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PODCAST

The Ravit Show

The Ravit Show aims to interview interesting guests, panels, companies and help the community to gain valuable insights and trends in the Data Science and AI space! The show has CEOs, CTOs, Professors, Tech Authors, Data Scientists, Data Engineers, Data Analysts and many more from the industry and academia side. We do live shows on LinkedIn, YouTube, Facebook and other platforms. The motto of The Ravit Show is to the Data Science/AI community grow together!

technology

All Episodes

00:15:02

Azure Cosmos DB Conf 2026

The Ravit Show ·

2026/04/25

If you are building anything in AI right now, you need to pay attention to this. I recently sat down with Kirill Gavrylyuk, VP of Azure Cosmos DB, Microsoft on The Ravit Show, and one thing was very clear. The biggest challenge in AI today is not just models. It is the data layer. We talked about where things are actually breaking. Teams are building AI apps, but they struggle with memory, real-time data, and systems that need to scale globally. This is exactly where Cosmos DB is becoming

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00:04:35

Solidigm Explains: Why GPU Utilization Drops Without...

The Ravit Show ·

2026/04/23

Everyone at NVIDIA GTC is talking about GPUs. But my conversation with Greg Matson from Solidigm was a good reminder. AI does not run on GPUs alone. It runs on data. And how fast you can move that data. What stood out is how much pressure new NVIDIA systems are putting on storage. The demand is not just for capacity anymore, but for performance and efficiency at a completely different level.Solidigm is right in the middle of this shift. They are working with NVIDIA on things like liquid-cooled SSDs

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00:09:00

If You’re Not Thinking About AI, You’re Not Taking...

The Ravit Show ·

2026/04/21

Everyone in AI is talking about GPUs. Almost no one is talking about storage. At NVIDIA GTC, I sat down with Greg Matson from Solidigm, and this gap became very clear. Because behind every model, every training run, every inference pipeline… there is data. And how you store, move, and access that data changes everything. We talked about what companies are missing when they say they are “all in on AI.”Most are focused on compute. Very few are rethinking their data and storage strategy. And that

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00:09:56

AI Factories and Full AI Stacks for Large Scale AI

The Ravit Show ·

2026/04/21

AI is no longer just a technology conversation. It is becoming a national strategy. I spoke to with Thierry Pienaar, Chief Tech Officer at Hewlett Packard Enterprise at #NVIDIAGTC, and we discussed something that is quickly gaining momentum: Sovereign AI.Countries and organizations are starting to realize that where AI is built, trained, and deployed matters just as much as the models themselves. This is not just about innovation. It is about control, data ownership, and long-term independence.In

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00:08:10

Advancing Secure Enterprise AI with HPE Private Cloud AI

The Ravit Show ·

2026/04/19

Most enterprise AI projects are still stuck in pilot mode!!! But the real shift happening right now is not about better models. It is about where AI actually runs. I had a great conversation with Sadeepa Wijesekara from Hewlett Packard Enterprise at NVIDIA GTC, and one thing stood out:Private cloud is becoming the foundation for enterprise AI. Not just for control and security, but for actually scaling AI across the business.In this conversation, we discussed:-- Why private cloud is becoming the

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00:14:41

AI Factory Bus Tour

The Ravit Show ·

2026/04/17

I saw something at NVIDIA GTC that genuinely changed how I think about AI. Not another dashboard or abstract demo, but a full AI Factory built inside a bus by DDN. You walk in and suddenly AI is not a concept anymore, it is something you can see, touch, and understand end to end. I spent time on The Ravit Show inside the bus speaking with Jyothi Swaroop and Michelle (Pritoni) Scardino from DDN, and what stood out is how intentional this experience is. They are not just showcasing powerful

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00:14:57

What Is an AI Factory? DDN CEO Alex Bouzari Explains...

The Ravit Show ·

2026/04/16

Everyone at NVIDIA GTC is talking about AI factories. But most people still don’t fully understand what that actually means. I got a chance to sit down with Alex Bouzari, Chairman, Co-Founder and CEO of DDN on The Ravit Show, inside their AI factory bus to break this down in simple terms.What stood out to me from our conversation is this. An AI factory is not just about stacking GPUs or building infrastructure. It is about creating a system where data flows efficiently, models get trained and

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00:04:10

Enterprise AI in Action: Cognizant and AWS...

The Ravit Show ·

2026/04/16

Everyone at #NVIDIAGTC is talking about production AI. I found where to actually see it.Amazon Web Services (AWS) invited their AI Competency partners to demo real world solutions at their booth. My plan is to sit down with each of them and find out what they are building and how enterprises are using it.First up: Hareesh Kommepalli from Cognizant showing a computer vision solution for retail loss prevention.As more retailers move to self-checkout, losses from theft and scanning errors are going up

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00:06:13

Thoughtworks + AWS: Simplifying Enterprise AI

The Ravit Show ·

2026/04/13

AI adoption is not failing because of models. It is failing because of everything around them. At NVIDIA GTC, I spoke with Brian Blanchard from Thoughtworks, on The Ravit Show and this came through clearly.Most enterprises are still missing the basics.- AI-ready data- A proper control plane- Clear operating modelsThoughtworks is tackling this through modernization.From transforming legacy systems to building foundations for agentic AI with strong governance. What stood out is how they are

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00:04:44

Fireworks AI: Fine-Tuning Open Source Models at Scale

The Ravit Show ·

2026/04/10

AI models are easy. Making them useful is hard. At NVIDIA GTC, I had a blast chatting with Roberto Barroso-Luque from Fireworks AI at the Amazon Web Services (AWS) booth. Fireworks helps teams fine-tune open-source models and run them in production. Built on AWS, it gives you scale, speed, and reliability without managing infrastructure.Use cases are already real. Coding assistants. Customer support that resolves issuesYou can access it through AWS. Marketplace or start with an API. From models to

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00:02:23

Zilliz + AWS: Scaling Vector Databases for AI

The Ravit Show ·

2026/04/09

Everyone is talking about AI. But what actually powers it? At NVIDIA GTC, I spoke with Travis White from Zilliz at the Amazon Web Services (AWS) booth. Exciting conversation!!!!We talked about vector databases. The layer that helps AI search through images, videos, and text, not just tables. Zilliz offers Milvus (open source) and a managed version on AWS. That means you can scale, stay secure, and avoid managing infrastructure. Real use cases are already here. Autonomous vehiclesDrug discovery, and

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00:06:12

Building Flexible AI Systems with Deepset and AWS

The Ravit Show ·

2026/04/09

Everyone is building RAG. But the real question is what comes next. At NVIDIA GTC, I spoke with Jay Wilder from deepset, makers of Haystack, and the focus was clear. Moving from RAG to agents. Deepset, the team behind Haystack, is helping developers build flexible AI systems where you can choose your models, data, and guardrails.What stood out was their demo. They showed how RAG pipelines can evolve into agent-based systems by integrating across ecosystems like AWS, NVIDIA, and tools like Weights

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00:05:22

How Do You Trust AI Agents in Production? Deepchecks...

The Ravit Show ·

2026/04/08

One thing I keep thinking about from hashtag#NVIDIAGTC. We are moving too fast in building AI, but not fast enough in validating it. I spoke with David Arakelyan from Deepchecks, and the conversation really came down to trust. Once you move beyond demos, the question is no longer what your AI can do, but whether you can rely on it in production. Deepchecks is focused on this exact problem. Their LLM evaluation and monitoring solution helps teams test and stress their systems before they go live

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00:05:14

Bringing AI to Data with Snowflake Cortex on AWS

The Ravit Show ·

2026/04/07

Everyone at NVIDIA GTC is talking about AI. But my conversation with Vinay Sridhar from Snowflake came down to one thing. AI is only as good as the data behind it.Snowflake is building Cortex, an AI layer that runs directly on governed enterprise data. So instead of moving data to AI, teams bring AI to their data. We also touched on how tools like Cortex Code and text-to-SQL are changing how fast teams can build.And behind all of this is Amazon Web Services (AWS), powering the infrastructure and

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00:05:36

Inside the AWS Marketplace: Deploying Vector...

The Ravit Show ·

2026/04/07

AI agents are everywhere at NVIDIA GTC. But here is what stood out in my conversation with Rudy Chetty from Amazon Web Services (AWS) on The Ravit Show. AWS is leaning heavily into this with Marketplace. A growing hub where you can search, purchase, and deploy AI solutions in minutes. From foundation models to vector databases to monitoring tools, everything is starting to come together in one place.We also talked about the role of partners. Because scaling AI is not a one-company job. It takes an

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00:10:59

Data Quality at Equifax with Anomalo | What Actually...

The Ravit Show ·

2026/04/06

Data quality is still one of the most underestimated problems in AI. Everyone talks about models. Very few talk about whether the data behind those models can actually be trusted. At Gartner D&A, I sat down with Nick Oldham, COO at Equifax, and the conversation was very real. Equifax operates at the center of the global financial ecosystem. That means data integrity is not just a technical problem. It is a business risk. A regulatory risk. A trust problem.What stood out was this shift:- They are

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00:08:38

The Data Quality Crisis No One Talks About

The Ravit Show ·

2026/04/03

We are surrounded by the biggest Data and AI leaders at Gartner. Yet one question keeps coming up. Why are so many AI initiatives still failing? I asked Rich Hoyland, President, Global Field Operations, Anomalo to answer that directly on The Ravit Show at Gartner Orlando.His take was simple.AI does not fail because of ambition.It fails because of bad data.We spoke about:-- Why agentic AI raises the stakes for data quality-- Why speed without trust is a risk for executives-- What data quality failure

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00:10:41

From Messy PDFs to Trusted AI: How bem Powers...

The Ravit Show ·

2026/04/02

At Gartner D&A Day 1, I sat down with Antonio, CEO and Co-Founder of BEM, to talk about a problem many enterprises quietly struggle with.Messy data.While everyone is excited about agents, Antonio made one thing clear.Agents do not work well with unstructured, inconsistent inputs. That is where hallucinations and failures begin.BEM focuses on turning messy inputs, from PDFs and contracts to voice and video, into clean, structured outputs that enterprises can actually trust.We discussed:* Why so

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00:13:24

TextQL vs Legacy BI: Is This the End of Traditional...

The Ravit Show ·

2026/04/01

“Your data is fine. Your AI isn’t good enough.” That is the bold statement behind TextQL, and it immediately caught my attention here at Gartner. I sat down with Ethan Ding, Co-Founder, CEO & Head of Product, TextQL, to unpack what he means by that and why they are challenging many assumptions around BI and analytics.Most enterprises have spent years building ETL pipelines, cleaning data, and preparing dashboards. The belief has been that AI will only work once data is perfectly structured.Ethan

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00:08:21

How Federated Agentic Intelligence Actually Works

The Ravit Show ·

2026/03/31

Most AI analytics platforms assume one thing. Your data lives in one place. Kapil Chhabra, Co-Founder and CPO at WisdomAI on The Ravit Show challenged that assumption immediately. Enterprises are distributed. Their data is fragmented across clouds, warehouses, operational systems, and business units. Forcing everything into a single layer before AI can work is slow and expensive.That is why WisdomAI introduced Federated Agentic Intelligence.Instead of centralizing first and analyzing later, the

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414 results

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