The STEMINISTS Podcast

Everyone's obsessed with AI right now. Bigger models. Faster training. More GPUs. More data centers. More everything. But there's one small problem: none of that AI infrastructure exists without semiconductors. And the companies designing those chips are suddenly competing for the exact same resources.  

Welcome to the ultimate tech plot twist. 

In this episode of The STEMINISTS Podcast, host Phoebe Goh sits down with Diane Patton, Senior Product Manager at NetApp, to unpack how the AI boom is reshaping the silicon supply chain and putting unprecedented pressure on Electronic Design Automation (EDA), the critical technology behind modern chip design. 

As AI demand drives a global scramble for GPUs, RAM, and high-performance compute resources, chip designers are facing a new challenge. The infrastructure required to design semiconductors is becoming just as difficult to obtain as the infrastructure needed to run AI itself.  

Diane breaks down why EDA workloads are among the most demanding in enterprise IT, requiring massive compute power, low-latency storage, and the ability to process enormous volumes of data at scale. She also explains why waiting months for hardware procurement is no longer a viable strategy when innovation cycles are moving at AI speed and today's "latest and greatest" GPU can become yesterday's news before it's even installed.  

The conversation explores how semiconductor companies are turning to cloud and hybrid-cloud architectures to bypass infrastructure bottlenecks, accelerate chip development, and gain access to scalable compute resources on demand. From cloud bursting and intelligent data caching to storage tiering and AI-powered workflows, you'll hear how organizations are modernizing chip design for a world where flexibility is becoming a competitive advantage.  

Key Takeaways: 

What Electronic Design Automation (EDA) actually is 

Why AI is reshaping semiconductor infrastructure requirements 

GPU and RAM shortages facing chip design teams 

High-performance storage for EDA workloads 

Cloud vs. on-premises semiconductor design environments 

Hybrid cloud strategies for semiconductor companies 

Data management challenges in chip development 

AI-enabled opportunities for EDA workflows 

The future of semiconductor innovation and the silicon supply chain 

Whether you're a semiconductor professional, infrastructure architect, cloud strategist, or simply curious about the technology powering the AI revolution, this episode offers an insider's look at the future of chip design, EDA infrastructure, cloud computing, and the evolving silicon supply chain.

 

Learn More:

https://www.netapp.com/industries/electronic-design-automation-eda/  

https://www.netapp.com/blog/semiconductor-design-netapp-all-flash-portfolio/  

 

Connect with us!

https://www.linkedin.com/in/phoebegoh/ 

https://www.linkedin.com/in/diane-patton-7519634/

Security teams have more data than ever before. More dashboards. More alerts. More telemetry. More AI. So why is answering the simple question, "Are we actually secure?" still so difficult? 

In this episode of The STEMINISTS Podcast, Phoebe Goh sits down with Cole Neumark, Security Analytics professional at NetApp and Vice Chair of Proud, NetApp's LGBTQ+ employee resource group, to unpack why cybersecurity isn't just a technology challenge, it's a people challenge.  

With a career path that started in English and art history rather than computer science, Cole brings a refreshingly different perspective to cybersecurity. Together, Phoebe and Cole explore the reality of security analytics: turning mountains of signals, alerts, and vulnerability data into meaningful decisions that leaders can actually use. Because data alone doesn't create security. Context does. And context is still a very human skill.  

The conversation dives into the promises and pitfalls of AI in security, why faster isn't always smarter, and why the most valuable skill in an AI-powered future may be asking better questions. They also discuss the often-overlooked role of communication, creativity, and storytelling in helping organizations understand risk and take action.  

Cole shares how they transformed a cybersecurity training exercise into an immersive fictional world called Pineland, complete with fake social media posts, characters, and realistic incident scenarios. The goal? Make security memorable. Because people don't remember dashboards. They remember stories. And when security awareness feels more like solving a mystery than surviving a PowerPoint presentation, people pay attention. 

The episode also explores the importance of belonging, diverse perspectives, and community in cybersecurity. Through their work with Proud, Cole reflects on how creating spaces where people feel seen, valued, and empowered ultimately leads to better collaboration, stronger teams, and smarter security decisions.  

Key takeaways: 

Why security analytics is as much about communication as it is about data 

How storytelling can turn cybersecurity from forgettable to unforgettable 

Where AI accelerates security teams, and where human judgment remains essential 

Why humanities skills are surprisingly powerful in technical careers 

How diverse perspectives help organizations solve complex security challenges 

Why "security is defended by people" may be the most important cybersecurity lesson of all  

Plus: a conversation about metal music, live concerts, and why even cybersecurity professionals need a great soundtrack. 

 

Learn more: 

https://www.netapp.com/cyber-resilience/  

 

Connect with us!

https://www.linkedin.com/in/cole-neumark/

https://www.linkedin.com/in/phoebegoh/

We were promised that AI would make information easier to find. Nobody mentioned we'd also need a PhD in figuring out what to trust. 

In this episode of The STEMINISTS Podcast, Phoebe Goh sits down with Julia Fedorova, who leads Analyst Relations at NetApp, to tackle one of the biggest challenges in the AI era: making smart decisions when everyone, everything, and every chatbot seems to have an opinion.  

As generative AI floods our feeds with answers, recommendations, and hot takes, access to information is no longer the problem. The real challenge is knowing which sources are credible, which insights are backed by evidence, and which recommendations deserve a healthy dose of skepticism.  

Julia pulls back the curtain on the often-misunderstood world of industry analysts and explains why many of the biggest technology purchasing decisions still rely on research grounded in rigorous methodologies, market validation, and years of expertise. Together, she and Phoebe explore the idea of "pools of trust," the risks of AI-powered echo chambers, and why trusting the first answer you get is rarely a winning strategy.  

The conversation also dives into how enterprise buyers can avoid blind spots, why getting a second opinion matters just as much in technology as it does in healthcare, and how the smartest leaders are balancing AI-driven insights with human judgment. Along the way, Julia shares a surprisingly simple piece of advice for navigating a rapidly changing market: pause. Before you click, buy, migrate, modernize, or panic. Just pause.  

In this episode: 

Why more information doesn't automatically lead to better decisions.  

How industry analysts build credibility and trust through research and methodology.  

The growing challenge of AI-generated echo chambers and personalized information bubbles.  

Why enterprise buyers should seek multiple perspectives before making major technology decisions.  

How to evaluate whether a source is genuinely trustworthy.  

Why storage and data infrastructure have suddenly become central to AI conversations.  

The surprisingly underrated power of slowing down before making a decision.  

Plus, Julia weighs in on an age-old debate: do audiobooks count as real books? (Spoiler: yes, and she's willing to defend that position.)  

Because in a world overflowing with AI-generated answers, the real competitive advantage might just be knowing which questions are worth asking in the first place. 

As always, if you enjoyed this conversation please gives us a follow to stay in the loop for all things STEMINISTS. We would also love to hear what topics would you like for us to discuss. Feel free to share what you want to hear next.  

 

Learn More: 

https://www.netapp.com/artificial-intelligence/generative-ai-solutions/  

 

Connect with us!

https://www.linkedin.com/in/julia-fedorova-she-her-012a9624/  

https://www.linkedin.com/in/phoebegoh/

Everyone loves to say RAG is the answer to AI hallucinations. But what if the real answer is a little more complicated? 

In this episode of The STEMINISTS Podcast, Phoebe Goh sits down with Ramya Ravi, AI Developer Advocate at NetApp Instaclustr, to unpack what Retrieval-Augmented Generation (RAG) actually does, why it's become a cornerstone of enterprise AI, and where organizations are still getting it wrong.  

Together, they demystify the mechanics behind RAG, from embeddings and vector search to semantic search and hybrid search. Ramya explains why RAG isn't magic (it's math), how it helps AI systems find relevant business knowledge, and why simply implementing RAG doesn't automatically eliminate hallucinations.  

The conversation also explores one of the biggest challenges facing AI projects today: data quality. From duplicate documents and stale content to weak evaluation practices, Ramya shares practical advice on what organizations should tackle before rushing into a RAG implementation.  

Looking ahead, Phoebe and Ramya discuss long context windows, the next evolution of enterprise AI, and why the future may not be a choice between RAG and large context models, but a powerful combination of both.  

In this episode: 

What RAG actually is and how it works behind the scenes 

Why RAG reduces hallucinations but doesn't eliminate them 

The difference between keyword, semantic, and hybrid search 

Why data quality is often the hidden factor in AI success 

How to properly evaluate a RAG implementation 

When to use long context windows versus retrieval systems 

Why the future of enterprise AI will likely rely on both approaches  

If you've been told that RAG is the silver bullet for enterprise AI, this episode offers a smarter, more practical perspective on what it can do, what it can't do, and how to make it work in the real world. 

 

Connect with us! 

https://www.linkedin.com/in/ramya-ravi19/

https://www.linkedin.com/in/mekkacodes/ 

https://www.linkedin.com/in/phoebegoh/

Fan Favorite Replay: As AI continues to reshape how organizations work, lead, and grow, we're bringing back one of our most popular conversations on preparing people and businesses for the future. The insights in this episode are just as relevant today as when it first aired, making it a must-listen for leaders navigating the age of AI. 

Are you ready to lead in a world transformed by AI? You'd better be, and this episode will help you get there. 

Hosts Phoebe Goh and Mekka Williams sit down with Sarah Bartel, Accenture's Global Cloud Talent and Organizational Change Lead, for an engaging discussion about what it takes to prepare teams, cultures, and organizations for the future of work. Drawing on her extensive experience helping organizations navigate technology-driven transformation, and her role co-teaching MIT's Leading the AI Driven Organization course, Sarah offers practical strategies for leading through change while keeping people at the center. 

Together, they explore how leaders can build more adaptable organizations, why traditional approaches to talent management are evolving, and what it takes to create a workforce ready to thrive alongside AI. You'll learn why skills-based hiring and team design are becoming critical competitive advantages, how trust serves as the foundation for successful transformation, and why AI works best when it's used to elevate human potential rather than replace it. 

Key Takeaway: The future belongs to organizations that invest in both technology and people. Leaders who embrace continuous learning, build cultures of trust, and focus on skills over job titles will be best positioned to succeed in an AI-powered world. 

Whether you're leading a large-scale transformation, building the next generation of talent, or simply looking to become a more effective leader in a rapidly changing environment, this fan-favorite episode is packed with actionable insights and fresh perspectives. 

Tune in and discover how to lead with confidence, adaptability, and a people-first mindset in the AI era. 

 

Work, Workforce, Workers Age of Generative AI Report 

https://www.accenture.com/content/dam/accenture/final/accenture-com/document-2/Accenture-Work-Can-Become-Era-Generative-AI.pdf  

 

Leading the AI Driven Organization MIT Course  

https://executive.mit.edu/course/leading-the-ai-driven-organization/a054v00000r9U5cAAE.html  

 

Develop your skills with NetApp  

https://www.netapp.com/support-and-training/netapp-learning-services/learning-paths/  

 

Connect with us! 

https://www.linkedin.com/in/sarah-gottry-bartel/  

https://www.linkedin.com/in/mekkacodes/ 

https://www.linkedin.com/in/phoebegoh/