Building for a Real-time Data Future_Subbu Iyer.pdf
•
0 likes•57 views
This document discusses the history and future of artificial intelligence and how real-time data is fueling innovation. It summarizes that AI is driving smarter decisions across many industries and that AI needs real-time data to provide context and accuracy, leading to better decisions. The document also notes that AI demands a real-time data platform that can provide unlimited scale, low latency, and high performance.
Report
Share
Report
Share
Download to read offline
Recommended
Six IIoT Success Stories Powered by the PI System
See 6 examples of how OSIsoft's customers are using the PI System to strategically leverage the Industrial Internet of Things (IIoT). Discover how wireless sensors and edge gateway computers are enabling companies to connect with their industrial assets in a new and innovative way.
CWIN16 UK Event - The Future of Infrastructure
What technologies made the biggest impact and which ones will impact us in the future? Will technology advances slow down, stay the same of speed up? What trends and technologies should I consider?
The Digital agenda, shifting business models, as well as the need for speed at lower cost are impacting, shaping and forming new technologies; creating new opportunities at an ever increasing pace.
During the 30 min presentation Gunnar will outline the various key infrastructure related trends and technologies that are and will be key going forward.
AWS O&G Day - Ambyint and AWS
The document discusses challenges in the oil and gas industry with legacy equipment and the need for scalable IoT solutions. It proposes that AWS IoT architecture can address issues of security, scalability and integrating old and new devices by connecting things at the edge to analytics and computing resources in the cloud. Examples are given of how Ambyint has used high-resolution sensor data and machine learning on AWS to develop autonomous solutions for well optimization, improving productivity and reducing costs.
巨量資料入門 The evolution of data architecture
There’s been a great interest in applying Data Science and Machine Learning algorithms for the insight from data lately. Fundamentally, these techniques are only made practical by today’s scale-out Modern Data Architecture, which enables these algorithms to perform computation at massive scale economically.
The focus of this talk is on the scale-out architecture, pioneered by Google. Initially a niche system architecture that is only applicable to Google, the systems built on top of the same principles are used in production across many industries, empowering enterprises to get better insights into their business, to become more agile and to do more things that were not possible previously.
I will start the talk by providing the historical context behind the evolution of data architecture, and then dive into the technical details of the scale-out system, Hadoop and its ecosystem. Afterwards, I will present a few notable production use cases of the system. Finally, I will touch upon some of the exciting challenges and opportunities lying ahead for the future data architecture.
How AWS can help you on quality and data products
This document discusses how AWS can help with quality and data products. It provides an overview of AWS capabilities for data analytics including machine learning, artificial intelligence, and big data. It also discusses how these capabilities can help industries like manufacturing through use cases like predictive maintenance, production quality monitoring, and real-time process optimization. Finally, it presents a case study of a discrete manufacturing company using IoT and edge computing on AWS to connect machines and sensors for issues detection and root cause analysis.
What is aerospike database and why is it vastly superior to other database an...
This document discusses Aerospike's hyperscale data solutions and its advantages over other NoSQL solutions. It highlights Aerospike's superior reliability and persistence, uniquely hyperscale architecture, proven adoption by industry pioneers, and ability to eliminate costs and complexity. It also discusses Aerospike's patented flash-optimized storage layer, multi-threaded massively parallel processing, and self-healing clusters. The document positions Aerospike as simplifying legacy architectures while solving scaling problems for enterprises.
Supermicro AI Pod that’s Super Simple, Super Scalable, and Super Affordable
The worlds of HPC and AI are evolving at a tremendous rate. The demands of modern-day applications put immense pressure on local IT teams and resources. More often than not, this pressure can come from requiring an AI strategy to speed up mission-critical applications - but this can come at a cost which can hinder adoption. In this webinar, Supermicro, together with International Computer Concepts (ICC) and Define Tech, will demonstrate their AI Super Pod that delivers on AI strategy needs without breaking the bank.
The Future of Infrastructure: Key Trends to consider
Gunnar Menzel Vice President, Chief Architect - Capgemini
Which technologies have made the biggest impact, and which ones will impact us greatest in the future? Will technology advances slow down, stay the same, or speed-up? Which trends and technologies should I consider? The Digital Agenda; shifting business models; and the need for speed at lower cost are impacting, shaping and forming new technologies – creating new opportunities at an ever-increasing pace. Gunnar will outline the various infrastructure-related trends and technologies that are currently key, in addition to those that will prove to be significant going forward.
Recommended
Six IIoT Success Stories Powered by the PI System
See 6 examples of how OSIsoft's customers are using the PI System to strategically leverage the Industrial Internet of Things (IIoT). Discover how wireless sensors and edge gateway computers are enabling companies to connect with their industrial assets in a new and innovative way.
CWIN16 UK Event - The Future of Infrastructure
What technologies made the biggest impact and which ones will impact us in the future? Will technology advances slow down, stay the same of speed up? What trends and technologies should I consider?
The Digital agenda, shifting business models, as well as the need for speed at lower cost are impacting, shaping and forming new technologies; creating new opportunities at an ever increasing pace.
During the 30 min presentation Gunnar will outline the various key infrastructure related trends and technologies that are and will be key going forward.
AWS O&G Day - Ambyint and AWS
The document discusses challenges in the oil and gas industry with legacy equipment and the need for scalable IoT solutions. It proposes that AWS IoT architecture can address issues of security, scalability and integrating old and new devices by connecting things at the edge to analytics and computing resources in the cloud. Examples are given of how Ambyint has used high-resolution sensor data and machine learning on AWS to develop autonomous solutions for well optimization, improving productivity and reducing costs.
巨量資料入門 The evolution of data architecture
There’s been a great interest in applying Data Science and Machine Learning algorithms for the insight from data lately. Fundamentally, these techniques are only made practical by today’s scale-out Modern Data Architecture, which enables these algorithms to perform computation at massive scale economically.
The focus of this talk is on the scale-out architecture, pioneered by Google. Initially a niche system architecture that is only applicable to Google, the systems built on top of the same principles are used in production across many industries, empowering enterprises to get better insights into their business, to become more agile and to do more things that were not possible previously.
I will start the talk by providing the historical context behind the evolution of data architecture, and then dive into the technical details of the scale-out system, Hadoop and its ecosystem. Afterwards, I will present a few notable production use cases of the system. Finally, I will touch upon some of the exciting challenges and opportunities lying ahead for the future data architecture.
How AWS can help you on quality and data products
This document discusses how AWS can help with quality and data products. It provides an overview of AWS capabilities for data analytics including machine learning, artificial intelligence, and big data. It also discusses how these capabilities can help industries like manufacturing through use cases like predictive maintenance, production quality monitoring, and real-time process optimization. Finally, it presents a case study of a discrete manufacturing company using IoT and edge computing on AWS to connect machines and sensors for issues detection and root cause analysis.
What is aerospike database and why is it vastly superior to other database an...
This document discusses Aerospike's hyperscale data solutions and its advantages over other NoSQL solutions. It highlights Aerospike's superior reliability and persistence, uniquely hyperscale architecture, proven adoption by industry pioneers, and ability to eliminate costs and complexity. It also discusses Aerospike's patented flash-optimized storage layer, multi-threaded massively parallel processing, and self-healing clusters. The document positions Aerospike as simplifying legacy architectures while solving scaling problems for enterprises.
Supermicro AI Pod that’s Super Simple, Super Scalable, and Super Affordable
The worlds of HPC and AI are evolving at a tremendous rate. The demands of modern-day applications put immense pressure on local IT teams and resources. More often than not, this pressure can come from requiring an AI strategy to speed up mission-critical applications - but this can come at a cost which can hinder adoption. In this webinar, Supermicro, together with International Computer Concepts (ICC) and Define Tech, will demonstrate their AI Super Pod that delivers on AI strategy needs without breaking the bank.
The Future of Infrastructure: Key Trends to consider
Gunnar Menzel Vice President, Chief Architect - Capgemini
Which technologies have made the biggest impact, and which ones will impact us greatest in the future? Will technology advances slow down, stay the same, or speed-up? Which trends and technologies should I consider? The Digital Agenda; shifting business models; and the need for speed at lower cost are impacting, shaping and forming new technologies – creating new opportunities at an ever-increasing pace. Gunnar will outline the various infrastructure-related trends and technologies that are currently key, in addition to those that will prove to be significant going forward.
AI in the enterprise
The document discusses AI in the enterprise, including use cases, infrastructure considerations, and the AI lifecycle. It provides examples of how AI can be applied in various industries and common patterns of analytics using AI. It also outlines the data science model development workflow and considerations for AI infrastructure, software, and data management throughout the AI lifecycle.
Predictive Maintenance by analysing acoustic data in an industrial environment
This document discusses predictive maintenance through acoustic data analysis in an industrial setting. It describes using sensors and data collection from machines to detect potential issues through acoustic and vibration analysis. The customer case study involves implementing a predictive maintenance platform using acoustic data from an air compressor to identify mechanical, electrical, and other problems to decrease maintenance costs and increase machine availability. The solution involves collecting machine and sensor data, storing it in an IIoT platform, and performing analytics using predictive models and dashboards.
Amazon Kinesis - Building Serverless real-time solution - Tel Aviv Summit 2018
Amazon Kinesis Streams was born of necessity, to enable Amazon Web Services to capture millions of individual metering records per second from AWS services and EC2 instances and aggregate these records by account identifier to produce a customer billing record in real time. Today, Kinesis is a foundational service which over a dozen AWS and Amazon retail services use to capture and process streaming data.
Since the launch of Kinesis Streams, Amazon has worked with customers as their stream processing needs have evolved, subsequently launching Kinesis Firehose—which enables customers to capture streaming data, perform in-line processing to clean, format, and deliver this data to service destinations, such as S3, Redshift, Elasticsearch, and Lambda, in minutes—and Kinesis Analytics—which enables customers to process streaming data in real time using ANSI SQL..
Today, Kinesis data streaming services are foundational for business critical workflows, providing customers with a new way to process big data and extract actionable insights. In this session, we offer an overview of Kinesis, Amazon’s data streaming platform—highlighting key architectural features—and explains how customers have architected their applications using Kinesis services for low-latency and extreme scale. We will also demonstrate how to build an end-to-end solution using the latest and greatest AWS Data and analytics services like Athena, Glue, Lambda and more.
Dell AI Oil and Gas Webinar
The document discusses artificial intelligence (AI) and data analytics opportunities in the oil and gas industry. It provides examples of how AI can be used for virtual assistants, video analytics, fleet management, production optimization, preventative maintenance, and precision drilling. The benefits of these applications include increased profitability, risk mitigation, improved agility, and cost reductions. It also discusses Dell Technologies AI and HPC solutions that can enable oil and gas companies to leverage AI for applications like reservoir modeling and autonomous vehicles.
"The Future of Manufacturing" by Sujeet Chand, SVP&CTO, Rockwell Automation
This talk was part of The Hive Annual Summit 2017.
You can watch Chand’s talk on a YouTube HiveMumble channel.
Artificial Intelligence: Context of application of AI in Chemicals
1) Artificial intelligence is transforming industries like chemicals, oil and gas by automating processes, augmenting human workers, and enabling new innovations.
2) AI is being applied to improve operations like reducing defects at manufacturing plants by using data to optimize conditions and product quality.
3) A cognitive plant uses AI techniques like machine learning, predictive modeling and intelligent search of historical data to help operators leverage data science for better decision making.
Big Data - A Real Life Revolution
Presented by Manuel Sevilla, Global CTO Business Information Management
April 2014, Teradata Universe
Cognitive IoT Platform as Enabler of the Smart Factory
The document discusses how cognitive IoT platforms can enable smart factories. It notes that increasing demand for customization is driving Industry 4.0 trends. It then provides examples of how IBM's cognitive IoT platform gathers data, visualizes patterns, performs analytics, and infuses solutions with cognitive capabilities. Specific use cases discussed include predictive quality inspection, field advisors, and virtual/augmented reality applications. The platform aims to drive both operational excellence internally and new revenue streams externally for manufacturers.
Miguel Angel Perdiguero - Head of BIG data & analytics Atos Iberia - semanain...
This document discusses Industry 4.0 and the digital transformation of industry. It describes key technological pillars like the Internet of Things, additive manufacturing, and data analytics. It provides examples of how these technologies can be applied through predictive maintenance and customized products. The document also introduces Atos Codex, an open industrial analytics platform that uses big data, high performance computing, and machine learning to deliver business insights and solutions.
Getting Microservices and Legacy to Play Nicely Together with Event-Driven Ar...
The document discusses techniques for modernizing legacy systems, including digital decoupling. Digital decoupling aims to isolate legacy systems to break the cycle of increasing costs when adding features. It unlocks constrained legacy data and delivers new business value on a modern cloud architecture. This allows replacing the core systems over time while continuously delivering value. The key techniques discussed are using microservices, change data capture, event-driven architectures, and domain-driven design to begin digitally decoupling legacy systems.
Ahluwalia ibm up con keynote (published)
This document summarizes a keynote talk given by Gurvinder Singh Ahluwalia (Guri), CTO of Cloud Computing at IBM, about IBM's cloud portfolio. The talk discusses how technology disruptions like cloud computing, mobile devices, and big data are impacting businesses. It outlines IBM's response to help clients think about, build, and tap into cloud solutions through its end-to-end cloud portfolio including public, private and hybrid cloud offerings. Specific examples discussed include workload analysis and migration to cloud, high performance computing, and IBM's acquisition of SoftLayer to gain infrastructure as a service capabilities.
Deploying Massive Scale Graphs for Realtime Insights
Graph databases have been at the forefront of helping organizations manage and generate insights from data relationships, and applying those insights in real-time to drive competitive advantage. As organizations gain value in deploying graph databases, the data volumes managed are growing exponentially pushing the limits of large-scale in-memory graph processing. Neo4j and IBM Power Systems combined forces to deliver a market leading scalable graph database platform capable of affordably storing and processing graphs of extremely large size and offering real-time insights, using flash and FPGA accelerators. In this session we will cover the use cases driving the need for this extremely scalable platform and how this platform offers an easy to deploy model for extreme scale graph databases.
Dell NVIDIA AI Roadshow - South Western Ontario
- Artificial intelligence (AI) is mimicking human intelligence through machine algorithms like those used for chess and facial recognition. Machine learning (ML) is a subset of AI that uses algorithms to parse data, learn from data, and make predictions. Deep learning (DL) uses artificial neural networks to develop relationships in data and is used for applications like driverless cars and cybersecurity.
- AI technologies are enabling digital transformation and require infrastructure like edge computing, GPUs, FPGAs, deep learning accelerators, and specialized hardware to power applications of AI, ML, and DL. Dell Technologies provides platforms and solutions to accelerate AI workloads and support digital transformation.
Powering the Internet of Things with Apache Hadoop
Without the right data management strategy, investments in Internet of Things (IoT) can yield limited results. Apache Hadoop has emerged as a key architectural component that can help make sense of IoT data, enabling never before seen data products and solutions.
Integrate the AWS Cloud with Responsive Xilinx Machine Learning at the Edge (...
In this workshop, learn how you can integrate Xilinx edge machine learning with massive scale AWS Cloud analytics, machine learning model building, and dashboards. Based on an Oil & Gas scenario, you will learn how to combine AWS Cloud services with AWS Greengrass on Zynq Ultrascale+ and Amazon FreeRTOS on Xilinx Zynq-7000. After this workshop, you will have a concrete understanding of Machine Learning applicability at the edge and its relationship with the AWS Cloud.
Data warehouse modernization programme by TOBY WOOLFE at Big Data Spain 2014
General Motors (GM) is in the process of constructing a single global information warehouse that will become the foundation for all business analytics and decision support across the enterprise.
How Can Edge Computing and IoT Transform Your Business?
Level: Introductory
The infinite computing power of cloud is creating new business models and driving operational efficiencies in every sector. But how can you extend cloud capabilities to the edge? Join this webinar for real-world examples of how AWS customers are exploiting both IoT data and the power of the cloud. We'll also discuss how you can deploy analytics and machine learning at the edge through AWS building blocks such as AWS Greengrass and Amazon Sagemaker.
Customer use cases to be explored include:
- Nokia optimises communications to oil platforms by processing data nearer to the source
- Stanley Black&Decker performs predictive maintenance by identifying faulty parts before they fail
- Pentair overcomes intermittent connectivity issues to automate its water filtration plants
Who Should Attend: Business Directors, Business Leaders, Project Managers, IT Managers, Business Consultants, Heads of Innovation, Data Scientists and Product Marketeers.
How to build containerized architectures for deep learning - Data Festival 20...
When it comes to AI data scientists/engineers tend to focus on tools. Though the data platform that enables these tools is equally important, it’s often overlooked. In fact, 90% of the effort required for success in ML is not the algorithm – it’s the data logistics. In this workshop we will talk about common architecture blueprints to integrate AI in your data centers and how the right data platform choice can make all the difference in launching your AI use case into production! Presented at Data Festival Munich, 2019.
The value of the platform play in real world use cases Software AG cwin18 tou...
Software AG Cumulocity IoT and Capgemini key enablers to to go beyond the current paradigms and transform the business by seamlessly combining people, things and differentiation.
Omniverse for the Metaverse
The document provides predictions for advancements in AI technology in 2023, including:
1) Large-scale digital twins and generative AI transforming production applications and customer service.
2) Coupling of large language models with the ability to describe biology and chemistry for drug discovery.
3) Photorealistic simulation combining with generative AI to create scenarios for training robust autonomous systems.
4) Increasing robot deployment with human interaction through learning safe operation and environments.
What a Modern Database Enables_Srini Srinivasan.pdf
Learn about our founding design principles from the Aerospike CTO and Founder, Srini Srinivasan, and how Aerospike avoided tradeoffs other systems seem unable to avoid. Hear about our foundational design centers for leveraging processor, storage, and network advances to the limit, network route + connection model optimization, self-managing clustering capabilities, hyper parallelism, and geo-distributed transaction capabilities - and why they make all the difference for Aerospike customers. Learn how we plan to bring our advantages to bear for building AI/ML applications that are key to the future.
Aerospike & Unity_Connecting Developer Communities_Matt Dondelinger and Stace...
Unity Ads is the ad monetization solution for mobile games from Unity Technologies. It enables mobile game developers to monetize their entire player base, via ads that are native to Unity-based games. As a Unity Senior Dev Advocate, Matt Dondelinger is an expert in monetization and he shares his perspective on Aerospike, which powers the real-time data that helps players make better decisions. He’ll also share his viewpoint on the Future of Gaming and how connecting with the Developer Relations team at Aerospike has created new opportunities to educate and connect with developers to build better.
More Related Content
Similar to Building for a Real-time Data Future_Subbu Iyer.pdf
AI in the enterprise
The document discusses AI in the enterprise, including use cases, infrastructure considerations, and the AI lifecycle. It provides examples of how AI can be applied in various industries and common patterns of analytics using AI. It also outlines the data science model development workflow and considerations for AI infrastructure, software, and data management throughout the AI lifecycle.
Predictive Maintenance by analysing acoustic data in an industrial environment
This document discusses predictive maintenance through acoustic data analysis in an industrial setting. It describes using sensors and data collection from machines to detect potential issues through acoustic and vibration analysis. The customer case study involves implementing a predictive maintenance platform using acoustic data from an air compressor to identify mechanical, electrical, and other problems to decrease maintenance costs and increase machine availability. The solution involves collecting machine and sensor data, storing it in an IIoT platform, and performing analytics using predictive models and dashboards.
Amazon Kinesis - Building Serverless real-time solution - Tel Aviv Summit 2018
Amazon Kinesis Streams was born of necessity, to enable Amazon Web Services to capture millions of individual metering records per second from AWS services and EC2 instances and aggregate these records by account identifier to produce a customer billing record in real time. Today, Kinesis is a foundational service which over a dozen AWS and Amazon retail services use to capture and process streaming data.
Since the launch of Kinesis Streams, Amazon has worked with customers as their stream processing needs have evolved, subsequently launching Kinesis Firehose—which enables customers to capture streaming data, perform in-line processing to clean, format, and deliver this data to service destinations, such as S3, Redshift, Elasticsearch, and Lambda, in minutes—and Kinesis Analytics—which enables customers to process streaming data in real time using ANSI SQL..
Today, Kinesis data streaming services are foundational for business critical workflows, providing customers with a new way to process big data and extract actionable insights. In this session, we offer an overview of Kinesis, Amazon’s data streaming platform—highlighting key architectural features—and explains how customers have architected their applications using Kinesis services for low-latency and extreme scale. We will also demonstrate how to build an end-to-end solution using the latest and greatest AWS Data and analytics services like Athena, Glue, Lambda and more.
Dell AI Oil and Gas Webinar
The document discusses artificial intelligence (AI) and data analytics opportunities in the oil and gas industry. It provides examples of how AI can be used for virtual assistants, video analytics, fleet management, production optimization, preventative maintenance, and precision drilling. The benefits of these applications include increased profitability, risk mitigation, improved agility, and cost reductions. It also discusses Dell Technologies AI and HPC solutions that can enable oil and gas companies to leverage AI for applications like reservoir modeling and autonomous vehicles.
"The Future of Manufacturing" by Sujeet Chand, SVP&CTO, Rockwell Automation
This talk was part of The Hive Annual Summit 2017.
You can watch Chand’s talk on a YouTube HiveMumble channel.
Artificial Intelligence: Context of application of AI in Chemicals
1) Artificial intelligence is transforming industries like chemicals, oil and gas by automating processes, augmenting human workers, and enabling new innovations.
2) AI is being applied to improve operations like reducing defects at manufacturing plants by using data to optimize conditions and product quality.
3) A cognitive plant uses AI techniques like machine learning, predictive modeling and intelligent search of historical data to help operators leverage data science for better decision making.
Big Data - A Real Life Revolution
Presented by Manuel Sevilla, Global CTO Business Information Management
April 2014, Teradata Universe
Cognitive IoT Platform as Enabler of the Smart Factory
The document discusses how cognitive IoT platforms can enable smart factories. It notes that increasing demand for customization is driving Industry 4.0 trends. It then provides examples of how IBM's cognitive IoT platform gathers data, visualizes patterns, performs analytics, and infuses solutions with cognitive capabilities. Specific use cases discussed include predictive quality inspection, field advisors, and virtual/augmented reality applications. The platform aims to drive both operational excellence internally and new revenue streams externally for manufacturers.
Miguel Angel Perdiguero - Head of BIG data & analytics Atos Iberia - semanain...
This document discusses Industry 4.0 and the digital transformation of industry. It describes key technological pillars like the Internet of Things, additive manufacturing, and data analytics. It provides examples of how these technologies can be applied through predictive maintenance and customized products. The document also introduces Atos Codex, an open industrial analytics platform that uses big data, high performance computing, and machine learning to deliver business insights and solutions.
Getting Microservices and Legacy to Play Nicely Together with Event-Driven Ar...
The document discusses techniques for modernizing legacy systems, including digital decoupling. Digital decoupling aims to isolate legacy systems to break the cycle of increasing costs when adding features. It unlocks constrained legacy data and delivers new business value on a modern cloud architecture. This allows replacing the core systems over time while continuously delivering value. The key techniques discussed are using microservices, change data capture, event-driven architectures, and domain-driven design to begin digitally decoupling legacy systems.
Ahluwalia ibm up con keynote (published)
This document summarizes a keynote talk given by Gurvinder Singh Ahluwalia (Guri), CTO of Cloud Computing at IBM, about IBM's cloud portfolio. The talk discusses how technology disruptions like cloud computing, mobile devices, and big data are impacting businesses. It outlines IBM's response to help clients think about, build, and tap into cloud solutions through its end-to-end cloud portfolio including public, private and hybrid cloud offerings. Specific examples discussed include workload analysis and migration to cloud, high performance computing, and IBM's acquisition of SoftLayer to gain infrastructure as a service capabilities.
Deploying Massive Scale Graphs for Realtime Insights
Graph databases have been at the forefront of helping organizations manage and generate insights from data relationships, and applying those insights in real-time to drive competitive advantage. As organizations gain value in deploying graph databases, the data volumes managed are growing exponentially pushing the limits of large-scale in-memory graph processing. Neo4j and IBM Power Systems combined forces to deliver a market leading scalable graph database platform capable of affordably storing and processing graphs of extremely large size and offering real-time insights, using flash and FPGA accelerators. In this session we will cover the use cases driving the need for this extremely scalable platform and how this platform offers an easy to deploy model for extreme scale graph databases.
Dell NVIDIA AI Roadshow - South Western Ontario
- Artificial intelligence (AI) is mimicking human intelligence through machine algorithms like those used for chess and facial recognition. Machine learning (ML) is a subset of AI that uses algorithms to parse data, learn from data, and make predictions. Deep learning (DL) uses artificial neural networks to develop relationships in data and is used for applications like driverless cars and cybersecurity.
- AI technologies are enabling digital transformation and require infrastructure like edge computing, GPUs, FPGAs, deep learning accelerators, and specialized hardware to power applications of AI, ML, and DL. Dell Technologies provides platforms and solutions to accelerate AI workloads and support digital transformation.
Powering the Internet of Things with Apache Hadoop
Without the right data management strategy, investments in Internet of Things (IoT) can yield limited results. Apache Hadoop has emerged as a key architectural component that can help make sense of IoT data, enabling never before seen data products and solutions.
Integrate the AWS Cloud with Responsive Xilinx Machine Learning at the Edge (...
In this workshop, learn how you can integrate Xilinx edge machine learning with massive scale AWS Cloud analytics, machine learning model building, and dashboards. Based on an Oil & Gas scenario, you will learn how to combine AWS Cloud services with AWS Greengrass on Zynq Ultrascale+ and Amazon FreeRTOS on Xilinx Zynq-7000. After this workshop, you will have a concrete understanding of Machine Learning applicability at the edge and its relationship with the AWS Cloud.
Data warehouse modernization programme by TOBY WOOLFE at Big Data Spain 2014
General Motors (GM) is in the process of constructing a single global information warehouse that will become the foundation for all business analytics and decision support across the enterprise.
How Can Edge Computing and IoT Transform Your Business?
Level: Introductory
The infinite computing power of cloud is creating new business models and driving operational efficiencies in every sector. But how can you extend cloud capabilities to the edge? Join this webinar for real-world examples of how AWS customers are exploiting both IoT data and the power of the cloud. We'll also discuss how you can deploy analytics and machine learning at the edge through AWS building blocks such as AWS Greengrass and Amazon Sagemaker.
Customer use cases to be explored include:
- Nokia optimises communications to oil platforms by processing data nearer to the source
- Stanley Black&Decker performs predictive maintenance by identifying faulty parts before they fail
- Pentair overcomes intermittent connectivity issues to automate its water filtration plants
Who Should Attend: Business Directors, Business Leaders, Project Managers, IT Managers, Business Consultants, Heads of Innovation, Data Scientists and Product Marketeers.
How to build containerized architectures for deep learning - Data Festival 20...
When it comes to AI data scientists/engineers tend to focus on tools. Though the data platform that enables these tools is equally important, it’s often overlooked. In fact, 90% of the effort required for success in ML is not the algorithm – it’s the data logistics. In this workshop we will talk about common architecture blueprints to integrate AI in your data centers and how the right data platform choice can make all the difference in launching your AI use case into production! Presented at Data Festival Munich, 2019.
The value of the platform play in real world use cases Software AG cwin18 tou...
Software AG Cumulocity IoT and Capgemini key enablers to to go beyond the current paradigms and transform the business by seamlessly combining people, things and differentiation.
Omniverse for the Metaverse
The document provides predictions for advancements in AI technology in 2023, including:
1) Large-scale digital twins and generative AI transforming production applications and customer service.
2) Coupling of large language models with the ability to describe biology and chemistry for drug discovery.
3) Photorealistic simulation combining with generative AI to create scenarios for training robust autonomous systems.
4) Increasing robot deployment with human interaction through learning safe operation and environments.
Similar to Building for a Real-time Data Future_Subbu Iyer.pdf (20)
Predictive Maintenance by analysing acoustic data in an industrial environment
Predictive Maintenance by analysing acoustic data in an industrial environment
Amazon Kinesis - Building Serverless real-time solution - Tel Aviv Summit 2018
Amazon Kinesis - Building Serverless real-time solution - Tel Aviv Summit 2018
"The Future of Manufacturing" by Sujeet Chand, SVP&CTO, Rockwell Automation
"The Future of Manufacturing" by Sujeet Chand, SVP&CTO, Rockwell Automation
Artificial Intelligence: Context of application of AI in Chemicals
Artificial Intelligence: Context of application of AI in Chemicals
Cognitive IoT Platform as Enabler of the Smart Factory
Cognitive IoT Platform as Enabler of the Smart Factory
Miguel Angel Perdiguero - Head of BIG data & analytics Atos Iberia - semanain...
Miguel Angel Perdiguero - Head of BIG data & analytics Atos Iberia - semanain...
Getting Microservices and Legacy to Play Nicely Together with Event-Driven Ar...
Getting Microservices and Legacy to Play Nicely Together with Event-Driven Ar...
Deploying Massive Scale Graphs for Realtime Insights
Deploying Massive Scale Graphs for Realtime Insights
Powering the Internet of Things with Apache Hadoop
Powering the Internet of Things with Apache Hadoop
Integrate the AWS Cloud with Responsive Xilinx Machine Learning at the Edge (...
Integrate the AWS Cloud with Responsive Xilinx Machine Learning at the Edge (...
Data warehouse modernization programme by TOBY WOOLFE at Big Data Spain 2014
Data warehouse modernization programme by TOBY WOOLFE at Big Data Spain 2014
How Can Edge Computing and IoT Transform Your Business?
How Can Edge Computing and IoT Transform Your Business?
How to build containerized architectures for deep learning - Data Festival 20...
How to build containerized architectures for deep learning - Data Festival 20...
The value of the platform play in real world use cases Software AG cwin18 tou...
The value of the platform play in real world use cases Software AG cwin18 tou...
More from Aerospike, Inc.
What a Modern Database Enables_Srini Srinivasan.pdf
Learn about our founding design principles from the Aerospike CTO and Founder, Srini Srinivasan, and how Aerospike avoided tradeoffs other systems seem unable to avoid. Hear about our foundational design centers for leveraging processor, storage, and network advances to the limit, network route + connection model optimization, self-managing clustering capabilities, hyper parallelism, and geo-distributed transaction capabilities - and why they make all the difference for Aerospike customers. Learn how we plan to bring our advantages to bear for building AI/ML applications that are key to the future.
Aerospike & Unity_Connecting Developer Communities_Matt Dondelinger and Stace...
Unity Ads is the ad monetization solution for mobile games from Unity Technologies. It enables mobile game developers to monetize their entire player base, via ads that are native to Unity-based games. As a Unity Senior Dev Advocate, Matt Dondelinger is an expert in monetization and he shares his perspective on Aerospike, which powers the real-time data that helps players make better decisions. He’ll also share his viewpoint on the Future of Gaming and how connecting with the Developer Relations team at Aerospike has created new opportunities to educate and connect with developers to build better.
App Modernization with Aerospike as an Intraday System of Record_Venkat Thamm...
1) Charles Schwab modernized its trading architecture to use Aerospike as an intraday system of record, moving applications from the mainframe to .NET on distributed databases.
2) The modernization strategy involved 3 phases - migrating all read applications, then write applications, and building new capabilities with Aerospike as the system of record.
3) Current stats show Aerospike storing over 150TB of data with 75 billion transactions per day at sub-millisecond latencies and over 2 million transactions per minute of throughput.
Aerospike & AWS Working backward from the customer.pdf
With the rapid growth of real-time data applications, customers are looking for more efficient infrastructure and real-time data platforms. AWS and Aerospike provide an ideal starting point for building these next-generation services.
In this session, Raj Pai, AWS VP of EC2 Product Management, will discuss the Aerospike-AWS partnership, customer momentum, and details about new AWS Graviton instances. AWS Graviton processors and AWS Nitro SSDs, specifically, provide Aerospike customers with compelling price performance.
Update on Aerospike Database, Clients and Frameworks_Ronen Botzer.pdf
Ever wonder what the latest Aerospike product capabilities can do? In this session, see various Product Managers demonstrate and discuss our wares covering the latest advances in observability and management, graph, cloud, Elasticsearch, and our core database.
Developing for Real-time_Art Anderson.pdf
Curious about developing applications with Aerospike? This high level session walks through the basics of developing with Aerospike, exploring:
Data modeling
Basic operations
Connecting your data
Helpful tools
With additional focus on providing you with the necessary tools for learning, through the Aerospike Developer Hub and other great, free content. Join us as we develop for real-time with Aerospike!
Aerospike Today and Tomorrow Product Roadmap 2023_Lenley Hensarling.pdf
The Aerospike data platform pushes the boundaries of what a real-time data system can do stemming from our core design center principles. Hear from the Aerospike Chief Product Officer, Lenley Hensarling, about the advances being made now and in the near future surrounding multi-model capabilities like support for property graphs, multi-record transactions, observability and management, in-memory advances, Kubernetes operator, and more.
Now in AI- How we got here_Ashwin Rao.pdf
1) The document discusses the history and current state of artificial intelligence, including major developments in machine learning techniques like neural networks, deep learning, and transformers.
2) It explains different types and applications of AI, such as assistive AI, augmented AI, autonomous AI, narrow AI, and generative AI. It also covers supervised, unsupervised, and reinforcement learning.
3) The document predicts that in the future, AI will continue to improve through techniques like massive data, advanced software engineering, and a focus on safety and ethics, and that both information retrieval and physical tasks automation will see more development.
Art of the Possible_Tim Faulkes.pdf
Aerospike is a high performance, highly resilient, distributed database. Since “seeing is believing,” this session will demonstrate multiple elements of Aerospike exhibiting multiple aspects of our database including:
Time required to insert 10 million records
How strong consistency works with only two copies
Linear performance and throughput for removal then re-addition of a node and zone.
Mixed workload uninterrupted performance for concurrent massive reads and writes.
More from Aerospike, Inc. (9)
What a Modern Database Enables_Srini Srinivasan.pdf
What a Modern Database Enables_Srini Srinivasan.pdf
Aerospike & Unity_Connecting Developer Communities_Matt Dondelinger and Stace...
Aerospike & Unity_Connecting Developer Communities_Matt Dondelinger and Stace...
App Modernization with Aerospike as an Intraday System of Record_Venkat Thamm...
App Modernization with Aerospike as an Intraday System of Record_Venkat Thamm...
Aerospike & AWS Working backward from the customer.pdf
Aerospike & AWS Working backward from the customer.pdf
Update on Aerospike Database, Clients and Frameworks_Ronen Botzer.pdf
Update on Aerospike Database, Clients and Frameworks_Ronen Botzer.pdf
Aerospike Today and Tomorrow Product Roadmap 2023_Lenley Hensarling.pdf
Aerospike Today and Tomorrow Product Roadmap 2023_Lenley Hensarling.pdf
Recently uploaded
20240607 QFM018 Elixir Reading List May 2024
Everything I found interesting about the Elixir programming ecosystem in May 2024
Full-RAG: A modern architecture for hyper-personalization
Mike Del Balso, CEO & Co-Founder at Tecton, presents "Full RAG," a novel approach to AI recommendation systems, aiming to push beyond the limitations of traditional models through a deep integration of contextual insights and real-time data, leveraging the Retrieval-Augmented Generation architecture. This talk will outline Full RAG's potential to significantly enhance personalization, address engineering challenges such as data management and model training, and introduce data enrichment with reranking as a key solution. Attendees will gain crucial insights into the importance of hyperpersonalization in AI, the capabilities of Full RAG for advanced personalization, and strategies for managing complex data integrations for deploying cutting-edge AI solutions.
Microsoft - Power Platform_G.Aspiotis.pdf
Revolutionizing Application Development
with AI-powered low-code, presentation by George Aspiotis, Sr. Partner Development Manager, Microsoft
Generative AI Deep Dive: Advancing from Proof of Concept to Production
Join Maher Hanafi, VP of Engineering at Betterworks, in this new session where he'll share a practical framework to transform Gen AI prototypes into impactful products! He'll delve into the complexities of data collection and management, model selection and optimization, and ensuring security, scalability, and responsible use.
Essentials of Automations: The Art of Triggers and Actions in FME
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
Removing Uninteresting Bytes in Software Fuzzing
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
Introducing Milvus Lite: Easy-to-Install, Easy-to-Use vector database for you...
Join us to introduce Milvus Lite, a vector database that can run on notebooks and laptops, share the same API with Milvus, and integrate with every popular GenAI framework. This webinar is perfect for developers seeking easy-to-use, well-integrated vector databases for their GenAI apps.
20 Comprehensive Checklist of Designing and Developing a Website
Dive into the world of Website Designing and Developing with Pixlogix! Looking to create a stunning online presence? Look no further! Our comprehensive checklist covers everything you need to know to craft a website that stands out. From user-friendly design to seamless functionality, we've got you covered. Don't miss out on this invaluable resource! Check out our checklist now at Pixlogix and start your journey towards a captivating online presence today.
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdf
Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
I, a former op, would like to extend an invitation to all application developers to join the observability party will share these foundational concepts to build on:
GraphSummit Singapore | Graphing Success: Revolutionising Organisational Stru...
Sudheer Mechineni, Head of Application Frameworks, Standard Chartered Bank
Discover how Standard Chartered Bank harnessed the power of Neo4j to transform complex data access challenges into a dynamic, scalable graph database solution. This keynote will cover their journey from initial adoption to deploying a fully automated, enterprise-grade causal cluster, highlighting key strategies for modelling organisational changes and ensuring robust disaster recovery. Learn how these innovations have not only enhanced Standard Chartered Bank’s data infrastructure but also positioned them as pioneers in the banking sector’s adoption of graph technology.
TrustArc Webinar - 2024 Global Privacy Survey
How does your privacy program stack up against your peers? What challenges are privacy teams tackling and prioritizing in 2024?
In the fifth annual Global Privacy Benchmarks Survey, we asked over 1,800 global privacy professionals and business executives to share their perspectives on the current state of privacy inside and outside of their organizations. This year’s report focused on emerging areas of importance for privacy and compliance professionals, including considerations and implications of Artificial Intelligence (AI) technologies, building brand trust, and different approaches for achieving higher privacy competence scores.
See how organizational priorities and strategic approaches to data security and privacy are evolving around the globe.
This webinar will review:
- The top 10 privacy insights from the fifth annual Global Privacy Benchmarks Survey
- The top challenges for privacy leaders, practitioners, and organizations in 2024
- Key themes to consider in developing and maintaining your privacy program
“I’m still / I’m still / Chaining from the Block”
“An Outlook of the Ongoing and Future Relationship between Blockchain Technologies and Process-aware Information Systems.” Invited talk at the joint workshop on Blockchain for Information Systems (BC4IS) and Blockchain for Trusted Data Sharing (B4TDS), co-located with with the 36th International Conference on Advanced Information Systems Engineering (CAiSE), 3 June 2024, Limassol, Cyprus.
Pushing the limits of ePRTC: 100ns holdover for 100 days
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
National Security Agency - NSA mobile device best practices
Threats to mobile devices are more prevalent and increasing in scope and complexity. Users of mobile devices desire to take full advantage of the features
available on those devices, but many of the features provide convenience and capability but sacrifice security. This best practices guide outlines steps the users can take to better protect personal devices and information.
Enchancing adoption of Open Source Libraries. A case study on Albumentations.AI
Enchancing adoption of Open Source Libraries. A case study on Albumentations.AIVladimir Iglovikov, Ph.D.
Presented by Vladimir Iglovikov:
- https://www.linkedin.com/in/iglovikov/
- https://x.com/viglovikov
- https://www.instagram.com/ternaus/
This presentation delves into the journey of Albumentations.ai, a highly successful open-source library for data augmentation.
Created out of a necessity for superior performance in Kaggle competitions, Albumentations has grown to become a widely used tool among data scientists and machine learning practitioners.
This case study covers various aspects, including:
People: The contributors and community that have supported Albumentations.
Metrics: The success indicators such as downloads, daily active users, GitHub stars, and financial contributions.
Challenges: The hurdles in monetizing open-source projects and measuring user engagement.
Development Practices: Best practices for creating, maintaining, and scaling open-source libraries, including code hygiene, CI/CD, and fast iteration.
Community Building: Strategies for making adoption easy, iterating quickly, and fostering a vibrant, engaged community.
Marketing: Both online and offline marketing tactics, focusing on real, impactful interactions and collaborations.
Mental Health: Maintaining balance and not feeling pressured by user demands.
Key insights include the importance of automation, making the adoption process seamless, and leveraging offline interactions for marketing. The presentation also emphasizes the need for continuous small improvements and building a friendly, inclusive community that contributes to the project's growth.
Vladimir Iglovikov brings his extensive experience as a Kaggle Grandmaster, ex-Staff ML Engineer at Lyft, sharing valuable lessons and practical advice for anyone looking to enhance the adoption of their open-source projects.
Explore more about Albumentations and join the community at:
GitHub: https://github.com/albumentations-team/albumentations
Website: https://albumentations.ai/
LinkedIn: https://www.linkedin.com/company/100504475
Twitter: https://x.com/albumentationsVideo Streaming: Then, Now, and in the Future
In his public lecture, Christian Timmerer provides insights into the fascinating history of video streaming, starting from its humble beginnings before YouTube to the groundbreaking technologies that now dominate platforms like Netflix and ORF ON. Timmerer also presents provocative contributions of his own that have significantly influenced the industry. He concludes by looking at future challenges and invites the audience to join in a discussion.
20240609 QFM020 Irresponsible AI Reading List May 2024
Everything I found interesting about the irresponsible use of machine intelligence in May 2024
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...
The choice of an operating system plays a pivotal role in shaping our computing experience. For decades, Microsoft's Windows has dominated the market, offering a familiar and widely adopted platform for personal and professional use. However, as technological advancements continue to push the boundaries of innovation, alternative operating systems have emerged, challenging the status quo and offering users a fresh perspective on computing.
One such alternative that has garnered significant attention and acclaim is Nitrux Linux 3.5.0, a sleek, powerful, and user-friendly Linux distribution that promises to redefine the way we interact with our devices. With its focus on performance, security, and customization, Nitrux Linux presents a compelling case for those seeking to break free from the constraints of proprietary software and embrace the freedom and flexibility of open-source computing.
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
Discover the seamless integration of RPA (Robotic Process Automation), COMPOSER, and APM with AWS IDP enhanced with Slack notifications. Explore how these technologies converge to streamline workflows, optimize performance, and ensure secure access, all while leveraging the power of AWS IDP and real-time communication via Slack notifications.
Recently uploaded (20)
Full-RAG: A modern architecture for hyper-personalization
Full-RAG: A modern architecture for hyper-personalization
Generative AI Deep Dive: Advancing from Proof of Concept to Production
Generative AI Deep Dive: Advancing from Proof of Concept to Production
Essentials of Automations: The Art of Triggers and Actions in FME
Essentials of Automations: The Art of Triggers and Actions in FME
Introducing Milvus Lite: Easy-to-Install, Easy-to-Use vector database for you...
Introducing Milvus Lite: Easy-to-Install, Easy-to-Use vector database for you...
20 Comprehensive Checklist of Designing and Developing a Website
20 Comprehensive Checklist of Designing and Developing a Website
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdf
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdf
GraphSummit Singapore | Graphing Success: Revolutionising Organisational Stru...
GraphSummit Singapore | Graphing Success: Revolutionising Organisational Stru...
Pushing the limits of ePRTC: 100ns holdover for 100 days
Pushing the limits of ePRTC: 100ns holdover for 100 days
National Security Agency - NSA mobile device best practices
National Security Agency - NSA mobile device best practices
Enchancing adoption of Open Source Libraries. A case study on Albumentations.AI
Enchancing adoption of Open Source Libraries. A case study on Albumentations.AI
20240609 QFM020 Irresponsible AI Reading List May 2024
20240609 QFM020 Irresponsible AI Reading List May 2024
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
Building for a Real-time Data Future_Subbu Iyer.pdf
- 1. Building for a Real-time Data Future Subbu Iyer Chief Executive Officer Aerospike
- 2. All rights reserved. © 2023 Aerospike, Inc. 2 Recent History of AI 1980 1990 2000 2010 1980s: Expert Systems and Revival of Neural Networks 1987-1993: Second AI Winter Expert Systems, AI companies failed 1994-2010: Low-hype practical progress, Moore’s Law Compute Power 2011-Present: Big Data, Deep Learning, Shades of AGI 2020 2023: ChatGPT-4 Launched 2012: Hinton builds Neural network
- 3. All rights reserved. © 2023 Aerospike, Inc. 3 AI Fueling Next Wave of Innovation
- 4. All rights reserved. © 2023 Aerospike, Inc. AI is Driving Smarter Decisions… 4 Agriculture Healthcare Drug Development IoT Smart Retail Supply Chain Telecom Autonomous Vehicle
- 5. All rights reserved. © 2023 Aerospike, Inc. How Our Customers Use AI/ML 5 Hyper-personalized recommendations Feature Store Fraud Prevention Real-time Risk Assessment Slashed fraud Risk calculations in minutes, not hours Personalized recommendations for 200m users Improved cart size
- 6. All rights reserved. © 2023 Aerospike, Inc. 6
- 7. All rights reserved. © 2023 Aerospike, Inc. AI Today: Offline Learning Aerospike Data Platform Key value Document Graph Vector Real-time Ingestion at Scale Company Transactional Data Global Contextual Data Offline Learning ML AI Real-time Decisioning
- 8. All rights reserved. © 2023 Aerospike, Inc. 8 AI Future: Continuous Learning Aerospike Data Platform Key value Document Graph Vector Real-time Ingestion at Scale Company Transactional Data Global Contextual Data Continuous Learning ML AI Real-time Decisioning Real-time data adds context and accuracy resulting in better decisions
- 9. All rights reserved. © 2023 Aerospike, Inc. Aerospike Real-Time Data Platform 9 Always On Five-nines with globally distributed, strongly consistent data Lowest Cost Reduce server/instance footprints by up to 80% Sub-millisecond performance Lowest latency Unlimited scale Predictable performance from GB-to-PB
- 10. All rights reserved. © 2023 Aerospike, Inc. 10 Announcing Aerospike Graph – Available NOW ü Massively scalable – Billions of vertices, each with 1000s of edges ü Real-time OLTP performance – >100’s K QPS with sub-5ms latency for 2-3 hop queries ü Lowest TCO – independently scale compute and storage NEW
- 11. All rights reserved. © 2023 Aerospike, Inc. 11 Looking Forward Vector
- 12. All rights reserved. © 2023 Aerospike, Inc. Summary AI changes EVERYTHING ü AI needs to incorporate real-time data for context, accuracy, and better decisions ü AI demands a real-time data platform that provides limitless scale, low latency, and high performance ü 12
- 13. All rights reserved. © 2023 Aerospike, Inc. Thank You