News from the AI & ML world
DeeperML - #ibm
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IBM is expanding its artificial intelligence offerings with a major initiative focused on agentic AI, unveiled at the THINK 2025 conference. The company is introducing a suite of domain-specific AI agents and tools designed to help enterprises move beyond basic AI assistants and embrace more sophisticated, autonomous AI agents. These agents can be integrated using watsonx Orchestrate, a framework added to IBM's integration portfolio. The goal is to make it easier for businesses to build, deploy, and benefit from AI agents in real-world applications.
IBM's new agentic AI capabilities include an AI Agent Catalog, offering a centralized hub for pre-built agents, and Agent Connect, a partner program for third-party developers. Domain-specific agent templates for sales, procurement, and HR are also being provided, along with a no-code agent builder for business users and an agent development toolkit for developers. A multi-agent orchestrator enables agent-to-agent collaboration, and Agent Ops (in private preview) offers telemetry and observability. The core aim is to bridge the gap between AI experimentation and tangible business benefits. IBM CEO Arvind Krishna believes that over a billion new applications will be built with generative AI in the coming years, emphasizing AI's potential to drive productivity, cost savings, and revenue scaling. IBM's initiative directly addresses the challenges enterprises face in achieving a return on investment from their AI projects, including data silos and hybrid infrastructure complexities. These new tools and integration capabilities intend to facilitate AI agent adoption across various vendors and platforms.
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Dataminr and IBM are making significant strides in leveraging agentic AI to enhance security operations. Dataminr has introduced Dataminr Intel Agents, an autonomous AI capability designed to provide contextual analysis of emerging events, threats, and risks. These Intel Agents are part of a broader AI roadmap aimed at improving real-time decision-making by providing continuously updated insights derived from public and proprietary data. This allows organizations to respond faster and more effectively to dynamic situations, sorting through the noise to understand what matters most in real-time.
IBM is also delivering autonomous security operations through agentic AI, with new capabilities designed to transform cybersecurity operations. This includes driving efficiency and precision in threat hunting, detection, investigation, and response. IBM is launching Autonomous Threat Operations Machine (ATOM), an agentic AI system designed for autonomous threat triage, investigation, and remediation with minimal human intervention. ATOM is powered by IBM's Threat Detection and Response (TDR) services, leveraging an AI agentic framework and orchestration engine to augment existing security analytics solutions. These advancements are critical as cybersecurity faces a unique moment where AI-enhanced threat intelligence can give defenders an advantage over evolving threats. Agentic AI is redefining the cybersecurity landscape, creating new opportunities and demanding a rethinking of how to secure AI. By automating threat hunting and improving detection and response processes, companies like Dataminr and IBM are helping organizations unlock new value from security operations and free up valuable security resources, enabling them to focus on high-priority threats.
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