Digital experience twins have arrived for enterprise networks, and it's changing everything about how IT teams manage infrastructure. Meet Marvis Minis — Juniper Networks' groundbreaking digital twin technology that acts as your virtual user, constantly testing network connectivity and application performance when real users aren't present.

Juniper’s Kumar Putta Swamy and Shirley Wu join us to explore how this game-changing innovation helps network administrators validate

The impact for customers has been substantial. Already deployed across 16,000 sites, Marvis Minis have

What sets this technology apart is its complete client-to-cloud visibility and integration with Juniper's Marvis® AI engine. The system automatically detects configuration changes, builds appropriate test plans, executes validations, and feeds results back to Marvis for correlation and root cause analysis. Even more impressive —

For network teams struggling with changes that break applications in unexpected ways, Marvis Minis offers a proactive solution that identifies problems before users ever experience them. Ready to see how your network performs when nobody's watching? Discover how digital experience twins are transforming network operations and user experience.

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Key points covered:

Introduction to Marvis Minis

Benefits of Marvis Minis

Examples of Marvis Minis in action

Technical details of Marvis Minis

Deployment and updates

Customer use cases

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Where to find Kumar?

LinkedIn - https://www.linkedin.com/in/kumar-putta-swamy/

Where to find Shirley?

LinkedIn - https://www.linkedin.com/in/shirley-wu-ab32171/

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Bob, Principal Analyst at Cube Research, reveals fascinating insights on enterprise AI adoption from his latest research. His four-stage adoption model shows organizations progressing from basic alerts (21%) to recommendations (28%), manual automation (26%), and fully automated responses (24%), highlighting the journey as enterprises build trust in AI systems.

• Research shows enterprises slowly gaining comfort with AI adoption across four distinct stages
• An astonishing 97% of enterprises would switch vendors for better AI operations technology
• The 20-60-20 "maturity model" applies to AI adoption with leaders embracing full automation
• Getting started with AI is crucial for organizations to build experience and confidence
• Consumer AI applications like ChatGPT help enterprises get comfortable with the technology
• Network complexity increases the need for AI-driven operational efficiency
• To identify genuine AI solutions, look for vendors with 5-10+ years of experience
• Effective AI systems incorporate closed-loop feedback and leverage customer support insights

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Key points covered:

Adoption of AI in enterprises: The discussion highlights the different stages of AI adoption in enterprises, ranging from generating alerts to fully automating responses. It emphasizes the importance of organizations becoming comfortable with AI technology and gradually transitioning from manual automation to full automation.

Impact of AI on vendor selection: The conversation reveals that a significant percentage of enterprises are willing to switch vendors if they can get better AI operations technology. This underscores the value enterprises place on AI solutions and their potential to drive operational efficiency.

Evaluating AI solutions: The document discussion provides insights into how enterprises can differentiate between marketing AI and real AI. Key indicators include the vendor's experience, the presence of a closed-loop system, and collaboration with customer support teams to ensure the efficacy of AI solutions.

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Where to find Bob Laliberte?

LinkedIn - https://www.linkedin.com/in/boblaliberte90/

Website - https://thecuberesearch.com/

Where to find Bob Friday?

LinkedIn - https://www.linkedin.com/in/bobfriday/

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To stay updated on the latest episodes of The Q&AI Podcast and other exciting content, subscribe to our podcast on the following channels:

Apple Podcasts - https://podcasts.apple.com/us/podcast/the-q-ai-podcast/id1774055892

Spotify - https://open.spotify.com/show/0S1A318OkkstWZROYOn3dU?si=5d2347e0696640c2

YouTube - https://www.youtube.com/playlist?list=PLGvolzhkU_gTogP5IBMfwZ7glLp_Tqp-C

We hope you enjoyed this episode!

In this episode of The Q&AI Podcast, host Bob Friday welcomes Nagarjun Srinivasan, cofounder of Lune and former Juniper engineer, to explore how AI is transforming the music industry. From winning an innovation award at South by Southwest to developing AI-powered learning tools, Nagarjun shares insights on how technology is reshaping music education, creation, and performance.

They discuss AI’s role in music transcription, gamification for skill building, the ethical challenges of AI-generated music, and the future of AI-assisted content creation. Tune in to discover how AI is making music more accessible and interactive for both beginners and professionals.

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Key points covered:

Winning at South by Southwest: How Lune started as an experimental prototype and went on to win an Innovation Award for Human-Computer Interaction

AI for music learning: AI’s role in transcribing music, generating real-time feedback, and making learning more engaging through gamification

Gamification and muscle memory: How AI-powered games help musicians develop dexterity and improve faster

AI for content creators: How AI is streamlining music production, mixing, and mastering, making professional-quality content more accessible

The copyright debate: The ethical and legal implications of AI-generated music, including lawsuits against companies using unlicensed music for training

AI vs human musicians: Will AI ever replace human musicians, or will it always be a tool for enhancing creativity?

The role of hardware in AI music: Why specialized hardware and data collection are crucial for advancing AI-driven music experiences

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Where to find Nagarjun Srinivasan?

LinkedIn - https://www.linkedin.com/in/nagarjun-srinivasan/

Where to find Bob Friday?

LinkedIn - https://www.linkedin.com/in/bobfriday/

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To stay updated on the latest episodes of The Q&AI Podcast and other exciting content, subscribe to our podcast on the following channels:

Apple Podcasts - https://podcasts.apple.com/us/podcast/the-q-ai-podcast/id1774055892

Spotify - https://open.spotify.com/show/0S1A318OkkstWZROYOn3dU?si=5d2347e0696640c2

YouTube - https://www.youtube.com/playlist?list=PLGvolzhkU_gTogP5IBMfwZ7glLp_Tqp-C

We hope you enjoyed this episode!

In this episode of The Q&AI Podcast, Bob sits down with Claudionor Coelho, Chief AI Officer at Zscaler, to unravel the complexities and transformative potential of artificial intelligence in today's rapidly evolving technological landscape. They explore Claudionor's unique journey from semiconductor research to leading AI strategy in cybersecurity, providing insights into the crucial role of a Chief AI Officer and the imperative of securing AI in an interconnected world. Tune in as Bob and Claudionor discuss the shift from LLMs to AI agents, the challenges of hallucination, and the future of AI in various industries.

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Key points covered:

Claudionor's diverse AI journey: From early semiconductor work to leading AI strategy at Zscaler, highlighting his evolution in the field.

The strategic role of a Chief AI Officer: Balancing external engagement and internal product development, and navigating AI's impact on business.

The critical importance of secure AI: Addressing vulnerabilities and ensuring responsible AI use in an increasingly connected world.

The shift to AI agents: Exploring the capabilities and implications of multi-agent systems beyond traditional LLMs.

Data quality and hallucination challenges: Emphasizing the significance of data management and mitigating inconsistencies in AI outputs.

AI's impact on cybersecurity: Leveraging AI for threat detection while securing AI systems themselves.

Insights into the future of AI: Discussions on AI agents, potential advancements, and the ongoing debate surrounding AI singularity.

Practical AI applications and tool selection: Real-world examples (including self-driving cars) and the importance of using the appropriate AI tools for specific tasks.

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Where to find Claudionor Coelho?

LinkedIn - https://www.linkedin.com/in/claudionor-coelho-jr-b156b01/

Where to find Bob Friday?

LinkedIn - https://www.linkedin.com/in/bobfriday/

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Keywords:

AI accelerations, cybersecurity, predictive machine learning, anomaly detection, generative AI, AI agents, multi-agent systems, large language models, deep learning, machine learning, AI for security, secure AI

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To stay updated on the latest episodes of The Q&AI Podcast and other exciting content, subscribe to our podcast on the following channels:

Apple Podcasts - https://podcasts.apple.com/us/podcast/the-q-ai-podcast/id1774055892

Spotify - https://open.spotify.com/show/0S1A318OkkstWZROYOn3dU?si=5d2347e0696640c2

YouTube - https://www.youtube.com/playlist?list=PLGvolzhkU_gTogP5IBMfwZ7glLp_Tqp-C

We hope you enjoyed this episode!

In this special episode of Bob Friday Talks, recorded live from the Fontainebleau in Las Vegas, Bob Friday welcomes John Bollen, ServiceNow Industry Leader of Solutions, to discuss the transformative role of AI in hospitality and gaming. With years of experience in the industry, John shares insights on how AI and networking advancements are shaping guest experiences, employee operations, and the future of integrated resorts.

The incorporation of AI in hospitality serves as a transformative catalyst, redefining operational efficiencies and guest experiences. Key developments in the AI in hospitality industry underscore the technology's pivotal role in automating services, personalizing interactions, and streamlining management processes within hotels.

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Key points covered:

Enhanced guest services: AI-driven solutions in hotels provide instant support and improved accessibility to services.

Personalization: AI enables personalized guest experiences by analyzing preferences and behavior history.

Operational efficiency: Through machine learning algorithms, hotels are optimizing logistics, inventory management, and staff deployment.

Cost reduction: AI applications aid in scaling down operational expenses by automating routine tasks.

Predictive analytics: Leveraging AI for predictive analysis enables the anticipation of future trends and customer needs, allowing for proactive strategy adjustments.

Data management: Critical to the hospitality sector, AI-driven data management systems efficiently parse guest data, fostering enhanced marketing and service quality.

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Where to find John Bollen?

LinkedIn - https://www.linkedin.com/in/johnbollen/

Where to find Bob Friday?

LinkedIn - https://www.linkedin.com/in/bobfriday/

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Keywords

ai in hospitality, ai in hospitality industry, ai in hotels

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To stay updated on the latest episodes of The Q&AI Podcast and other exciting content, subscribe to our podcast on the following channels:

Apple Podcasts - https://podcasts.apple.com/us/podcast/the-q-ai-podcast/id1774055892

Spotify - https://open.spotify.com/show/0S1A318OkkstWZROYOn3dU?si=5d2347e0696640c2

YouTube - https://www.youtube.com/playlist?list=PLGvolzhkU_gTogP5IBMfwZ7glLp_Tqp-C

We hope you enjoyed this episode!

In this episode of The Q&AI Podcast, host Bob Laliberte sits down with Juniper Networks' Chief AI Officer Bob Friday to explore the journey toward self-driving networks. As network complexity grows, organizations must adopt AI-driven solutions to ensure performance, reliability, and security. Bob Laliberte and Bob Friday break down the five stages of AI in networking, from data collection to full autonomy, and discuss the cultural and technological shifts required to build trust in AI-driven network operations.

Tune in as they share real-world examples, insights on AI adoption, and how businesses can take the first steps toward a fully autonomous network.

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Key points covered:

The path to self-driving networks: Understanding the five stages of AI-driven networking and how they build trust in automation

AI’s impact on network operations: How AI improves efficiency, speeds up issue resolution, and enhances user experiences

Overcoming AI adoption challenges: Addressing skill gaps, trust concerns, and separating real AI from marketing buzz

The shift to AI-driven IT: How IT teams can transition from traditional operations to AI-assisted decision-making

Getting started with AI in networking: Why starting small with a production POC is the key to successful AI adoption

The future of AI in networking: How AI will continue to evolve, making networks smarter and more autonomous

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Where to find Bob Laliberte?

LinkedIn - https://www.linkedin.com/in/boblaliberte90/

Website - https://thecuberesearch.com/

Where to find Bob Friday?

LinkedIn - https://www.linkedin.com/in/bobfriday/

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Keywords

self-driving networks, juniper ai-driven enterprise, juniper self-driving network, ai-assisted decision-making, ai-powered network optimization, ai adoption in it, autonomous networking solutions, ai for proactive issue resolution, ai and machine learning in networking, ai-based network troubleshooting

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To stay updated on the latest episodes of The Q&AI Podcast and other exciting content, subscribe to our podcast on the following channels:

Apple Podcasts - https://podcasts.apple.com/us/podcast/the-q-ai-podcast/id1774055892

Spotify - https://open.spotify.com/show/0S1A318OkkstWZROYOn3dU?si=5d2347e0696640c2

YouTube - https://www.youtube.com/playlist?list=PLGvolzhkU_gTogP5IBMfwZ7glLp_Tqp-C

We hope you enjoyed this episode!

In this episode of The Q&AI Podcast, Bob chats with Ram Velaga of Broadcom about their pivotal role in the AI world. They explore the rise of custom AI accelerators, the GenAI boom, and how Broadcom enables massive AI clusters. They also discuss AI's practical applications within Broadcom, build vs buy strategies, the future of AI, and the networking revolution it's driving, both in data centers and at the edge.

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Key points covered:

Broadcom's role in AI: How Broadcom provides essential IP and networking solutions for AI development, despite not producing GPUs directly

The rise of custom accelerators: The trend of large cloud providers developing their own in-house accelerators for AI workloads

Generative AI and LLMs: The current focus on building large language models and their potential impact on various industries

AI within Broadcom: Exploring internal use cases for AI, including customer support, software development, and silicon design

Build vs buy for AI solutions: Strategies for leveraging existing LLMs while protecting proprietary data

The future of AI: Ram's perspective on the timeline for achieving more advanced AI capabilities and the massive investments being made

A new software paradigm: Discussion of potential shifts in software development practices due to AI

Networking for AI: The critical role of high-speed, scalable networks in supporting distributed AI computing

AI at the edge: Exploring use cases for AI processing at the network edge, including set-top boxes, Wi-Fi, and computer vision

The multi-billion-dollar question: The potential for AI to generate significant revenue and the need for diverse applications

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Where to find Ram Velaga?

LinkedIn - https://www.linkedin.com/in/ram-v-124b79/

Where to find Bob Friday?

LinkedIn - https://www.linkedin.com/in/bobfriday/

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To stay updated on the latest episodes of The Q&AI Podcast and other exciting content, subscribe to our podcast on the following channels:

Apple Podcasts - https://podcasts.apple.com/us/podcast/the-q-ai-podcast/id1774055892

Spotify - https://open.spotify.com/show/0S1A318OkkstWZROYOn3dU?si=5d2347e0696640c2

YouTube - https://www.youtube.com/playlist?list=PLGvolzhkU_gTogP5IBMfwZ7glLp_Tqp-C

We hope you enjoyed this episode!

In this episode of The Q&AI Podcast, Juniper Networks' Bob Friday is joined by Abhi Shamsundar, Director of Product Management, to explore how AI is revolutionizing network switching. They discuss how AI enhances communication, mitigates congestion, improves security, and optimizes user experiences in wired networks. They also delve into anomaly detection, self-driving networks, and the launch of Juniper's cutting-edge EX4000 AI-Native switch.

Abhi shares insights into leveraging cloud data for smarter decisions, automating network tasks to reduce downtime, and creating seamless user experiences. Discover how Juniper is shaping the future of network reliability and efficiency through AI-Native innovation.

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Key points covered:

AI in network switching: Leveraging AI to detect anomalies, optimize packet flow, and enhance security in wired networks

Marvis data science: Using anomaly detection and event correlation to identify and address network issues proactively

Self-driving network progress: Automating network tasks like port resets and optimizing processes to minimize user disruptions

Introducing the EX4000 Switch: Juniper’s newest AI-Native, cloud-ready switch with faster boot times, advanced telemetry, and innovative design features

Inter-switch communication: How switches exchange data to improve network troubleshooting and reduce manual intervention

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Find the transcript and show notes at:

Transcript - https://www.juniper.net/us/en/the-feed/topics/ai-and-machine-learning/the-q-and-ai-switching-to-intelligence-ai-redefines-network-ops.html

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Where to find Bob Friday?
LinkedIn - https://www.linkedin.com/in/bobfriday/

Where to find Abhi Shamsundar?
LinkedIn - https://www.linkedin.com/in/abhiramms/

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To stay updated on the latest episodes of The Q&AI Podcast and other exciting content, subscribe to our podcast on the following channels:

Apple Podcasts - https://podcasts.apple.com/us/podcast/the-q-ai-podcast/id1774055892

Spotify - https://open.spotify.com/show/0S1A318OkkstWZROYOn3dU?si=5d2347e0696640c2

YouTube - https://www.youtube.com/playlist?list=PLGvolzhkU_gTogP5IBMfwZ7glLp_Tqp-C

We hope you enjoyed this episode!