Product Management Event Held at the Product Conference in Silicon Valley.
Aarthi Srinivasan, Director of Product at Target, shared her information on tech singularity. She gave an introduction to Artificial Intelligence and Blockchain, and talked about the different types of AI and blockchain. She also discussed the intersection between AI and Blockchain.
Types of Blockchain - permissioned vs. permissionless platforms
Types of AI - Unsupervised, Supervised and Reinforcement Learning, Deep Learning
Future of Blockchain and AI
IBM Academy of Technology & Cognitive ComputingNico Chillemi
I delivered this presentation at University at Chieti-Pescara in Abruzzo (Italy) in September 2015, introducing IBM Academy of Technology and talking about Cognitiva Computing and Analytics with IBM Watson and IBM IT Operations Analytics Log Analysis (ITOA). The video in Italian is available on YouTube, please contact me if you are interested. Thanks to Amanda Tenedini for the help with Social Media and to Piero Leo for the help with IBM Watson.
What AI is and examples of how it is used in legalBen Gardner
This presentation was given at Legal Geek on 10th Dec 2015. It is a scenesetting peice that looks to de-mystify artificial intelligence by looking beyond the hype.
Types of Blockchain - permissioned vs. permissionless platforms
Types of AI - Unsupervised, Supervised and Reinforcement Learning, Deep Learning
Future of Blockchain and AI
IBM Academy of Technology & Cognitive ComputingNico Chillemi
I delivered this presentation at University at Chieti-Pescara in Abruzzo (Italy) in September 2015, introducing IBM Academy of Technology and talking about Cognitiva Computing and Analytics with IBM Watson and IBM IT Operations Analytics Log Analysis (ITOA). The video in Italian is available on YouTube, please contact me if you are interested. Thanks to Amanda Tenedini for the help with Social Media and to Piero Leo for the help with IBM Watson.
What AI is and examples of how it is used in legalBen Gardner
This presentation was given at Legal Geek on 10th Dec 2015. It is a scenesetting peice that looks to de-mystify artificial intelligence by looking beyond the hype.
SmartData Webinar: Cognitive Computing in the Mobile App EconomyDATAVERSITY
Mobility is transforming work and life throughout the planet. Mobile apps--built for a growing range of handhelds, wearables, Internet of Things, and other platforms--are becoming the universal access paths to commerce, content, and community in the 21st century. The app economy refers to this new world where every decision, action, exploration, and experience is continuously enriched and optimized through the cloud-served apps that accompany you everywhere. In this webinar, James Kobielus, IBM's Big Data Evangelist, will discuss the potential of cognitive computing to super-power the emerging app economy. In addition to providing an overview of IBM's Watson strategy for cognitive computing, Kobielus will go in-depth on IBM's strategic partnership with Apple to draw on the strengths of each company to transform enterprise mobility through a new class of apps that leverage IBM’s Watson-based big data analytics cloud and add value to Apple's iPhone and iPad platforms in diverse industries.
Gene Villeneuve - Moving from descriptive to cognitive analyticsIBM Sverige
As the scope of big data rapidly expands, so does the scope of the analytics that are necessary to extract insight from that data. It is simply impossible for humans or indeed rules-based engines to take that information to action. More and more, clients need analytics to make the best decisions possible; or better yet, embed those analytics into processes to automate the decision-making process, which they simply the answers based on the questions being asked at the point of impact. In order to address these rapidly evolving needs, we need to ensure the right analytics capability are deployed to suit each situation, each point of interaction and each decision point within a process. Join this session, and learn how IBM can provide a solution for the varying types of analytics: from descriptive to predictive to prescriptive to cognitive.
Gamifying Strategy - Enterprise AI use cases on agent-based simulation and re...AnandSRao1962
This talk was presented at the 2018 O'Reilly AI conference in New York. It highlights how advances in AI gaming technology can be used to solve strategic problems in business. It combines agent-based modeling with reinforcement learning to solve strategic problems in financial services and mobility as a service sectors.
How blockchain and artificial intelligence/machine learning technologies can synergically enhance each other and why blockchain is critical for the future AI evolvement. Report from iforum.ua conference in 2017 by Dr Maxim Orlovsky, BICA Labs
Ibm cognitive business_strategy_presentationdiannepatricia
IBM Cognitive Business Strategy presentation. Presented by Dianne Fodell and Jim Spohrer at the Cognitive Systems Institute Group Speaker Series call on October 8, 2015.
Cognitive analytics: What's coming in 2016?IBM Analytics
Cognitive analytics is innovating and evolving rapidly. Expert predictions in this area are essential for organizations that plan to leverage cognitive analytics in their big data analytics strategies in 2016 and beyond. It is the core investment that organizations everywhere should make to stay relevant in the insight economy. IBM is the premier solution provider, with IBM Watson as its flagship cognitive analytics platform, for realizing the opportunities this innovative technology makes possible.
Learn more about IBM Analytics at http://ibm.co/advancedanalytics
Explore our analysis of technology trends for 2019 and beyond: AI, IoT, Security, Big Data / Data Science, Mobile Apps Development, AR/VR, RPA (Robot Process Automation), Blockchain, Automotive Solutions, Business Intelligence, Cloud Computing, Service Desk, Autonomous Things, Augmented Analytics, AI-Driven Development, Digital Twins, Empowered Edge, Immersive Experience, Smart Spaces, Quantum Computing, and more.
Check our recommendations for businesses to stay current with the latest IT tendencies.
Includes a video by Gartner.
The slide has details on below points:
1. Introduction to Machine Learning
2. What are the challenges in acceptance of Machine Learning in Banks
3. How to overcome the challenges in adoption of Machine Learning in Banks
4. How to find new use cases of Machine Learning
5. Few current interesting use cases of Machine Learning
Please contact me (shekup@gmail.com) or connect with me on LinkedIn (https://www.linkedin.com/in/shekup/) for more explanation on ML and how it may help your business.
The slides are inspired by:
Survey & interviews done by me with Bankers & Technology Professionals
Presentation from Google NEXT 2017
Presentation by DATUM on Youtube
Royal Society Machine Learning
Big Data & Social Analytics Course from MIT & GetSmarter
Part I. Artificial Intelligence Applications for Patents
1. AI Innovations
Video Link: https://www.youtube.com/watch?v=z0GuRDLHRYU
AI Innovation Frontline
Top 100 AI Technology Innovation Entities
AI Demos: Autonomous Cars
AI Demos: Digital Human/Avatar
AI vs. Human
2. AI Application Demos
Video Link:https://www.youtube.com/watch?v=yoPkP-BZAa8
Computer Vision/Healthcare:
(CBIR) Content Based Image Retrieval for eye disease/chest X-ray diagnostics
Natural Language Processing/Understanding/Generation:
Hugging Face BERT Sentence Completion/ Text Classification/Question Answer
Sentence BERT Movie Recommender
Facebook ParlAI Chatbot
Finance:
Credit Card Fraud Detection
Stock Price Prediction
Stock Trade Simulation
Financial Statements Analysis
3. Artificial Intelligence Applications for Patents Demos
Video Link: https://www.youtube.com/watch?v=kVmHmh0Kbos
Patent Word Cloud Analysis
I & Blockchain patents
Patent Semantic Search
AI patents search using an abstract
LTE standard essential patent search using a standard specification
Patent Text Translation
English patent to German/French/Chinese/Japanese
Patent Text Summarization
legal/patent/technical text
Patent Classifier
AI CPC classification
RFID technology landscaping
LTE standard essential patent classification
AI+Blockchain+IoT convergence research
Patent Claim Generation
AI & Blockchain patent claim automatic generation
Claim Charts for Standard Essential Patents
[Prerequisite] pre-trained/fine-tuned BERT/GPT2 models using specific standard specifications
Part II. Blockchain Applications for Patents
1. Blockchain Innovation Status and Applications
Video Link:https://www.youtube.com/watch?v=l8cq-DB7VbM
Top 100 Blockchain Technology Innovation Entities
Blockchain Innovation Frontline
AI+Blockchain+IoT Convergence
AI+Blockchain System Demo for Medical Data Sharing
AI+ Blockchain System Demo for E-Commerce Use Case
2. DeFi Based Patent Monetization Platform Development
Video Link: https://www.youtube.com/watch?v=JarYMPIxlr4
Wanted to explore more details from the industry experts of big data hadoop training in Bangalore, then get the clear evolution & history of this technology from these big data hadoop training in Bangalore providers.
Intelligent enterprise: Cognitive Business Presentation from World of WatsonNancy Pearson
How Companies Are Using Cognitive Computing to Drive Tangible Results including information from the 2016 Cognitive Advantage Report: http://www.ibm.com/cognitive/advantage-reports/
Mathematical Finance & Financial Data Science Seminar
AI and machine learning are entering every aspect of our life. Marketing, autonomous driving, personalization, computer vision, finance, wearables, travel are all benefiting from the advances in AI in the last decade. As more and more AI applications are being deployed in enterprises, concerns are growing about potential "AI accidents" and the misuse of AI. With increased complexity, some are questioning whether the models actually work! As the debate about fairness, bias, and privacy grow, there is increased attention to understanding how the models work and whether the models are thoroughly tested and designed to address potential issues.
The area "Responsible AI" is fast emerging and becoming an important aspect of the adoption of machine learning and AI products in the enterprise. Companies are now incorporating formal ethics reviews, model validation exercises, and independent algorithmic auditing to ensure that the adoption of AI is transparent and has gone through formal validation phases.
In this talk, Sri will introduce Algorithmic auditing and discuss why Algorithmic auditing will be a formal process industries using AI will need. Sri will also discuss the emerging risks in the adoption of AI and discuss how QuSandbox, his company is building, will address the emerging needs of formal Algorithmic auditing practices in enterprises.
This talk provides an overview of privacy-preserving analytics and data mining systems at LinkedIn, highlighting the practical challenges/requirements, techniques, and lessons learned from deployment. The first part presents a framework to compute robust, privacy-preserving analytics, while the second part focuses on the privacy challenges/design for a large crowdsourced system (LinkedIn Salary). This presentation is an expanded version of the talk given at the Differential Privacy Deployed workshop, co-organized by Cynthia Dwork and held at Harvard / American Academy of Sciences in September, 2018.
Keynote presentation at the HUBB Conference.
Adj Prof Mascarella clarifies terms, mechanisms and what is the roadmap to use innovation for new business.
SmartData Webinar: Cognitive Computing in the Mobile App EconomyDATAVERSITY
Mobility is transforming work and life throughout the planet. Mobile apps--built for a growing range of handhelds, wearables, Internet of Things, and other platforms--are becoming the universal access paths to commerce, content, and community in the 21st century. The app economy refers to this new world where every decision, action, exploration, and experience is continuously enriched and optimized through the cloud-served apps that accompany you everywhere. In this webinar, James Kobielus, IBM's Big Data Evangelist, will discuss the potential of cognitive computing to super-power the emerging app economy. In addition to providing an overview of IBM's Watson strategy for cognitive computing, Kobielus will go in-depth on IBM's strategic partnership with Apple to draw on the strengths of each company to transform enterprise mobility through a new class of apps that leverage IBM’s Watson-based big data analytics cloud and add value to Apple's iPhone and iPad platforms in diverse industries.
Gene Villeneuve - Moving from descriptive to cognitive analyticsIBM Sverige
As the scope of big data rapidly expands, so does the scope of the analytics that are necessary to extract insight from that data. It is simply impossible for humans or indeed rules-based engines to take that information to action. More and more, clients need analytics to make the best decisions possible; or better yet, embed those analytics into processes to automate the decision-making process, which they simply the answers based on the questions being asked at the point of impact. In order to address these rapidly evolving needs, we need to ensure the right analytics capability are deployed to suit each situation, each point of interaction and each decision point within a process. Join this session, and learn how IBM can provide a solution for the varying types of analytics: from descriptive to predictive to prescriptive to cognitive.
Gamifying Strategy - Enterprise AI use cases on agent-based simulation and re...AnandSRao1962
This talk was presented at the 2018 O'Reilly AI conference in New York. It highlights how advances in AI gaming technology can be used to solve strategic problems in business. It combines agent-based modeling with reinforcement learning to solve strategic problems in financial services and mobility as a service sectors.
How blockchain and artificial intelligence/machine learning technologies can synergically enhance each other and why blockchain is critical for the future AI evolvement. Report from iforum.ua conference in 2017 by Dr Maxim Orlovsky, BICA Labs
Ibm cognitive business_strategy_presentationdiannepatricia
IBM Cognitive Business Strategy presentation. Presented by Dianne Fodell and Jim Spohrer at the Cognitive Systems Institute Group Speaker Series call on October 8, 2015.
Cognitive analytics: What's coming in 2016?IBM Analytics
Cognitive analytics is innovating and evolving rapidly. Expert predictions in this area are essential for organizations that plan to leverage cognitive analytics in their big data analytics strategies in 2016 and beyond. It is the core investment that organizations everywhere should make to stay relevant in the insight economy. IBM is the premier solution provider, with IBM Watson as its flagship cognitive analytics platform, for realizing the opportunities this innovative technology makes possible.
Learn more about IBM Analytics at http://ibm.co/advancedanalytics
Explore our analysis of technology trends for 2019 and beyond: AI, IoT, Security, Big Data / Data Science, Mobile Apps Development, AR/VR, RPA (Robot Process Automation), Blockchain, Automotive Solutions, Business Intelligence, Cloud Computing, Service Desk, Autonomous Things, Augmented Analytics, AI-Driven Development, Digital Twins, Empowered Edge, Immersive Experience, Smart Spaces, Quantum Computing, and more.
Check our recommendations for businesses to stay current with the latest IT tendencies.
Includes a video by Gartner.
The slide has details on below points:
1. Introduction to Machine Learning
2. What are the challenges in acceptance of Machine Learning in Banks
3. How to overcome the challenges in adoption of Machine Learning in Banks
4. How to find new use cases of Machine Learning
5. Few current interesting use cases of Machine Learning
Please contact me (shekup@gmail.com) or connect with me on LinkedIn (https://www.linkedin.com/in/shekup/) for more explanation on ML and how it may help your business.
The slides are inspired by:
Survey & interviews done by me with Bankers & Technology Professionals
Presentation from Google NEXT 2017
Presentation by DATUM on Youtube
Royal Society Machine Learning
Big Data & Social Analytics Course from MIT & GetSmarter
Part I. Artificial Intelligence Applications for Patents
1. AI Innovations
Video Link: https://www.youtube.com/watch?v=z0GuRDLHRYU
AI Innovation Frontline
Top 100 AI Technology Innovation Entities
AI Demos: Autonomous Cars
AI Demos: Digital Human/Avatar
AI vs. Human
2. AI Application Demos
Video Link:https://www.youtube.com/watch?v=yoPkP-BZAa8
Computer Vision/Healthcare:
(CBIR) Content Based Image Retrieval for eye disease/chest X-ray diagnostics
Natural Language Processing/Understanding/Generation:
Hugging Face BERT Sentence Completion/ Text Classification/Question Answer
Sentence BERT Movie Recommender
Facebook ParlAI Chatbot
Finance:
Credit Card Fraud Detection
Stock Price Prediction
Stock Trade Simulation
Financial Statements Analysis
3. Artificial Intelligence Applications for Patents Demos
Video Link: https://www.youtube.com/watch?v=kVmHmh0Kbos
Patent Word Cloud Analysis
I & Blockchain patents
Patent Semantic Search
AI patents search using an abstract
LTE standard essential patent search using a standard specification
Patent Text Translation
English patent to German/French/Chinese/Japanese
Patent Text Summarization
legal/patent/technical text
Patent Classifier
AI CPC classification
RFID technology landscaping
LTE standard essential patent classification
AI+Blockchain+IoT convergence research
Patent Claim Generation
AI & Blockchain patent claim automatic generation
Claim Charts for Standard Essential Patents
[Prerequisite] pre-trained/fine-tuned BERT/GPT2 models using specific standard specifications
Part II. Blockchain Applications for Patents
1. Blockchain Innovation Status and Applications
Video Link:https://www.youtube.com/watch?v=l8cq-DB7VbM
Top 100 Blockchain Technology Innovation Entities
Blockchain Innovation Frontline
AI+Blockchain+IoT Convergence
AI+Blockchain System Demo for Medical Data Sharing
AI+ Blockchain System Demo for E-Commerce Use Case
2. DeFi Based Patent Monetization Platform Development
Video Link: https://www.youtube.com/watch?v=JarYMPIxlr4
Wanted to explore more details from the industry experts of big data hadoop training in Bangalore, then get the clear evolution & history of this technology from these big data hadoop training in Bangalore providers.
Intelligent enterprise: Cognitive Business Presentation from World of WatsonNancy Pearson
How Companies Are Using Cognitive Computing to Drive Tangible Results including information from the 2016 Cognitive Advantage Report: http://www.ibm.com/cognitive/advantage-reports/
Mathematical Finance & Financial Data Science Seminar
AI and machine learning are entering every aspect of our life. Marketing, autonomous driving, personalization, computer vision, finance, wearables, travel are all benefiting from the advances in AI in the last decade. As more and more AI applications are being deployed in enterprises, concerns are growing about potential "AI accidents" and the misuse of AI. With increased complexity, some are questioning whether the models actually work! As the debate about fairness, bias, and privacy grow, there is increased attention to understanding how the models work and whether the models are thoroughly tested and designed to address potential issues.
The area "Responsible AI" is fast emerging and becoming an important aspect of the adoption of machine learning and AI products in the enterprise. Companies are now incorporating formal ethics reviews, model validation exercises, and independent algorithmic auditing to ensure that the adoption of AI is transparent and has gone through formal validation phases.
In this talk, Sri will introduce Algorithmic auditing and discuss why Algorithmic auditing will be a formal process industries using AI will need. Sri will also discuss the emerging risks in the adoption of AI and discuss how QuSandbox, his company is building, will address the emerging needs of formal Algorithmic auditing practices in enterprises.
This talk provides an overview of privacy-preserving analytics and data mining systems at LinkedIn, highlighting the practical challenges/requirements, techniques, and lessons learned from deployment. The first part presents a framework to compute robust, privacy-preserving analytics, while the second part focuses on the privacy challenges/design for a large crowdsourced system (LinkedIn Salary). This presentation is an expanded version of the talk given at the Differential Privacy Deployed workshop, co-organized by Cynthia Dwork and held at Harvard / American Academy of Sciences in September, 2018.
Keynote presentation at the HUBB Conference.
Adj Prof Mascarella clarifies terms, mechanisms and what is the roadmap to use innovation for new business.
Blockchain in Media. Description of blockchain and smart contracts. Presented Media pain points and possible solutions. Peeped into various frameworks built on Hyperledger fabric and ethereum for media
The AI Platform Business Revolution: Matchmaking, Empathetic Technology, and ...Steve Omohundro
Popular media is full of stories about self-driving cars, video deepfakes, and robot citizens. But this kind of popular artificial intelligence is having very little business impact. The actual impact of AI on business is in automating business processes and in creating the "AI Platform Business Revolution". Platform companies create value by facilitating exchanges between two or more groups. AI is central to these businesses for matchmaking between producers and consumers, organizing massive data flows, eliminating malicious content, providing empathetic personalization, and generating engagement through gamification. The platform structure creates moats which generate outsized sustainable profits. This is why platform businesses are now dominating the world economy. The top five companies by market cap, half of the unicorn startups, and most of the biggest IPOs and acquisitions are platforms. For example, the platform startup ByteDance is now worth $75 billion based on three simple AI technologies.
In this talk we survey the current state of AI and show how it will generate massive business value in coming years. A recent McKinsey study estimates that AI will likely create over 70 trillion dollars of value by 2030. Every business must carefully choose its AI strategy now in order to thrive over coming decades. We discuss the limitations of today's deep learning based systems and the "Software 2.0" infrastructure which has arisen to support it. We discuss the likely next steps in natural language, machine vision, machine learning, and robotic systems. We argue that the biggest impact will be created by systems which serve to engage, connect, and help individuals. There is an enormous opportunity to use this technology to create both social and business value.
In this webinar Prof. Banafa will discuss in details the use of Blockchain in the following businesses: Insurance; Payments; Internet-of-Things (IoT); Supply Chain; Healthcare; Government; Identity; Advertising; Marketing; Banking.
Blockchain and XBRL at the 2017 American Accounting Association presented b...Workiva
The integration of "Blockchain and XBRL" provides a seamless data solution, with blockchain as a potential output from XBRL based reporting.
Blockchain’s smart contracts might also be facilitated by an XBRL’s powerful persistent data model.
Week 5 - Blockchain Economics: Strategic Value in Private Blockchain Roger Royse
Instructor: Roger Royse, Founder of Royse Law Firm
Course Title: The Business Basics of Blockchain, Cryptocurrencies, and Tokens
Location: Stanford Continuing Studies
Week: 5 (of 7)
The fifth class will get into how blockchain technology will shape innovation in different industries. Relying on economic theory, we will address the question of “How can companies determine if there is strategic value in blockchain?” We will evaluate blockchain’s value in short-term and long-term perspective and explain how companies take a structured approach in developing blockchain strategies. We will examine several successful private blockchain projects such as Maersk TradeLens and look at the factors that come into play when determining whether to use a public or a private blockchain.
FinTech: The revolution is here!
In this session, we will introduce fintech and discuss the eight key innovations in fintech that are revolutionizing how companies are doing business. This session is geared towards fintech enthusiasts and financial industry professionals who are intrigued and fascinated by the innovations in fintech and would like to learn and adapt to the new realities of the 21st century
The year 2018 is the year of blockchain applications with several ongoing use-cases coming to realization and the vendor landscape also gained more depth and a better structure after years of press and vendor hype, fueled equally by commercial self-interest and a genuine desire for innovation.
Blockchain Technology and Its Application in Artificial Intelligence and Mach...Dr. Kotrappa Sirbi
Blockchain and Artificial Intelligence are two of the hottest technology trends right now. Even though the two technologies have highly different developing parties and applications, researchers have been discussing and exploring their combination .
Blockchain Introduction - Canada Nov 2017.pptxAntony Welfare
Back in 2017 I joined the world of #Blockchain and presented my first ever Blockchain presentation on 14th November 2017 at a Tech meetup in Penticton, BC (Canada)
A few key highlights:
* The fundamentals of Blockchain technology have not changed (Trust, Transparency, Security, Quality/Certainty, Reduced costs)
* We were talking about Web 3.0 back in 2017 😉
* People still miss define Blockchain
* Janet Yellen and Christine Lagarde were commenting on Blockchain back in 2017
* Checkout the Dapps section – I was ahead of my time there!
* And the last three slides on the Market cap and increases – I was excited to tell people the market cap was $200bn, BTC was $8,000 and ETH was nearly $400 ……… Ahhh the good old days 😉
And finally – my “leaders comment” back in 2017 still stands “Blockchain is the next disruptive technology to transform the lives of our customers and our business operations”
What a journey so far…and guess what…its only just begun 👍👍👍
2018 has been a roller-coaster ride for blockchain technology mostly at the hands of cryptocurrencies – blockchain’s main beneficiary. Extreme price volatility, unsuccessful ICOs, fraud, cyber security issues, and negative press around cryptocurrency would have all but killed most emerging technologies. But not blockchain.
Blockchain is entering into a new evolutionary phase with the help of tech giants like IBM, Amazon and Google who recognize the wider applicability of blockchain as a game changer in data storage, commerce, and security. Even cryptocurrency is showing promising signs as it moves out of the domain of overnight Bitcoin millionaires (and more who have lost fortunes when speculating on cryptocurrencies) to risk averse financial heavyweights such as Goldman Sachs and JP Morgan. Like the Internet, e-commerce, social media, and cloud computing before it, blockchain is on a fast track to become a ubiquitous technology.
Innovation potential of the blockchain, and of decentralized applicationsJan Brejcha
The chain of transaction blocks, or blockchain, is a trustless shared public ledger of bitcoin transactions, synchronized in a peer-to-peer network. Thanks to decentralization the ledger is immutable.
Nov 2 security for blockchain and analytics ulf mattsson 2020 nov 2bUlf Mattsson
Blockchain
- What is Blockchain?
- Blockchain trends
Emerging data protection techniques
- Secure multiparty computation
- Trusted execution environments
- Use cases for analytics
- Industry Standards
Tokenization
- Convert a digital value into a digital token
- Tokenization local or in a centralized model
- Tokenization and scalability
Cloud
- Analytics in Hybrid cloud
Similar to Machine Learning and Blockchain by Director of Product at Target (20)
Webinar How PMs Use AI to 10X Their Productivity by Product School EiR.pdfProduct School
Explore AI tools hands-on and smoothly integrate them into your work routine. This practical experience is here to empower you, offering insights into the mindset of successful Product Managers. Learn the skills to become a more effective Product Manager.
Main Takeaways:
Hands-On AI Integration:
Learn practical strategies for integrating AI tools into your workflow effectively.
Mindset Insights for Success:
Gain valuable insights into the mindset of successful Product Managers, unlocking the secrets to their achievements.
Skill Empowerment for Growth:
Acquire essential skills that empower your evolution toward becoming a more effective and impactful Product Manager.
Webinar: Using GenAI for Increasing Productivity in PM by Amazon PM LeaderProduct School
In this webinar, you will learn how AI can take work off your plate, allowing you to focus on deep thinking or critical work. Cut out the drudge work in Product Management and get more out of your day.
Learnings:
Improve workflows that are high frequency - "manual tasks"
Increase the quality of output that has high importance - "brainy tasks"
Put GenAI to work today
Unlocking High-Performance Product Teams by former Meta Global PMMProduct School
Main Takeaways:
- High-Performing Team Dynamics: You’ll gain insights into fostering high-performance teamwork.
- Unveiling Team Personas: You’ll learn about different personas in the team and how to foster these differences.
- Decoding the Team Needs x Productivity Equation: You’ll learn about different team needs and how they correlate with engagement and productivity.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
PHP Frameworks: I want to break free (IPC Berlin 2024)Ralf Eggert
In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
Search and Society: Reimagining Information Access for Radical FuturesBhaskar Mitra
The field of Information retrieval (IR) is currently undergoing a transformative shift, at least partly due to the emerging applications of generative AI to information access. In this talk, we will deliberate on the sociotechnical implications of generative AI for information access. We will argue that there is both a critical necessity and an exciting opportunity for the IR community to re-center our research agendas on societal needs while dismantling the artificial separation between the work on fairness, accountability, transparency, and ethics in IR and the rest of IR research. Instead of adopting a reactionary strategy of trying to mitigate potential social harms from emerging technologies, the community should aim to proactively set the research agenda for the kinds of systems we should build inspired by diverse explicitly stated sociotechnical imaginaries. The sociotechnical imaginaries that underpin the design and development of information access technologies needs to be explicitly articulated, and we need to develop theories of change in context of these diverse perspectives. Our guiding future imaginaries must be informed by other academic fields, such as democratic theory and critical theory, and should be co-developed with social science scholars, legal scholars, civil rights and social justice activists, and artists, among others.
"Impact of front-end architecture on development cost", Viktor TurskyiFwdays
I have heard many times that architecture is not important for the front-end. Also, many times I have seen how developers implement features on the front-end just following the standard rules for a framework and think that this is enough to successfully launch the project, and then the project fails. How to prevent this and what approach to choose? I have launched dozens of complex projects and during the talk we will analyze which approaches have worked for me and which have not.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Essentials of Automations: Optimizing FME Workflows with Parameters
Machine Learning and Blockchain by Director of Product at Target
1. Machine Learning and Blockchain by Director
of Product at Target
www.productschool.com
2. Who said this?
2
Mark my words, AI is far more dangerous than nukes
On what he’s afraid of
“I’m really quite close to the cutting edge in AI and it scares the hell out of me. It’s capable of
vastly more than almost anyone knows. And the rate of improvement is exponential. ... We
have to figure out some way to ensure that the advent of digital superintelligence is one
which is symbiotic with humanity. I think that’s the single biggest existential crisis that we
face, and the most pressing one. ... Mark my words, AI is far more dangerous than nukes.”
5. Successful if we discuss
1. Introduction to AI
2. Types of AI
3. Introduction to Blockchain
4. Types of Blockchain
5
Goal: Provide a view on the intersection of AI & Blockchain
6. AI is not new - Why now?
6
Ref – McKinsey Co, MIT Lex Fridman, HBR,
1. Computing scale: CPU, GPU,
ASICs
1. Datasets and infrastructure to
handle big data
1. Amazon, Google, FB, MSFT
investing in platforms
8. 8
ARTIFICIAL INTELLIGENCE
The capability of a machine to imitate
intelligent human behavior
MACHINE LEARNING
1.Getting computers to learn or
recognize something without being
explicitly programmed
DEEP LEARNING
Type of ML that can process a wider
range of data resources, requires less
data preprocessing by humans
Let’s get on the same page
9. 9
Types of AI
MACHINE LEARNING
Supervised Learning
Unsupervised
Learning
Reinforcement
Learning
DEEP
LEARNING
Convolutional Neural
Network - CNN
Recurrent Neural Network -
RNN
10. 10
Types of ML: Unsupervised Learning Algorithms
DESCRIPTIVE
Look into the Past
PREDICTIVE
Understand the future
PRESCRIPTIVE
Advise on outcome
Unsupervised Algorithms Hierarchical clustering • K-Means
• Gaussian
• Hierarchical clustering
Recommender Systems
Use cases • Segment customers in
groups based on
characteristics such as
age, income, interests
• Cluster loyalty-card
customers into
microsegments
• Segment customers based on
latent preferences for
campaigns and promotions
• Segmentation based on
likelihood of employee
attrition
• Social media keyword based
clustering
• Movie, Items, News
recommendations
based on preferences
& interests
Ref – McKinse.comy, https://halobi.com/blog/descriptive-predictive-and-prescriptive-analytics-explained/
11. 11
DESCRIPTIVE AND PREDICTIVE ALGORITMS EXAMPLE USE CASES
• Linear regression • Price of a diamond by its shape, size, clarity etc.
• Understand factors contributing to product sales such as prices, advertisements..
• Optimize price points and estimate price elasticity.
• Logistic regression (Classification) • Classify diagnosis as benign or malignant
• Classify customers as will payback loan or default
• Linear quadratic / discriminant analysis • Client churn prediction
• Sale closing probability
• Decision tree (can be regression of classification
model)
• Understand salient product attributes contributing to purchase
• Provide decisioning framework for hiring / health questions
• Naïve Bayes (Classification based on probability) • Analyze sentiment to analyze product perception
• Create classifiers to filter spam
• Support Vector Machine (SVM) • Predict patients per hour
• Predict likelihood of ad clicks
• Random Forest • Predict call volume for staffing decisions
• Predict power usage in an electrical-distribution grid
• Adaboost • Detect credit card fraudulent activity
• Simple low cost image classification e.g. sat images for climate change)
• Gradient-boosting Trees • Forecast product demand and inventory levels
• Predict price of cards based on characteristics such as mileage
• Simple Neural Network • Predict a patient’s likelihood to join a healthcare program
• Predict conversion of trial users to paid users
Types of ML: Supervised Learning
Reference: https://www.mckinsey.com, https://halobi.com/blog/descriptive-predictive-and-prescriptive-analytics-explained/, wiki, Papers
12. 12
Types of ML: Reinforcement Learning
PRESCRIPTIVE USE CASES
Advise on outcome
Reinforcement Learning - algorithm receives
reinforcing rewards for its positive actions (e.g.
portfolio optimization)
• Optimization of trading strategy for options trading
• Stock and pick inventory – robotics
• Optimize real time pricing for an online auction
• Balance electricity load in grids based on demand cycles
• Optimize self-driving car behavior
• Optimize driving routes in cars
Ref – McKinse.comy, https://halobi.com/blog/descriptive-predictive-and-prescriptive-analytics-explained/
13. 13
Types of Deep Learning
USE CASES
Convolutional Neural Network
A multilayered neural network designed to extract
increasingly complex features of the data at each layer to
determine the output
Used to infer data from unstructured data e.g. images
Complex Image recognition for:
1. Medical Scans
2. Manufacturing defects
3. Website & video game image monitoring
4. Human sentiment / communication through images
5. Ariel image surveillance
Recurrent Neural Network
A multilayered neural network that can store information
in context nodes, allowing it to learn data sequences and
output a number or another sequence
Used for time series or sequences such as audio or text
Sequenced data uses such as:
1. Language translations
2. Chat bots
3. Aerial surveillance sequences with CNN
4. Narratives for reports (Narrative Sciences)
5. Communication tips & Captions
Ref – McKinse.comy, https://halobi.com/blog/descriptive-predictive-and-prescriptive-analytics-explained/
16. What is a Blockchain?
16
• A blockchain is a growing list of digital records or blocks that are secured and linked.
Each block contains
• Hash value link to the previous block
• timestamp and
• Data
• Genesis block by Satoshi Nakamoto (Bitcoin paper) – 3rd Jan 2009
“The Times 03/Jan/2009 Chancellor on brink of second bailout for banks“
• Eliminate the intermediaries
• Creates a decentralized system
17. 17
ABC’s TX
VERIFIED BLOCK
John TX
& more new Txs
Nonce
Prev block reference
/ Previous hash
Timestamp
Example Bitcoin Blocks
New TX 1
NEW BLOCK
New TX 2
& more new Txs
Nonce
Prev block reference
/ Previous hash
Timestamp
…...
18. Types of Blockchain
18
PERMISSIONLESS
PERMISSIONED
• Anyone can participate and validate a block
• Common validation method proof of work
• Restricted actors can validate a block
• Various methods of consensus are used e.g.
Byzanthine fault tolerance
19. 19
Blockchain Technology Platforms
BITCOIN ETHEREUM HYPERLEDGER R3 CORDA
Verification Proof of work
Data format:
Merkle tree (20
txs per sec)
Proof of work
Data format: Patricia
tree
Consensus based –
Modular & Extensible
Consensus with
Financial sector as
focus area
Permission State Permissionless
with basic
contracts
Permissionless with
smart contracts (e.g.
solidity)
Permissioned with
smart contracts (e.g.
Golang, Java)
Permissioned with
Smart contracts
(Kotlin, Java)
Smart Legal prose
Distributed Distributed
system with all
accounts equal
access
Distributed system
with all accounts
equal access
Distributed system
with role-based
restricted access
Microledgers semi-
distributed systems
with restricted access
Block creators External account External Account,
Contract account
Multiple roles such as
Validator or Transactor
Multiple roles
including Notary
Cryptocurrency Bitcoin currency Ether or other tokens
via smart contract
No currency (chaincode
tokens if required)
No currency
Ref – McKinse.comy, https://halobi.com/blog/descriptive-predictive-and-prescriptive-analytics-explained/
20. AI $37B market by 2025
20
* - 2012 – 2017 ; Ref: Venture beat,
$15 B* AI investments with $15 Trillion impact on GDP by 2030
Images: Intershala
Start ups
~$8B (2012-2016)
Auto Tech
Core AI
(Training data)
Healthcare
2 31
Big Corporations
~$6B (2013 - 2016)
Voice is the
new Text
AI Platform
Cloud
1
2
Vision & Image
recognition
3
Ford invested $1B in Argo self-driving AI tech
21. Blockchain Future
21
Identity, Hardware &
Platforms
• Identify Platforms
• Blockchain
standardization
Crypto devices & Apps (Crowd data)
• Crypto wallets, phones / ipads
• Open source apps for
crowdsourcing
• All your phone apps using
Blockchain such as Airbnb,
Facebook, Searches, Twitter type
applications in Blockchain with
token rewards.
AI application with smart contracts
• Finance protection contracts
• Document fraud detection
• iOT safety & security (Pollution
monitoring, Museum art)
• Medical AI contracts
• Autonomous cars
• Decentralized Organizations
(Common Education Standards, Bot
shares, Refugee crisis, weaponry)
5 10
Company Token Description
Singularity Net AGI Connect Siloed AI algorithms & decentralize (Ben Goertzal OpenCog)
Effects.ai Mar 24 - EFX 1st : Mechanical Turk, 2nd :AI Marketplace, 3rd: Compute share
Medrec Private Blockchain authenticated by medical researchers to store medical records
Loomia - Clothing panel tile that does Lighting, Heating, Sensing data to collect you money
22. 22
We will achieve technology singularity with ethics
Ref – http://blog.crisman.com image with edits, Business times, Guardian
The "Kuratas" robot in Tokyo, Nov. 2012. The military
robot can be controlled by a pilot or via a smartphone. It is
armed with a futuristic weapons system, including a multi-
rocket launcher.
Elon Musk & Deepmind’s Mustafa Suleyman leading a
group of 116 specialists from across 26 countries who are
calling for the ban on autonomous weapons. - 2014
27. Bitcoin protocol steps
Aarthi Srinivasan
27
Start: Broadcast new
transaction
Verification: User
Signature & funds
Proof-of-work:
Prevent double
spending
Mining: Earn
bitcoin rewards
Recheck
transactions &
start new block
1
2
34
5
Search Engine Account e.g. ABC wants users to use its search engine and will pay them 1 crypto unit(or some fraction of a bitcoin) as a
reward in return for using the search engine.
28. Key Terms
28
• A set of data used to predict relationships. Data and answers for each
sample.
• E.g. A diamond’s size, cut, color and clarity helps predicts the price.
Training Set
• Uses training set to make a prediction.
• E.g. Model predicts diamond prices based on past prices.Supervised Learning
• Provide data without suggesting anything so computer can identify patterns
or groupings.
• E.g. Customer segmentation, DNA groupings.
Unsupervised Learning
• Each distinct measurable data value you select in the training data set.
• E.g. A diamonds’ size is one of the feature’s for predicting price.
Features/ Variables /
Attributes
• Using the features provided in the training set make a prediction. Fit a curve
using the data provided.
• E.g. Price of diamond = X*Cut + Y*Clarity + Z*Size + other features…
Supervised: Regression
• A defined set of categories that can be labeled for placing new observations.
• E.g. Presence of absence of cancer; Types of diabetesSupervised: Classification
• Process of assigning observations into subsets.
• E.g. Customer segment creationsUnsupervised: Clustering
30. Voice will be the new Text
30
Google
• 11+ acquisitions
• ML Platform creation
• Vision / Image and Speech
recognition
• Business Process improvements
Apple
• 7+ acquisitions
• Vision / Image and Speech
recognition
• Catch up with Google on
platform creation (Turi)
Facebook
• Vision / Image and Speech
recognition
• Voice activation SDKs
Microsoft
• Voice enabled assistant
• Type ahead predictor
• Voice activation SDKs (AI
Fund)
31. 31
These companies market cap surpass the GDP of
India (previously Russia and Canada)
Reference – Scott Gallowa
32. Part-time Product Management Courses in
San Francisco, Silicon Valley, Los Angeles, New
York, Austin, Boston, Seattle, Chicago, Denver,
London, Toronto
www.productschool.com