The document discusses Defined Capital's activities in Q3 2023, which included mapping out the AI revolution and meeting with startups to inform their investment strategy. Their thesis is to invest in startups using data and AI to solve problems in new ways compared to traditional software. The rest of the document discusses the state of AI adoption, opportunities, challenges, and predictions for 2024, which include multi-agent models becoming prominent and most enterprise software embedding generative AI, among other predictions.
COVID-19 has increased the need for intelligent decisioning through AI, but ROI is not guaranteed. Here's how to accelerate AI outcomes, according to our recent study.
Artificial Intelligence in Financial Services: From Nice to Have to Must HaveCognizant
AI is moving beyond experimentation to become a competitive differentiator in financial services — delivering a hyper-personalized customer experience, improving decision-making and boosting operational efficiency, our recent primary research reveals. Yet, many financial services companies will need to accelerate their efforts to infuse AI across the value chain while preparing for the next generation of evolutionary neural network technologies to keep pace with more forward-thinking players.
IT that matters in the new machine age prioritizes cybersecurity, innovation, time-to-market and customers over cost-cutting, according to our latest study. Here’s what the future looks like for IT infrastructure, including our HEROES framework to guide you along the way.
The State of Global AI Adoption in 2023InData Labs
In our inaugural report, 2023 State of AI, we examine trends in AI adoption across industries, the current state of the market, and technologies that shape the field.
The goal of this report is to help company leaders and executives get a better handle on the AI landscape and the opportunities it brings for the business.
2023 State of AI report will help you to answer questions such as:
-How are organizations applying artificial intelligence in the real world in 2023?
-What industries are leading in terms of AI maturity?
-How has generative AI impacted businesses?
-How can organizations prepare for AI transformation?
Download your free copy now and adopt the key technologies to improve your business.
Artificial intelligence (AI), also known as machine intelligence, is an aspect of computer science that deals will the designing of intelligent mechanical systems that work and react like humans. AI incorporates information from everything ranging from Google search algorithms to machinal processes. From SIRI to self-driving cars, everything is the outcome of artificial intelligence, which is rapidly progressing and taking over our human lives.
COVID-19 has increased the need for intelligent decisioning through AI, but ROI is not guaranteed. Here's how to accelerate AI outcomes, according to our recent study.
Artificial Intelligence in Financial Services: From Nice to Have to Must HaveCognizant
AI is moving beyond experimentation to become a competitive differentiator in financial services — delivering a hyper-personalized customer experience, improving decision-making and boosting operational efficiency, our recent primary research reveals. Yet, many financial services companies will need to accelerate their efforts to infuse AI across the value chain while preparing for the next generation of evolutionary neural network technologies to keep pace with more forward-thinking players.
IT that matters in the new machine age prioritizes cybersecurity, innovation, time-to-market and customers over cost-cutting, according to our latest study. Here’s what the future looks like for IT infrastructure, including our HEROES framework to guide you along the way.
The State of Global AI Adoption in 2023InData Labs
In our inaugural report, 2023 State of AI, we examine trends in AI adoption across industries, the current state of the market, and technologies that shape the field.
The goal of this report is to help company leaders and executives get a better handle on the AI landscape and the opportunities it brings for the business.
2023 State of AI report will help you to answer questions such as:
-How are organizations applying artificial intelligence in the real world in 2023?
-What industries are leading in terms of AI maturity?
-How has generative AI impacted businesses?
-How can organizations prepare for AI transformation?
Download your free copy now and adopt the key technologies to improve your business.
Artificial intelligence (AI), also known as machine intelligence, is an aspect of computer science that deals will the designing of intelligent mechanical systems that work and react like humans. AI incorporates information from everything ranging from Google search algorithms to machinal processes. From SIRI to self-driving cars, everything is the outcome of artificial intelligence, which is rapidly progressing and taking over our human lives.
How Companies Can Move AI from Labs to the Business CoreCognizant
APAC and Middle East organisations have big expectations from AI, but they’re only just getting started. To realise the full potential of AI-led innovation, they must rapidly, but smartly, scale their deployments and embrace a strong ethical foundation, keeping a close eye on the human implications and cultural changes required to convert machine intelligence from lofty concept to business reality.
Artificial intelligence (AI) offers new opportunities to radically reinvent the way we do business. This study explores how CEOs and top decision makers around the world are responding to the transformative potential of AI.
Patrick Couch - Intelligenta Maskiner & Smartare Tjänster IBM Sverige
Industriföretag, såväl tillverkare som användare av maskiner, fordon och utrustning, står inför ett paradigmskifte drivet av ökad global konkurrens, kunders förändrade efterfrågan samt det faktum att produkterna nu blir instrumenterade, ihopkopplade och mer intelligenta. Stora datamängder är inte ett buzzword för dessa företag, utan en reell verklighet som de behöver förhålla sig till för att säkra sin framtida verksamhet. I bästa fall omvandlar dessa företag denna teknologiska revolution (populärt kallad Internet of Things, Industrial Internet, M2M, Industri 4.0 etc.) till en motor för att utveckla verksamheten mot tillväxt och effektivare produktion. Detta skifte skapar framförallt stora möjligheter att förflytta sig mot leveranser av tjänster som kraftigt ökar mervärdet för kunderna, deras kunders kunder samt för producenten.
Artificial Intelligence: Competitive Edge for Business Solutions & Applications9 series
The growth of Artificial Intelligence in recent years brought forth a major challenge for brands in deploying such AI solutions. Many brands lack the clarity regarding where to start the AI integration process and profitably deploy these solutions in the most effective manner.
Mining intelligent insights with ease: AI/ML for Financial ServicesAmazon Web Services
This year, the focus goes beyond technology to mining business insights around how cloud enables strategic industry trends such as Open and Virtual Banking and Insurance, Security and Compliance, Data Analytics and AI/ ML, FinTech and RegTech, Surveillance and more through sharing of best practices and use cases. In sessions led by customers, partners, industry leaders and AWS subject matter experts, you’ll learn how AWS helps financial institutions to focus on the innovation and outcomes that truly drive business forward. Business stakeholders, market makers, and technology owners will all learn something new, valuable and actionable.
AI for Enterprises-The Value Paradigm By Venkat Subramanian VP Marketing at B...Analytics India Magazine
AI is here, call it buzz, cause it a bubble, we are smack in the middle of an AI revolution. While there is a strong view building about consumer AI applications, there still seems to be some scepticism about AI for enterprises, primarily due to the lack of clarity and focus on how AI can actually deliver value for enterprises. At BRIDGEi2i, we believe it is important to have a non-fragmented view of the AI ecosystem and a “Value Roadmap” for AI in the enterprise context. As CxOs, it is important to understand where the enterprise is in the transformation journey and define value accordingly. This talk will throw light on how to look at the enterprise AI ecosystem and build the right roadmap for value.
Ai - Artificial Intelligence predictions-2018-report - PWCRick Bouter
Here’s some actionable advice on artificial intelligence (AI), that you can
use today: If someone says they know exactly what AI will look like and
do in 10 years, smile politely, then change the subject or walk away.
AI in Media & Entertainment: Starting the Journey to ValueCognizant
Up to now, the global media & entertainment industry (M&E) has been lagging most other sectors in its adoption of artificial intelligence (AI). But our research shows that M&E companies are set to close the gap over the coming three years, as they ramp up their investments in AI and reap rising returns. The first steps? Getting a firm grip on data – the foundation of any successful AI strategy – and balancing technology spend with investments in AI skills.
Moving to the Cloud: Artificial Intelligence in Cloud-Based SolutionsAggregage
With the advent of chatbots, artificial intelligence, interactive voice response, and machine learning, novel technologies continue to disrupt the contact center industry. These advances initially gave the impression that automation will replace the human element. Join Rick Nucci, Co-Founder and CEO of Guru, as he demystifies AI, explains how machine learning helps contact centers rather than replaces them, and demonstrates how to leverage this new technology to create innovative solutions.
Moving to the Cloud: Artificial Intelligence in Cloud-Based SolutionsNicolas Rodriguez
With the advent of chatbots, artificial intelligence, interactive voice response, and machine learning, novel technologies continue to disrupt the contact center industry. These advances initially gave the impression that automation will replace the human element. Join Rick Nucci, Co-Founder and CEO of Guru, as he demystifies AI, explains how machine learning helps contact centers rather than replaces them, and demonstrates how to leverage this new technology to create innovative solutions.
AI in Manufacturing: moving AI from Idea to ExecutionbyteLAKE
#AI and #HPC convergence is here and is here to stay and accelerate innovations across industries. The increased availability of data, hardware advancements leading to increased computational capabilities, and new algorithms and mathematical models have collectively resulted in the accelerated AI expansion in all sorts of applications. This, however, creates high computational needs which naturally have been more and more successfully addressed by HPC (High-Performance Computing). In that sense, AI & HPC complement each other. HPC infrastructure is often used to train AI’s powerful algorithms by leveraging huge amounts of sample data (training set) and in that way enables AI models (trained algorithms) to recognize shapes, objects (machine vision), find answers hidden in the data (predictive maintenance, data analytics) or accelerate time to results (predict the outcome of complex engineering simulations).
We at byteLAKE have been closely working with Lenovo, Lenovo Infrastructure Solutions Group, Intel Corporation, NVIDIA and many more to ensure that our AI-powered products not only help our clients efficiently automate various operations and reduce time and cost but also are highly optimized and make the most of the hardware and software infrastructure where they are deployed. Besides our efforts in bringing AI solutions to the paper industry and manufacturing in general (which I described in my previous post), our efforts in bringing value thru AI in the chemical industry highly benefit from HPC's capabilities to dynamically scale and keep up with performance requirements. Our product, #CFDSuite (AI-accelerated CFD) leverages HPC to efficiently analyze historic CFD simulations and makes it possible for our clients to predict their outcomes on various edge devices i.e. laptops, desktop PCs or local edge servers. And with that in mind, I am very happy to see the byteLAKE team becoming one of the drivers of AI & HPC convergence and leveraging it to bring innovations to various industries.
Links:
- byteLAKE's Cognitive Services: www.byteLAKE.com/en/CognitiveServices (Cognitive Services (AI for Paper Industry & Manufacturing)). Related blog post series: www.byteLAKE.com/en/CognitiveServices-toc
- byteLAKE's CFD Suite: www.byteLAKE.com/en/CFDSuite. Related blog post series: www.byteLAKE.com/en/AI4CFD-toc
- byteLAKE’s CFD Suite (AI-accelerated CFD) — HPC scalability report: https://marcrojek.medium.com/bytelakes-cfd-suite-ai-accelerated-cfd-hpc-scalability-report-25f9786e6123 (full report: https://www.slideshare.net/byteLAKE/bytelakes-cfd-suite-aiaccelerated-cfd-hpc-scalability-report-april21)
- byteLAKE's CFD Suite (AI-accelerated CFD) - product community: www.bytelake.com/en/AI4CFD-pt2 (LinkedIn and Facebook groups)
#AI #IoT #Manufacturing #Automotive #Paper #PaperIndustry #ChemicalIndustry #CFD #FluidDynamics #OpenFOAM #ArtificialIntelligence #DeepLearning #MachineLearning #ComputerVision #Automation #Industry40
Our latest research reveals the need for companies to complement their technology advances with a focus on governance that drives ethics and trust. Otherwise, their AI efforts will fall short of competitors’ initiatives that responsibly embrace machine intelligence.
Each CIO post description includes something resembling the 12 roles and requirements. This list outlines what CEOs are currently looking for in their CIOs. However, it's not necessarily what CEOs really need from their CIOs.
In the current data-driven economy, in which analytics and software have become the main factors in business, executives must reconsider the hierarchies and silos that fueled the business in the past. There is no longer a need for "technology people" who work independently of "data people" who work in isolation from "sales" people or from "finance." Instead, they need to manage organizations where every employee is embraced by technology and data as integral to their work.
They also require CIOs to guide them there. In this regard, redefining the business to accommodate the new data economy is the primary task executives have to today's top-of-the-line CIOs.
Here's how:
from Software and the Business to Software is the Business
When Cargill began to put IoT sensors in shrimp ponds, Chief Information Officer Justin Kershaw realised that the $130 billion agriculture business was evolving into a digital enterprise. To determine the point at which IT should stop and where IoT technology engineering needs to begin, Kershaw did not call CIOs from other food and agricultural companies to discuss their experiences. He contacted the CIOs of SAP and Microsoft as well as various other companies that use software. He was thinking about reimagining the world's biggest agricultural business as a software business.
Modern Delivery
Moving software from a supporting role to leading position is the why is the issue, then modern delivery is the way to do it. Modern delivery involves an approach to product (rather as project) management rapid development and small teams of cross-functional experts which co-create, as well as continuous integration and delivery, all with a brand new financial model that supports "value" not "projects."
However, don't try to build an modern SDLC. Instead, build a software development cycle (SDLC) on an industrial infrastructure. The architecture that is intended for this data-driven economy relies on platforms and cloud-connected, makes use of APIs that connect with an ecosystem outside and splits monolithic applications into microservices.
"A platforms model encompasses more than just an architecture. It's a mental model that allows us to consider how vertically we can provide the vet, farmer, or pet's owners, then expand to think horizontally about ways to make solutions adaptable, scalable and secure" claims Wafaa Mamilli Chief Information Officer and Digital Officer of global animal health firm Zoetis. "Platforms can be flexible, intelligent and run algorithms that let us rapidly change. If we did not adopt the platform model and approach, we'd be funding these massive programs."
The Democratisation of IT
If you gift someone an uncooked fish, they can take a bite for a few hours.
Learn more about what senior insurance executives and employees are thinking and doing with regard to artificial intelligence. Read how roles and tasks are likely to change as people start to work more collaboratively with intelligent machines, and find out what the key steps are to developing the insurance workforce of the future.
Get Ready: AI Is Grown Up and Ready for BusinessCognizant
Despite great enthusiasm for AI, full-blown deployments remain the exception rather than the rule across businesses in the U.S. and Europe, according to our recent research. Businesses can turn the tide by honing their AI strategies, maintaining a human-centric approach, developing governance structures and ensuring AI applications are built on an ethical foundation.
Talent Augmentation: Through Intelligent Process Automation, Smart Robots Ext...Cognizant
Process automation is moving from the factory floor to the world of knowledge work. But robots can't do it alone. Companies that calibrate smart people with smart machines are already achieving higher productivity and superior business results.
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
Welocme to ViralQR, your best QR code generator.ViralQR
Welcome to ViralQR, your best QR code generator available on the market!
At ViralQR, we design static and dynamic QR codes. Our mission is to make business operations easier and customer engagement more powerful through the use of QR technology. Be it a small-scale business or a huge enterprise, our easy-to-use platform provides multiple choices that can be tailored according to your company's branding and marketing strategies.
Our Vision
We are here to make the process of creating QR codes easy and smooth, thus enhancing customer interaction and making business more fluid. We very strongly believe in the ability of QR codes to change the world for businesses in their interaction with customers and are set on making that technology accessible and usable far and wide.
Our Achievements
Ever since its inception, we have successfully served many clients by offering QR codes in their marketing, service delivery, and collection of feedback across various industries. Our platform has been recognized for its ease of use and amazing features, which helped a business to make QR codes.
Our Services
At ViralQR, here is a comprehensive suite of services that caters to your very needs:
Static QR Codes: Create free static QR codes. These QR codes are able to store significant information such as URLs, vCards, plain text, emails and SMS, Wi-Fi credentials, and Bitcoin addresses.
Dynamic QR codes: These also have all the advanced features but are subscription-based. They can directly link to PDF files, images, micro-landing pages, social accounts, review forms, business pages, and applications. In addition, they can be branded with CTAs, frames, patterns, colors, and logos to enhance your branding.
Pricing and Packages
Additionally, there is a 14-day free offer to ViralQR, which is an exceptional opportunity for new users to take a feel of this platform. One can easily subscribe from there and experience the full dynamic of using QR codes. The subscription plans are not only meant for business; they are priced very flexibly so that literally every business could afford to benefit from our service.
Why choose us?
ViralQR will provide services for marketing, advertising, catering, retail, and the like. The QR codes can be posted on fliers, packaging, merchandise, and banners, as well as to substitute for cash and cards in a restaurant or coffee shop. With QR codes integrated into your business, improve customer engagement and streamline operations.
Comprehensive Analytics
Subscribers of ViralQR receive detailed analytics and tracking tools in light of having a view of the core values of QR code performance. Our analytics dashboard shows aggregate views and unique views, as well as detailed information about each impression, including time, device, browser, and estimated location by city and country.
So, thank you for choosing ViralQR; we have an offer of nothing but the best in terms of QR code services to meet business diversity!
More Related Content
Similar to Defined Capital - Mapping the AI Revolution and State of Adoption.pdf
How Companies Can Move AI from Labs to the Business CoreCognizant
APAC and Middle East organisations have big expectations from AI, but they’re only just getting started. To realise the full potential of AI-led innovation, they must rapidly, but smartly, scale their deployments and embrace a strong ethical foundation, keeping a close eye on the human implications and cultural changes required to convert machine intelligence from lofty concept to business reality.
Artificial intelligence (AI) offers new opportunities to radically reinvent the way we do business. This study explores how CEOs and top decision makers around the world are responding to the transformative potential of AI.
Patrick Couch - Intelligenta Maskiner & Smartare Tjänster IBM Sverige
Industriföretag, såväl tillverkare som användare av maskiner, fordon och utrustning, står inför ett paradigmskifte drivet av ökad global konkurrens, kunders förändrade efterfrågan samt det faktum att produkterna nu blir instrumenterade, ihopkopplade och mer intelligenta. Stora datamängder är inte ett buzzword för dessa företag, utan en reell verklighet som de behöver förhålla sig till för att säkra sin framtida verksamhet. I bästa fall omvandlar dessa företag denna teknologiska revolution (populärt kallad Internet of Things, Industrial Internet, M2M, Industri 4.0 etc.) till en motor för att utveckla verksamheten mot tillväxt och effektivare produktion. Detta skifte skapar framförallt stora möjligheter att förflytta sig mot leveranser av tjänster som kraftigt ökar mervärdet för kunderna, deras kunders kunder samt för producenten.
Artificial Intelligence: Competitive Edge for Business Solutions & Applications9 series
The growth of Artificial Intelligence in recent years brought forth a major challenge for brands in deploying such AI solutions. Many brands lack the clarity regarding where to start the AI integration process and profitably deploy these solutions in the most effective manner.
Mining intelligent insights with ease: AI/ML for Financial ServicesAmazon Web Services
This year, the focus goes beyond technology to mining business insights around how cloud enables strategic industry trends such as Open and Virtual Banking and Insurance, Security and Compliance, Data Analytics and AI/ ML, FinTech and RegTech, Surveillance and more through sharing of best practices and use cases. In sessions led by customers, partners, industry leaders and AWS subject matter experts, you’ll learn how AWS helps financial institutions to focus on the innovation and outcomes that truly drive business forward. Business stakeholders, market makers, and technology owners will all learn something new, valuable and actionable.
AI for Enterprises-The Value Paradigm By Venkat Subramanian VP Marketing at B...Analytics India Magazine
AI is here, call it buzz, cause it a bubble, we are smack in the middle of an AI revolution. While there is a strong view building about consumer AI applications, there still seems to be some scepticism about AI for enterprises, primarily due to the lack of clarity and focus on how AI can actually deliver value for enterprises. At BRIDGEi2i, we believe it is important to have a non-fragmented view of the AI ecosystem and a “Value Roadmap” for AI in the enterprise context. As CxOs, it is important to understand where the enterprise is in the transformation journey and define value accordingly. This talk will throw light on how to look at the enterprise AI ecosystem and build the right roadmap for value.
Ai - Artificial Intelligence predictions-2018-report - PWCRick Bouter
Here’s some actionable advice on artificial intelligence (AI), that you can
use today: If someone says they know exactly what AI will look like and
do in 10 years, smile politely, then change the subject or walk away.
AI in Media & Entertainment: Starting the Journey to ValueCognizant
Up to now, the global media & entertainment industry (M&E) has been lagging most other sectors in its adoption of artificial intelligence (AI). But our research shows that M&E companies are set to close the gap over the coming three years, as they ramp up their investments in AI and reap rising returns. The first steps? Getting a firm grip on data – the foundation of any successful AI strategy – and balancing technology spend with investments in AI skills.
Moving to the Cloud: Artificial Intelligence in Cloud-Based SolutionsAggregage
With the advent of chatbots, artificial intelligence, interactive voice response, and machine learning, novel technologies continue to disrupt the contact center industry. These advances initially gave the impression that automation will replace the human element. Join Rick Nucci, Co-Founder and CEO of Guru, as he demystifies AI, explains how machine learning helps contact centers rather than replaces them, and demonstrates how to leverage this new technology to create innovative solutions.
Moving to the Cloud: Artificial Intelligence in Cloud-Based SolutionsNicolas Rodriguez
With the advent of chatbots, artificial intelligence, interactive voice response, and machine learning, novel technologies continue to disrupt the contact center industry. These advances initially gave the impression that automation will replace the human element. Join Rick Nucci, Co-Founder and CEO of Guru, as he demystifies AI, explains how machine learning helps contact centers rather than replaces them, and demonstrates how to leverage this new technology to create innovative solutions.
AI in Manufacturing: moving AI from Idea to ExecutionbyteLAKE
#AI and #HPC convergence is here and is here to stay and accelerate innovations across industries. The increased availability of data, hardware advancements leading to increased computational capabilities, and new algorithms and mathematical models have collectively resulted in the accelerated AI expansion in all sorts of applications. This, however, creates high computational needs which naturally have been more and more successfully addressed by HPC (High-Performance Computing). In that sense, AI & HPC complement each other. HPC infrastructure is often used to train AI’s powerful algorithms by leveraging huge amounts of sample data (training set) and in that way enables AI models (trained algorithms) to recognize shapes, objects (machine vision), find answers hidden in the data (predictive maintenance, data analytics) or accelerate time to results (predict the outcome of complex engineering simulations).
We at byteLAKE have been closely working with Lenovo, Lenovo Infrastructure Solutions Group, Intel Corporation, NVIDIA and many more to ensure that our AI-powered products not only help our clients efficiently automate various operations and reduce time and cost but also are highly optimized and make the most of the hardware and software infrastructure where they are deployed. Besides our efforts in bringing AI solutions to the paper industry and manufacturing in general (which I described in my previous post), our efforts in bringing value thru AI in the chemical industry highly benefit from HPC's capabilities to dynamically scale and keep up with performance requirements. Our product, #CFDSuite (AI-accelerated CFD) leverages HPC to efficiently analyze historic CFD simulations and makes it possible for our clients to predict their outcomes on various edge devices i.e. laptops, desktop PCs or local edge servers. And with that in mind, I am very happy to see the byteLAKE team becoming one of the drivers of AI & HPC convergence and leveraging it to bring innovations to various industries.
Links:
- byteLAKE's Cognitive Services: www.byteLAKE.com/en/CognitiveServices (Cognitive Services (AI for Paper Industry & Manufacturing)). Related blog post series: www.byteLAKE.com/en/CognitiveServices-toc
- byteLAKE's CFD Suite: www.byteLAKE.com/en/CFDSuite. Related blog post series: www.byteLAKE.com/en/AI4CFD-toc
- byteLAKE’s CFD Suite (AI-accelerated CFD) — HPC scalability report: https://marcrojek.medium.com/bytelakes-cfd-suite-ai-accelerated-cfd-hpc-scalability-report-25f9786e6123 (full report: https://www.slideshare.net/byteLAKE/bytelakes-cfd-suite-aiaccelerated-cfd-hpc-scalability-report-april21)
- byteLAKE's CFD Suite (AI-accelerated CFD) - product community: www.bytelake.com/en/AI4CFD-pt2 (LinkedIn and Facebook groups)
#AI #IoT #Manufacturing #Automotive #Paper #PaperIndustry #ChemicalIndustry #CFD #FluidDynamics #OpenFOAM #ArtificialIntelligence #DeepLearning #MachineLearning #ComputerVision #Automation #Industry40
Our latest research reveals the need for companies to complement their technology advances with a focus on governance that drives ethics and trust. Otherwise, their AI efforts will fall short of competitors’ initiatives that responsibly embrace machine intelligence.
Each CIO post description includes something resembling the 12 roles and requirements. This list outlines what CEOs are currently looking for in their CIOs. However, it's not necessarily what CEOs really need from their CIOs.
In the current data-driven economy, in which analytics and software have become the main factors in business, executives must reconsider the hierarchies and silos that fueled the business in the past. There is no longer a need for "technology people" who work independently of "data people" who work in isolation from "sales" people or from "finance." Instead, they need to manage organizations where every employee is embraced by technology and data as integral to their work.
They also require CIOs to guide them there. In this regard, redefining the business to accommodate the new data economy is the primary task executives have to today's top-of-the-line CIOs.
Here's how:
from Software and the Business to Software is the Business
When Cargill began to put IoT sensors in shrimp ponds, Chief Information Officer Justin Kershaw realised that the $130 billion agriculture business was evolving into a digital enterprise. To determine the point at which IT should stop and where IoT technology engineering needs to begin, Kershaw did not call CIOs from other food and agricultural companies to discuss their experiences. He contacted the CIOs of SAP and Microsoft as well as various other companies that use software. He was thinking about reimagining the world's biggest agricultural business as a software business.
Modern Delivery
Moving software from a supporting role to leading position is the why is the issue, then modern delivery is the way to do it. Modern delivery involves an approach to product (rather as project) management rapid development and small teams of cross-functional experts which co-create, as well as continuous integration and delivery, all with a brand new financial model that supports "value" not "projects."
However, don't try to build an modern SDLC. Instead, build a software development cycle (SDLC) on an industrial infrastructure. The architecture that is intended for this data-driven economy relies on platforms and cloud-connected, makes use of APIs that connect with an ecosystem outside and splits monolithic applications into microservices.
"A platforms model encompasses more than just an architecture. It's a mental model that allows us to consider how vertically we can provide the vet, farmer, or pet's owners, then expand to think horizontally about ways to make solutions adaptable, scalable and secure" claims Wafaa Mamilli Chief Information Officer and Digital Officer of global animal health firm Zoetis. "Platforms can be flexible, intelligent and run algorithms that let us rapidly change. If we did not adopt the platform model and approach, we'd be funding these massive programs."
The Democratisation of IT
If you gift someone an uncooked fish, they can take a bite for a few hours.
Learn more about what senior insurance executives and employees are thinking and doing with regard to artificial intelligence. Read how roles and tasks are likely to change as people start to work more collaboratively with intelligent machines, and find out what the key steps are to developing the insurance workforce of the future.
Get Ready: AI Is Grown Up and Ready for BusinessCognizant
Despite great enthusiasm for AI, full-blown deployments remain the exception rather than the rule across businesses in the U.S. and Europe, according to our recent research. Businesses can turn the tide by honing their AI strategies, maintaining a human-centric approach, developing governance structures and ensuring AI applications are built on an ethical foundation.
Talent Augmentation: Through Intelligent Process Automation, Smart Robots Ext...Cognizant
Process automation is moving from the factory floor to the world of knowledge work. But robots can't do it alone. Companies that calibrate smart people with smart machines are already achieving higher productivity and superior business results.
Similar to Defined Capital - Mapping the AI Revolution and State of Adoption.pdf (20)
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
Welocme to ViralQR, your best QR code generator.ViralQR
Welcome to ViralQR, your best QR code generator available on the market!
At ViralQR, we design static and dynamic QR codes. Our mission is to make business operations easier and customer engagement more powerful through the use of QR technology. Be it a small-scale business or a huge enterprise, our easy-to-use platform provides multiple choices that can be tailored according to your company's branding and marketing strategies.
Our Vision
We are here to make the process of creating QR codes easy and smooth, thus enhancing customer interaction and making business more fluid. We very strongly believe in the ability of QR codes to change the world for businesses in their interaction with customers and are set on making that technology accessible and usable far and wide.
Our Achievements
Ever since its inception, we have successfully served many clients by offering QR codes in their marketing, service delivery, and collection of feedback across various industries. Our platform has been recognized for its ease of use and amazing features, which helped a business to make QR codes.
Our Services
At ViralQR, here is a comprehensive suite of services that caters to your very needs:
Static QR Codes: Create free static QR codes. These QR codes are able to store significant information such as URLs, vCards, plain text, emails and SMS, Wi-Fi credentials, and Bitcoin addresses.
Dynamic QR codes: These also have all the advanced features but are subscription-based. They can directly link to PDF files, images, micro-landing pages, social accounts, review forms, business pages, and applications. In addition, they can be branded with CTAs, frames, patterns, colors, and logos to enhance your branding.
Pricing and Packages
Additionally, there is a 14-day free offer to ViralQR, which is an exceptional opportunity for new users to take a feel of this platform. One can easily subscribe from there and experience the full dynamic of using QR codes. The subscription plans are not only meant for business; they are priced very flexibly so that literally every business could afford to benefit from our service.
Why choose us?
ViralQR will provide services for marketing, advertising, catering, retail, and the like. The QR codes can be posted on fliers, packaging, merchandise, and banners, as well as to substitute for cash and cards in a restaurant or coffee shop. With QR codes integrated into your business, improve customer engagement and streamline operations.
Comprehensive Analytics
Subscribers of ViralQR receive detailed analytics and tracking tools in light of having a view of the core values of QR code performance. Our analytics dashboard shows aggregate views and unique views, as well as detailed information about each impression, including time, device, browser, and estimated location by city and country.
So, thank you for choosing ViralQR; we have an offer of nothing but the best in terms of QR code services to meet business diversity!
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
PHP Frameworks: I want to break free (IPC Berlin 2024)Ralf Eggert
In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
SAP Sapphire 2024 - ASUG301 building better apps with SAP Fiori.pdfPeter Spielvogel
Building better applications for business users with SAP Fiori.
• What is SAP Fiori and why it matters to you
• How a better user experience drives measurable business benefits
• How to get started with SAP Fiori today
• How SAP Fiori elements accelerates application development
• How SAP Build Code includes SAP Fiori tools and other generative artificial intelligence capabilities
• How SAP Fiori paves the way for using AI in SAP apps
Le nuove frontiere dell'AI nell'RPA con UiPath Autopilot™UiPathCommunity
In questo evento online gratuito, organizzato dalla Community Italiana di UiPath, potrai esplorare le nuove funzionalità di Autopilot, il tool che integra l'Intelligenza Artificiale nei processi di sviluppo e utilizzo delle Automazioni.
📕 Vedremo insieme alcuni esempi dell'utilizzo di Autopilot in diversi tool della Suite UiPath:
Autopilot per Studio Web
Autopilot per Studio
Autopilot per Apps
Clipboard AI
GenAI applicata alla Document Understanding
👨🏫👨💻 Speakers:
Stefano Negro, UiPath MVPx3, RPA Tech Lead @ BSP Consultant
Flavio Martinelli, UiPath MVP 2023, Technical Account Manager @UiPath
Andrei Tasca, RPA Solutions Team Lead @NTT Data
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Generative AI Deep Dive: Advancing from Proof of Concept to ProductionAggregage
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.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
2. Defined Capital | LP Update Q3 2023 | CONFIDENTIAL
We spent Q3 2023 mapping out the AI revolution to target our theses
and investments alongside engaging with a multitude of startups and
companies to inform our strategy and investment decisions.
Our thesis: to invest in startups solving well-defined problems with the
power of data and AI in ways that traditional software has not been
able to accomplish yet.
Defined is led by a proven VC and former operator and engineer with
15+ years of company building and investing in data, automation and AI.
2
Overview
3. Defined Capital | LP Update Q3 2023 | CONFIDENTIAL
2
Humans + Machines Relationship Inversion
1
It used to be to that humans had to communicate with machines in programming languages
designed for machines to comprehend – now they take input in our language and meet use
where we are at.
GenAI and NLP represent not just an AI revolution, but a profound inversion in the relationship
between humans and machines
It used to be that humans would create and computers would validate results – now the
machines create and humans QA.
3
Specialized and technically advantaged pick-and-shovel building blocks benefiting from
arms race
3
With new LLM capabilities, we see applications that go beyond what humans have been
capable of alone – look no further than machine-driven breakthrough in the natural sciences
like AlphaFold and GNoMe – and the emergence of systems of intelligence.
This is setting the stage for a profound shift in how products provide value and AI is adopted
into workflows
4. Defined Capital | LP Update Q3 2023 | CONFIDENTIAL
To Achieve Adoption, Need to Embrace “Four A’s” of Human Enablement with
AI to complete “Jobs to be Done”
4
I no longer need to do this
Job To be Done (JBTD)
because of AI.
AI helps automate low-
level, repetitive tasks
like debugging, lead
gen and outbound
emailing.
AI can help me do this
JTBD better.
More human-centric,
higher ROI work like
customer service,
strategy and
campaigns.
Automation
(tasks)
Augmentation
(capabilities)
Alignment
AI helps the whole company
do their jobs better
High potential to coordinate
with teams, department,
business units and wide
company towards shared
JBTDs, outcomes and goals
(KPIs, OKRs).
Adoption
Value of AI can only be
unlocked if can overcome
barriers to adoption of
humans and companies.
5. Defined Capital | LP Update Q3 2023 | CONFIDENTIAL
Key Criteria to Evaluate Attractiveness of JTBDs for AI
5
• A top pain point in many industries is workforce retention, especially among
workers who require significant upfront and ongoing training. These are areas
where hiring “AI staff members” (versus buying software and mandating
employees to change their workflow to use it) has high potential for uptake.
1
2
3
4
• Areas in which humans are prone to error or are generally slow and inefficient
(even when supported by software products) are most likely to benefit from AI
approaches.
• Areas of higher, more specialized labor spend, or areas in which an AI product
could simply ride existing revenue or transaction rails–either for substitute
human services or software tools.
Area of high
spend on highly
trained labor
Potential 10x
performance
with AI
Areas with low
adoption of
software
Established revenue
rails and financial
incentives
• Enterprises are more likely to adopt AI if its cost benefit is at least an order of
magnitude (and ideally more!) better than the status quo. Therefore, we’re likely to
see a stronger opportunity in areas that have a low penetration of existing
software tools, where AI cost benefit is being compared to human labor, versus
software.
6. Defined Capital | LP Update Q3 2023 | CONFIDENTIAL
Adoption Rate of Disruptive New Technologies
After its first decade, the cloud reach 30% of enterprise software spend; the internet 45% penetration;
and mobile nearly 85%, the pace of AI adoption will be dramatically faster.
Source: Menlo Ventures
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
1990 1995 2000 2005 2010 2015 2020 2025
Internet Smartphones Cloud AI
US Technology Adoption %
6
7. Defined Capital | LP Update Q3 2023 | CONFIDENTIAL 7
Comparison: Autonomous Vehicles vs. Generative AI
Gen AI advancing much faster than previous technological waves.
Levels of Autonomy Autonomous Vehicles Generative AI
L5
L4
L3
L2
L1
Fully autonomous
Highly autonomous
Self-driving with light
intervention
Tesla autopilot
Cruise control
Superhuman reasoning & perception
AI autopilots for complex tasks
AI co-pilot for skilled labor
Supporting humans with basic tasks
Generating basic content
15
Years
5
Years
Source: Coatue
8. Defined Capital | LP Update Q3 2023 | CONFIDENTIAL 8
Magnitude
Wave 1: AI Natives – Bard, Character, Midjourney, OpenAI
Wave 2.0: Early startup wave - Harvey, Perplexity, Langchain
Wave 2.1: Fast mid-market companies - Notion, Zapier
Wave 3 (Pending): Next startup wave - Showing sustainable value
Wave 4 (Pending): REAL enterprise adoption - BIG WAVE
Time
TODAY
AI Adoption Curves
True enterprise adoption is
still many quarters/years
away.
Given that large enterprise
planning cycles often take
3-6 months, and then
prototyping and building will
take a year for a large
company, we are still very
far away from peak AI usage
or peak AI hype.
Source: Elad Gill
9. Defined Capital | LP Update Q3 2023 | CONFIDENTIAL
Supervised Learning
(Labelling Things)
Generative AI
Reinforcement
Learning
Value from AI Technology Today → 3 Years
Supervised learning is massive majority of AI deployment, and Andrew Ng predicts it should double in the next 3
years. Generative AI should more than double, but it won't catch up in terms of scale.
Don't let online hype lead you astray. Learning the fundamentals is as important as it's always been.
Rather than view LLMs, Transformers, and diffusion models as part of a continuum with past "AI", it is worth
thinking of this as an entirely new era and discontinuity from the past
Unsupervised
Learning
9
Source: Andrew Ng, Stanford
10. Defined Capital | LP Update Q3 2023 | CONFIDENTIAL
AI Spend
10
Enterprise investment in GenAI - which is estimated to be $2.5B in 2023 is surprisingly small compared to
the enterprise budgets for traditional AI ($70B) and cloud software ($400B).
$400B
$70B
Cloud software spend Total AI Spend Gen. AI Spend
AI spend has potential to grow by
up to 6x in the next 7 years to
match current Cloud spend
$3B
Source: Menlo Ventures
11. Defined Capital | LP Update Q3 2023 | CONFIDENTIAL
Potential Annual Value of AI and Analytics Across Industries
11
CLICK HERE FOR INTERACTIVE CHART
$9.5T - $15.4T
Focusing investments where the most significant unlocks in value and market adoption will materialize
Source: MckInsey
12. Defined Capital | LP Update Q3 2023 | CONFIDENTIAL
State of AI Adoption – Where are we today?
12
• A majority (77.1%) of survey
respondents said that their
companies have made
some sort of effort to adopt
AI.
• But around half (48.9%)
said those efforts were
fledgling—just getting
started or ad-hoc use
cases.
• A non-trivial 15.7% haven’t
really started yet, and might
not anytime soon.
`
15.7% 29.6% 19.3% 14.8% 13.4%
We haven’t
started
adopting yet
We’re getting
the basics in
place
We have
some ad-hoc
use cases in
production
We have
several use
cases in
production
We’re leading
the industry in
AI adoption
It is early days for AI in most organizations with experimentation before production.
Company’s Level of AI Adoption
Source: Retool
13. Defined Capital | LP Update Q3 2023 | CONFIDENTIAL
The State of AI Adoption - Where are we today?
Data Is Key, But It’s Not Ready
• CDOs believe data is key to preparing for generative AI, but they haven’t done much with it yet.
• 93% agree that “data strategy is crucial to getting business value from generative AI.”
• However, 57% said that they had made no changes to data yet to prepare for generative AI.
• Only 38% agreed that “My team and I have the right data foundation to pivot to generative AI,” and only
11% agreed strongly with the statement.
• 71% agreed that “generative AI is interesting, but we are more focused on other data initiatives to
achieve more tangible value.” Tangible value is great, but perhaps this low priority is why many CDOs
haven’t been given responsibility for generative AI.
• At least they are planning to spend more on the technology: 62% said that their teams are planning on
investing more in generative AI.
13
Source: Menlo Ventures
14. Defined Capital | LP Update Q3 2023 | CONFIDENTIAL
Slow adoption at first and widespread adoption in second half of decade.
14
0%
10%
20%
30%
40%
50%
60%
70%
80%
F500 CEO Survey: % expectation of AI impact on headcount
Lower Labour Need Unchanged Labour Need
Lower Labour Need. Unchanged Labour Need.
Next Year Next 5 Years
Executive
Leadership
Senior
Management
Engineering
Sales
& Support
Growth
& Marketing
Operations
Finance
& Legal
Leadership
Product & Engineering
Sales, Support
& Marketing
Finance
& Legal
AI as a co-pilot or autopilot could transform how organizations scale for growth
→ Previously meant scaling headcount, with AI means scaling compute
Today Near Future
Product
The State of AI Adoption - Where are we going?
Source: Goldman Sachs, KPMG, Gartner, Coatue
16. Defined Capital | LP Update Q3 2023 | CONFIDENTIAL
Market Assessment
In long-term value will accrue in unexpected ways as realized during significant technological shifts historically.
In medium-term, rapid adoption of AI is a baseline, not differentiator for healthy growth, and it’s easy to forget that network effects (human, data,
brand, trust, distribution, etc.) and effective GTM serve as key differentiators between lasting winners and losers.
→ Likely majority of value created in 2-3 years after a platform disruption – Uber, Airbnb, and Instagram all created <3 years of the iPhone launch
AI advances (i.e. OpenAI Dev Day and Github Universe) are causing weekly disruption across the entire knowledge stack, from content creation
and code generation to intelligent decision-making systems, unlocking massive opportunities for growth and innovation on a scale that surpasses
previous AI milestones.
→ The result: reduced barriers to entry across the board for businesses and uncertainty on where value will truly accrue long term
Form factor is evolving. GenAI apps are now going beyond "first draft + human review" to increased autonomy to solve end to end (0 to level 5
autonomy). Midjourney’s introduction of camera panning and infilling is a nice illustration of how the generative AI-first user experience is evolving
with a new set of knobs and switches that are very different from traditional editing workflows – advancing from zero-shot to ask-and-adjust.
→ Form factors are evolving from individual to system-level productivity and from human-in-the-loop to execution-oriented agentic systems.
There is still an expectation vs. reality gap. Generative AI’s biggest problem is not finding use cases or demand or distribution, it is proving value.
User engagement is lackluster. Some of the best consumer companies have 60-65% DAU/MAU; WhatsApp’s is 85%. By contrast, generative AI apps
have a median of 14%. This means that users are not finding enough value in Generative AI products to use them every day yet.
→ To build enduring business, need to fix retention and generate deep enough value for customers that they stick and become daily active users
Despite challenges GenAI has already had a more successful start than SaaS, with >$1 billion in revenue from startups alone (it took the SaaS
market years, not months, to reach the same scale). Hype and flash are giving way to real value and whole product experiences. A shared playbook is
developing as companies figure out the path to enduring value. We now have shared techniques to make models useful, as well as emerging UI
paradigms that will shape generative AI’s second act.
Business models for AI are emerging to sell work, not software. We are seeing startups differentiating their business model compared to incumbents
by instead of selling software on a per seat basis to selling units of work our outcomes based on a user consumption basis. Selling work opens new
vertical opportunities that wouldn’t have otherwise supported a software company.
16
17. Defined Capital | LP Update Q3 2023 | CONFIDENTIAL
Is the GenAI bubble about to burst?
• In GenAI, we are experiencing Amara’s Law -- the phenomenon that we tend to overestimate the effect of a technology in the
short run and underestimate the effect in the long run or as futurist Paul Saffo says:
• “Never mistake a clear view for a short distance”
• While the technology holds profound promise, we see early signs that GenAI may get a “cold shower” in 2024 as the costs,
risks and complexity associated with the technology reach a tipping point.
• The hype of 2023 has ignored several obstacles that will slow progress in the short term. The cost of deployment is a
prohibitive factor for many organizations and developers. Additionally, future regulation and the social and commercial risks
of deploying generative AI in certain scenarios result in a period of evaluation prior to roll-out.
• We are therefore applying patience and judgment in our investment decisions, with careful attention to how founders are
solving the value problem.
• This prediction hold even more weight in light of several other recent developments:
• AI relies on chips to run, and there are serious concerns about a growing global chip shortage.
• The computing power necessary to keep large language models running is tremendous — not to mention the
environmental impact.
• AI startups seem to be facing increasing pressures too, with AI speech recognition startup Deepgram recently cutting
staff and AI marketing startup Jasper slashing revenue projections.
• Generative AI deals are also down per Pitchbook, with both deals and deal value slowing in the third quarter of 2023.
17
18. Defined Capital | LP Update Q3 2023 | CONFIDENTIAL
2024 Predictions
The next big phase of AI will be multi-agent models. Soon, we’ll enter a world where you might just be interacting with one model on the surface, yet that model can
search for and leverage many unique models “under the hood”.
→ Will see emergence of Large Behavior, Action, Vision Models (LBMs, LAMs and LVMs) and potentially other modalities.
Despite GenAI having a cold shower in 2024, almost all enterprise software companies will embed generative AI in at least some of their products in 2024.
Powerful pre-trained open-source models will dominate in the enterprise, with only a few (or maybe one) giant foundation model companies serving consumers
→ Models will go to the data lakes, not the other way around
EU AI Act is delayed and redrawn multiple times owing to the speed of AI advancement which makes the construction of a robust and workable regulatory
framework extremely difficult. There are differences of opinion between the US, EU and market participants, with Europe taking a far more structured and robust
approach to regulation. Legislation is not finalized until late 2024, leaving the industry to take the initial steps at self-regulation.
AI oversight committees become commonplace in large organizations by 2024. Companies establish diverse oversight committees composed of AI ethics experts,
legal advisors, data scientists and representatives to review applications of AI in the business, set guidelines, conduct audits and address ethical and legal concerns.
SLMs (Small Language Models) are likely to become a force to be reckoned with as LLMs keep pushing the scaling laws and become bigger and bigger, whereas the
SLM thesis centers around the viability of smaller, highly specialized, more affordable models for specific use cases (movement has partly been catalyzed by the rise
of open-source GenAI models)
18