let's now invite another guest up someone who is working on optimizing data in infrastructure for large scale analytics data management and AI all key considerations for technology leaders and Business Leaders a person who needs no introduction the CEO of Google cloud and my brother Thomas [Applause][Music][Applause]kurianwelcome Thomas welcome to n Insight thank you for coming thanks Thomas we were at google. next where we introduced Google Cloud net app volumes uh sort of incredible work that our two teams have collaborated on for many years and where we are seeing significant interest from customers today one of the classes of applications I know which you are investing in significantly are fast scalable and easy to use AI off offerings including an AI platform video and image analysis feat recognition multilanguage processing and so on how are Enterprises currently leveraging Ai and what are the use cases that are delivering value for their businesses and why should Business Leaders bet on Google Cloud to help them Embrace AI you know we've always looked at when we introduce generative AI we said the easiest way for people to think about it is to think of a digital persona for every role that can assist humans in performing the functions and we see customers adopting the technology in two different domains one domain is where they're transforming the core process of the company in assisting people and engaging customers for example Mercedes has changed the way that they're using AI models to help people identify if they're issues with thevehicle Mayo Clinic is using our AI models to synthesize all the information out on the internet as well as from the EHR clinical trial system so when a doctor meets a patient they have all that information in front of them searchable so they can find answers as they talk to the patient price line is reimagining the way that you book travel rather than saying I want to find a hotel room they say why don't you have a digital travel advisor where you can say I'd like to travel to Las Vegas watch two shows and I need to have I'm bringing my kids along so I need a hotel room near the last show so they're changing and there are hundreds of companies doing this they're changing the way they interact with their customers the same thing we also see them transforming the internal processes in a company procurement people are looking at using AI to find contracts that don't have indentification and warranties marketing people are using generative AI to create advertising both images as well as audio and video using models to do that HR people are using it to automate the benefits and HR help desk uh cios are using it to automate the way that their it help desk Works rather than have people have to reset passwords and things like that models are now doing many of these tasks and finally you know we have many companies who are using our AI tools to assist off Engineers to write code to do generate unit tasks to refactor code to document things and so in every role in your working life we're now seeing organizations adopt generative Ai and models to assist people in doing work one of the questions that we get from clients as they consider about you know using their private data with AI tools is how do they deal with security and privacy concerns and things like copyright as AI becomes more mainstream how do you all at Google Cloud help organizations deal with those concerns we've always felt thatwhat generative AI does is take AI out of the domain of a small number of people and make it available to every developer and every user in our organization so we do that by putting together a foundational platform we call vertexhas all the tools that organizations need in order to use AI efficiently it first of all it starts by protecting your data we guarantee that your data is your data and nobody else's it runs in a private virtual VPC no one even Google employees don't have access to your data so as a customer you can build models securely and safely we have a responsibility and safety framework that protects for example models from generating violent images making sure models don't have you know abusive speech in their response so you have all the controls we have 18 types of controls we have grounding to make sure that model answers are grounded in fact and are fresh and current not when the model finished training you have tuning and distillation to shrink the model so that it can be the most efficient cost-wise and also latency wise that it's very quick and then we added search and conversations so that you can use Google search but essentially for your data and you can also build conversational applications both to retrieve information and do tasks on your behalf to expose Enterprise Data Systems we've exposed a technique called embeddings and vectors so you can take data and essentially open it up and for all of those of you who have invested for so many years in storing your information in net app volume volumes think about what we've done as putting Google search in front of all the data you have and opening up conversations so you can essentially chat with your Enterprise data safely and securely so you mentioned vertex Ai and you mentioned some of the awesome advancements you've made how about we actually show our customers and partners the power of vertex AI with NetApp Google Cloud volumes and uh to show you that shall we do that let's do show you that let's bring up iki Ranson VP of Engineering in net apps uh Cloud engineering team this is a live demo there's no you know fake stuff here so iy have at it welcome thanks George uh I'm excited to show you all the incredible things you can do today with verx AI and Neta volumes so let's pick a volume and get started all right up in the corner here I see my volume I see the internal IP address that it has and that it's an NFS share uh it has some folders on it um bunch of files there basically unstructured data now this is a demo about the generative AI capabilities of verx AI when mixed with Neta volumes so let's look at a use case that's simple but real world let's imaginethat we work at the marketing department of an Enterprise company we were just tasked with creating a product landing page that supposed to be ready yesterday now um we can have a look at all of the data that we have here and try and read through all them but luckily we have an AI that can sift through all of our data and find the relevant things so let's ask verx AI about this topic here tell me about Google Cloud Neta volumes the product page is about Neta volumes and almost instantly verx AI finds all the relevant files that you can see down here it generated a summary based on a topic on our private data not publicly available information and it even told us which Pages it used to generate its responses in addition to that it's giving me key insights of each relevant file and with a click or a prompt I can even generate some more like I want to see the summary of all the relevant files here or tell me which people are mentioned within these files this is all possible by vectorizing our unstructured data that's sitting on Neta volumes and in this case we have both the data and the vector database indices on the volume itself ensuring privacy for our data in the cloud now back to our go here um we could go ahead and generate some more information with prompts or we could read all of these files and try to generate the product page but we could also just chat with our data so let's do that cool let's open up a chat here I've uh created some suggestions just to get the conversation going so I want to ask it first to give me two line summary of Google Cloud out of volumes that I can use onthe web page instantly replies great that looks good uh let's do some more what are the key features of Google Cloud net volumes yep took a second key benefits these are all typical things you would find on a product landing page and the last one what are the top five reasons to use Google Cloud net volumesawesome so we are getting all these responses from the AI uh but I want to pull it all together with some code so let's ask vertex AI if it can create that page for me can you create an HTML product page with your responses cool uh so it's going to be pretty boring if I don't have an image solet's use the verx a AI Vision API to generate an image and I'llgive it a prompt here let's give it the prompt Cloud let's say cloud data storage artwork okay cool the HTML is back I can have a look at that yep it's using all of the things that I asked it for key benefits top five reasons great and it's generated an image for me that looks cool uh I want to add that image somewhere in here so I'll add it after the first headline there so I'll ask verx AI if you can do that for me can you add the generated image below the firstheadline in the pageokay now when working with code you can both use the text model or the co- chat model it really just depends on the complexity of what you're working with so once it generates that I'll see if it worked yep look at that it's added the image file right after the first headline but this is live so uh bear with me uh let's save this response to a file and then see what it looks likeboom isn't that just like magic that's pretty amazing whatwe've seen here is you know the power of verx AI with Neta volumes we've seen Vector embedding in search conversational large language models image generation code Generation all on our un unstructured data right on top of net out volumes what about that QR code on the top righthey Pro in the pudding if you scan that QR code you're going to see the page that we just generated everything was live awesome thank you so much it's really powerful to bring together the most advanced AI capabilities in the world with the best unstructured data management capabilities in the world to help you make breakthrough advances so easy and simple I would ask all of you talk to your Google team talk to your netup sales team and let's find a way to use the power of vtex together with your unstructured data one final question Thomas Ai and particularly generative AI consumes massive amounts of energy and requires higher compute power how are you and the team at Google looking to strike the right balance between Ai and maintaining your sustainability objectives you know Google has been carbon neutral since 2007 that's 16 years now we publicly said and we are committed to being carbon free by 2030 and for us it's not a question of AI or sustainability it has to be we have to do both there are manytechniques that we have invented from data center design where data centers to run AI systems can be designed in a different way than data centers to run traditional computation we introduced roughly 6 years ago water cooled AI systems because you get roughly a 30 to 40% lift in overall throughput and machine efficiency we've invested in many techniques on compilers for example to really speed up both serving or inferencing and training and more recently we've also introduced techniques like distillation so for example if you're part of a preview you can use a model that has many of the skills that our AI system has to write but you can actually run it on Gmail when you type help me write and it runs directly on the Android iOS phone so it's because we've Shrunk the skills down all of that is designed to reduce the cost of power consumption the amount of power consumption and also to improve the latency and efficiency you saw how quick the model was in responding smaller models are better in terms of latency and responsiveness as well and so I would encourage all of you to try some of these capabilities if you saw the demo there was no coding or anything required the models allow you to interact with them just using text and we're opening it up for everybody to do these things with our deep partnership between net app and Google Cloud thank you for coming to net app Insight Thomas I'm happy we got to share more about our partnership and looking forward to our continued joint success with Google Cloud netup volumes you have an amazing solution for any general file use case like VMware sap Enterprise applications and databases and also as a platform to help you accelerate the use of advanced AI capabilities like vertex AI with your existing private data