What you'll get from this deck
1. The M&A race for AI: by the numbers
2. Watch out! hype ahead: definitions & disclaimers
3. Machine Learning drivers: why is Machine Learning a ‘thing’ now (vs before)
4. Venture Capital: forming an industry, the AI/ML landscape
5. The One Hundred (+13) AI startups to watch in the Enterprise
6. The great Enterprise pivot: applying Machine Learning at scale
7. - where to go next -
GENERATIVE AI, THE FUTURE OF PRODUCTIVITYAndre Muscat
Discuss the impact and opportunity of using Generative AI to support your development and creative teams
* Explore business challenges in content creation
* Cost-per-unit of different types of content
* Use AI to reduce cost-per-unit
* New partnerships being formed that will have a material impact on the way we search and engage with content
Part 4 of a 9 Part Research Series named "What matters in AI" published on www.andremuscat.com
Generative AI models, such as ChatGPT and Stable Diffusion, can create new and original content like text, images, video, audio, or other data from simple prompts, as well as handle complex dialogs and reason about problems with or without images. These models are disrupting traditional technologies, from search and content creation to automation and problem solving, and are fundamentally shaping the future user interface to computing devices. Generative AI can apply broadly across industries, providing significant enhancements for utility, productivity, and entertainment. As generative AI adoption grows at record-setting speeds and computing demands increase, on-device and hybrid processing are more important than ever. Just like traditional computing evolved from mainframes to today’s mix of cloud and edge devices, AI processing will be distributed between them for AI to scale and reach its full potential.
In this presentation you’ll learn about:
- Why on-device AI is key
- Full-stack AI optimizations to make on-device AI possible and efficient
- Advanced techniques like quantization, distillation, and speculative decoding
- How generative AI models can be run on device and examples of some running now
- Qualcomm Technologies’ role in scaling on-device generative AI
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.
A Framework for Navigating Generative Artificial Intelligence for EnterpriseRocketSource
Generative AI has dominated the headlines recently, which has caused many enterprises to put a full stop to implementing this technology until they can understand what’s behind the glitz and glamour. What if we shifted the conversation? What if the focus became a fresh, incremental approach to embracing the opportunities with generative artificial intelligence to keep organizations moving upward on the S Curve of Growth?
Brands stay relevant and solve complex problems by testing the barometer for one thing — will a new strategy, tool, or piece of technology improve humanity?
Human connections are more vital than using shiny new tools or technology. As your teams work to steer clear of the temptation to do what everyone else is doing in uniform, this post will highlight how to stand out, compete, and do so with less risk in today’s world of generative AI overload.
A journey into the business world of artificial intelligence. Explore at a high-level ongoing business experiments in creating new value.
* Review AI as a priority for value generation
* Explore ongoing experimentation
* Touch on how businesses are monetising AI
* Understand the intent of adoption by industries
* Discuss on the state of customer trust in AI
Part 1 of a 9 Part Research Series named "What matters in AI" published on https://www.andremuscat.com
How can we use generative AI in learning products? A rapid introduction to generative AI. Presented at ED Games Expo 2023 at the U.S. Department of Education, September 22, 2023.
Global Governance of Generative AI: The Right Way ForwardLilian Edwards
AI regulation has been a hot topic since the rise of machine learning (ML) in the “big data” era, but generative AI or “foundation models” tools like ChatGPT, DALL-E 2(now 3) and CoPilot, ike ML before them, may create serious societal risks, including embedding and outputting bias; generating fake news, illegal or harmful content and inadvertent “hallucinations”; infringing existing laws relating eg to copyright and privacy; as well as environmental, competition and workplace concerns.
Many nations are now considering regulation to address these worries, and can draw on a number of basic and hybrid models of governance. This paper canvasses models of mandatory comprehensive legislation (where the EU AI Act hopes to place itself as a gold standard model); vertical mandatory legislation (where China has quietly taken a lead); adapting existing law (see the many copyright lawsuits underway); and voluntary “soft law” such as codes of ethics, “blueprints”, or industry guidelines. Both the domestic and international regulatory scenes for AI are also increasingly politicised as the rise of "AI safety" hype shows. Against this backdrop what choices should smaller countries such as the UK and Australia make? will international harmonisation lead to a race to the top as with the GDPR, or the bottom - rule by tech for tech?
GENERATIVE AI, THE FUTURE OF PRODUCTIVITYAndre Muscat
Discuss the impact and opportunity of using Generative AI to support your development and creative teams
* Explore business challenges in content creation
* Cost-per-unit of different types of content
* Use AI to reduce cost-per-unit
* New partnerships being formed that will have a material impact on the way we search and engage with content
Part 4 of a 9 Part Research Series named "What matters in AI" published on www.andremuscat.com
Generative AI models, such as ChatGPT and Stable Diffusion, can create new and original content like text, images, video, audio, or other data from simple prompts, as well as handle complex dialogs and reason about problems with or without images. These models are disrupting traditional technologies, from search and content creation to automation and problem solving, and are fundamentally shaping the future user interface to computing devices. Generative AI can apply broadly across industries, providing significant enhancements for utility, productivity, and entertainment. As generative AI adoption grows at record-setting speeds and computing demands increase, on-device and hybrid processing are more important than ever. Just like traditional computing evolved from mainframes to today’s mix of cloud and edge devices, AI processing will be distributed between them for AI to scale and reach its full potential.
In this presentation you’ll learn about:
- Why on-device AI is key
- Full-stack AI optimizations to make on-device AI possible and efficient
- Advanced techniques like quantization, distillation, and speculative decoding
- How generative AI models can be run on device and examples of some running now
- Qualcomm Technologies’ role in scaling on-device generative AI
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.
A Framework for Navigating Generative Artificial Intelligence for EnterpriseRocketSource
Generative AI has dominated the headlines recently, which has caused many enterprises to put a full stop to implementing this technology until they can understand what’s behind the glitz and glamour. What if we shifted the conversation? What if the focus became a fresh, incremental approach to embracing the opportunities with generative artificial intelligence to keep organizations moving upward on the S Curve of Growth?
Brands stay relevant and solve complex problems by testing the barometer for one thing — will a new strategy, tool, or piece of technology improve humanity?
Human connections are more vital than using shiny new tools or technology. As your teams work to steer clear of the temptation to do what everyone else is doing in uniform, this post will highlight how to stand out, compete, and do so with less risk in today’s world of generative AI overload.
A journey into the business world of artificial intelligence. Explore at a high-level ongoing business experiments in creating new value.
* Review AI as a priority for value generation
* Explore ongoing experimentation
* Touch on how businesses are monetising AI
* Understand the intent of adoption by industries
* Discuss on the state of customer trust in AI
Part 1 of a 9 Part Research Series named "What matters in AI" published on https://www.andremuscat.com
How can we use generative AI in learning products? A rapid introduction to generative AI. Presented at ED Games Expo 2023 at the U.S. Department of Education, September 22, 2023.
Global Governance of Generative AI: The Right Way ForwardLilian Edwards
AI regulation has been a hot topic since the rise of machine learning (ML) in the “big data” era, but generative AI or “foundation models” tools like ChatGPT, DALL-E 2(now 3) and CoPilot, ike ML before them, may create serious societal risks, including embedding and outputting bias; generating fake news, illegal or harmful content and inadvertent “hallucinations”; infringing existing laws relating eg to copyright and privacy; as well as environmental, competition and workplace concerns.
Many nations are now considering regulation to address these worries, and can draw on a number of basic and hybrid models of governance. This paper canvasses models of mandatory comprehensive legislation (where the EU AI Act hopes to place itself as a gold standard model); vertical mandatory legislation (where China has quietly taken a lead); adapting existing law (see the many copyright lawsuits underway); and voluntary “soft law” such as codes of ethics, “blueprints”, or industry guidelines. Both the domestic and international regulatory scenes for AI are also increasingly politicised as the rise of "AI safety" hype shows. Against this backdrop what choices should smaller countries such as the UK and Australia make? will international harmonisation lead to a race to the top as with the GDPR, or the bottom - rule by tech for tech?
Leveraging Generative AI & Best practicesDianaGray10
In this event we will cover:
- What is Generative AI and how it is being for future of work.
- Best practices for developing and deploying generative AI based models in productions.
- Future of Generative AI, how generative AI is expected to evolve in the coming years.
As NFT projects continue to pop up and censorship woes become a reality, decentralized storage has become a beacon of hope for many. Let’s check out how much the decentralized storage sector has grown!
Let's talk about GPT: A crash course in Generative AI for researchersSteven Van Vaerenbergh
This talk delves into the extraordinary capabilities of the emerging technology of generative AI, outlining its recent history and emphasizing its growing influence on scientific endeavors. Through a series of practical examples tailored for researchers, we will explore the transformative influence of these powerful tools on scientific tasks such as writing, coding, data wrangling and literature review.
Today, I will be presenting on the topic of
"Generative AI, responsible innovation, and the law."
Artificial Intelligence has been making rapid strides in recent years,
and its applications are becoming increasingly diverse.
Generative AI, in particular, has emerged as a promising area of innovation, the potential to create highly realistic and compelling outputs.
Unlocking the Power of Generative AI An Executive's Guide.pdfPremNaraindas1
Generative AI is here, and it can revolutionize your business. With its powerful capabilities, this technology can help companies create more efficient processes, unlock new insights from data, and drive innovation. But how do you make the most of these opportunities?
This guide will provide you with the information and resources needed to understand the ins and outs of Generative AI, so you can make informed decisions and capitalize on the potential. It covers important topics such as strategies for leveraging large language models, optimizing MLOps processes, and best practices for building with Generative AI.
Presenting the landscape of AI/ML in 2023 by introducing a quick summary of the last 10 years of its progress, current situation, and looking at things happening behind the scene.
AI and Machine Learning Demystified by Carol Smith at Midwest UX 2017Carol Smith
What is machine learning? Is UX relevant in the age of artificial intelligence (AI)? How can I take advantage of cognitive computing? Get answers to these questions and learn about the implications for your work in this session. Carol will help you understand at a basic level how these systems are built and what is required to get insights from them. Carol will present examples of how machine learning is already being used and explore the ethical challenges inherent in creating AI. You will walk away with an awareness of the weaknesses of AI and the knowledge of how these systems work.
For this plenary talk at the Charlotte AI Institute for Smarter Learning, Dr. Cori Faklaris introduces her fellow college educators to the exciting world of generative AI tools. She gives a high-level overview of the generative AI landscape and how these tools use machine learning algorithms to generate creative content such as music, art, and text. She then shares some examples of generative AI tools and demonstrate how she has used some of these tools to enhance teaching and learning in the classroom and to boost her productivity in other areas of academic life.
Conversational AI and Chatbot IntegrationsCristina Vidu
Conversational AI and Chatbots (or rather - and more extensively - Virtual Agents) offer great benefits, especially in combination with technologies like RPA or IDP. Corneliu Niculite (Presales Director - EMEA @DRUID AI) and Roman Tobler (CEO @Routinuum & UiPath MVP) are discussing Conversational AI and why Virtual Agents play a significant role in modern ways of working. Moreover, Corneliu will be displaying how to build a Workflow and showcase an Accounts Payable Use Case, integrating DRUID and UiPath Robots.
📙 Agenda:
The focus of our meetup is around the following areas - with a lot of room to discuss and share experiences:
- What is "Conversational AI" and why do we need Chatbots (Virtual Agents);
- Deep-Dive to a DRUID-UiPath Integration via an Accounts Payable Use Case;
- Discussion, Q&A
Speakers:
👨🏻💻 Corneliu Niculite, Presales Director - EMEA DRUID AI
👨🏼💻 Roman Tobler, UiPath MVP, Co-Founder & CEO Routinuum GmbH
This session streamed live on March 8, 2023, 16:00 PM CET.
Check out our upcoming events at: community.uipath.com
Contact us at: community@uipath.com
The Future Of Work & The Work Of The FutureArturo Pelayo
What Happens When Robots And Machines Learn On Their Own?
This slide deck is an introduction to exponential technologies for an audience of designers and developers of workforce training materials.
The Blended Learning And Technologies Forum (BLAT Forum) is a quarterly event in Auckland, New Zealand that welcomes practitioners, designers and developers of blended learning instructional deliverables across different industries of the New Zealand economy.
In this session, you'll get all the answers about how ChatGPT and other GPT-X models can be applied to your current or future project. First, we'll put in order all the terms – OpenAI, GPT-3, ChatGPT, Codex, Dall-E, etc., and explain why Microsoft and Azure are often mentioned in this context. Then, we'll go through the main capabilities of the Azure OpenAI and respective usecases that might inspire you to either optimize your product or build a completely new one.
Explore how different industries are embracing the utility of AI to create and deliver new value for their customers and organisation
* Discuss the state of maturity of AI across industries
* Get an appreciation of business posture to AI projects
We also review the utility of AI across several industries including:
* Healthcare
* Newsroom & Journalism
* Travel
* Finance
* Supply Chain / eCommerce / Retail
* Streaming & Gaming
* Transportation
* Logistics
* Manufacturing
* Agriculture
* Defense & Cybersecurity
Part of the What Matters in AI series as published on www.andremuscat.com
Give a background of Data Science and Artificial Intelligence, to better understand the current state of the art (SOTA) for Large Language Models (LLMs) and Generative AI. Then start a discussion on the direction things are going in the future.
* "Responsible AI Leadership: A Global Summit on Generative AI"
*April 2023 guide for experts and policymakers
* Developing and governing generative AI systems
* + 100 thought leaders and practitioners participated
* Recommendations for responsible development, open innovation & social progress
* 30 action-oriented recommendations aim
* Navigate AI complexities
10 New Business Models for this Decade (beta)
1. Localized Low-Cost Business Model
2. One-Off Experience Business Model
3. Beyond Advertising Business Model
4. Markets Are Conversations Business Model
5. Low-Budget Innovation Business Model
6. Community-Funded Business Model
7. Sustainability-Focused Business Model
8. Twisted Freemium Business Model
9. Unlimited Niches Business Model
10. In-Crowd Customers Business Model
TREND RESEARCH BY Trend Firm trendwatching.com
MARKET ANALYSIS BY Strategy Boutique Thaesis
BUSINESS MODEL DESIGN BY Strategy Consultant/Graphic Facilitator Ouke Arts
Leveraging Generative AI & Best practicesDianaGray10
In this event we will cover:
- What is Generative AI and how it is being for future of work.
- Best practices for developing and deploying generative AI based models in productions.
- Future of Generative AI, how generative AI is expected to evolve in the coming years.
As NFT projects continue to pop up and censorship woes become a reality, decentralized storage has become a beacon of hope for many. Let’s check out how much the decentralized storage sector has grown!
Let's talk about GPT: A crash course in Generative AI for researchersSteven Van Vaerenbergh
This talk delves into the extraordinary capabilities of the emerging technology of generative AI, outlining its recent history and emphasizing its growing influence on scientific endeavors. Through a series of practical examples tailored for researchers, we will explore the transformative influence of these powerful tools on scientific tasks such as writing, coding, data wrangling and literature review.
Today, I will be presenting on the topic of
"Generative AI, responsible innovation, and the law."
Artificial Intelligence has been making rapid strides in recent years,
and its applications are becoming increasingly diverse.
Generative AI, in particular, has emerged as a promising area of innovation, the potential to create highly realistic and compelling outputs.
Unlocking the Power of Generative AI An Executive's Guide.pdfPremNaraindas1
Generative AI is here, and it can revolutionize your business. With its powerful capabilities, this technology can help companies create more efficient processes, unlock new insights from data, and drive innovation. But how do you make the most of these opportunities?
This guide will provide you with the information and resources needed to understand the ins and outs of Generative AI, so you can make informed decisions and capitalize on the potential. It covers important topics such as strategies for leveraging large language models, optimizing MLOps processes, and best practices for building with Generative AI.
Presenting the landscape of AI/ML in 2023 by introducing a quick summary of the last 10 years of its progress, current situation, and looking at things happening behind the scene.
AI and Machine Learning Demystified by Carol Smith at Midwest UX 2017Carol Smith
What is machine learning? Is UX relevant in the age of artificial intelligence (AI)? How can I take advantage of cognitive computing? Get answers to these questions and learn about the implications for your work in this session. Carol will help you understand at a basic level how these systems are built and what is required to get insights from them. Carol will present examples of how machine learning is already being used and explore the ethical challenges inherent in creating AI. You will walk away with an awareness of the weaknesses of AI and the knowledge of how these systems work.
For this plenary talk at the Charlotte AI Institute for Smarter Learning, Dr. Cori Faklaris introduces her fellow college educators to the exciting world of generative AI tools. She gives a high-level overview of the generative AI landscape and how these tools use machine learning algorithms to generate creative content such as music, art, and text. She then shares some examples of generative AI tools and demonstrate how she has used some of these tools to enhance teaching and learning in the classroom and to boost her productivity in other areas of academic life.
Conversational AI and Chatbot IntegrationsCristina Vidu
Conversational AI and Chatbots (or rather - and more extensively - Virtual Agents) offer great benefits, especially in combination with technologies like RPA or IDP. Corneliu Niculite (Presales Director - EMEA @DRUID AI) and Roman Tobler (CEO @Routinuum & UiPath MVP) are discussing Conversational AI and why Virtual Agents play a significant role in modern ways of working. Moreover, Corneliu will be displaying how to build a Workflow and showcase an Accounts Payable Use Case, integrating DRUID and UiPath Robots.
📙 Agenda:
The focus of our meetup is around the following areas - with a lot of room to discuss and share experiences:
- What is "Conversational AI" and why do we need Chatbots (Virtual Agents);
- Deep-Dive to a DRUID-UiPath Integration via an Accounts Payable Use Case;
- Discussion, Q&A
Speakers:
👨🏻💻 Corneliu Niculite, Presales Director - EMEA DRUID AI
👨🏼💻 Roman Tobler, UiPath MVP, Co-Founder & CEO Routinuum GmbH
This session streamed live on March 8, 2023, 16:00 PM CET.
Check out our upcoming events at: community.uipath.com
Contact us at: community@uipath.com
The Future Of Work & The Work Of The FutureArturo Pelayo
What Happens When Robots And Machines Learn On Their Own?
This slide deck is an introduction to exponential technologies for an audience of designers and developers of workforce training materials.
The Blended Learning And Technologies Forum (BLAT Forum) is a quarterly event in Auckland, New Zealand that welcomes practitioners, designers and developers of blended learning instructional deliverables across different industries of the New Zealand economy.
In this session, you'll get all the answers about how ChatGPT and other GPT-X models can be applied to your current or future project. First, we'll put in order all the terms – OpenAI, GPT-3, ChatGPT, Codex, Dall-E, etc., and explain why Microsoft and Azure are often mentioned in this context. Then, we'll go through the main capabilities of the Azure OpenAI and respective usecases that might inspire you to either optimize your product or build a completely new one.
Explore how different industries are embracing the utility of AI to create and deliver new value for their customers and organisation
* Discuss the state of maturity of AI across industries
* Get an appreciation of business posture to AI projects
We also review the utility of AI across several industries including:
* Healthcare
* Newsroom & Journalism
* Travel
* Finance
* Supply Chain / eCommerce / Retail
* Streaming & Gaming
* Transportation
* Logistics
* Manufacturing
* Agriculture
* Defense & Cybersecurity
Part of the What Matters in AI series as published on www.andremuscat.com
Give a background of Data Science and Artificial Intelligence, to better understand the current state of the art (SOTA) for Large Language Models (LLMs) and Generative AI. Then start a discussion on the direction things are going in the future.
* "Responsible AI Leadership: A Global Summit on Generative AI"
*April 2023 guide for experts and policymakers
* Developing and governing generative AI systems
* + 100 thought leaders and practitioners participated
* Recommendations for responsible development, open innovation & social progress
* 30 action-oriented recommendations aim
* Navigate AI complexities
10 New Business Models for this Decade (beta)
1. Localized Low-Cost Business Model
2. One-Off Experience Business Model
3. Beyond Advertising Business Model
4. Markets Are Conversations Business Model
5. Low-Budget Innovation Business Model
6. Community-Funded Business Model
7. Sustainability-Focused Business Model
8. Twisted Freemium Business Model
9. Unlimited Niches Business Model
10. In-Crowd Customers Business Model
TREND RESEARCH BY Trend Firm trendwatching.com
MARKET ANALYSIS BY Strategy Boutique Thaesis
BUSINESS MODEL DESIGN BY Strategy Consultant/Graphic Facilitator Ouke Arts
The Wealthfront Equity Plan (Stanford GSB, March 2016)Adam Nash
This is a version of the presentation explaining the Wealthfront Equity Plan, a playbook for CEOs & Founders of hyper growth startups on the right way to distribute equity compensation to employees. Based on the original deck by Andy Rachleff, co-founder of Wealthfront.
Building an enduring, multi-billion dollar consumer technology company is hard. As an investor, knowing which startups have the potential to be massive and long-lasting is also hard. From both perspectives, identifying companies with this potential is a combination of “art” and “science” — the art is understanding how products work, and the science is knowing how to measure it. At the earliest stages of a company, it comes down to understanding how a product is built to maximize and leverage user engagement.
In this presentation, Sarah Tavel shares her "Hierarchy of Engagement" framework she uses to evaluate non-transactional consumer companies she is looking to invest in.
Find here India's most popular designer fancy kurti available in market. Get contact details of fancy kurti manufacturers, suppliers, dealers and trader in India.
Network effects. It’s one of the most important concepts for business in general and especially for tech businesses, as it’s the key dynamic behind many successful software-based companies. Understanding network effects not only helps build better products, but it helps build moats and protect software companies against competitors’ eating away at their margins.
Yet what IS a network effect? How do we untangle the nuances of 'network effects' with 'marketplaces' and 'platforms'? What’s the difference between network effects, virality, supply-side economies of scale? And how do we know a company has network effects?
Most importantly, what questions can entrepreneurs and product managers ask to counter the wishful thinking and sometimes faulty assumption behind the belief that “if we build it, they will come” … and instead go about more deterministically creating network effects in their business? Because it's not a winner-take-all market by accident.
Habits at Work - Merci Victoria Grace, Growth, Slack - 2016 Habit SummitHabit Summit
Presented at the 2016 Habit Summit at Stanford (see: www.HabitSummit.com)
Merci Victoria Grace leads the Growth team at Slack.
Prior to joining Slack, she started a venture-backed game company, designed The Sims Social at Electronic Arts, and worked at a range of consumer, mobile and enterprise startups.
Here she shares insights on putting "Habits to Work at Work".
10 Best Practices of a Best Company to Work ForO.C. Tanner
What does it take to be named a Best Company to Work for by FORTUNE magazine? For starters, a winning culture, collaboration, and creating an environment for learning and growth. Take a look at these slides for more ideas!
So you've built a great product. Everyone is happy, the team is stoked and the only thing left to do is regularly check the bank account to see if it's growing steadily...right?
Of course the reality couldn't be more different if it wanted to. Getting a person to use your product or service is often one of the most difficult challenges any business will face. Especially when those people will need to pay for that product or service.
When you've built a reputation and boast a solid user base things are much smoother, but those first customers...
This SlideShare does not promise success, but hopefully it'll inspire you to close those first deals. Good luck!
www.floown.com
14 Tips to Entrepreneurs to start the Right StuffPatrick Stähler
14 tips for Entrepreneurs how they can develop from an idea the Right Thing. The Right is being loved by your customers, gives meaning to you and employees and is profitable. Finding and later doing the Right Thing is an agile and iterative learning journey. With these 14 tips you can profit from the experience of successful entrepreneurs since you do not have to experience and fail by yourself. Hopefully, the slide deck helps other entrepreneurs.
2017 holiday survey: An annual analysis of the peak shopping seasonDeloitte United States
Holiday retail spending is bucking trends this season with only one-third of holiday budgets going toward gifts. Online spending is expected to exceed in-store for the first time. In addition to gifts for others this year, spending on experiences and self-gifting increased. Explore more consumer spending trends in our 32nd annual holiday survey. For more: http://deloi.tt/2yH1VAn.
Lee Rainie, director of internet and technology research at Pew Research Center, presented these findings at the International Monetary Fund/World Bank’s Youth Dialogue and its program, “A World Without Work?” The findings tie to several pieces of research at the Center, including reports on the state of American jobs, automation in everyday life, and the future of jobs training programs.
This PPT is about AI 100 Startups all over the world based on "The AI 100 -CB insights".
In this research paper, you can find each capital, scale, general info(ref: CB Insights), and features.
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 can AI & Automation make your business processes intelligentMindfields Global
Enterprises gain a deeper understanding of their processes as they progress further into their automation journey. Exploring the connection between AI, automation and understanding how these technologies help make your business processes intelligent is a necessary next step.
AI & India : The potential to be the next global centre of innovationUmakant Soni
The combination of a large and rapidly growing mobile-internet connected population along with startups being able to access their data along with open-source intelligence research means they can leverage decades of research, apply it to data, and pipe the results to build context-aware, predictive and extremely personalised business models.
This can be built on intelligent process automation and forecasting frameworks for speed and precision. Overall, these businesses will have potential for step-changes in operational efficiency and effectiveness in understanding and fulfilling customer needs.
This is especially so in India, where small screens on many smartphones can create vast pools of data to power AI. By further automating business decisions through machine learning, and surfacing them through smart, intelligent interfaces, these startups will disrupt older technologies and traditional businesses – based on heuristical approaches – and can emerge as “new category leaders”.
Flint Capital and international venture capital investor provides an investor's perspective on a state of Ai (artificial intelligence) in 2018 and the impact of various factors like algorithms development, hardware development, datasets development, opensource software development, investments and overall interest to a topic on a growth the category. Deep deal analysis and Ai market data and artificial intelligence market growth as is at the end of 2017, including Gartner, Forester, CBInsights, Pitchbook data sources as long as Flint Capital own analytics. Ai investment framework is given as an example of a potential investors approach to analyze startups and business cases. Plus World top 5 most active vc investors in Ai.
5 ways to enhance your business using ai venkat k - mediumusmsystem
Artificial intelligence (AI) is fast becoming a competitive tool in business. Companies have been discussing the pros and cons of AI in the past. From enhanced chatbots to customer service to data analytics to recommendations, deep learning and artificial intelligence are seen as an important tool for business leaders in their many forms.
Unlock the future of AI/ML services with our insights into the 9 key trends shaping 2024. From advanced neural networks to ethical AI practices, stay ahead with cutting-edge innovations. Discover how Mooglelabs is revolutionizing AI/ML services to drive efficiency, enhance customer experiences, and propel businesses into the future.
7 Rules for Surviving the AI Hype MachineAllen Bonde
AI is super-exciting. Especially the field of machine learning (and sub-field of "deep learning" - an area I've studied for over 25 years). AI and ML offer to revolutionize the way we monitor, and model, and generate answers from all the big and small data that is swirling around of us. But it’s not going to happen overnight. Especially since many organizations still struggle with the best ways to select, apply and monetize AI for practical, everyday use. This presentation aims to cut through the hype and lays out 7 rules for AI project sponsors, managers and practitioners alike - each supported by examples and resources to learn more, as well as key influencers and vendors worth checking out.
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.
Artificial Intelligence is trendy. Every event, every strategy meeting and every consulting firm talks about it. This whitepaper aims to separate actual facts and important background information from the overarching marketing buzz.
You will get a short but information-rich wrap up about: What causes the current hype? Where are we today? What are the innovation leaders doing with AI? And what are immediate action points to focus on by applying artificial intelligence to your business?
“IT Technology Trends in 2017… and Beyond”diannepatricia
William Chamberlin, IBM Distinguished Market Intelligence Professional, presented “IT Technology Trends in 2017… and Beyond” as part of the Cognitive Systems Institute Speaker Series on January 26, 2017.
Purpose: The slides provide an overview on the Cognitive Computing trend for IBM clients and external stakeholders
Content: Summary information about the Cognitive Computing trend is provided along with many links to additional resources.
How To Use This Report: This report is best read/studied and used as a learning document. You may want to view the slides in slideshow mode so you can easily follow the links
Available on Slideshare: This presentation (and other HorizonWatch Trend Reports for 2015) will be available publically on Slideshare at http://www.slideshare.net/horizonwatching
Please Note: This report is based on internal IBM analysis and is not meant to be a statement of direction by IBM nor is IBM committing to any particular technology or solution.
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Solve for X with AI: a VC view of the Machine Learning & AI landscape
1. Solve
for X
with AI:
a VC view of the machine learning
& AI landscape Ed Fernandez @efernandez
2. Mentor, Advisor at Singularity
University & Berkeley’s Center for
Entrepreneurship & Technology
Early Stage & Start-Up VC at Naiss.io
- VC boutique/Palo Alto
Investor/board director @ BigML inc
(MLaaS: Machine Learning as a
Service)
Former corporate EVP at BlackBerry &
Nokia
@efernandez
ed@naiss.io
+15614104388
3. What you’ll get from this deck
1. The M&A race for AI: by the numbers
2. Watch out! hype ahead
3. Machine Learning drivers: why is Machine Learning a ‘thing’ now (vs before)
4. Venture Capital: forming an industry, the AI/ML landscape
5. The One Hundred (+13) AI startups to watch in the Enterprise
6. The great Enterprise pivot: applying Machine Learning at scale
7. - where to go next -
4. Definitions & Disclaimer
Machine Learning is NOT Deep Learning NOR AI or AGI
ML is here
AI:
much of the
data in
these slides
Deep
Learning
5. By number of deals, quarterly
www.cbinsights.comhttps://www.cbinsights.com/blog/top-acquirers-ai-startups-ma-timeline/
Google is the most active acquirer of AI startups, having acquired 11
startups since 2012. Apple, which has been ramping up its M&A efforts,
ranked second with 7 acquisitions under its belt. Newer entrants in the
race include Ford, which acquired Argo AI for $1B in Q1’17, cybersecurity
company Sophos, and Amazon.
200+
Acquisitions
since 2012
30+
M&A deals in
Q1’17
11
Acquisitions by
Google
The M&A race for AI
6. latest update
The M&A race for AI
September 8th Update - CBinsights :
There were 85 disclosed M&A deals targeting AI startups in
2017 year-to-date.
This is more than the 75 we saw in 2016.
Includes Facebook’s acquisition of Ozlo and
Nasdaq acquisition of eVestment ($705M).
John Deere acquired agricultural tech company Blue River
Technology for $305M.
7. Entering the second wave of acquisitions
www.cbinsights.com 11https://www.cbinsights.com/blog/top-acquirers-ai-startups-ma-timeline/
Google is the most active acquirer of AI startups, having acquired 11
startups since 2012. Apple, which has been ramping up its M&A efforts,
ranked second with 7 acquisitions under its belt. Newer entrants in the
race include Ford, which acquired Argo AI for $1B in Q1’17, cybersecurity
company Sophos, and Amazon.
200+
Acquisitions
since 2012
30+
M&A deals in
Q1’17
11
Acquisitions by
Google
The M&A race for AI
1st Wave - Tech giants:
Google, Facebook, Twitter,
Apple, Intel, Microsoft, IBM,
Yahoo, eBay
Entering into the 2nd wave -
now:
John Deere, General Electric,
Ford, Samsung, Uber, Oracle,
Sophos, Meltwater
10. Content
1. The M&A race for AI: by the numbers
2. Watch out! hype ahead
3. Machine Learning drivers: why is ML changing everything
4. Venture Capital: and the AI/ML landscape
5. The One Hundred (& Thirteen) AI startups to watch in the Enterprise
6. The great Enterprise pivot: applying Machine Learning at scale
7. - where to go next -
11. Machine Learning why now
The perfect storm
Value
Creation
01
02
Data
Algorithms
03
04
Hardware
Talent
(humans)
and tools
(for humans)
12.
13. Machine Learning drivers:
Data: massive datasets, ‘dark’ data, crowd source and open source data
01
02
Data
Algorithms
03
04
Data growth:
From 8,5 EXAbytes in
2015 to 40K EXAbytes in
2020 = 40 trillion GB
15K EXAbytes in the cloud
by 2020 = 37%
Kryders law: storage
density doubles every 18
months (driven by cloud)
5G access accelerates
mobile data & video
Unlocking ‘dark’ data &
data silos in corporations
14. Machine Learning drivers
Algorithms
01
02
Data
Algorithms
Widespread adoption of machine
learning algorithms
• ML as a Service
• APIs
• Tools and open source libraries &
ML frameworks
Faster hardware acceleration
Better input & more data
Neuroscience driving new
algorithms
15. Content
1. The M&A race for AI: by the numbers
2. Watch out! hype ahead: definitions & disclaimers
3. Machine Learning drivers: why is this ML revolution happening
4. Venture Capital: and the AI/ML landscape
5. The One Hundred (& Thirteen) AI startups to watch in the Enterprise
6. The great Enterprise pivot: applying Machine Learning at scale
7. - where to go next -
16. 46% of AI acquired
companies are VC backed
Total # of funding rounds/
deals grew 4,6x from 150 in
2012 to 698 in 2016
245 funding deals in Q1
2017 for a total of $1,73 Bn
Nearly 48% in seed/angel
stage (new startups)
Financing rounds
Venture Capital - Machine Learning/AI
Q1’17 MOST ACTIVE
QUARTER FOR AI
STARTUPS
Before the close of Q1’17
(as of 3/23/17) AI
startups received 245
deals and $1.7B in
funding. Nearly 48% of
the deals in Q1’17 were in
the seed/angel stage,
indicating newer
companies are
continuing to enter the
space.
www.cbinsights.com 28
ARTIFICIAL INTELLIGENCE: QUARTERLY FUNDING
Q1’12-Q1’17 (as of 3/23/2017)
17. ML is driving efficiencies,
productivity and ROI for the
enterprise
Savings, labor cost &
automation improvement
Financing rounds: deal distribution by category, heat map
Venture Capital - Machine Learning/AI
Fintech & Insurance
Healthcare
Horizontal platforms/apps
Commerce/ad
BI/analytics
IoT
18. Content
1. The M&A race for AI: by the numbers
2. Watch out! hype ahead: definitions & disclaimers
3. Machine Learning drivers: why is this ML revolution happening
4. Venture Capital: and the AI/ML landscape
5. The One Hundred (+13) AI startups to watch in the Enterprise
6. The great Enterprise pivot: applying Machine Learning at scale
7. - where to go next -
19. Big players AMZ, Google, MS, IBM
trying to drive cloud and
infrastructure by offering ML in the
cloud as part of wider portfolio.
Lack of focus and customer
orientation, ‘small’ market <$1Bn
Wrong business models, charging
by prediction, black box models,
can’t be exported.
Greenfield for Startups
Enterprise AI start-ups to watch
Business
Intelligence
Customer
Management
Finance &
Operations
Industrials &
Manufacturing
Consumer
Marketing
Digital
Commerce
B2B Sales
& Marketing
Productivity
Engineering
Security & Risk
Data Science
Enterprise
AI Companies
Presented by
HR & Talent
BigML
DataRobot
H2O
Dataiku
Google ML API
Amazon ML
Microsoft Azure ML
IBM MLaaS
vs
Cloud Wars - MLaaS: Machine Learning as a Service
http://www.topbots.com/essential-landscape-overview-enterprise-artificial-intelligence/
21. The Great Pivot - ML platform revolution
Systems of Intelligence/ML drive efficiencies (1st), competitive advantages (2nd) & next
defensible business models ultimately
• Most large technology companies are
reconfiguring themselves around ML.
• Google was (arguably) the first company to
move, followed by Microsoft, Facebook,
Amazon, Apple and IBM.
• 2nd tier corporations following suit: GE,
Uber, even carriers as AT&T
• Not only a US phenomena - Alibaba, Baidu
chief Robin Li said in an internal memo that
Baidu’s strategic future relies on AI
• Ultimately all global players will need to re-
tool their processes adopting a ML driven
approach.
h/t Jerry Chen - Greylock Partners
https://news.greylock.com/the-new-moats-53f61aeac2d9
23. Fast-Forward to 2017: MWC - 4YFN
MWC - 4YFN: Mobile World Congress - 4 Years From Now
24. Content
1. The M&A race for AI: by the numbers
2. Watch out! hype ahead: definitions & disclaimers
3. Machine Learning drivers: why is this ML revolution happening
4. Venture Capital: and the AI/ML landscape
5. The One Hundred (+13) AI startups to watch in the Enterprise
6. The Great Enterprise pivot: applying Machine Learning at scale
7. - where to go next -
26. Amazon
Jeff Bezos’ letter to Amazon shareholders - May, 2017
“Machine learning and AI is a horizontal
enabling layer. It will empower and improve
every business, every government
organization, every philanthropy —
basically there’s no institution in the world
that cannot be improved with machine
learning” .
Jeff Bezos
27. Google
FBlearner Flow: Facebook’s ML platform for internal use - March, 2017
Google MLaaS was released in
Beta to developers in 2016
Internal use since 2015
28. Facebook
FBlearner Flow: Facebook’s ML platform for internal use - May, 2016
Facebook ML platform is
used by more than 25% of its
engineering team
+1Mn ML models trained
+6 Mn predictions/sec
29. The Great Pivot - ML platform revolution
Systems of Intelligence/ML drive efficiencies (1st), competitive advantages (2nd) & next
defensible business models ultimately
h/t Jerry Chen - Greylock Partners
https://news.greylock.com/the-new-moats-53f61aeac2d9
30. Content
1. The M&A race for AI: by the numbers
2. Watch out! hype ahead: definitions & disclaimers
3. Machine Learning drivers: why is this ML revolution happening
4. Venture Capital: and the AI/ML landscape
5. The One Hundred (+13) AI startups to watch in the Enterprise
6. The Great Enterprise pivot: applying Machine Learning at scale
7. - where to go next -
31. Where to go next
http://www.pcmag.com/article/353293/7-tips-for-machine-learning-success
A few tips for machine learning success
• Focus on Features (vs Algorithms)
• Same with Data (vs Algorithms): right data, clean data
• Faster trial & error, rapid prototyping (vs Algorithms)
• Use tools & ML platforms, cloud is friendly (Algorithms
aren’t)
• See next 5 min - DIY machine learning sales hack (and
forget Algorithms)
32. √
Sales Hacking with Machine Learning
DIY practical example:
WHAT
A practical sales hack using machine learning to
identify & engage in real time your competitor’s
unhappy users
HOW
• Twitter
• Monkeylearn
• Slack
• Zapier
REQUIREMENTS
• a laptop with WiFi connectivity
• 10 min of undivided attention time
• Twitter, Monkeylearn, Slack & Zapier free accounts
• Cup of coffee (to look cool while setting it up)
Monitor mentions on
competitors in social media
Trigger: automatically analyze
and classify mentions using
machine learning and detect
users complaining
Alert & Action: notify sales
team for real time action &
engagement
Automate process, set up
rules, integrate services
33. Steps:
1. Create a Zap.
2. Select Twitter as Trigger App.
3. Select Search Mention as Trigger.
4. Input your competitor search query: trigger
whenever someone mentions competitor.
Type in:
“[NameOfCompetitor] bad service filter:retweets”
Filtering out tweets not referring to ‘bad service’
and retweets.
Min 1: Monitor & Trigger
34. 4. Select MonkeyLearn as Action App.
5. Select Classify Text as Action.
6. Select a Sentiment Analysis Model. Classify your competitors mentions: Negative, Neutral
or Positive tweets. You can use a pre-trained model or eventually train your own custom
model.
7. Select text to classify (Tweet text)
Min 3: Apply Machine Learning
35. Min 5: Filter & Trigger Alert & Action
8. Select Filter Action App.
9. Filter out Positive and Neutral tweets, only continue with negative
10. Select Slack Action App. A slack notification will arrive at the selected channel.
36. √
What the *heck* just happened
Technical Debt - Legacy vs lean/API and cloud
Corporate Startup
IT
infrastructure
HW/SW
provisioning
$0 - cloud
Integration 1 month, internal
budget or 3rd
party
Zapier pro plan
- $30/month
Personnel Data Scientist -
IT experts
Part time Uber
driver &
developer
Testing &
deployment
1-3 months same day
CAC inbound sales/
CRM
Chatbot
Monitor mentions on
competitors in social media
Trigger: automatically analyze
and classify mentions using
machine learning and detect
users complaining
Alert & Action: notify sales
team for real time action &
engagement
Automate process, set up
rules, integrate services