Varun Parmar

NEW JOB TITLES IF YOU ARE DEPLOYING AGENTIC AI🤓😜 If you’re deploying agentic AI in a regulated industry… Congratulations. You just created a whole new org chart. Because the moment an AI agent touches healthcare, law, insurance, or finance, you don’t just have “AI.” And the rules about accountability and professional responsibility have not changed. Here are the new job titles every regulated industry will have to consider: 1. Chief “Who Approved This?” Officer 2. Licensed AI Babysitter 3. Director of Nope 4. AI Hallucination Containment Lead 5. Stop-the-Line Button Owner 6. Head of Proof (a.k.a. Exhibit A) 7. AI Decision Trail Detective 8. Regulator Whisperer 9. VP of “That’s Not What We Meant” 10. AI Permission Police 11. Professional Responsibility Enforcer 12. The Person Who Gets Deposed But when the board, regulators, or judge asks: “Who approved this?” “The system did” is not an answer. It’s a confession. Protect the people you serve, including yourself. #iGovernAI™ 🤓❣️ #GovernBeforeYouAutomate™ #GovernBeforeYouInnovate™

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We chose a good subject for our march Autotech Council meeting, and after this year's CES, it seems even more obvious. Our meeting on the AI Defined Vehicle will show how it's a natural next step after the Software Defined Vehicle phase that we've been in Tesla launched the Model S in 2012. Now, most carmakers have SDVs. It's time to layer on the AI in user-facing roles, and in invisible functions managing the vehicle.

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🔆 Why Decentralized AI Matters — And Why You Should Be Paying Attention This week marked a major milestone for Vana. Our work was featured in WIRED, spotlighting our partnership with Flower Labs on COLLECTIVE-1, the world’s first decentralized, user-owned large language model (LLM). A huge thanks to Will Knight for covering this story and helping bring awareness to an entirely new approach to building AI—one that prioritizes people, privacy, and permission. ❓Why does this coverage matter ❓ It's a proof point for something many think is impossible: We can build powerful, truly open AI systems without handing control to a few centralized tech giants. Decentralized AI is more than a philosophy. It’s a fundamentally different architecture for intelligence—and it’s already working with Vana leading the way. 🛠️ How Decentralized AI Works It comes down to two breakthrough shifts: 1. User-Owned Data In the current AI ecosystem, most models are trained on scraped data—your emails, public posts, and digital footprint—without consent or compensation. In decentralized AI, that changes. People can contribute data voluntarily, retain ownership, and participate in the upside of the models they help train. This means better data, fairer incentives, and AI that reflects the real world—not just what’s available online. 2. Permissionless, Distributed Compute Training massive AI models used to require centralized supercomputers. Now, with projects like Flower Labs, it’s possible to train models across distributed networks of devices—more resilient, more inclusive, and impossible to monopolize. This isn’t science fiction. It’s already live. ❓ Why You Should Care ❓ If you work in AI, data, or digital policy—and you’re frustrated by the closed nature of today’s models—you should be paying attention. Decentralized AI offers: • Transparency in how models are built • Sovereignty over your personal data • Participation in the next wave of innovation This space is where data ethics, technical innovation, and economic inclusion intersect. And it’s moving fast. I’m grateful to work alongside Vana's founders Anna Kazlauskas Art A. who not only see a better future for the global digital economy but are delivering on it every day.

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The quantum shift in SDLC/app lifecycle is upon us and no one can do it alone. Shlomi Ben Haim, CEO of JFrog was joined on stage at #swampUP by our key platform ecosystem partners on this journey - Justin Boitano, VP of Enterprise AI at NVIDIA; Rahul Tripathi, GVP and GM ITSM at ServiceNow, and Tariq Shaukat, CEO of Sonar. What is the quantum shift? With the explosive pace of releases, ubiquitous AI apps, and higher security threats - the way we do software releases has to shift. We need a application lifecycle that is - faster, more secure, with a unified ecosystem approach and a single system of record. Shlomi and our partners shared how our collective tech integrations enrich JFrog as the system of record for your application lifecycle: 1. JFrog platform incorporates code qaulity from Sonar for more reliable releases 2. ITSM information and DevOps practices are deeply intertwined for faster and trusted app lifecycle 3. And with JFrog - the secure model registry - you can more confidently release your AI apps. Proud moment for us, watch all the innovation launching today. #jfrogFly, #jfrogAIcatalog, #AppTrust and more.

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Twilio's SVP of Strategy & Operations, Ivy Grant, shares insights on reimagining AI approaches in InformationWeek. She discusses starting with friction points rather than function, the importance of dual-speed implementation, and creating flywheels of acceleration for meaningful AI transformation. 👇

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New short! For enterprise AI budgets, it's not about speed or scale of implementation but small steps, finding the right partners, and focusing on human role and imapct amidst all the changes. More sharings from WIZ.AI's Robin Li from working with hundreds of enterprise partners across the globe on implementing their conversational AI solutions for their businesses. Follow Insignia Ventures Partners for the latest episode of On Call with Insignia. #AI #ArtificialIntelligence #AIArchitecture #Leadership #Innovation #ashortaday

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Ex-OpenAI CTO Mira Murati's AI startup Thinking Machines Lab officially closed a $2B seed round led by Andreessen Horowitz, with participation from Nvidia, Accel, ServiceNow, CISCO, AMD, and Jane Street. With billions in funding, Murati may have enough of a war chest to train frontier AI models, but Thinking Machines Lab has an uphill battle to catch up with other AI labs. It’s likely banking on novel research breakthroughs to set it apart; however, that’s an increasingly difficult task as Meta, Google DeepMind, Anthropic, and OpenAI invest billions in their own research teams. https://lnkd.in/gYfEUxQy

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The global race for AI talent is accelerating. I spoke with Frank Holland on CNBC this morning about how Uniphore is attracting the brightest minds to shape the future of Business AI. Top AI researchers aren’t driven by compensation alone; they are driven by MISSION. Some are working to build the future of superintelligence. Others are pursuing fit-for-purpose AI…solving the toughest challenges businesses face today. That’s where Uniphore is focused. With our scale and platform, Uniphore enables researchers and engineers to deliver innovations that make an immediate, measurable impact in the real world. In the not-too-distant future, AI’s impact will be measured by productivity gains, which may very well mean a few more long weekends like the one we just had in the US. As Business AI accelerates, Uniphore is pushing the boundaries of what’s possible and redefining how companies engage, operate, and grow.

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