Musing about Muse’s new supporting AI models, unruly DeepSeek models

There’s networking for AI, and then there’s AI for networking, and Joe Vaccaro, senior vice president and general manager at Cisco Network Platform and ThousandEyes, breaks down the distinction on the latest Targeting AI podcast from TechTarget. According to Vaccaro, AI for networking assists network operations, while networking for AI builds resilient infrastructure for AI workloads and traffic. Vaccaro also outlines how agentic AI can help operate increasingly complex networks. He discusses the controls needed to make those agents trustworthy, from deterministic workflows and digital-twin validation to business-context guardrails and agent security. In this episode, we discuss how: Cisco’s agentic loop moves through sensing, diagnosing, planning, validating, and acting. Cisco’s Deep Network Model and an ensemble of Cisco, small-language, and frontier models are presented as ways to apply network-specific knowledge and capabilities. Industrial and IoT environments bring physical AI workloads such as factory robots and vision systems, creating demand for focused models that can operate close to the edge in near real time. Cisco Cloud Control is a shared context layer for business intent, security policies, observability objectives and standard operating procedures. Agent security includes non-human identities with scoped roles and permissions, as well as protections against risks such as model jailbreaking. To dive deeper into topics about AI and networking, check out TechTarget AI from Informa TechTarget, and please subscribe to our newsletter to keep up to date on the most important AI news. To watch video clips from our podcast, subscribe to our YouTube channel, @EyeonTech. References: Cisco embeds agentic AI across customer journey Cisco advances AI infrastructure services at Cisco Live AI-native networking vs. traditional network automation  

On this episode of Targeting AI in the Moment (AIM), the new weekly news podcast from TechTarget.com and AI Business, the three co-hosts chat about the Anthropic IPO and what it means for enterprise AI. They also examine what OpenAI model pricing means in the context of the “Chinese invasion” of low-cost, open-weight models. AI news writer and podcast producer and host Esther Shittu, AI news and features writer Kinza Yasar and their editor, Shaun Sutner, report and analyze the news on TechTarget AI and offer more analysis, perspective and context in the news podcast series. Kinza Yasar covers AI and emerging technology for TechTarget, with a focus on ethics, enterprise adoption, governance and business strategy. Before moving into journalism, she worked in IT and network support roles, giving her a systems-level perspective on how enterprise technologies are built, deployed and managed. Esther Shittu is an Informa TechTarget covering AI technology. Shaun Sutner is a journalist with more than 30 years of experience and 12 years at TechTarget as an editor and writer.

From internal enablement and training to product features such as MCP and Smart Assist, work management vendor Smartsheet is using AI across its company. Marcus McKay Fleisch, the project management and work collaboration platform’s professional services enablement director, joins TechTarget’s Targeting AI podcast to discuss how his team is moving beyond basic adoption metrics to focus on workflow-level impact, security guardrails, and measurable business outcomes. He dives into how AI is changing daily work for Smartsheet users, why shadow AI shows up when internal tooling is missing, and how IT, product, security, and enablement must work together to make AI useful without introducing new risks. In this episode, we discuss: Smartsheet’s focus on natural language access using MCP (model context protocol) and Smart Assist. The biggest everyday benefit for users is automation inside real workflows, such as checking due tasks, prioritizing work, and completing updates with AI-assisted actions. Enablement at Smartsheet goes beyond training and includes behavior change, tooling access, security review, and close coordination with IT. Smartsheet’s main large language model tools. How Smartsheet is shifting its AI adoption strategy. Shadow AI as a signal that employees need approved tools or capabilities that the company does not yet offer internally. How Smartsheet treats security as a human and organizational problem as much as a technical one, with quarterly security training, threat modeling, and tighter controls around features such as browser and computer use. To dive more into topics about generative AI-driven software, check out TechTarget AI & Emerging Tech, and please subscribe to our newsletter to keep up to date on the most important AI news. To watch video clips from our podcast, subscribe to our YouTube channel, @EyeonTech. References: Build vs. buy: the AI agent landscape for businesses How enterprises should combat the growing shadow AI problem AI changes the ROI equation. Here’s how some have found success

On Targeting AI in the Moment (AIM), the weekly news podcast from TechTarget.com, this week’s co-hosts chat about the latest developments in the turbulent world of generative AI. AI news writer Esther Shittu and her editor, Shaun Sutner, report the news on the sites and offer more analysis, perspective and context on recent AI developments in this short-form news podcast series. Check out these new stories: Meta joins enterprise agent race with Muse Wonder, facing a trust gap DeepSeek and what enterprises should learn from AI agent exploits Shaun Sutner is senior news director and lead editor for TechTarget’s AI & Emerging Tech news coverage. He is a veteran journalist with more than 30 years of news experience. Esther Shittu is a TechTarget news writer and podcast producer and host who covers AI software and systems. Together, they host the Targeting AI podcast.

On Targeting AI in the Moment (AIM), the weekly news podcast from TechTarget, the three co-hosts chat about the latest developments in the turbulent world of generative AI. AI news writer and podcaster Esther Shittu, AI news and features writer Kinza Yasar and their editor, Shaun Sutner, report the news on the sites and offer more analysis, perspective and context on recent AI developments in the new podcast series. Check out these new stories on TechTarget.com: Reflection’s Beam model signals deepening split in global AI market AI teaching systems raise new questions for school districts | TechTarget

Context is critical in AI, according to Celonis CEO and co-founder Alex Rinke. The enterprise software development vendor specializes in process mining and process intelligence. On this Targeting AI episode, Rinke argues that process intelligence needs context, particularly business context, so that AI agents can understand workflows, operate more effectively and deliver measurable ROI. In this episode, we discuss: The evolution from process mining to process intelligence How digital twins model organizational processes The role of AI in automating complex workflows Security and privacy in enterprise AI Partnerships for sovereign AI and data governance The impact of generative AI on process optimization Measuring ROI in AI-driven process improvements To dive more into topics about process mining and data, check out TechTarget AI & Emerging Tech from Informa TechTarget, and please subscribe to our newsletter to keep up to date on the most important AI news. To watch video clips from our podcast, subscribe to our YouTube channel, @EyeonTech. References: SAP agrees to allow Celonis data access until case resolved Process mining matures in the age of generative AI Contextual data is important for enterprises’ AI projects

AI is abuzz with talk of self-regulation or some form of federal oversight; President Trump renaming AI as "superintelligence"; and open vs. closed AI amid the AI slowdown. On the debut episode of Targeting AI in the Moment (AIM), the new weekly news podcast from AI Business and TechTarget.com, the three co-hosts chat about the latest developments in the fast-churning world of generative AI. AI news writer and podcaster Esther Shittu, AI news and features writer Kinza Yasar and their editor, Shaun Sutner, report the news on the sites and offer more analysis, perspective and context in the new podcast series.

While physical AI has been accelerating in China, the technology is just starting to gain momentum in the U.S. In this Targeting AI episode, Sce Pike, vice president of AI growth and solutions at Telus Digital, discusses the future of physical AI and robotics, focusing on data collection challenges, standardization efforts, and the cultural acceptance of robots in different regions. In this episode we discuss: Data collection problems for physical AI Standardization efforts in robotics data Training data for generalist robotic models Safety and quality issues in robotics data Cultural acceptance of robots in different regions To dive more into topics about robotics, check out TechTarget AI from Informa TechTarget, and please subscribe to our newsletter to keep up to date on the most important AI news. To watch video clips from our podcast, subscribe to our YouTube channel, @EyeonTech. References: Humanoid robots: The next frontier in physical AI Physical AI challenge: Making humanoid robots work in the real world Smarter robots: agentic and physical AI converge in business

With Google one of the leading model makers in the AI race, the tech giant is continually addressing challenges in interoperability, governance and the future of enterprise AI. On this episode of Targeting AI, Michael Clark, director of product management at Google Cloud, dives into how AI agents are evolving, their applications in enterprise environments, and the importance of trust and security. In this episode, we discuss: AI agent ecosystem and interoperability challenges Google Cloud's Gemini Enterprise Agent Platform Governance, security, and trust in AI systems Building and scaling enterprise AI agents Future trends in AI agent development To read more into topics about Google and agentic AI, check out AI Business from Informa TechTarget, and please subscribe to our newsletter to keep up to date on the most important AI news. To watch video clips from our podcast, subscribe to our YouTube channel, @EyeonTech. References: Google Cloud Bets Big on the Agentic Enterprise What Google’s Release of Gemini 3.8 Says About the AI Market In Catch-up Mode, Google Intros AI Agents for Financial, Legal Services

Most enterprises are familiar with probabilistic AI systems such as generative AI and agentic AI. According to Maha Achour, CEO and founder of enterprise AI platform vendor Kodamai, another form of AI could help enterprises better trust these systems: math-based AI. In this episode of Targeting AI, Achour discusses how math-based AI can be trusted more than other forms of AI because it is harder to hack or be manipulated. She dives deep into the mathematical principles that Kodamai uses, including category theory and type theory. In this episode, we discuss: Mathematical principles such as category theory and type theory could help remove the black box behind current forms of AI. The importance of using neuro-symbolic AI. What grounding AI systems in mathematical certainty rather than probabilistic approximations means for challenges such as hallucinations, governance and security. Why artificial general intelligence and artificial superintelligence require human collaboration. The superiority of human intuition. To learn more about generative and agentic AI, check out AI Business from Informa TechTarget, and please subscribe to our newsletter to keep up to date on the most important AI news. To watch video clips from our podcast, subscribe to our YouTube channel, @EyeonTech. References: Startup Pioneering Neuro-Symbolic AI Secures Bridge Funding Mathematical Superintelligence Startup Valued at $1.45B An Explanation of the Different Types of AI