Artificial intelligence and machine learning are becoming increasingly important in app development. Danny Lange discussed how AI is changing programming by moving from programming explicit rules to training algorithms on large datasets. Machine learning algorithms can now be applied throughout organizations to optimize processes using automated prediction and decision making. Unity's tools are helping developers apply machine learning techniques like reinforcement learning to virtual environments to solve real-world problems.
The document discusses trends in venture capital and emerging technologies. It notes that:
1) Venture capital has shifted towards earlier stage "seed" investing as technology has lowered the cost of starting a company.
2) While many unicorns (private companies valued over $1B) have emerged, the expected IPO boom has not occurred, as many companies stay private longer.
3) Emerging technologies like blockchain, AI, and IoT have potential for massive disruption, but many such as VR remain over-hyped and 5 years from widespread impact. The future remains uncertain.
The document discusses frameworks for early stage company growth, covering topics such as crossing the chasm model, hype curve, and the 8 fundamental parts of company building: idea, team, customer development, market development, business plan, operations, product, and fundraising. It provides guidance on validating ideas, building a strong team, gathering customer feedback, developing markets, creating business plans, running operations, and targeting the right investors at different stages. The overall message is that all parts are important for startup success, and companies should learn and iterate constantly.
The document discusses what investors look for when deciding whether to invest in startups. It explains that there are different types of investors, including VC/private funds, angels, strategic investors, public markets, incubators, and crowdfunding. All investors want to see a large market opportunity, a great management team, and a compelling product or service. However, each investor type has different motivations. VC/private funds seek huge returns from just a few companies and aim for 10x returns. Angels want involvement but can be unpredictable. Strategic investors may have conflicts of interest. Public markets and incubators have clear rules that startups must follow. Crowdfunding relies on creating hype and attracting followers. The document
This document provides guidance on validating business assumptions and ideas with customers. It emphasizes that the most important thing is creating value for customers and making something people want to buy. To do this, one must test assumptions, be prepared to be wrong, and consider the customer's perspective through methods like ethnography, interviews, and surveys. Ethnography involves observing customers in natural settings without interfering to interpret their behaviors and needs. Interviews require listening more than talking and asking open questions. Validating assumptions with customers is key to avoiding expensive failures and better understanding what problems customers need solved.
This presentation discusses getting a product to product-market fit. It emphasizes starting with the customer by observing their needs through jobs, pains, and gains. The presenter recommends designing solutions that address only the most essential customer needs to constrain solutions and increase scalability. Unique value propositions should be defined by how customers view solutions versus competitors. Validating ideas with customers through experiments and metrics is important before significant investment. The presentation outlines next steps of achieving problem-solution fit, then product-market fit, and ultimately business model fit through a scalable financial model.
This document discusses how to create a tipping point through social media. It explains that a tipping point is when small changes lead to significant larger changes. It then outlines six principles of influence from the book Influence by Robert Cialdini: authority, social proof, liking, reciprocity, commitment and consistency, and scarcity. The document provides tips on how to leverage these principles on social media, such as showing your authority, using social proof like endorsements, being relatable, and creating scarcity through limited offers. It also introduces Dave McClure's AARRR framework and provides a growth hacking toolkit and testing strategies to acquire customers through social media.
This document discusses the importance of understanding customers in building a startup. It recommends creating a customer persona to represent who your target customers are. The document then discusses how to validate hypotheses about customers by directly talking to them, asking open-ended questions about their problems and needs rather than closed-ended questions. The goal of validation is to better understand the customer's perspective and needs to build the right solution for them.
Artificial intelligence and machine learning are becoming increasingly important in app development. Danny Lange discussed how AI is changing programming by moving from programming explicit rules to training algorithms on large datasets. Machine learning algorithms can now be applied throughout organizations to optimize processes using automated prediction and decision making. Unity's tools are helping developers apply machine learning techniques like reinforcement learning to virtual environments to solve real-world problems.
The document discusses trends in venture capital and emerging technologies. It notes that:
1) Venture capital has shifted towards earlier stage "seed" investing as technology has lowered the cost of starting a company.
2) While many unicorns (private companies valued over $1B) have emerged, the expected IPO boom has not occurred, as many companies stay private longer.
3) Emerging technologies like blockchain, AI, and IoT have potential for massive disruption, but many such as VR remain over-hyped and 5 years from widespread impact. The future remains uncertain.
The document discusses frameworks for early stage company growth, covering topics such as crossing the chasm model, hype curve, and the 8 fundamental parts of company building: idea, team, customer development, market development, business plan, operations, product, and fundraising. It provides guidance on validating ideas, building a strong team, gathering customer feedback, developing markets, creating business plans, running operations, and targeting the right investors at different stages. The overall message is that all parts are important for startup success, and companies should learn and iterate constantly.
The document discusses what investors look for when deciding whether to invest in startups. It explains that there are different types of investors, including VC/private funds, angels, strategic investors, public markets, incubators, and crowdfunding. All investors want to see a large market opportunity, a great management team, and a compelling product or service. However, each investor type has different motivations. VC/private funds seek huge returns from just a few companies and aim for 10x returns. Angels want involvement but can be unpredictable. Strategic investors may have conflicts of interest. Public markets and incubators have clear rules that startups must follow. Crowdfunding relies on creating hype and attracting followers. The document
This document provides guidance on validating business assumptions and ideas with customers. It emphasizes that the most important thing is creating value for customers and making something people want to buy. To do this, one must test assumptions, be prepared to be wrong, and consider the customer's perspective through methods like ethnography, interviews, and surveys. Ethnography involves observing customers in natural settings without interfering to interpret their behaviors and needs. Interviews require listening more than talking and asking open questions. Validating assumptions with customers is key to avoiding expensive failures and better understanding what problems customers need solved.
This presentation discusses getting a product to product-market fit. It emphasizes starting with the customer by observing their needs through jobs, pains, and gains. The presenter recommends designing solutions that address only the most essential customer needs to constrain solutions and increase scalability. Unique value propositions should be defined by how customers view solutions versus competitors. Validating ideas with customers through experiments and metrics is important before significant investment. The presentation outlines next steps of achieving problem-solution fit, then product-market fit, and ultimately business model fit through a scalable financial model.
This document discusses how to create a tipping point through social media. It explains that a tipping point is when small changes lead to significant larger changes. It then outlines six principles of influence from the book Influence by Robert Cialdini: authority, social proof, liking, reciprocity, commitment and consistency, and scarcity. The document provides tips on how to leverage these principles on social media, such as showing your authority, using social proof like endorsements, being relatable, and creating scarcity through limited offers. It also introduces Dave McClure's AARRR framework and provides a growth hacking toolkit and testing strategies to acquire customers through social media.
This document discusses the importance of understanding customers in building a startup. It recommends creating a customer persona to represent who your target customers are. The document then discusses how to validate hypotheses about customers by directly talking to them, asking open-ended questions about their problems and needs rather than closed-ended questions. The goal of validation is to better understand the customer's perspective and needs to build the right solution for them.
The document discusses the concepts of innovation ambition and disruptive innovation. It provides examples of companies that achieved 10x growth through disruptive strategies like Spotify which disrupted the music industry revenue model and moved to a freemium subscription and ad-supported model. It also discusses the need to solve large problems that impact billions of people when aiming for breakthrough innovation. Metrics like frequency of use and ambition to change whole industries and markets at scale are presented as important factors for innovation success.
The document provides tips for pitching an idea or business to investors. It discusses the different types of pitches from a one sentence elevator pitch to a full investor deck presentation. It emphasizes that pitching is a skill that needs to be practiced. A successful pitch tells a story using facts and emotions, shares the vision, provides customer examples, includes a demo if possible, discusses the team, market size, business model, competition, and asks for something at the end such as funding or partnership. The document outlines the components that should be included in a pitch and stresses the importance of memorizing the pitch and delivering it with energy and focus on the key points.
The document provides an overview of unit economics concepts including understanding unit revenue, unit costs, and fixed costs. It discusses calculating unit profit, gross profit, profit margins, and how to build income statements and profit and loss statements. Examples are provided for calculating costs, revenues, profits and margins for hypothetical products over a five year period. The key information covered includes understanding the costs and revenues associated with individual units and how these figures scale up to provide overall business financial metrics.
This document discusses Google tools that can help developers test and validate business models through a process called Customer Development. It describes tools like Google Trends, Analytics, and Consumer Surveys that can help with tasks like determining market size, testing features with customers, validating problems and solutions, and testing sales and monetization strategies. The document advocates an agile approach to product development focused on testing hypotheses about the business model before prematurely scaling the business.
Mr. Progress provides a framework for building powerful sales messaging to win customers, get press coverage, and close investors. The document outlines why sales messaging is important, how to understand customer problems and frame solutions, and provides examples of startup messaging. It also discusses tailoring messaging for different stakeholders like investors, press, employees, and websites. The goal is to help founders effectively communicate their value and vision to various audiences.
This document provides an overview of venture capital topics including funding strategies, company valuations, exit strategies, and negotiating terms with investors. It discusses the three main sources of cash for startups, how VCs make money, common valuation methods and terms, negotiating best practices, and exit options. The presenter is Ravi Belani, a former VC and current director of Alchemist Accelerator, who provides the content as part of a lecture on entrepreneurship.
This document discusses growth hacking strategies for startups. It recommends building a funnel that focuses on acquisition, activation, retention, and revenue. It also suggests giving value first through community building and brand experiences before asking for sales. Specific tactics mentioned include using LinkedIn advanced filters for acquisition, webinars and scarcity for activation, deep links and Facebook Live for retention, and trial journeys and proposal acceleration for revenue. Referral strategies like viral contests are also recommended. The document advocates executing growth hacking coherently across the entire customer journey.
The document provides an overview of tools and software that can help get a company's first customers. It discusses thinking like a marketer by setting goals and KPIs. It also covers building landing pages, using Google Analytics for data and analytics, researching competitors, and using social media and influencer outreach tools for word-of-mouth marketing. Specific tools mentioned include Instapage, Unbounce, and Launchrock for building landing pages, and Semrush, Majestic, and Google Alerts for competitor and industry research.
This document outlines strategies for hacking the media algorithm to gain attention and coverage. It explains that the media system works like an algorithm, with smaller outlets and blogs reporting stories that national and international media then pick up and amplify on social media. A case study of the Protein World campaign shows how creating an emotional response and rebellion can make a story go viral. The document advises approaching media outlets directly or "trading up the chain" from smaller to larger outlets. It also notes that journalists and editors are under pressure to publish stories that generate page views. Overall, the strategies aim to position clients' stories and control the media narrative for publicity and business goals.
The document provides an overview of strategies for increasing traction and understanding users. It discusses focusing on behavior to build traction rather than what can be easily copied. Specific strategies covered include understanding how chemicals in the body like endorphins, dopamine, serotonin, and oxytocin can be leveraged. It also discusses action triggers, how small things matter, and provides real life examples.
Daimler AG consists of five divisions and had revenue of 153 billion Euros in 2016. The automotive industry is undergoing profound changes towards connectivity, autonomy, sharing, and electrification (CASE) due to structural trends. These changes are supported by Daimler's DigitalLife initiative which addresses over 4,600 employees annually on topics like health and AI. Daimler collaborates with universities on prototypes and technologies to drive cultural change from within by pitching novel ideas from its Digital Solutions and Services Team.
This document discusses Portugal's potential as a startup nation and highlights some Portuguese startups. It notes that Portugal invests only 1.29% of its GDP in research and development, below the OECD average, but that some Portuguese startups are having global success in bringing their innovations to the world market. One startup mentioned is Uniplaces, which has created an online platform for students to find and book accommodation, serving a growing market of over 262 million students worldwide by 2025.
The document outlines a 100-day plan to launch a new product or service. It includes forming an innovation team, gathering customer feedback, developing a technical prototype, testing and validating the prototype, and preparing for a commercial launch. Key stages include preparing for launch, implementing and developing the solution, and deciding to launch. The plan emphasizes failing fast and cheap to support innovation, and provides a checklist and timeline to guide the 100-day process.
This document outlines 75 launch tactics for acquiring customers with little to no marketing budget. It is authored by Jesse Leimgruber, the founder of NeoReach, a digital marketing firm. The tactics range from posting on sites like Reddit, ProductHunt, and HackerNews to more direct approaches like reaching out to competitors' followers, running giveaways and contests, guest posting, and leveraging referral programs and influencer marketing. The overall document provides a wide array of mostly free or low-cost tactics for startups and small businesses to generate awareness and signups during a product launch.
This document provides information on zero budget user acquisition strategies. It discusses public relations (PR), inbound marketing, and outbound marketing tactics. For PR, it emphasizes the importance of strategic earned media coverage and building relationships with journalists, analysts, and influencers on Twitter. For inbound marketing, it recommends content creation tactics like blogging, thought leadership pieces, and guest blogging. For outbound marketing, it discusses drip email campaigns, account-based marketing (ABM), phone calls, and using various tools to find contact information and track email opens. International considerations and keeping in touch with current customers are also addressed.
The document discusses Ken Singer's "Berkeley Method" for entrepreneurship and startup teams. It outlines Singer's model for the startup journey, emphasizing the importance of team formation and diversity. Successful teams require a variety of skills and personalities. When choosing teammates, it is important to find people with complementary strengths to balance the team across business functions, roles, experiences, and other aspects of diversity. Teammates should be chosen for their skills and ability to work through disagreements, rather than just being agreeable.
The three secrets to startup success are:
1. Achieving product-market fit by ensuring customers are actively buying your product. This prevents startups from dying due to lack of market.
2. Convincing investors you have potential for huge growth by estimating a large total addressable market, sizable serviceable market, and realistic obtainable market in the short term.
3. Picking an initial small target market that has strong pain, then progressively expanding to larger markets over time, as Facebook and Amazon did starting with colleges and books respectively.
Martin Omander is a developer advocate at Google who has worked there for 11 years. He gives a presentation about building conversational apps for Google Home using Actions on Google. He demonstrates building a sample app that provides school bell schedule information and discusses best practices for conversational design, including establishing a persona, thinking creatively about structure and dialog, and treating unexpected user responses as new turns in a conversation.
This document discusses various business model ideas and revenue models for making money with an app or online business. It begins by defining a business model as an organization's logic for creating, delivering, and capturing value. It then provides examples of different business model patterns involving transactions between products, money, data, services, and other elements. The document explores revenue models such as paid apps and freemium models, as well as models where a third party pays the bills through advertising, affiliate marketing, or partnerships. It encourages experimenting with different pricing strategies and mixed or subsidized business models.
The document provides information about a 15-day intensive training program at EIA to help attendees start and accelerate their businesses. It discusses topics that will be covered including customer discovery, team formation, prototyping, pitching to investors, and getting customers. It emphasizes the importance of ambition, risk-taking, and an experimental mindset to drive innovation. Examples are given of ambitious problems to tackle and trends like drones, artificial intelligence, chatbots, and autonomous products that could enable innovation.
The document discusses using Google Cloud Machine Learning APIs to curate online content. It provides examples of analyzing images of people from Google+ contacts to identify labels like "hair", "face", and "person". It then sorts the labels and associated photos into potential guests for a party ("invited") and those that should be excluded. This is done by training a simple model and using it to make predictions about new images.
The document discusses the concepts of innovation ambition and disruptive innovation. It provides examples of companies that achieved 10x growth through disruptive strategies like Spotify which disrupted the music industry revenue model and moved to a freemium subscription and ad-supported model. It also discusses the need to solve large problems that impact billions of people when aiming for breakthrough innovation. Metrics like frequency of use and ambition to change whole industries and markets at scale are presented as important factors for innovation success.
The document provides tips for pitching an idea or business to investors. It discusses the different types of pitches from a one sentence elevator pitch to a full investor deck presentation. It emphasizes that pitching is a skill that needs to be practiced. A successful pitch tells a story using facts and emotions, shares the vision, provides customer examples, includes a demo if possible, discusses the team, market size, business model, competition, and asks for something at the end such as funding or partnership. The document outlines the components that should be included in a pitch and stresses the importance of memorizing the pitch and delivering it with energy and focus on the key points.
The document provides an overview of unit economics concepts including understanding unit revenue, unit costs, and fixed costs. It discusses calculating unit profit, gross profit, profit margins, and how to build income statements and profit and loss statements. Examples are provided for calculating costs, revenues, profits and margins for hypothetical products over a five year period. The key information covered includes understanding the costs and revenues associated with individual units and how these figures scale up to provide overall business financial metrics.
This document discusses Google tools that can help developers test and validate business models through a process called Customer Development. It describes tools like Google Trends, Analytics, and Consumer Surveys that can help with tasks like determining market size, testing features with customers, validating problems and solutions, and testing sales and monetization strategies. The document advocates an agile approach to product development focused on testing hypotheses about the business model before prematurely scaling the business.
Mr. Progress provides a framework for building powerful sales messaging to win customers, get press coverage, and close investors. The document outlines why sales messaging is important, how to understand customer problems and frame solutions, and provides examples of startup messaging. It also discusses tailoring messaging for different stakeholders like investors, press, employees, and websites. The goal is to help founders effectively communicate their value and vision to various audiences.
This document provides an overview of venture capital topics including funding strategies, company valuations, exit strategies, and negotiating terms with investors. It discusses the three main sources of cash for startups, how VCs make money, common valuation methods and terms, negotiating best practices, and exit options. The presenter is Ravi Belani, a former VC and current director of Alchemist Accelerator, who provides the content as part of a lecture on entrepreneurship.
This document discusses growth hacking strategies for startups. It recommends building a funnel that focuses on acquisition, activation, retention, and revenue. It also suggests giving value first through community building and brand experiences before asking for sales. Specific tactics mentioned include using LinkedIn advanced filters for acquisition, webinars and scarcity for activation, deep links and Facebook Live for retention, and trial journeys and proposal acceleration for revenue. Referral strategies like viral contests are also recommended. The document advocates executing growth hacking coherently across the entire customer journey.
The document provides an overview of tools and software that can help get a company's first customers. It discusses thinking like a marketer by setting goals and KPIs. It also covers building landing pages, using Google Analytics for data and analytics, researching competitors, and using social media and influencer outreach tools for word-of-mouth marketing. Specific tools mentioned include Instapage, Unbounce, and Launchrock for building landing pages, and Semrush, Majestic, and Google Alerts for competitor and industry research.
This document outlines strategies for hacking the media algorithm to gain attention and coverage. It explains that the media system works like an algorithm, with smaller outlets and blogs reporting stories that national and international media then pick up and amplify on social media. A case study of the Protein World campaign shows how creating an emotional response and rebellion can make a story go viral. The document advises approaching media outlets directly or "trading up the chain" from smaller to larger outlets. It also notes that journalists and editors are under pressure to publish stories that generate page views. Overall, the strategies aim to position clients' stories and control the media narrative for publicity and business goals.
The document provides an overview of strategies for increasing traction and understanding users. It discusses focusing on behavior to build traction rather than what can be easily copied. Specific strategies covered include understanding how chemicals in the body like endorphins, dopamine, serotonin, and oxytocin can be leveraged. It also discusses action triggers, how small things matter, and provides real life examples.
Daimler AG consists of five divisions and had revenue of 153 billion Euros in 2016. The automotive industry is undergoing profound changes towards connectivity, autonomy, sharing, and electrification (CASE) due to structural trends. These changes are supported by Daimler's DigitalLife initiative which addresses over 4,600 employees annually on topics like health and AI. Daimler collaborates with universities on prototypes and technologies to drive cultural change from within by pitching novel ideas from its Digital Solutions and Services Team.
This document discusses Portugal's potential as a startup nation and highlights some Portuguese startups. It notes that Portugal invests only 1.29% of its GDP in research and development, below the OECD average, but that some Portuguese startups are having global success in bringing their innovations to the world market. One startup mentioned is Uniplaces, which has created an online platform for students to find and book accommodation, serving a growing market of over 262 million students worldwide by 2025.
The document outlines a 100-day plan to launch a new product or service. It includes forming an innovation team, gathering customer feedback, developing a technical prototype, testing and validating the prototype, and preparing for a commercial launch. Key stages include preparing for launch, implementing and developing the solution, and deciding to launch. The plan emphasizes failing fast and cheap to support innovation, and provides a checklist and timeline to guide the 100-day process.
This document outlines 75 launch tactics for acquiring customers with little to no marketing budget. It is authored by Jesse Leimgruber, the founder of NeoReach, a digital marketing firm. The tactics range from posting on sites like Reddit, ProductHunt, and HackerNews to more direct approaches like reaching out to competitors' followers, running giveaways and contests, guest posting, and leveraging referral programs and influencer marketing. The overall document provides a wide array of mostly free or low-cost tactics for startups and small businesses to generate awareness and signups during a product launch.
This document provides information on zero budget user acquisition strategies. It discusses public relations (PR), inbound marketing, and outbound marketing tactics. For PR, it emphasizes the importance of strategic earned media coverage and building relationships with journalists, analysts, and influencers on Twitter. For inbound marketing, it recommends content creation tactics like blogging, thought leadership pieces, and guest blogging. For outbound marketing, it discusses drip email campaigns, account-based marketing (ABM), phone calls, and using various tools to find contact information and track email opens. International considerations and keeping in touch with current customers are also addressed.
The document discusses Ken Singer's "Berkeley Method" for entrepreneurship and startup teams. It outlines Singer's model for the startup journey, emphasizing the importance of team formation and diversity. Successful teams require a variety of skills and personalities. When choosing teammates, it is important to find people with complementary strengths to balance the team across business functions, roles, experiences, and other aspects of diversity. Teammates should be chosen for their skills and ability to work through disagreements, rather than just being agreeable.
The three secrets to startup success are:
1. Achieving product-market fit by ensuring customers are actively buying your product. This prevents startups from dying due to lack of market.
2. Convincing investors you have potential for huge growth by estimating a large total addressable market, sizable serviceable market, and realistic obtainable market in the short term.
3. Picking an initial small target market that has strong pain, then progressively expanding to larger markets over time, as Facebook and Amazon did starting with colleges and books respectively.
Martin Omander is a developer advocate at Google who has worked there for 11 years. He gives a presentation about building conversational apps for Google Home using Actions on Google. He demonstrates building a sample app that provides school bell schedule information and discusses best practices for conversational design, including establishing a persona, thinking creatively about structure and dialog, and treating unexpected user responses as new turns in a conversation.
This document discusses various business model ideas and revenue models for making money with an app or online business. It begins by defining a business model as an organization's logic for creating, delivering, and capturing value. It then provides examples of different business model patterns involving transactions between products, money, data, services, and other elements. The document explores revenue models such as paid apps and freemium models, as well as models where a third party pays the bills through advertising, affiliate marketing, or partnerships. It encourages experimenting with different pricing strategies and mixed or subsidized business models.
The document provides information about a 15-day intensive training program at EIA to help attendees start and accelerate their businesses. It discusses topics that will be covered including customer discovery, team formation, prototyping, pitching to investors, and getting customers. It emphasizes the importance of ambition, risk-taking, and an experimental mindset to drive innovation. Examples are given of ambitious problems to tackle and trends like drones, artificial intelligence, chatbots, and autonomous products that could enable innovation.
The document discusses using Google Cloud Machine Learning APIs to curate online content. It provides examples of analyzing images of people from Google+ contacts to identify labels like "hair", "face", and "person". It then sorts the labels and associated photos into potential guests for a party ("invited") and those that should be excluded. This is done by training a simple model and using it to make predictions about new images.
The document discusses Google Cloud Platform machine learning capabilities for unstructured data like text, speech and images. It introduces the Cloud Vision, Speech and Translate APIs which provide pre-trained machine learning models through REST interfaces to understand unstructured data without requiring ML expertise. Examples are given of using the APIs for tasks like content moderation, sentiment analysis and extracting text/metadata from images.
MongoDB World 2019: Gaining ML Insight with Google Vision API and MongoDBMongoDB
We will demonstrate how easy it is to use the Google Vision API to gain additional insights from a batch of photos that have no prior metadata attached. By using this workflow, we will be able to quickly build a descriptive metadata database that can be leveraged for a variety of business use-cases.
Building a Data Cloud to enable Analytics & AI-Driven Innovation - Lak Lakshm...Daniel Zivkovic
Learn how Google Cloud addresses the key challenges when building an Agile Data & AI platform. This lecture is important regardless of the Cloud you are (will be) using because most businesses face the same 6 challenges:
1. High-quality AI requires a lot of data
2. AI Expertise is in high demand
3. Getting the value of ML requires a modern data platform
4. Activating ML requires surfacing AI into decision UIs
5. Operationalizing ML is hard
6. State-of-the-art changes rapidly
The lecture recording with Q&A is at https://youtu.be/ntBEQdD1IeQ
MongoDB.local Sydney 2019: Building Intelligent Apps with MongoDB & Google CloudMongoDB
Intelligent apps are emerging as the next frontier in analytics and application development. Learn how to build intelligent apps on MongoDB powered by Google Cloud with TensorFlow for machine learning and DialogFlow for artificial intelligence. Get your developers and data scientists to finally work together to build applications that understand your customer, automate their tasks, and provide knowledge and decision support.
MongoDB.local Austin 2018: Building Intelligent Apps with MongoDB & Google CloudMongoDB
Intelligent apps are emerging as the next frontier in analytics and application development. Learn how to build intelligent apps on MongoDB powered by Google Cloud with TensorFlow for machine learning and DialogFlow for artificial intelligence. Get your developers and data scientists to finally work together to build applications that understand your customer, automate their tasks, and provide knowledge and decision support.
Worst Practices in Artificial IntelligenceWilliam Tsoi
In this talk I discuss six "worst practices" in Artificial Intelligence, so that you don't make the same mistakes as you embark on your AI and Machine Learning journey!
The full talk (in cantonese) is here: https://youtu.be/NIIztmpA6Hc?t=1172
MongoDB World 2018: Building Intelligent Apps with MongoDB & Google CloudMongoDB
Building intelligent apps involves combining real-time analytics, machine learning, and artificial intelligence to provide personalized recommendations and automate tasks for customers. Developers can use MongoDB and Google Cloud to build intelligent apps in 3 steps: 1) create a base ecommerce app, 2) add a recommendation engine using machine learning, and 3) enable shopping via chat with artificial intelligence. This brings data scientists and developers together to create applications that understand and assist customers.
Advanced Analytics and Artificial Intelligence - Transforming Your Business T...David J Rosenthal
Recent advances in AI have incredible potential and they are already fundamentally changing our lives in ways we couldn’t have imagined even five years ago. And yet, AI is also probably one of the least understood technological breakthroughs in modern times. Come to this event to learn about breakthrough advances in AI and the power of the cloud, and how Microsoft provides a flexible platform for you to infuse intelligence into your own products and services. Microsoft empowers you to transform your business, uniquely combining AI innovation with a proven Enterprise platform, deriving intelligence from a wide range of data relevant to your business no matter where it lives.
This document provides an agenda for an AI workshop that covers various Microsoft AI technologies including computer vision, speech, and language. The agenda includes discussions on Microsoft's breakthroughs in computer vision by winning ImageNet competitions five years in a row. It also covers Microsoft's speech breakthroughs and ongoing momentum. The bulk of the agenda focuses on demonstrating various Microsoft Cognitive Services like Vision, Speech, Language, Translator, LUIS, and Bing APIs. It provides examples of calling the Computer Vision and Translator APIs and summarizes several Cognitive Services like Text Analytics, Spell Check, and Language Understanding. The document aims to educate attendees on Microsoft's broad portfolio of AI services and tools.
Teams lifecycle management with office 365 tools only - Microsoft 365 Virtual...Michael Plettner
This session from the Microsoft 365 virtual marathon event in May 2020, gives you a short overview of available #lifecycle methods and automation procedures to handle #lifecycle and #governance on an enterprise level.
Building Intelligent Apps with MongoDB & Google CloudMongoDB
Intelligent apps are emerging as the next frontier in analytics and application development. Learn how to build intelligent apps on MongoDB powered by Google Cloud with TensorFlow for machine learning and DialogFlow for artificial intelligence. Get your developers and data scientists to finally work together to build applications that understand your customer, automate their tasks, and provide knowledge and decision support.
Why Don’t You Understand Me? Build Intelligence into Your AppsEran Stiller
Artificial Intelligence is not something exotic anymore. With Siri, Cortana & Google Assistant on virtually any device, our users have come to expect our applications to understand them in more meaningful ways than ever before. Luckily for us, various platforms have emerged which enable us to integrate this kind of functionality into our applications and services without having to do the heavy lifting by ourselves.
In this session we will take a full-fledged cross platform Xamarin application built around a public image API, and enhance it with intelligence using Azure Cognitive Services. We'll see how we can add vision, language and speech into our applications, making them smarter than ever before. Stand out in the crowd - bring intelligence into your apps!
Azure Cognitive Services provides various AI capabilities like computer vision, speech, language, search, and decision-making through APIs and SDKs. It includes over 20 services that are in general availability and growing. Cognitive Services aims to make AI accessible to developers through pre-built and customizable AI models.
Unleash office 365 with the power of cognitive services and microsoft graph apiEstelle Auberix
This document contains a summary of a presentation about unleashing the power of Office 365 with Cognitive Services and the Microsoft Graph API. The presentation introduces Estelle Auberix as the speaker and discusses Office 365, the Microsoft Graph API, and various cognitive services like Cortana, vision, language processing, and translation services. It provides examples of how these cognitive services and the Graph API can be used to enhance Office 365 features and the user experience. The presentation also includes a demo and concludes by emphasizing the importance of data and new technologies like cloud, IoT, AI, and blockchain for digital transformation.
Build Cloud-Native Applications in an Enterprise Environment (BAP205-S) - AWS...Amazon Web Services
Learn how Volkswagen Financial Services is reaching its ambition to have core financial products online, worldwide by 2022. In this session, Daniel Matthies, Head of the Digital Unit at Volkswagen Financial Services, discusses how to leverage AWS for development and create a compliant SaaS office solution. Discover where the areas of freedom are when working within local markets. Learn best practices for engaging subsidiary companies and a cross-location team to ensure everyone is truly enabled, while tackling the doubts some colleagues may have previously had about stepping into the world of cloud technology and solutions. This session is brought to you by AWS partner, Cloudreach Inc.
Windays14 - How to (remote) control Office 365 with Azureatwork
This document discusses how to remotely control and automate Office 365 using Azure. It begins with an overview of why remote control of Office 365 is useful for automation. It then demonstrates authenticating to Azure Active Directory and Office 365 services like SharePoint and Exchange. The document discusses the various APIs and tools available to access and integrate with Office 365 services when deployed on Azure. It provides links to documentation, SDKs, blogs and samples to help developers build automated solutions using Office 365 and Azure.
The document outlines an agenda for a Design Day event. It includes times for welcome, introductions, a design sprint, break, visual and product design, technical architecture wrap up. It then provides more details on the individual sessions, including an overview of the design sprint process and examples of information hierarchy, grid systems, and minimum viable products. It concludes with a discussion of technical architecture considerations and a workshop.
Similar to EIA2017Portugal - Andres L. Martinez Ortiz - Curating Content with Google Machine Learning Application Programming Interfaces (20)
The document discusses different funding avenues for startups including grants, equity, debt, and revenue. It covers venture capital, angel investing, equity crowdfunding, SBA loans, bank loans, and factoring. It notes that VC/angel funding provides fast access to capital and strategic help but requires giving up control and pressure to grow. Debt options retain control but are hard to qualify for. The document also discusses term sheets, deciding how much to raise and at what valuation, additional terms, board composition, information rights, and pro rata rights for seed stage investors.
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19. Confidential & ProprietaryGoogle Cloud Platform 19
So…. Why APIs?
{ Google Cloud Platform }
1. We want to offer businesses the tools to differentiate by offering a powerful set of APIs
that enable apps to see, hear and understand the world
2. Reduce your Time to Market (TMM) when launching your next-generation app
3. Provide you easy access to machine learning technology to give any developer the
freedom to work in the language and tools they want
4. Provide virtually limitless scalability to your application without needing to manage
back-end servers running deep learning
20. Pre-Trained Machine Learning Models
Fully trained ML models from Google Cloud that allow a general developer to
take advantage of rich machine learning capabilities with simple REST based
services.
21. Confidential & ProprietaryGoogle Cloud Platform 21
Introducing
Cloud Natural Language API
Sentiment analysis and entity
recognition for text
22. Confidential & ProprietaryGoogle Cloud Platform 22
Features
Extract sentence, identify parts of
speech and create dependency parse
trees for each sentence
Identify entities and label by types such
as person, organization, location, events,
products and media
Understand the overall sentiment of a
block of text
Access via REST API. Text can be
uploaded in the request or integrated
with Google Cloud Storage
Syntax Analysis Entity Recognition
Sentiment Analysis Integrated REST API
24. Confidential & ProprietaryGoogle Cloud Platform 24
Faces: Faces, facial landmarks,
emotions
OCR: Read and extract text, with
support for > 10 languages
Photo credit Getty Images
Label: Detect entities from furniture to
transportation
Logos: Identify product logos
Landmarks & Image Properties
Detect landmarks & dominant
color of image
Safe Search: Detect explicit content -
adult, violent, medical and spoof
Cloud Vision API
Call API from anywhere, with support for embeddable images, and Google Cloud Storage
34. Main shellplus_contacts = get_plus_contacts()
print "Processing %d contacts" % len(plus_contacts)
for plus_id in plus_contacts:
plus_profile = get_plus_profile(plus_id)
image_uri = plus_profile['image']['url'].replace("?sz=50","?sz=250")
image_data = analyze_img(image_uri)
if image_data is not None:
print(image_uri)
if 'labelAnnotations' in image_data['responses'][0]:
for label in image_data['responses'][0]['labelAnnotations']:
print label['description']; label['score']; image_uri
35. get_plus_contacts: oAuth
storage = Storage('/home/almo/dev/keys/ex1/oAuth_credentials.dat')
credentials = storage.get()
if credentials is None or credentials.invalid:
PEOPLE_API='https://www.googleapis.com/auth/contacts.readonly'
flow = flow_from_clientsecrets('/home/almo/dev/keys/ex1/oAuth_key.json',
scope=[PEOPLE_API])
credentials = run_flow(flow, storage)
http = credentials.authorize(httplib2.Http())
service = build('people','v1',http=http)
request = service.people().connections().list(resourceName='people/me',
pageSize=500)
53. Curating Online Content with
Google ML APIs
Andres L. Martinez a.k.a almo
Google Developer Relations Manager
@davilagrau
Editor's Notes
TensorFlow
Open sourced in November 2015
Make clear that it's not only for Neural Nets, but rather it's a generalized ML lib for all sorts of machine learning problems (decision trees, support vector machines, reinforcement learning, and more)
Goal is to emulate the neural networks inside your brain using a data flow framework
A tensor is a multidimensional array, and TF is a data flow framework for tensors. With TF you can represent and perform computations on multi-dimensional data flowing through a graph. Developers + researchers can build and train their own models
Input => algorithms => output
Runs on many platforms: data centers, CPUs and GPUs, mobile phones
Get started with the MNIST example, basically the “Hello World” of machine learning. It uses a dataset of bitmap images of handwritten numbers - you use this to train a model to recognize numbers from handwritten images
Needs more background, understanding of ML and math, more code
Cloud ML
Fully managed service
Train using a custom TensorFlow graph
Batch and online predictions, at scale
Integrated Datalab experience
Regression and classification tasks
Great use case if you have a pile of data, a custom classification, and you don't want to hire (or become) a machine learning expert (aka get a PhD)
When you’d want to use TF vs. Cloud ML: the largest challenge for NN users now is the scalability for distributed training. It's so hard to build a GPU cluster. Cloud ML solves that.
The cool thing about the vision + speech APIs is that you don’t need to be an ML expert to use them. You just need to be able to make a REST request!
Machine Learning APIs, meant for people building applications
Access fully-trained models...as a service
Black box the ML part, and let you move on with your life: If you can make a REST API call, you can use it.
Examples include vision api, speech api, and translate api. More to come!
<CLICK> Vision API = Friendly Machine Learning, not the acronym (FML?)
faces photo is from our mobile vision website: https://developers.google.com/vision/
People pictured above are Google employees, from the London developer relations team.
ship photo is from Getty Images
Receipt Photo is from istock photos
Logo Image: New Google Logo 2015 - YouTube - www.youtube.com1270 × 720Search by image
Let me walk you through what Vision API can really do:
Label Detection: The API can detect broad sets of categories within an image, ranging from modes of transportation to animals.
Face Detection: The API can detect multiple faces within an image, along with the associated key facial attributes like emotional state or wearing headwear.
OCR: The API can detect and extract text within an image, with support for a broad range of languages.
Explicit Content Detection: We can detect explicit content like adult content or violent content within an image.
Landmark Detection: The APi can detect popular natural and manmade structures within an image.
Logo Detection: We can detect popular product logos within an image.