The document discusses leveraging AI to boost ROI for SaaS products and businesses. It provides examples of startups that have successfully used AI like Netflix, which built recommendation systems to increase customer retention. The presentation outlines strategies for integrating AI into SaaS ecosystems, including using AI for personalization, automation, prediction, search and improving the software release process. It also covers best practices for AI product planning, development and deployment.
re:cap Generative AI journey with BedrockPhilipBasford
Wherever you are on your Generative AI journey — Amazon Bedrock allows you to rapidly prototype Generative AI concepts, using the latest Foundational Models. This session also included architectures to accelerate your prototype into a real-world GenAI solution using LLMOps. Providing the safeguards to keep your data private & secure, handle any regulatory compliance and responsibility requirements.
How to Build Enterprise AI Products by IBM Product ManagerProduct School
Main takeaways:
- Introduction to AI in the enterprise
- Unique challenges and opportunities for building AI products for the enterprise
- Planning your Enterprise AI journey
At Amazon, we’ve been investing deeply in artificial intelligence for over 20 years. Machine learning (ML) algorithms drive many of our internal systems. It's also core to the capabilities our customers experience – from the path optimization in our fulfillment centers, and Amazon.com’s recommendations engine, to Echo powered by Alexa, our drone initiative Prime Air, and our new retail experience Amazon Go. This is just the beginning. Our mission is to share our learnings and ML capabilities as fully managed services, and put them into the hands of every developer and data scientist.
No Code AI - How to Deploy Machine Learning Models with Zero Code?Skyl.ai
In the past, getting insights from the data using machine learning (ML) and artificial intelligence (AI) required experts with coding skills and knowledge of math & statistics. The scarcity of talent and huge infrastructure set up cost, often makes it difficult for organizations to get early results from their Machine Learning initiatives.
Through this webinar, we will learn how 'No Code AI' tools make it possible to leverage the power of machine learning without needing to code. It is helping business analysts, domain experts, and business decision-makers to experiment and get started with quick-win Machine Learning projects.
What you'll learn
- Traditional vs No Code AI Process
- Best practices to accelerate machine learning adoption
- Demo: How organizations are deploying machine learning models without coding expertise within hours, not weeks
re:cap Generative AI journey with BedrockPhilipBasford
Wherever you are on your Generative AI journey — Amazon Bedrock allows you to rapidly prototype Generative AI concepts, using the latest Foundational Models. This session also included architectures to accelerate your prototype into a real-world GenAI solution using LLMOps. Providing the safeguards to keep your data private & secure, handle any regulatory compliance and responsibility requirements.
How to Build Enterprise AI Products by IBM Product ManagerProduct School
Main takeaways:
- Introduction to AI in the enterprise
- Unique challenges and opportunities for building AI products for the enterprise
- Planning your Enterprise AI journey
At Amazon, we’ve been investing deeply in artificial intelligence for over 20 years. Machine learning (ML) algorithms drive many of our internal systems. It's also core to the capabilities our customers experience – from the path optimization in our fulfillment centers, and Amazon.com’s recommendations engine, to Echo powered by Alexa, our drone initiative Prime Air, and our new retail experience Amazon Go. This is just the beginning. Our mission is to share our learnings and ML capabilities as fully managed services, and put them into the hands of every developer and data scientist.
No Code AI - How to Deploy Machine Learning Models with Zero Code?Skyl.ai
In the past, getting insights from the data using machine learning (ML) and artificial intelligence (AI) required experts with coding skills and knowledge of math & statistics. The scarcity of talent and huge infrastructure set up cost, often makes it difficult for organizations to get early results from their Machine Learning initiatives.
Through this webinar, we will learn how 'No Code AI' tools make it possible to leverage the power of machine learning without needing to code. It is helping business analysts, domain experts, and business decision-makers to experiment and get started with quick-win Machine Learning projects.
What you'll learn
- Traditional vs No Code AI Process
- Best practices to accelerate machine learning adoption
- Demo: How organizations are deploying machine learning models without coding expertise within hours, not weeks
How could OpenAI, a small organization of just 200 employees, managed to shake the foundations of large companies like Google and Meta? Everyone dreams about being a unicorn – having razor sharp focus, high talent-density , rapid speed of innovation but in reality, even startups end up becoming slow organizations very quickly. Why does this happen?
Intro to Artificial Intelligence w/ Target's Director of PMProduct School
Given that Machine Learning (ML) is on every product enthusiast’s mind, this talk gave a broad view of the investment landscape for future innovation. Director of Product Management at Target, Aarthi Srinivasan, talked about macro AI themes & trends, how you can build your AI team and how to create a ML backed product vision.
Additionally, this talk armed the attendees with enough information to create your Point of View (POV) on how to incorporate AI into your business.
Shift AI 2020: Building AI-first Products - Ehsan Yousefzadeh (AIG Investments)Shift Conference
Shift AI was a success, connecting hundreds of professionals that were eager to propel the progress of AI and discuss the newest technologies in data mining, machine learning and neural networks. More at https://ai.shiftconf.co/.
Talk description:
With rapid advancements in AI research, new breakthroughs lead to new product opportunities. In this presentation, I will discuss the AI product development process, along with the challenges and rewards that come with it. I’ll also discuss the various degrees of AI products, the teams needed to build them, and what it takes to be a great AI-first product manager.
Dr Christoph Nieuwoudt- AI in Financial Servicesitnewsafrica
Dr. Christoff Nieuwoudt delivered a keynote on AI in Financial Services at Digital Finance Africa 2023 on the 2nd of August 2023 at Gallagher Convention Centre, Johannesburg, Midrand.
Building a Data Cloud to enable Analytics & AI-Driven Innovation - Lak Lakshm...Daniel Zivkovic
Learn how Google Cloud addresses the key challenges when building an Agile Data & AI platform. This lecture is important regardless of the Cloud you are (will be) using because most businesses face the same 6 challenges:
1. High-quality AI requires a lot of data
2. AI Expertise is in high demand
3. Getting the value of ML requires a modern data platform
4. Activating ML requires surfacing AI into decision UIs
5. Operationalizing ML is hard
6. State-of-the-art changes rapidly
The lecture recording with Q&A is at https://youtu.be/ntBEQdD1IeQ
IBM i & digital transformation - Presentation & basic demo
IBM Watson Studio, IBM DSX Local w/ Open Source (Spark) & IBM Technology (OpenPower, CAPI, NVLINK)
SpigitEngage - The latest release of our Enterprise Innovation PlatformMilind Pansare
On October 23, 2013, Charles and I presented the newest release of SpigitEngage (Fall 2013) on a Spigit Cafe webinar. This webinar introduced Enterprise Innovation Management solutions, then did a deep dive into Spigit with a Demo ( the demo was a major portion of the webinar, no slides for that though). There are also a few slides here that talk about Mindjet and our product portfolio post-merger with Spigit.
Disrupting Corporates with AI by Hicham MhannaData Con LA
Abstract:- Discussion of various applied cases of artificial intelligence solutions stemming from our venture work across verticals including consumer, financial and media.
IBM's Watson is a machine-learning platform that’s been built to mirror the same learning process that humans have: Observe, Interpret, Evaluate and Decide. Through the use of this cognitive framework, Watson can search through a database of information and pull out key insights to bridge gaps in human knowledge. It’s expertise scaling for enterprise.
Watson has already helped businesses across a variety of industries increase their customer engagement, data discovery and informed decision making abilities. Is your business next?
AI for Customer Service: How to Improve Contact Center Efficiency with Machin...Skyl.ai
About the webinar
It only takes one bad interaction for a customer to abandon a service or product. Businesses are no longer just competing with other companies’ products, they’re competing with a customer’s last service experience. All contact centers worldwide are looking for new and strategic ways to increase operational performance, reduce cost, and still provide high-touch customer experiences that improve customer loyalty and highlight ways to increase revenue and productivity.
Through this webinar, we will understand how AI can augment the effort, focus and problem-solving abilities of human agents so that they can tackle more complex or creative tasks. With an abundance of data from logs, emails, chat, and voice recordings, contact centers can ingest this data to provide contextual customer service at the right time with the right way providing satisfactory customer service and retain the brand value.
What you will learn
- How organizations are building engaging interactions that deliver value to customers
- Best practices to automate AI/ML models
- Demo: How to route customer queries to the right department or professional
Keynote presentation from IBM Solutions Connect 2013 covering topics such as changing business world today and how technologies can help organisations cope with this change and move forward.
test - Future of Ecommerce: How to Improve the Online Shopping Experience Usi...Skyl.ai
About the webinar
It’s no secret that a well-organized product catalog becomes extremely crucial as consumers look for a more rich and consistent online experience while E-shopping. Often, the task of digitizing the catalog of the fast-moving and large volume products becomes daunting due to insufficient, erroneous and fragmented data.
This leads us to the question: If E-commerce and fashion companies need to be agile and consumer-friendly, then why are so many still using the same product catalog management methods that were devised years ago? The manual product classification and data attribution process are only leading to an increased risk of error and time delay affecting the brand reputation. Also, leading to lost sales opportunities due to incomplete or inaccurate product records that don’t really reflect the actual product.
In this webinar, we will discuss how to efficiently manage machine learning projects without tech headaches by plugging in your data and building your models instantly.
What you'll learn
- How E-commerce companies are using AI to drive more sales and seamless customer experience
- Know the secret sauce of automating time-intensive, repetitive steps to quickly build models
- Demo: A deeper understanding of the end-to-end machine learning workflow for a fashion product catalog management using Skyl.ai
Future of Ecommerce: How to Improve the Online Shopping Experience Using Mach...Skyl.ai
About the webinar
It’s no secret that a well-organized product catalog becomes extremely crucial as consumers look for a more rich and consistent online experience while E-shopping. Often, the task of digitizing the catalog of the fast-moving and large volume products becomes daunting due to insufficient, erroneous, and fragmented data.
This leads us to the question: If E-commerce and fashion companies need to be agile and consumer-friendly, then why are so many still using the same product catalog management methods that were devised years ago? The manual product classification and data attribution process are only leading to an increased risk of error and time delay affecting the brand reputation. Also, leading to lost sales opportunities due to incomplete or inaccurate product records that don’t really reflect the actual product.
In this webinar, we will discuss how to efficiently manage machine learning projects without tech headaches by plugging in your data and building your models instantly.
What you will learn
- How E-commerce companies are using AI to drive more sales and seamless customer experience
- Know the secret sauce of automating time-intensive, repetitive steps to quickly build models
- Demo: A deeper understanding of the end-to-end machine learning workflow for a fashion product catalog management using Skyl.ai
Solving the dilemma should you build or buy aiSkyl.ai
About the webinar
Long gone are the days of questioning if your organization requires Artificial Intelligence to drive competitive advantage. 84% of businesses say AI will enable them to obtain or sustain the competitive advantage [Forbes].
AI offers highly data-driven insights, automates mundane processes, enhances customer experience, and hence increases overall efficiency. 36% of executives say their primary goal for AI is to free up workers to be more creative by automating tasks [HBR].
Businesses know what AI solutions they need but the real challenge lies in getting them implemented. AI initiatives require proper evaluation of the organizations’ ability to build in-house AI technology or buy commercially available AI applications.
Through this webinar, you will know the factors to consider while making the decision of AI implementation, and you get the answer to your biggest question - whether to build or buy AI application.
What you will learn
What factors to evaluate before making a decision to build or buy an AI solution
What will you require to build an AI model specific to your organizational need
How does building an AI solution fit into the long-term business model and help in gaining competitive advantage
How could OpenAI, a small organization of just 200 employees, managed to shake the foundations of large companies like Google and Meta? Everyone dreams about being a unicorn – having razor sharp focus, high talent-density , rapid speed of innovation but in reality, even startups end up becoming slow organizations very quickly. Why does this happen?
Intro to Artificial Intelligence w/ Target's Director of PMProduct School
Given that Machine Learning (ML) is on every product enthusiast’s mind, this talk gave a broad view of the investment landscape for future innovation. Director of Product Management at Target, Aarthi Srinivasan, talked about macro AI themes & trends, how you can build your AI team and how to create a ML backed product vision.
Additionally, this talk armed the attendees with enough information to create your Point of View (POV) on how to incorporate AI into your business.
Shift AI 2020: Building AI-first Products - Ehsan Yousefzadeh (AIG Investments)Shift Conference
Shift AI was a success, connecting hundreds of professionals that were eager to propel the progress of AI and discuss the newest technologies in data mining, machine learning and neural networks. More at https://ai.shiftconf.co/.
Talk description:
With rapid advancements in AI research, new breakthroughs lead to new product opportunities. In this presentation, I will discuss the AI product development process, along with the challenges and rewards that come with it. I’ll also discuss the various degrees of AI products, the teams needed to build them, and what it takes to be a great AI-first product manager.
Dr Christoph Nieuwoudt- AI in Financial Servicesitnewsafrica
Dr. Christoff Nieuwoudt delivered a keynote on AI in Financial Services at Digital Finance Africa 2023 on the 2nd of August 2023 at Gallagher Convention Centre, Johannesburg, Midrand.
Building a Data Cloud to enable Analytics & AI-Driven Innovation - Lak Lakshm...Daniel Zivkovic
Learn how Google Cloud addresses the key challenges when building an Agile Data & AI platform. This lecture is important regardless of the Cloud you are (will be) using because most businesses face the same 6 challenges:
1. High-quality AI requires a lot of data
2. AI Expertise is in high demand
3. Getting the value of ML requires a modern data platform
4. Activating ML requires surfacing AI into decision UIs
5. Operationalizing ML is hard
6. State-of-the-art changes rapidly
The lecture recording with Q&A is at https://youtu.be/ntBEQdD1IeQ
IBM i & digital transformation - Presentation & basic demo
IBM Watson Studio, IBM DSX Local w/ Open Source (Spark) & IBM Technology (OpenPower, CAPI, NVLINK)
SpigitEngage - The latest release of our Enterprise Innovation PlatformMilind Pansare
On October 23, 2013, Charles and I presented the newest release of SpigitEngage (Fall 2013) on a Spigit Cafe webinar. This webinar introduced Enterprise Innovation Management solutions, then did a deep dive into Spigit with a Demo ( the demo was a major portion of the webinar, no slides for that though). There are also a few slides here that talk about Mindjet and our product portfolio post-merger with Spigit.
Disrupting Corporates with AI by Hicham MhannaData Con LA
Abstract:- Discussion of various applied cases of artificial intelligence solutions stemming from our venture work across verticals including consumer, financial and media.
IBM's Watson is a machine-learning platform that’s been built to mirror the same learning process that humans have: Observe, Interpret, Evaluate and Decide. Through the use of this cognitive framework, Watson can search through a database of information and pull out key insights to bridge gaps in human knowledge. It’s expertise scaling for enterprise.
Watson has already helped businesses across a variety of industries increase their customer engagement, data discovery and informed decision making abilities. Is your business next?
AI for Customer Service: How to Improve Contact Center Efficiency with Machin...Skyl.ai
About the webinar
It only takes one bad interaction for a customer to abandon a service or product. Businesses are no longer just competing with other companies’ products, they’re competing with a customer’s last service experience. All contact centers worldwide are looking for new and strategic ways to increase operational performance, reduce cost, and still provide high-touch customer experiences that improve customer loyalty and highlight ways to increase revenue and productivity.
Through this webinar, we will understand how AI can augment the effort, focus and problem-solving abilities of human agents so that they can tackle more complex or creative tasks. With an abundance of data from logs, emails, chat, and voice recordings, contact centers can ingest this data to provide contextual customer service at the right time with the right way providing satisfactory customer service and retain the brand value.
What you will learn
- How organizations are building engaging interactions that deliver value to customers
- Best practices to automate AI/ML models
- Demo: How to route customer queries to the right department or professional
Keynote presentation from IBM Solutions Connect 2013 covering topics such as changing business world today and how technologies can help organisations cope with this change and move forward.
test - Future of Ecommerce: How to Improve the Online Shopping Experience Usi...Skyl.ai
About the webinar
It’s no secret that a well-organized product catalog becomes extremely crucial as consumers look for a more rich and consistent online experience while E-shopping. Often, the task of digitizing the catalog of the fast-moving and large volume products becomes daunting due to insufficient, erroneous and fragmented data.
This leads us to the question: If E-commerce and fashion companies need to be agile and consumer-friendly, then why are so many still using the same product catalog management methods that were devised years ago? The manual product classification and data attribution process are only leading to an increased risk of error and time delay affecting the brand reputation. Also, leading to lost sales opportunities due to incomplete or inaccurate product records that don’t really reflect the actual product.
In this webinar, we will discuss how to efficiently manage machine learning projects without tech headaches by plugging in your data and building your models instantly.
What you'll learn
- How E-commerce companies are using AI to drive more sales and seamless customer experience
- Know the secret sauce of automating time-intensive, repetitive steps to quickly build models
- Demo: A deeper understanding of the end-to-end machine learning workflow for a fashion product catalog management using Skyl.ai
Future of Ecommerce: How to Improve the Online Shopping Experience Using Mach...Skyl.ai
About the webinar
It’s no secret that a well-organized product catalog becomes extremely crucial as consumers look for a more rich and consistent online experience while E-shopping. Often, the task of digitizing the catalog of the fast-moving and large volume products becomes daunting due to insufficient, erroneous, and fragmented data.
This leads us to the question: If E-commerce and fashion companies need to be agile and consumer-friendly, then why are so many still using the same product catalog management methods that were devised years ago? The manual product classification and data attribution process are only leading to an increased risk of error and time delay affecting the brand reputation. Also, leading to lost sales opportunities due to incomplete or inaccurate product records that don’t really reflect the actual product.
In this webinar, we will discuss how to efficiently manage machine learning projects without tech headaches by plugging in your data and building your models instantly.
What you will learn
- How E-commerce companies are using AI to drive more sales and seamless customer experience
- Know the secret sauce of automating time-intensive, repetitive steps to quickly build models
- Demo: A deeper understanding of the end-to-end machine learning workflow for a fashion product catalog management using Skyl.ai
Solving the dilemma should you build or buy aiSkyl.ai
About the webinar
Long gone are the days of questioning if your organization requires Artificial Intelligence to drive competitive advantage. 84% of businesses say AI will enable them to obtain or sustain the competitive advantage [Forbes].
AI offers highly data-driven insights, automates mundane processes, enhances customer experience, and hence increases overall efficiency. 36% of executives say their primary goal for AI is to free up workers to be more creative by automating tasks [HBR].
Businesses know what AI solutions they need but the real challenge lies in getting them implemented. AI initiatives require proper evaluation of the organizations’ ability to build in-house AI technology or buy commercially available AI applications.
Through this webinar, you will know the factors to consider while making the decision of AI implementation, and you get the answer to your biggest question - whether to build or buy AI application.
What you will learn
What factors to evaluate before making a decision to build or buy an AI solution
What will you require to build an AI model specific to your organizational need
How does building an AI solution fit into the long-term business model and help in gaining competitive advantage
Similar to Driving valie with AI for SaaS Products (20)
Cyaniclab : Software Development Agency Portfolio.pdfCyanic lab
CyanicLab, an offshore custom software development company based in Sweden,India, Finland, is your go-to partner for startup development and innovative web design solutions. Our expert team specializes in crafting cutting-edge software tailored to meet the unique needs of startups and established enterprises alike. From conceptualization to execution, we offer comprehensive services including web and mobile app development, UI/UX design, and ongoing software maintenance. Ready to elevate your business? Contact CyanicLab today and let us propel your vision to success with our top-notch IT solutions.
How to Position Your Globus Data Portal for Success Ten Good PracticesGlobus
Science gateways allow science and engineering communities to access shared data, software, computing services, and instruments. Science gateways have gained a lot of traction in the last twenty years, as evidenced by projects such as the Science Gateways Community Institute (SGCI) and the Center of Excellence on Science Gateways (SGX3) in the US, The Australian Research Data Commons (ARDC) and its platforms in Australia, and the projects around Virtual Research Environments in Europe. A few mature frameworks have evolved with their different strengths and foci and have been taken up by a larger community such as the Globus Data Portal, Hubzero, Tapis, and Galaxy. However, even when gateways are built on successful frameworks, they continue to face the challenges of ongoing maintenance costs and how to meet the ever-expanding needs of the community they serve with enhanced features. It is not uncommon that gateways with compelling use cases are nonetheless unable to get past the prototype phase and become a full production service, or if they do, they don't survive more than a couple of years. While there is no guaranteed pathway to success, it seems likely that for any gateway there is a need for a strong community and/or solid funding streams to create and sustain its success. With over twenty years of examples to draw from, this presentation goes into detail for ten factors common to successful and enduring gateways that effectively serve as best practices for any new or developing gateway.
Custom Healthcare Software for Managing Chronic Conditions and Remote Patient...Mind IT Systems
Healthcare providers often struggle with the complexities of chronic conditions and remote patient monitoring, as each patient requires personalized care and ongoing monitoring. Off-the-shelf solutions may not meet these diverse needs, leading to inefficiencies and gaps in care. It’s here, custom healthcare software offers a tailored solution, ensuring improved care and effectiveness.
Large Language Models and the End of ProgrammingMatt Welsh
Talk by Matt Welsh at Craft Conference 2024 on the impact that Large Language Models will have on the future of software development. In this talk, I discuss the ways in which LLMs will impact the software industry, from replacing human software developers with AI, to replacing conventional software with models that perform reasoning, computation, and problem-solving.
Navigating the Metaverse: A Journey into Virtual Evolution"Donna Lenk
Join us for an exploration of the Metaverse's evolution, where innovation meets imagination. Discover new dimensions of virtual events, engage with thought-provoking discussions, and witness the transformative power of digital realms."
Top Features to Include in Your Winzo Clone App for Business Growth (4).pptxrickgrimesss22
Discover the essential features to incorporate in your Winzo clone app to boost business growth, enhance user engagement, and drive revenue. Learn how to create a compelling gaming experience that stands out in the competitive market.
Top 7 Unique WhatsApp API Benefits | Saudi ArabiaYara Milbes
Discover the transformative power of the WhatsApp API in our latest SlideShare presentation, "Top 7 Unique WhatsApp API Benefits." In today's fast-paced digital era, effective communication is crucial for both personal and professional success. Whether you're a small business looking to enhance customer interactions or an individual seeking seamless communication with loved ones, the WhatsApp API offers robust capabilities that can significantly elevate your experience.
In this presentation, we delve into the top 7 distinctive benefits of the WhatsApp API, provided by the leading WhatsApp API service provider in Saudi Arabia. Learn how to streamline customer support, automate notifications, leverage rich media messaging, run scalable marketing campaigns, integrate secure payments, synchronize with CRM systems, and ensure enhanced security and privacy.
Launch Your Streaming Platforms in MinutesRoshan Dwivedi
The claim of launching a streaming platform in minutes might be a bit of an exaggeration, but there are services that can significantly streamline the process. Here's a breakdown:
Pros of Speedy Streaming Platform Launch Services:
No coding required: These services often use drag-and-drop interfaces or pre-built templates, eliminating the need for programming knowledge.
Faster setup: Compared to building from scratch, these platforms can get you up and running much quicker.
All-in-one solutions: Many services offer features like content management systems (CMS), video players, and monetization tools, reducing the need for multiple integrations.
Things to Consider:
Limited customization: These platforms may offer less flexibility in design and functionality compared to custom-built solutions.
Scalability: As your audience grows, you might need to upgrade to a more robust platform or encounter limitations with the "quick launch" option.
Features: Carefully evaluate which features are included and if they meet your specific needs (e.g., live streaming, subscription options).
Examples of Services for Launching Streaming Platforms:
Muvi [muvi com]
Uscreen [usencreen tv]
Alternatives to Consider:
Existing Streaming platforms: Platforms like YouTube or Twitch might be suitable for basic streaming needs, though monetization options might be limited.
Custom Development: While more time-consuming, custom development offers the most control and flexibility for your platform.
Overall, launching a streaming platform in minutes might not be entirely realistic, but these services can significantly speed up the process compared to building from scratch. Carefully consider your needs and budget when choosing the best option for you.
Field Employee Tracking System| MiTrack App| Best Employee Tracking Solution|...informapgpstrackings
Keep tabs on your field staff effortlessly with Informap Technology Centre LLC. Real-time tracking, task assignment, and smart features for efficient management. Request a live demo today!
For more details, visit us : https://informapuae.com/field-staff-tracking/
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
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!
Unleash Unlimited Potential with One-Time Purchase
BoxLang is more than just a language; it's a community. By choosing a Visionary License, you're not just investing in your success, you're actively contributing to the ongoing development and support of BoxLang.
Providing Globus Services to Users of JASMIN for Environmental Data AnalysisGlobus
JASMIN is the UK’s high-performance data analysis platform for environmental science, operated by STFC on behalf of the UK Natural Environment Research Council (NERC). In addition to its role in hosting the CEDA Archive (NERC’s long-term repository for climate, atmospheric science & Earth observation data in the UK), JASMIN provides a collaborative platform to a community of around 2,000 scientists in the UK and beyond, providing nearly 400 environmental science projects with working space, compute resources and tools to facilitate their work. High-performance data transfer into and out of JASMIN has always been a key feature, with many scientists bringing model outputs from supercomputers elsewhere in the UK, to analyse against observational or other model data in the CEDA Archive. A growing number of JASMIN users are now realising the benefits of using the Globus service to provide reliable and efficient data movement and other tasks in this and other contexts. Further use cases involve long-distance (intercontinental) transfers to and from JASMIN, and collecting results from a mobile atmospheric radar system, pushing data to JASMIN via a lightweight Globus deployment. We provide details of how Globus fits into our current infrastructure, our experience of the recent migration to GCSv5.4, and of our interest in developing use of the wider ecosystem of Globus services for the benefit of our user community.
Utilocate offers a comprehensive solution for locate ticket management by automating and streamlining the entire process. By integrating with Geospatial Information Systems (GIS), it provides accurate mapping and visualization of utility locations, enhancing decision-making and reducing the risk of errors. The system's advanced data analytics tools help identify trends, predict potential issues, and optimize resource allocation, making the locate ticket management process smarter and more efficient. Additionally, automated ticket management ensures consistency and reduces human error, while real-time notifications keep all relevant personnel informed and ready to respond promptly.
The system's ability to streamline workflows and automate ticket routing significantly reduces the time taken to process each ticket, making the process faster and more efficient. Mobile access allows field technicians to update ticket information on the go, ensuring that the latest information is always available and accelerating the locate process. Overall, Utilocate not only enhances the efficiency and accuracy of locate ticket management but also improves safety by minimizing the risk of utility damage through precise and timely locates.
OpenFOAM solver for Helmholtz equation, helmholtzFoam / helmholtzBubbleFoamtakuyayamamoto1800
In this slide, we show the simulation example and the way to compile this solver.
In this solver, the Helmholtz equation can be solved by helmholtzFoam. Also, the Helmholtz equation with uniformly dispersed bubbles can be simulated by helmholtzBubbleFoam.
We describe the deployment and use of Globus Compute for remote computation. This content is aimed at researchers who wish to compute on remote resources using a unified programming interface, as well as system administrators who will deploy and operate Globus Compute services on their research computing infrastructure.
Climate Science Flows: Enabling Petabyte-Scale Climate Analysis with the Eart...Globus
The Earth System Grid Federation (ESGF) is a global network of data servers that archives and distributes the planet’s largest collection of Earth system model output for thousands of climate and environmental scientists worldwide. Many of these petabyte-scale data archives are located in proximity to large high-performance computing (HPC) or cloud computing resources, but the primary workflow for data users consists of transferring data, and applying computations on a different system. As a part of the ESGF 2.0 US project (funded by the United States Department of Energy Office of Science), we developed pre-defined data workflows, which can be run on-demand, capable of applying many data reduction and data analysis to the large ESGF data archives, transferring only the resultant analysis (ex. visualizations, smaller data files). In this talk, we will showcase a few of these workflows, highlighting how Globus Flows can be used for petabyte-scale climate analysis.
In the ever-evolving landscape of technology, enterprise software development is undergoing a significant transformation. Traditional coding methods are being challenged by innovative no-code solutions, which promise to streamline and democratize the software development process.
This shift is particularly impactful for enterprises, which require robust, scalable, and efficient software to manage their operations. In this article, we will explore the various facets of enterprise software development with no-code solutions, examining their benefits, challenges, and the future potential they hold.
Enterprise Software Development with No Code Solutions.pptx
Driving valie with AI for SaaS Products
1. Leveraging AI for boosting your SaaS
product/business ROI’s
COPYRIGHT@ VISHAL SETHI, VISHAL@STARTUPOMEGA.COM
A Presentation by Vishal Sethi, Data Product Leader, Silicon Valley
AVP, Bristlecone, Founder Startupomega.com
2. Insights
Building AI Products
Integrating AI in SaaS Ecosystem
Role of ML in transforming SaaS Product
ML as a Service
Let us walk through
fundamental product design
and development thinking
behind building world class AI
products, that leverage AI to
enhance SaaS business drawing
examples from tech industry.
COPYRIGHT@ VISHAL SETHI, VISHAL@STARTUPOMEGA.COM
3. About Me?
20+ Years Cross Industry Contributions within Data, Analytics and AI
Product Leader, Investor, Technology evangelist, StartUp mentor
Brought a wide array of Enterprise B2B and B2C Products to life
What makes my experience unique is diversity of AI projects that I have worked on
Keynote speaker in C level summits
MSC – Data Science, MBA – strategy, Six sigma – champion, and Master in Finance management
Heartfulness meditation practitioner
Vishal.sethi@bristlecone.com
vishal@startupomega.com
COPYRIGHT@ VISHAL SETHI, VISHAL@STARTUPOMEGA.COM
4. Goal of this talk today?
Inspire and inform product leaders
Ideas and methodologies and technologies great products leverage
Applied examples to illustrate above
COPYRIGHT@ VISHAL SETHI, VISHAL@STARTUPOMEGA.COM
5. Thinking of an AI Startup?
Open AI - 5-year search growth: 99X+, Funding: $1B (Corporate Round)
◦ creating artificial general intelligence (AI) to benefit humanity.
Frame AI - 5-year search growth: 462%, Funding: $17.9M (Series B)
◦ The Voice of the Customer engine
Moveworks - 5-year search growth: 1000%, Funding: $305M (Series C)
◦ platform is able to support employees’ issues end-to-end
Cloudminds - 5-year search growth: -100%, Funding: $468.6M (Series B)
◦ open end-to-end software for robots
H2O.AI - 5-year search growth: -100%, Funding: $251.1M (Series E)
◦ open-source AI platform that allows developers to import algorithms for different use cases
Argo - Search growth status: Exploding, Funding: $3.6B (Corporate Round)
◦ first fully integrated self-driving system
Eightfold - Search growth status: Exploding, Funding: $396.8M (Series E)
◦ AI to power a suite of HR-related products aimed at retaining, training, and finding the best talent
Source: Crunchbase
Unicorns
Moorethread – 528.5M
Mobvoi – 252.8M
Scale.AI – 602M
Insider – 167 M
COPYRIGHT@ VISHAL SETHI, VISHAL@STARTUPOMEGA.COM
6. Rethinking products and business models
Walter Thompson and Microsoft, 2016
148 MP, 168263 scans, 300 paintings
Features –Caucasian male, 30-40 yrs, Facial
hair, hat, white collar, facing right
Rembrandt Harmenszoon van Rijn, 1606
lead white pigment and oils like linseed oil
Titian, Hendrick ter brugghen, High
viscosity and slow drying of oil paint
COPYRIGHT@ VISHAL SETHI, VISHAL@STARTUPOMEGA.COM
7. AI and Product-Market Economics?
Business model Digital Abundance New Possibilities
AI Is changing the
world
AI helps you capture
digital abundance
AI helps you leverage
economies of scope and
learning beyond scale.
COPYRIGHT@ VISHAL SETHI, VISHAL@STARTUPOMEGA.COM
8. Algorithms at the core od producst?
More data
Better
algorithms
Better
service
More
usage
Algorithm delivers customer
experience and operational
processes, and thus learn and
becomes better over a period of
time.
COPYRIGHT@ VISHAL SETHI, VISHAL@STARTUPOMEGA.COM
9. Why AI for SaaS and Digital Economy?
Source
Competing in the Age of AI, Marco Lansiti
COPYRIGHT@ VISHAL SETHI, VISHAL@STARTUPOMEGA.COM
10. Idea of an AI factory
AI Factory as Operational Foundation
COPYRIGHT@ VISHAL SETHI, VISHAL@STARTUPOMEGA.COM
11. Idea of an AI factory
Source - Sciencedirect.com
COPYRIGHT@ VISHAL SETHI, VISHAL@STARTUPOMEGA.COM
13. Quick review and thought reference?
How to augment human touchpoints with AI for
networking and learning?
How to build and leverage network effect for value?
How to create learning effects to build competitive
advantage?
Mapping business networks for value for targeted user
groups?
What networks are key to providing that service, and
what are their characteristics?
How to overcome challenges with network clustering?
Multihoming? Disintermediation?
Where are we experiencing or likely to experience
strong learning or network effects?
AI
Learning
Effects
Network
Effects
COPYRIGHT@ VISHAL SETHI, VISHAL@STARTUPOMEGA.COM
14. Convergence of technologies
Virtualization Cloud
Networking IoT/Device
AI
Compute cost
Storage cost
Data sourcing and
generation
Data abstraction
AI for AI
COPYRIGHT@ VISHAL SETHI, VISHAL@STARTUPOMEGA.COM
15. Product Planning
Business
Understanding
Data
Understanding
Data
Preparation
Modeling
Evalution
Deployment
Source - CRISP-DM model
O'Reilly
Not just magnitude but sentiments
Clear vision on focus for feature
engineering
Experimentation and appetite for failure
High touch custom productionable
architecture
Monitoring to observability
E.g. fraud monitoring for credit card burst
Learning system for physically challenged
COPYRIGHT@ VISHAL SETHI, VISHAL@STARTUPOMEGA.COM
16. Roadmap Execution
Data Quality
and
Standadization
Interface
Design
Prototypes and
MVP’s
Right Scope
Augmenting
product
with
Technical
Leadership
Testing AI/ML Products
UX driven design, user do not care about AI
Apple sense of design scope making
things work
Minimize black box
Create appetite for experimentation and failure
Create a ecosystem of product design
Form right technical partnership
A/B, Multivariate testing, Model
evaluation, fit and recalibrations, Data
biases and more
COPYRIGHT@ VISHAL SETHI, VISHAL@STARTUPOMEGA.COM
18. Netflix – Can a algorithm save a billion
dollar?
1 M $ price to build a baseline algorithm
Algorithm that saves 1B in customer retention
Recommendation system influence 80% content
geolocation, time, weather-data, device, voice recognition
etc to recommend the best and most relevant content
Viewing history, time and duration
Similar members with taste and preferences
Featuers such as Genre, categories, actors, releases
Personalization of thumb nails
Trending now
Continue watching
Because you watched a movie
COPYRIGHT@ VISHAL SETHI, VISHAL@STARTUPOMEGA.COM
19. Netflix and AI
Personalized
recommendations
Auto generation
of thumbnails
Location scouting Streaming quality
Movie editing
Personalized
learning to rank
Context awareness
Presentation
effects
Social
recommendations
Full page
optimization
Cold start
COPYRIGHT@ VISHAL SETHI, VISHAL@STARTUPOMEGA.COM
20. Netflix – A sneak peek
Strategy Metric Tactic/Project
Personalization RMSE Modal algorithm test, Voice ID,
Movie personality quick,
Language detection
Original content % of members who watch at
least 10 hours month of a
original content
Cold start merchandising test,
weekly release test, episodic
micro docs
Watching experience % of customers who watch at
least 40 hours/month
Ultra HD, customer playback
speed, shared viewing, lip synch,
algorithms (40 languages)
Interactive storytelling % of members who watch at
least one hour interactive
content per month
Support for real timing
branching prototyping, Kimmy,
Schmidt, launch
Strategy Q2 Q3 Q4 Q1
Personalization Mood algorithm
test
Voice recognition Language
detection
Movie personality
quiz
Original content Cold start system Weekly release
test
Support for
episodic micro
docs
Expert panel
forecasting
Watching
experience
Shared viewing Customer
playback speed
Automated lip
syncing in 40
languages
Ulta HD custom
mobile devices
Interactive
storytelling
Kimmy scmidt
launch
Real time branch
prototyping
Voice activated
decisions
Banderstrach#2
Source - Gibson Biddle, Productled
COPYRIGHT@ VISHAL SETHI, VISHAL@STARTUPOMEGA.COM
21. Netflix Data Stack a quick glance
COPYRIGHT@ VISHAL SETHI, VISHAL@STARTUPOMEGA.COM
Source Netflix Blog
22. A Guiding Framework
• Pain and gain
• User benefits
• MVP – HIP, HBS
• Product KPI’s
Value
Proposition
• Automation,
Assistance, and
Personalization
• ML technique
• Model metrics and UI
Problem
Framing • Engineers and Data
scientists
• Data and variable
engineering
• Inhouse or Incloud
Skills Data,
Platform
• Architecture – training
time, infrastructure as
a service
• Model best practices
• Integrations
Microservices
• Enhance UX
• Enhance model
• Enhance data
Experiment
and Iterate
COPYRIGHT@ VISHAL SETHI, VISHAL@STARTUPOMEGA.COM
23. ML Platform Conceptual View
Source
Towards data science
1. Data ingestion and
engineering
2. Feature store
3. Model management
and obersvability
GCP, AWS, Azure offer a
verity of services that can
be architected to enable
this in a short time
COPYRIGHT@ VISHAL SETHI, VISHAL@STARTUPOMEGA.COM
24. After deployment product management
Inputs to pipeline, confidence of model,
output it produces
Inputs are complete, comply
distributions, trigger alarms, model
retaining and shutdowns
GPU/TPU performance and caching. SLI’
SLO and SLA’s
Time based model retaining, Continuous
retaining
Create a ecosystem of product design
Form right technical partnership
Michelengalo, Zipine, H2O.ai, Mlflow,
Kubeflow, Seldon.io, Dask
Debugging
I/O validation
Task Speed and SlO’s
Durability and Monitoring
Frameworks
COPYRIGHT@ VISHAL SETHI, VISHAL@STARTUPOMEGA.COM
25. Embedding AI/ML in SaaS Ecosystem
Create MVP
don’t disrupt
Feature
Evaluation
Project
Estimation
Cloud platform
and Open stack
Teams and
Skills
Secure your
product
COPYRIGHT@ VISHAL SETHI, VISHAL@STARTUPOMEGA.COM
26. Driving Value with AI in SaaS ecosystem
AI’s capacity to
learn from a user’s
prior experiences
can be used to
customize
interface design in
SaaS.
Personalization
Human-machine,
machine-machine
processes may it
be repetitive or
intelligence can be
automated with AI
and mesh
technologies.
Automation
Machine learning
can help to predict
user preferences
or behavior,
product
performances,
then perhaps
trigger alerts or
actions when it
appears the user is
disengaging
Prediction
An easy and
intuitive search
reduces the
friction leaving
customer satisfied
in getting relevant
results of their
searches.
Search
AI can augment
SaaS developers
own coding
abilities by
providing the
necessary checks
that the coding is
good. This avoid
early release
crashes and bugs
while significantly
reducing release
cycle times.
Release
COPYRIGHT@ VISHAL SETHI, VISHAL@STARTUPOMEGA.COM
27. Some cool examples
Personalized
styling and
clothing
recommendation
Personalization
Customer support
bots are able to
login to systems
and reset
passwords based
on user request.
Automation
Uber predicts
surges in demand
to determine
pricing for peak
period and
optimizes its
margins.
Prediction
Power BI offers
voice services to
query dashboards
and reports.
Search
Alipay Tencent
analyzes the data
through machine
learning
algorithms to
inform and
automate an
expanding variety
of services.
Release
COPYRIGHT@ VISHAL SETHI, VISHAL@STARTUPOMEGA.COM
28. Take aways for Product Leaders
Problem Framing
Ethics
Planning and managing
project
Metrics
it’s even possible for an AI product “intervention” to move an
upstream business metric, e.g. is recommendation even good?
The scale and impact of a product over the
difficulty of product development.
AI performance tends to degrade over time
Is it a problem that should be solved? How can the solution
be abused?
Markkula Institute at the University of Santa Clara
Fault tolerance vs fault intolerant
Guardrail metrics, they ensure that the product analytics
aren’t giving the wrong signals. E.g reduce pick up time
per user vs maximize trips per user
COPYRIGHT@ VISHAL SETHI, VISHAL@STARTUPOMEGA.COM
29. Trends for Product Leaders to watch
Human in the loop
MLOps and FinOps
Observability and Automation
No Code
Data Fabric
COPYRIGHT@ VISHAL SETHI, VISHAL@STARTUPOMEGA.COM