The Ravit Show

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 deployed faster, and outcomes are measurable.

We also spoke about why DDN chose to bring this concept to life through a physical, mobile experience instead of a traditional booth. When you walk through it, you see the full pipeline in action, not just slides or demos. It makes the idea of an AI factory much more real.

Another key part of the conversation was around real-world use cases. From inference and RAG to genomics and video analytics, one thing became clear. The biggest bottleneck is not models. It is how data is handled, moved, and made usable across systems.

And then there is the shift toward physical AI. With robotics, simulation, and real-world systems, AI is no longer just producing digital outputs. It is starting to interact with the physical world, which changes how we think about infrastructure, latency, and reliability.

If there is one takeaway, it is this. Scaling AI is not about adding more compute. It is about building systems that can turn data into outcomes efficiently.

#ai #data #aifactory #nvidiagtc #ddn #api #aifactory #theravitshow

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.

Cognizant is combining #NVIDIA computer vision with #AWS to help retailers catch those losses as they happen.

Cognizant is one of the world's leading professional services companies and they have 25 listings on AWS Marketplace. That tells you something. Retail is just one example. They are working with enterprises on use cases like real time call translation for contact centers, AI agents for SAP, intelligent document processing for insurance, data clean rooms for sports sponsorship, and agentic AI for travel.

Check out their listings: https://aws.amazon.com/marketplace/seller-profile?id=2a641c19-3444-4890-9738-e82a8ea39302&trk=5004eff9-71db-4806-9d01-fd7db0dd46bb&sc_channel=el

More AWS AI Competency partners coming throughout the show. Stay tuned.

#data #ai #awspartner #cognizant #awsmarketplace #retail #theravitshow

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 models

Thoughtworks 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 simplifying complexity. Instead of stitching together multiple tools, they are bringing it into one platform. And all of this is built on Amazon Web Services (AWS), using services like SageMaker and Bedrock, with solutions available on AWS Marketplace.

This is the real shift. AI is not just a technology problem. It is a systems and operations problem.

Check out the video and learn more!!!!

#data #ai #awspartner #nvidiagtc #theravitshow

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 issues

You can access it through AWS. Marketplace or start with an API. From models to real applications.

#data #ai #AWSPartner #NVIDIAGTC #fireworks #api #models #theravitshow

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 vehicles

Drug discovery, and a few more

You can also find Zilliz on AWS Marketplace and get started quickly. Simple idea. AI is not just models. It is the data layer underneath. Learn more from the conversation!!!!

#data #ai #awspartner #nvidiagtc #theravitshow

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 & Biases. This is where things get real.

In banking, workflows that took weeks are now being done in hours.

In pharma, teams are testing and iterating on complex data pipelines much faster.

And all of this is built with flexibility in mind. Not locked into one stack. With Amazon Web Services (AWS) as a long-time partner and availability through AWS Marketplace, it is becoming easier for teams to get started and scale.

This is the shift I am seeing. From static pipelines to adaptive AI systems.

#data #ai #awspartner #NVIDIAGTC #deepset #api #haystack #theravitshow

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. What stood out was their new feature, Know Your Agent, which lets you generate a full report on your AI system with just an API key and understand where it can break.

They are also one of the few solutions integrated directly into AWS SageMaker as a partner app and available on AWS Marketplace, making it easier for teams to bring this layer into their workflows.

What do you think about it?

#data #ai #awspartner #NVIDIAGTC #deepcheck #api #evals #theravitshow

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 scale.

This is the shift. From models to data-driven AI systems. Learn more from the conversation!!!!

#data #ai #AWSPartner #NVIDIAGTC #snowflake #NVIDIAGTC #api #models #theravitshow

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 ecosystem. AWS provides the infrastructure.

More from the AWS Marketplace Kiosk at GTC.

#data #ai #awspartner #nvidiagtc #nvidiagtc2026 #api #awsmarketplace #theravitshow

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 not treating data quality as a one-time cleanup anymore.

- They are building systems to monitor, detect, and fix issues continuously.

That is where platforms like Anomalo come in.

Instead of reacting to broken dashboards or failed pipelines, the goal is simple

Catch issues before they impact the business. And this becomes even more critical as AI enters the picture. Because AI systems do not fail loudly. They fail quietly when the data is wrong.

Nick also shared how their journey was not just about tools. The harder part was organizational.

- Aligning teams on what “good data” actually means

- Moving from siloed ownership to shared accountability

- Bridging the gap between data strategy and real execution

Looking ahead, with investments in Google Cloud and tools like Dataplex, the direction is clear

More automation

More observability

Less manual firefighting

If you are building AI without solving for data integrity first, you are building on weak foundations.

If this topic interests you, Nick will be going deeper into this at an upcoming session: The Road to Self-Driving Data, April 2 go for it

https://engage.anomalo.com/the-road-to-self-driving-data

This is one of those conversations that is less about hype and more about what it actually takes to make data work at scale.

#data #ai #anomalo #dataquality #theravitshow