News from the AI & ML world
DeeperML - #aiplatform
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Coen van@Techzine Global
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ServiceNow is making significant strides in the realm of agentic AI, highlighted at their Knowledge 2025 conference. A key announcement is a partnership with Nvidia to develop Apriel Nemotron 15B, an open-source reasoning model. This model is designed to be faster and more cost-effective than larger language models, while still providing enterprise-grade intelligence. The ambition is to give businesses a single, coherent way to get all their different AI tools and intelligent agents working together, right across the company.
NVIDIA NeMo, NVIDIA Llama Nemotron open datasets and ServiceNow domain data trained on NVIDIA DGX Cloud was used to create this new model. Apriel Nemotron 15B is engineered for reasoning. It draws inferences, weighs goals, and navigates rules in real-time. This makes it well-suited for powering AI agents that can support thousands of concurrent enterprise workflows. Furthermore, ServiceNow and NVIDIA are introducing a new data flywheel architecture, integrating ServiceNow’s Workflow Data Fabric with NVIDIA NeMo microservices, enabling continuous learning and improvement for the AI model. In addition to the Nvidia partnership, ServiceNow is launching Agentforce for HR Service. This initiative brings AI agents and Service Cloud capabilities to human resources, empowering employees to get personalized answers to HR-related questions and take action on their own, freeing overwhelmed HR teams to focus on more strategic work. ServiceNow believes AI innovation is the answer here, a way to fundamentally change how businesses run – making them more resilient, more efficient, and helping them get a handle on costs, all while chipping away at that mountain of tech debt and operational guesswork. Recommended read:
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Coen van@Techzine Global
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ServiceNow has announced the launch of AI Control Tower, a centralized control center designed to manage, secure, and optimize AI agents, models, and workflows across an organization. Unveiled at Knowledge 2025 in Las Vegas, this platform provides a holistic view of the entire AI ecosystem, enabling enterprises to monitor and manage both ServiceNow and third-party AI agents from a single location. The AI Control Tower aims to address the growing complexity of managing AI deployments, giving users a central point to see all AI systems, their deployment status, and ensuring governance and understanding of their activities.
The AI Control Tower offers key benefits such as enterprise-wide AI visibility, built-in compliance and AI governance, end-to-end lifecycle management of agentic processes, real-time reporting, and improved alignment. It is designed to help AI systems administrators and other stakeholders monitor and manage every AI agent, model, or workflow within their system, providing real-time reporting for different metrics and embedded compliance and AI governance. The platform helps users understand the different systems by provider and type, improving risk and compliance management. In addition to the AI Control Tower, ServiceNow introduced AI Agent Fabric, facilitating communication between AI agents and partner integrations. ServiceNow has also partnered with NVIDIA to engineer an open-source model, Apriel Nemotron 15B, designed to drive advancements in enterprise large language models (LLMs) and power AI agents that support various enterprise workflows. The Apriel Nemotron 15B, developed using NVIDIA NeMo and ServiceNow domain-specific data, is engineered for reasoning, drawing inferences, weighing goals, and navigating rules in real time, making it efficient and scalable for concurrent enterprise workflows. Recommended read:
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@developer.nvidia.com
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NVIDIA Newsroom
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NVIDIA continues to advance the capabilities of AI across various sectors with its integrated hardware and software platforms. The NVIDIA Isaac GR00T N1 represents a significant leap in robotics, offering a hardware-software combination designed to provide humanoid robots with advanced cognitive abilities. This platform aims to bridge the gap between large language models and real-world dexterity, enabling robots to learn from single demonstrations and adapt to different tasks in diverse environments such as homes, factories, and disaster zones. Powered by the Jetson Thor chip and built on the Isaac robotics platform, GR00T N1 focuses on adaptability through foundation model reinforcement learning, allowing robots to reason and generalize insights, rather than simply reacting to pre-programmed instructions.
Agentic AI is transforming cybersecurity by introducing both new opportunities and challenges. These AI agents can autonomously interact with tools, environments, and sensitive data, enhancing threat detection, response, and overall security. Cybersecurity teams, often overwhelmed by talent shortages and high alert volumes, can leverage agentic AI to bolster their defenses. These systems can perceive, reason, and act autonomously to solve complex problems, serving as intelligent collaborators for cyber experts. Organizations such as Deloitte are utilizing NVIDIA AI Blueprints, NIM, and Morpheus to accelerate software patching and vulnerability management, while CrowdStrike and Trend Micro are leveraging NVIDIA AI software to improve security alert triaging and reduce alert fatigue. NVIDIA NIM Operator 2.0 enhances AI deployment by supporting NVIDIA NeMo microservices, streamlining the management of inference pipelines for MLOps and LLMOps engineers. This new release simplifies the deployment, auto-scaling, and upgrading of NIM on Kubernetes clusters, building upon the capabilities of the initial NIM Operator. The NIM Operator 2.0 introduces the ability to deploy and manage the lifecycle of NVIDIA NeMo microservices, including NeMo Customizer for fine-tuning LLMs, NeMo Evaluator for comprehensive evaluation of LLMs, and NeMo Guardrails for adding safety checks and content moderation to LLM endpoints. These enhancements provide efficient model caching and boost overall operational efficiency for deploying and managing NIM on various infrastructures, as highlighted by Cisco Systems. Recommended read:
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staff@insideAI News
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Dataiku, an AI platform company, has launched AI Agents with Dataiku, offering capabilities to create and control AI agents at scale. This new development aims to deliver a novel class of AI applications powered by analytics, predictive models, and agents. The company emphasizes that these agents can be grounded in trusted data, embedded in operational workflows, connected to all AI inputs, and governed with the same rigor as any business-critical asset, ensuring enterprise-level control and reliability. Dataiku highlights that over 20% of their customers are already leveraging Dataiku to integrate GenAI into their business and data workflows, showcasing the platform's growing adoption.
Dataiku's approach seeks to address the challenges of uncontrolled agent proliferation within organizations, which can lead to inconsistent quality, lack of IT oversight, and ungoverned deployments across various teams. To counter this, Dataiku provides options for central agent creation, including a visual, no-code environment for business users and a full-code environment for developers. This dual approach ensures accessibility for users with varying technical skills while maintaining key capabilities to ensure the creation, connection, and control of AI agents at scale with confidence. The goal is to ensure that companies can move from exploration to operationalization of agents with centralized creation, optimized performance, and orchestration through existing IT assets. According to Florian Douetteau, co-founder and CEO of Dataiku, the time has come for companies to take control of AI's raw power. He believes that companies are on the cusp of repurposing existing enterprise applications built on systems like Snowflake, Workday, and SAP, by adding a new layer of AI-native applications. Dataiku's Universal AI Platform aims to meet the emerging market need by centralizing agent creation for governance, continuously optimizing performance, and fully orchestrating agents through existing IT assets. The company is focused on building the required capabilities within its platform to facilitate this transition. Recommended read:
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Rhys Fisher@CX Today
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MoneyCheck
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Salesforce has announced significant progress with its Agentforce AI platform, reporting the closure of 5,000 deals since October. CEO Marc Benioff highlighted this milestone during the company’s Q4 2025 earnings call, describing the growth as unprecedented. Among these deals, 3,000 are paid, with companies like Singapore Air, Equinox, and Jacuzzi adopting the platform.
Agentforce is proving to be a valuable asset for Salesforce clients. OpenTable has managed 73% of restaurant web queries with Agentforce, and Goodyear is aiming to reduce repair times through vehicle insights and automated appointment scheduling. Pfizer is deploying Agentforce to enhance customer-facing operations, supporting 20,000 employees. Internally, Salesforce has seen 84% of 380,000 service requests autonomously resolved by Agentforce. Despite this growth, the company projects only a modest revenue contribution from Agentforce in 2025, anticipating a more substantial impact in 2026. Recommended read:
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Fiona Jackson@eWEEK
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Nvidia has launched Signs, a new AI-powered platform designed to teach American Sign Language (ASL). Developed in partnership with the American Society for Deaf Children and creative agency Hello Monday, Signs aims to bridge communication gaps by providing an interactive web platform for ASL learning. The platform utilizes AI to analyze users' movements through their webcams, offering real-time feedback and instruction via a 3D avatar demonstrating signs. It currently features a validated library of 100 signs, with plans to expand to 1,000 by collecting 400,000 video clips.
Signs is designed to support sign language learners of all levels and also allows contributors to add to Nvidia's growing ASL open-source video dataset. The dataset will be validated by fluent ASL users and interpreters. This dataset, slated for release later this year, will be a valuable resource for building accessible technologies like AI agents, digital human applications, and video conferencing tools. While the current focus is on hand movements and finger positions, future versions aim to incorporate facial expressions, head movements, and nuances like slang and regional variations. Recommended read:
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