment. Enterprises are recognizing that moving beyond proof-of-concept stages is critical for fully realizing the potential of AI agents and ensuring their widespread adoption. Recommended read:
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Aminu Abdullahi@eWEEK
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eWEEK
, www.techradar.com
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Yum! Brands, the parent company of fast-food giants Taco Bell, KFC, and Pizza Hut, is partnering with Nvidia to integrate AI-powered order-taking systems at 500 locations by the end of 2025. The aim is to enhance voice recording, improve drive-thru efficiency, and streamline overall restaurant operations. This initiative marks a significant step in the company’s push to digitize its operations and stay ahead in the competitive quick-service restaurant industry.
These AI voice agents, built using Nvidia’s AI tools, can understand natural speech, process complex orders, and even suggest add-ons like extra fries or a dessert. Yum! is also using Nvidia’s computer vision tech to help restaurants analyze drive-thru traffic and improve speed during peak hours, potentially reducing wait times and improving staffing decisions. The technology could also determine whether the food being served matches what was ordered by analyzing images from existing CCTV cameras. Recommended read:
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@oodaloop.com
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OODAloop
, TechCrunch
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Symbotic, a robotics firm, has announced it is acquiring Walmart’s automation division for an initial payment of $200 million, with the potential for an additional $350 million based on the deal's performance. This acquisition solidifies Symbotic's role as a key technology supplier to Walmart and significantly expands its presence in the automation market. The agreement sees Walmart purchasing automation systems from Symbotic, which avoids the prospect of Walmart developing rival automation solutions in-house. The partnership is not just an aquisition, it is expected to provide Symbotic with immediate revenue and strengthens an already established relationship with the retail giant.
The deal will see Symbotic take control of automating Walmart’s pickup and delivery centers, with Walmart funding a development program worth $520 million to support the technology. This includes the initial $200m, with the remainder in future payments. Walmart aims to improve customer experience through quicker, more efficient service with the implementation of Symbotic's automated systems. This strategic move builds on a relationship that began in 2017 and positions Symbotic to enhance Walmart's in-store Accelerated Pickup and Delivery capabilities. The transaction is projected to close in the second quarter of 2025. Recommended read:
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@blogs.microsoft.com
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IEEE Spectrum
, IEEE Spectrum
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Anthropic, Google DeepMind, and OpenAI are at the forefront of developing AI agents with the ability to interact with computers in a human-like manner. These agents are designed to perform a range of tasks, including web searches, form completion, and button clicks, enabling them to order groceries, request rides, or book flights. The models employ chain-of-thought reasoning to decompose complex instructions into manageable steps, requesting user input when necessary and seeking confirmation before executing final actions.
To address safety concerns such as prompt injection attacks, developers are implementing restrictions, such as preventing the agents from logging into websites or entering payment information. Anthropic was the first to unveil this functionality in October, with its Claude chatbot now capable of "using computers the way humans do." Google DeepMind is developing Mariner, built on top of Google’s Gemini 2 language model and OpenAI launched its computer-use agent (CUA), called Operator. Recommended read:
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Gurhan Kok,@AIwire
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Practical AI
, AIwire
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AI is rapidly transforming retail, healthcare, and cybersecurity. In retail, AI-powered demand forecasting combines sales data with external factors to generate precise predictions, reducing stockouts and minimizing overstocking. AI automates inventory management tasks, anticipates demand changes, and optimizes inventory transfers between locations. These advancements reshape retail operations, enabling customized experiences and boosting productivity.
In healthcare, AI is assisting doctors with data analysis and offering preventative care. Wearable devices track daily activities, allowing predictive analytics to identify behaviors that may threaten health in the future. This enables personalized interventions and helps individuals understand the impact of their lifestyle choices on their well-being, ultimately improving quality of life and potentially extending lifespan. In cybersecurity, AI is changing the cyber threat landscape, with experts discussing the AI standoff between cyber threat actors and cyber defenders. The Digital Trust & Safety Partnership (DTSP) has unveiled new best practices for incorporating AI and automation into trust and safety operations, aiming to address content and conduct-related abuse on digital platforms. Recommended read:
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@pub.towardsai.net
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Recent developments in AI agent frameworks are paving the way for more efficient and scalable applications. The Jido framework, built in Elixir, is designed to run thousands of agents using minimal resources. Each agent requires only 25KB of memory at rest, enabling large-scale deployment without heavy infrastructure. This capability could significantly reduce the cost and complexity of running multiple parallel agents, a common challenge in current agent frameworks. Jido also allows agents to dynamically manage their own workflows and sub-agents utilizing Elixir's concurrency features and OTP architecture.
The core of Jido centers around four key concepts: Actions, Workflows, Agents, and Sensors. Actions represent small, reusable tasks, while workflows chain these actions together to achieve broader goals. Agents are stateful entities that can plan and execute these workflows. The focus is on creating a system where the agents can, to a degree, manage themselves without constant human intervention. Jido provides a practical approach to building autonomous, distributed systems through functional programming principles, and dynamic error handling. Recommended read:
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