IBM's Watson is a question answering computer system developed by IBM to answer questions posed in natural language. It was named after IBM's founder Thomas J. Watson and was initially created to compete on the game show Jeopardy! where it defeated human champions in 2011. Watson uses advanced natural language processing, semantic analysis, and machine learning to defeat human opponents. It is capable of answering complex questions with nuanced language and is being developed by IBM for commercial applications in fields like healthcare, finance and education.
IBM Watson overview presented by Mike Pointer, Watson Sr. Solution Architect, at Penn State's Nittany Watson Challenge Immersion event on January 19-20, 2017.
Conversational AI and Chatbot IntegrationsCristina Vidu
Conversational AI and Chatbots (or rather - and more extensively - Virtual Agents) offer great benefits, especially in combination with technologies like RPA or IDP. Corneliu Niculite (Presales Director - EMEA @DRUID AI) and Roman Tobler (CEO @Routinuum & UiPath MVP) are discussing Conversational AI and why Virtual Agents play a significant role in modern ways of working. Moreover, Corneliu will be displaying how to build a Workflow and showcase an Accounts Payable Use Case, integrating DRUID and UiPath Robots.
📙 Agenda:
The focus of our meetup is around the following areas - with a lot of room to discuss and share experiences:
- What is "Conversational AI" and why do we need Chatbots (Virtual Agents);
- Deep-Dive to a DRUID-UiPath Integration via an Accounts Payable Use Case;
- Discussion, Q&A
Speakers:
👨🏻💻 Corneliu Niculite, Presales Director - EMEA DRUID AI
👨🏼💻 Roman Tobler, UiPath MVP, Co-Founder & CEO Routinuum GmbH
This session streamed live on March 8, 2023, 16:00 PM CET.
Check out our upcoming events at: community.uipath.com
Contact us at: community@uipath.com
IBM Watson overview presented by Mike Pointer, Watson Sr. Solution Architect, at Penn State's Nittany Watson Challenge Immersion event on January 19-20, 2017.
Conversational AI and Chatbot IntegrationsCristina Vidu
Conversational AI and Chatbots (or rather - and more extensively - Virtual Agents) offer great benefits, especially in combination with technologies like RPA or IDP. Corneliu Niculite (Presales Director - EMEA @DRUID AI) and Roman Tobler (CEO @Routinuum & UiPath MVP) are discussing Conversational AI and why Virtual Agents play a significant role in modern ways of working. Moreover, Corneliu will be displaying how to build a Workflow and showcase an Accounts Payable Use Case, integrating DRUID and UiPath Robots.
📙 Agenda:
The focus of our meetup is around the following areas - with a lot of room to discuss and share experiences:
- What is "Conversational AI" and why do we need Chatbots (Virtual Agents);
- Deep-Dive to a DRUID-UiPath Integration via an Accounts Payable Use Case;
- Discussion, Q&A
Speakers:
👨🏻💻 Corneliu Niculite, Presales Director - EMEA DRUID AI
👨🏼💻 Roman Tobler, UiPath MVP, Co-Founder & CEO Routinuum GmbH
This session streamed live on March 8, 2023, 16:00 PM CET.
Check out our upcoming events at: community.uipath.com
Contact us at: community@uipath.com
Artificial intelligence is intelligence demonstrated by machines, as opposed to the natural intelligence displayed by animals including humans. It is a branch of computer science concerned with building machines capable of performing tasks that typically require human intelligence.
🔹How will AI-based content-generating tools change your mission and products?
🔹This complimentary webinar [ON-DEMAND] explores multiple use cases that drive adoption in their early adopter customer base to provide product leaders with insights into the future of generative AI-powered businesses, and the potential generative AI holds for driving innovation and improving business processes.
Slides from my 2023 Leadership Institute Talk on CSIRO's Our Future World Report, which identifies seven Global Megatrends which will influence society for the next two decades. With reference to work in digital solutions to help address these megatrends
A brief overview of artificial intelligence (AI), followed by a few examples of practical use within small businesses, large enterprises, and nonprofits.
Generative AI models, such as ChatGPT and Stable Diffusion, can create new and original content like text, images, video, audio, or other data from simple prompts, as well as handle complex dialogs and reason about problems with or without images. These models are disrupting traditional technologies, from search and content creation to automation and problem solving, and are fundamentally shaping the future user interface to computing devices. Generative AI can apply broadly across industries, providing significant enhancements for utility, productivity, and entertainment. As generative AI adoption grows at record-setting speeds and computing demands increase, on-device and hybrid processing are more important than ever. Just like traditional computing evolved from mainframes to today’s mix of cloud and edge devices, AI processing will be distributed between them for AI to scale and reach its full potential.
In this presentation you’ll learn about:
- Why on-device AI is key
- Full-stack AI optimizations to make on-device AI possible and efficient
- Advanced techniques like quantization, distillation, and speculative decoding
- How generative AI models can be run on device and examples of some running now
- Qualcomm Technologies’ role in scaling on-device generative AI
UiPath Community Event - UiPath Action Center and UiPath Apps - human in the ...TomaszGaczynski
Presentation for UiPath Community Event in Kuala Lumpur Chapter covering UiPath Action Center and UiPath Apps put together to automate human-in-the-loop processes. Presentation introduces UiPath Action Center and UiPath Apps, as well as shows you how you can build automation using both UiPath Automation platform modules.
Event video available: https://youtu.be/PjezuYATd4Q
Chat bot making process using Python 3 & TensorFlowJeongkyu Shin
Recently, chat bot has become the center of public attention as a new mobile user interface since 2015. Chat bots are widely used to reduce human-to-human interaction, from consultation to online shopping and negotiation, and still expanding the application coverage. Also, chat bot is the basic of conversational interface and non-physical input interface with combination of voice recognition.
Traditional chat bots were developed based on the natural language processing (NLP) and bayesian statistics for user intention recognition and template-based response. However, since 2012, accelerated advance in deep-learning technology and NLPs using deep-learning opened the possibilities to create chat bots with machine learning. Machine learning (ML)-based chat bot development has advantages, for instance, ML-based bots can generate (somewhat non-sense but acceptable) responses to random asks that has no connection with the context once the model is constructed with appropriate learning level.
In this talk, I will introduce the garage chat bot creation process step-by-step. I share the idea and implementations of multi-modal machine learning model with context engine and conversion engine. Also, how to implement Korean natural language processing, continuous conversion and tone manipulation is also discussed.
Chat bot (챗 봇)은 2015년부터 모바일을 중심으로 새로운 사용자 UI로 주목받고 있다. 챗 봇은 상담시 인간-인간 인터랙션을 줄이는 용도부터 온라인 쇼핑 구매에 이르기까지 다양한 분야에 활용되고 있으며 그 범위를 넓혀 나가고 있다. 챗 봇은 대화형 인터페이스의 기초이면서 동시에 (음성 인식과 결합을 통한) 무입력 방식 인터페이스의 기반 기술이기도 하다.
기존의 챗 봇들은 자연어 분석과 베이지안 통계에 기반한 사용자 의도 패턴 인식과 그에 따른 템플릿 응답을 기본 원리로 하여 개발되었다. 그러나 2012년 이후 급속도로 발전한 딥러닝 및 그에 기초한 자연어 인식 기술은 기계 학습을 이용해 챗 봇을 만들 수 있는 가능성을 열었다. 기계학습을 통해 챗 봇을 개발할 경우, 충분한 학습도의 모델을 구축한 후에는 학습 데이터에 따라 컨텍스트에서 벗어난 임의의 문장 입력에 대해서도 적당한 답을 생성할 수 있다는 장점이 있다.
이 발표에서는 Python 3 및 TensorFlow를 이용하여 딥러닝 기반의 챗 봇을 만들 경우에 경험하게 되는 문제점들 및 해결 방법을 다룬다. 봇의 컨텍스트 엔진과 대화 엔진간의 다형성 모델을 구현하고 연결하는 아이디어와 함께 자연어 처리 및 연속 대화 구현, 어법 처리 등을 어떻게 모델링할 수 있는 지에 대한 아이디어 및 구현과 팁을 공유하고자 한다.
AI is a scoring machine to automate data processing to get an inference.
Quality of the data defines the quality of the AI
Quality of feature engineering either does
No domain knowledge - no AI
Data Scientist works on data and models, to build an application Engineers and DevOps are required
In the real world a model will encounter a case it was never trained for. Continuous Retraining is a must.
Robotic Process Automation
Over the last few years, RPA (robotic process automation) has quickly become a transformative force across many industries. RPA uses software robots to manipulate and communicate with business systems and applications, streamlining processes and reducing the burden on human employees.
This our kick-off session for the RPA Summer School program. In this session we will provide you with the tools and information needed to go smoothly through our following 3 sessions. We will address the introduction into RPA and UiPath StudioX technology.
18:00 Hello & welcome to RPA Summer School
18:05 Introduction to RPA technology and processes
18:35 Introduction to UiPath StudioX: download, install, features
18:55 Small automation demo using StudioX
19:00 Interaction and Q&A
19:20 Academy follow-up and examples.
A.I based chatbot on healthcare and medical sciencePrashant Gupta
Hello friends , I am Prashant Gupta . I created a presentation on artificial intelligence based chatbot on healthcare and medical science . In this presentation i include all necessary points related chatbot .
If you like this presentation then please press like button, comment your feedback and share .
Thank you
AI and ML Series - Leveraging Generative AI and LLMs Using the UiPath Platfor...DianaGray10
📣 AI plays a crucial role in the UiPath Business Automation Platform. In this session you will learn about how the UiPath Business Automation Platform is well-suited for AI, the use of LLM and integrations you can use. Topics include the following:
Introductions.
AI powered automations overview.
Discover why the UiPath Business Automation Platform is well-suited for AI.
LLM + Automation framework and integrations with LangChain.
Generative AI Automation Patterns Demonstration.
👨🏽🤝👨🏻 Speakers:
Dhruv Patel, Senior Sales Solution Architect @UiPath
Russel Alfeche, Technology Leader, RPA @qBotica and UiPath MVP
Delve into this insightful article to explore the current state of generative AI, its ethical implications, and the power of generative AI models across various industries.
Presented at All Things Open RTP Meetup
Presented by Karthik Uppuluri, Fidelity
Title: Generative AI
Abstract: In this session, let us embark on a journey into the fascinating world of generative artificial intelligence. As an emergent and captivating branch of machine learning, generative AI has become instrumental in myriad of sectors, ranging from visual arts to creating software for technological solutions. This session requires no prior expertise in machine learning or AI. It aims to inculcate a robust understanding of fundamental concepts and principles of generative AI and its diverse applications. Join us as we delve into the mechanics of this transformative technology and unpack its potential.
UiPath REFramework Overview Developer Series - Part 1 of 4Diana Gray, MBA
What is the REFramework and why should it be used
Robotic Enterprise Framework is a project template based on State Machines. It's created to fit all the best practices regarding logging, exception handling, application initialization, and others, ready to tackle a complex business scenario.
In this session, we'll cover the following:
-Exception Planning
-Error Screenshots
-Logging
-Organize Project
Speaker: Chris Bolin, Senior Analyst/Finance Technology w/Mary Kay and UiPath MVP 2022
Artificial intelligence is intelligence demonstrated by machines, as opposed to the natural intelligence displayed by animals including humans. It is a branch of computer science concerned with building machines capable of performing tasks that typically require human intelligence.
🔹How will AI-based content-generating tools change your mission and products?
🔹This complimentary webinar [ON-DEMAND] explores multiple use cases that drive adoption in their early adopter customer base to provide product leaders with insights into the future of generative AI-powered businesses, and the potential generative AI holds for driving innovation and improving business processes.
Slides from my 2023 Leadership Institute Talk on CSIRO's Our Future World Report, which identifies seven Global Megatrends which will influence society for the next two decades. With reference to work in digital solutions to help address these megatrends
A brief overview of artificial intelligence (AI), followed by a few examples of practical use within small businesses, large enterprises, and nonprofits.
Generative AI models, such as ChatGPT and Stable Diffusion, can create new and original content like text, images, video, audio, or other data from simple prompts, as well as handle complex dialogs and reason about problems with or without images. These models are disrupting traditional technologies, from search and content creation to automation and problem solving, and are fundamentally shaping the future user interface to computing devices. Generative AI can apply broadly across industries, providing significant enhancements for utility, productivity, and entertainment. As generative AI adoption grows at record-setting speeds and computing demands increase, on-device and hybrid processing are more important than ever. Just like traditional computing evolved from mainframes to today’s mix of cloud and edge devices, AI processing will be distributed between them for AI to scale and reach its full potential.
In this presentation you’ll learn about:
- Why on-device AI is key
- Full-stack AI optimizations to make on-device AI possible and efficient
- Advanced techniques like quantization, distillation, and speculative decoding
- How generative AI models can be run on device and examples of some running now
- Qualcomm Technologies’ role in scaling on-device generative AI
UiPath Community Event - UiPath Action Center and UiPath Apps - human in the ...TomaszGaczynski
Presentation for UiPath Community Event in Kuala Lumpur Chapter covering UiPath Action Center and UiPath Apps put together to automate human-in-the-loop processes. Presentation introduces UiPath Action Center and UiPath Apps, as well as shows you how you can build automation using both UiPath Automation platform modules.
Event video available: https://youtu.be/PjezuYATd4Q
Chat bot making process using Python 3 & TensorFlowJeongkyu Shin
Recently, chat bot has become the center of public attention as a new mobile user interface since 2015. Chat bots are widely used to reduce human-to-human interaction, from consultation to online shopping and negotiation, and still expanding the application coverage. Also, chat bot is the basic of conversational interface and non-physical input interface with combination of voice recognition.
Traditional chat bots were developed based on the natural language processing (NLP) and bayesian statistics for user intention recognition and template-based response. However, since 2012, accelerated advance in deep-learning technology and NLPs using deep-learning opened the possibilities to create chat bots with machine learning. Machine learning (ML)-based chat bot development has advantages, for instance, ML-based bots can generate (somewhat non-sense but acceptable) responses to random asks that has no connection with the context once the model is constructed with appropriate learning level.
In this talk, I will introduce the garage chat bot creation process step-by-step. I share the idea and implementations of multi-modal machine learning model with context engine and conversion engine. Also, how to implement Korean natural language processing, continuous conversion and tone manipulation is also discussed.
Chat bot (챗 봇)은 2015년부터 모바일을 중심으로 새로운 사용자 UI로 주목받고 있다. 챗 봇은 상담시 인간-인간 인터랙션을 줄이는 용도부터 온라인 쇼핑 구매에 이르기까지 다양한 분야에 활용되고 있으며 그 범위를 넓혀 나가고 있다. 챗 봇은 대화형 인터페이스의 기초이면서 동시에 (음성 인식과 결합을 통한) 무입력 방식 인터페이스의 기반 기술이기도 하다.
기존의 챗 봇들은 자연어 분석과 베이지안 통계에 기반한 사용자 의도 패턴 인식과 그에 따른 템플릿 응답을 기본 원리로 하여 개발되었다. 그러나 2012년 이후 급속도로 발전한 딥러닝 및 그에 기초한 자연어 인식 기술은 기계 학습을 이용해 챗 봇을 만들 수 있는 가능성을 열었다. 기계학습을 통해 챗 봇을 개발할 경우, 충분한 학습도의 모델을 구축한 후에는 학습 데이터에 따라 컨텍스트에서 벗어난 임의의 문장 입력에 대해서도 적당한 답을 생성할 수 있다는 장점이 있다.
이 발표에서는 Python 3 및 TensorFlow를 이용하여 딥러닝 기반의 챗 봇을 만들 경우에 경험하게 되는 문제점들 및 해결 방법을 다룬다. 봇의 컨텍스트 엔진과 대화 엔진간의 다형성 모델을 구현하고 연결하는 아이디어와 함께 자연어 처리 및 연속 대화 구현, 어법 처리 등을 어떻게 모델링할 수 있는 지에 대한 아이디어 및 구현과 팁을 공유하고자 한다.
AI is a scoring machine to automate data processing to get an inference.
Quality of the data defines the quality of the AI
Quality of feature engineering either does
No domain knowledge - no AI
Data Scientist works on data and models, to build an application Engineers and DevOps are required
In the real world a model will encounter a case it was never trained for. Continuous Retraining is a must.
Robotic Process Automation
Over the last few years, RPA (robotic process automation) has quickly become a transformative force across many industries. RPA uses software robots to manipulate and communicate with business systems and applications, streamlining processes and reducing the burden on human employees.
This our kick-off session for the RPA Summer School program. In this session we will provide you with the tools and information needed to go smoothly through our following 3 sessions. We will address the introduction into RPA and UiPath StudioX technology.
18:00 Hello & welcome to RPA Summer School
18:05 Introduction to RPA technology and processes
18:35 Introduction to UiPath StudioX: download, install, features
18:55 Small automation demo using StudioX
19:00 Interaction and Q&A
19:20 Academy follow-up and examples.
A.I based chatbot on healthcare and medical sciencePrashant Gupta
Hello friends , I am Prashant Gupta . I created a presentation on artificial intelligence based chatbot on healthcare and medical science . In this presentation i include all necessary points related chatbot .
If you like this presentation then please press like button, comment your feedback and share .
Thank you
AI and ML Series - Leveraging Generative AI and LLMs Using the UiPath Platfor...DianaGray10
📣 AI plays a crucial role in the UiPath Business Automation Platform. In this session you will learn about how the UiPath Business Automation Platform is well-suited for AI, the use of LLM and integrations you can use. Topics include the following:
Introductions.
AI powered automations overview.
Discover why the UiPath Business Automation Platform is well-suited for AI.
LLM + Automation framework and integrations with LangChain.
Generative AI Automation Patterns Demonstration.
👨🏽🤝👨🏻 Speakers:
Dhruv Patel, Senior Sales Solution Architect @UiPath
Russel Alfeche, Technology Leader, RPA @qBotica and UiPath MVP
Delve into this insightful article to explore the current state of generative AI, its ethical implications, and the power of generative AI models across various industries.
Presented at All Things Open RTP Meetup
Presented by Karthik Uppuluri, Fidelity
Title: Generative AI
Abstract: In this session, let us embark on a journey into the fascinating world of generative artificial intelligence. As an emergent and captivating branch of machine learning, generative AI has become instrumental in myriad of sectors, ranging from visual arts to creating software for technological solutions. This session requires no prior expertise in machine learning or AI. It aims to inculcate a robust understanding of fundamental concepts and principles of generative AI and its diverse applications. Join us as we delve into the mechanics of this transformative technology and unpack its potential.
UiPath REFramework Overview Developer Series - Part 1 of 4Diana Gray, MBA
What is the REFramework and why should it be used
Robotic Enterprise Framework is a project template based on State Machines. It's created to fit all the best practices regarding logging, exception handling, application initialization, and others, ready to tackle a complex business scenario.
In this session, we'll cover the following:
-Exception Planning
-Error Screenshots
-Logging
-Organize Project
Speaker: Chris Bolin, Senior Analyst/Finance Technology w/Mary Kay and UiPath MVP 2022
This deck covers the new IBM Voice Gateway product which introduces a next generate IVR system that is conversational and built on IBM Watson cognitive services. It can also transcribe calls in real time to enable agent assist type applications. Use capabilities like the Watson Conversation service, Speech To Text and Text To Speech, the IBM Voice Gateway is built on cloud native principles.
Introduction•Super Computer developed by IBM Research•Named for .pdfanupambedcovers
Introduction
•Super Computer developed by IBM Research
•Named for IMB’s founder: Thomas J. Watson
•Initially created for Jeopardy! Game Show
Dr. David Ferrucci leads the Watson project
Development
•Search engines deliver thousands of results that match keywords
•University’s have worked on a consistent question answering software for years
•Programmed by 25 IBM scientists
Not connected to the internet
Jeopardy! Challenge
•Set out to answer complex Jeopardy! Questions
•Language is hard for computers because of “intended meaning”
•During trials, it won 70% of practice games
•February 2011: First computer to compete against humans in Jeopardy!
•Defeated shows greatest two champions Ken Jennings and Brad Rutter
Purpose of Watson
•Idea formed during IBM top executives brainstorming publicity stunts
•DeepBlue– chess supercomputer defeated Garry Kasparov
•IBM’s previous most advanced machine was slow and inaccurate
•Overall goal: “to create a new generation of technology that can find answers from data more
effectively than current search engines”
Technology
•Question-answering Technology
•Deep understanding of natural language.
–Process and answer complex questions that have puns, irony, and/or riddles
•Computer running Software called Deep QA
•Runs on cluster of Power 750 computers
–ten racks holding 90 servers, for a total of 2880 processor cores running DeepQA software and
storage
–Holds approximately one million books worth of information
Managerial Purposes
•Financial Assistant: Working with Citi Bank
–Help analyze customer needs
–Process financial, economic, product, and client data
–Help financial professionals make better decision
•Could IBM Watson rival complex derivatives on the trade floor?
Other Possibilities?
•Travel
•Retail
•Healthcare
Classroom
Advantages
•Provides Services that revolve around the new, digital world
•Gives immediate answers instead of search results
•Healthcare uses
–Diagnosis
–Information Warehouse
•Efficiency and Organization
Disadvantages
•Cannot read PET and CT scans to identify tumors
•Questions asked must be in text
•Less human effort
–Too reliant upon technology
–Less personal interaction between doctors and patients
•Not cognitive
–Only manipulates symbols
•Limits understanding and reasoning behind decisions
Competition
•Thus far there are no other computers that are near the performance level of Watson
•Microsoft and GE announced plans to create something similar to use in the healthcare industry
–Aim to use analytics, high performance software technologies to deliver patient outcomes and
clinical applications
Applications to SIT
•New technology for a business’ Decision Making Processes
–Organizational structure may shift based on allocation of decision making
•Potentially eliminates the needs/advantages of Virtual Teams (especially in healthcare)
•Changes Knowledge Management Processes
Solution
Introduction
•Super Computer developed by IBM Research
•Named for IMB’s founder: Thomas J. Watson
•Initially creat.
[DSC Europe 22] On the Aspects of Artificial Intelligence and Robotic Autonom...DataScienceConferenc1
Autonomy in targeting is a function that could be applied to any intelligent system, in particular the rapidly expanding array of robotic systems, in the air, on land and at sea – including swarms of small robots. This is an area of significant investment and emphasis for many armed forces, and the question is not so much whether we will see more intelligent robots, but whether and by what means they will remain under human control. Today’s remote-controlled weapons could become tomorrow’s autonomous weapons with just a software upgrade. The central element of any future autonomous weapon system will be the software. Military powers are investing in AI for a wide range of applications10 and significant efforts are already underway to harness developments in image, facial and behavior recognition using AI and machine learning techniques for intelligence gathering and “automatic target recognition” to identify people, objects or patterns. Although not all autonomous weapon systems incorporate AI and machine learning, this software could form the basis of future autonomous weapon systems.
Big Data and Artificial Intelligence: Game ChangerDavid Asirvatham
Introduces the role of Big Data and AI in the transformation of jobs. It will provide an overview of the skills needed by students if they are seeking for jobs in the area of Big Data and AI.
Intro to Artificial Intelligence w/ Target's Director of PMProduct School
Given that Machine Learning (ML) is on every product enthusiast’s mind, this talk gave a broad view of the investment landscape for future innovation. Director of Product Management at Target, Aarthi Srinivasan, talked about macro AI themes & trends, how you can build your AI team and how to create a ML backed product vision.
Additionally, this talk armed the attendees with enough information to create your Point of View (POV) on how to incorporate AI into your business.
It has been said that Mobiles +Cloud + Social + Big Data = Better Run The World. IBM has invested over $20 billion since 2005 to grow its analytics business, many companies will invest more than $120 billion by 2015 on analytics, hardware, software and services critical in almost every industry like ; Healthcare, media, sports, finance, government, etc.
It has been estimated that there is a shortage of 140,000 – 190,000 people with deep analytical skills to fill the demand of jobs in the U.S. by 2018.
Decoding the human genome originally took 10 years to process; now it can be achieved in one week with the power of Analytic and BI (Business Intelligence). This lecture’s Key Messages is that Analytics provide a competitive edge to individuals , companies and institutions and that Analytics and BI are often critical to the success of any organization.
Methodology used is to teach analytic techniques through real world examples and real data with this goal to convince audience of the Analytics Edge and power of BI, and inspire them to use analytics and BI in their career and their life.
If You Are Not Embedding Analytics Into Your Day To Day Processes, You Are Do...Dell World
Becoming data-driven requires analytics to be embedded throughout the organization in different functional areas and different operational processes. But how do you provide more and more people with the ability to run any analytics on any data anywhere– without breaking the bank? In this session, you’ll see real-world examples of Dell customers who have successfully embedded analytics across processes and operations to drive innovation.We will also demonstrate how embedding analytics enables faster innovation and improves collaboration between data scientists, business analysts, and business stakeholders, leading to a competitive advantage.
Once you’ve made the decision to leverage AI and/or machine learning, now you need to figure out how you will source the training data that is necessary for a fully functioning algorithm. Depending on your use case, you might need a significant amount of training data, and you’ll want to consider how that is labeled and annotated too.
View Applause's webinar with Cognilytica principal analysts Ronald Schmelzer and Kathleen Walch, alongside Kristin Simonini, Applause’s Vice President of Product, as they tackle the modern challenges that today’s companies face with sourcing training data.
There is a good chance that you have heard of artificial intelligence, machine learning, blockchain and bots. However, do you know what the implications of each of these technologies are? How it can and will impact your business in the near future? In this talk, we will discuss these technological trends, as well as a few others, that you will need to be familiar with as your association prepares to compete over the next few years. Let's take a peek into the future that is already here!
Companies that understand how to apply AI will scale and win their respective markets over the next decade. That said, delivering on this promise and managing machine learning projects is much harder than most people anticpate. Many organizations hire teams of PhDs and data scientists, then fail to ship products that move business metrics. The root cause is often a lack of product strategy for AI, or the failure to adapt their product development processes to the needs of machine learning systems. This talk will cover some of the common ways machine learning fails in practice, the tactical responsibilities of AI product managers, and how to approach product strategy for AI.
Peter Skomoroch, former Head of Data Products at Workday and LinkedIn, will describe how you can navigate these challenges to ship metric moving AI products that matter to your business.
Peter will provide practical advice on:
* The role of an AI Product Manager
* How to evaluate and prioritize your AI projects
* The ways AI product management differs from traditional product management
* Bridging the worlds of design and machine learning
* Making trade offs between data quality and other business metrics
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
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
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
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.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
2. Introduction
• Super Computer developed by IBM Research
• Named for IMB’s founder: Thomas J. Watson
• Initially created for Jeopardy! Game Show
• Dr. David Ferrucci leads the Watson project
3. Development
• Search engines deliver thousands of results that
match keywords
• University’s have worked on a consistent question
answering software for years
• Programmed by 25 IBM scientists
• Not connected to the internet
4. Jeopardy! Challenge
• Set out to answer complex Jeopardy!
Questions
• Language is hard for computers because of
“intended meaning”
• During trials, it won 70% of practice games
5. Jeopardy! Challenge
• February 2011: First computer to compete against humans
in Jeopardy!
• Defeated shows greatest two champions Ken Jennings and
Brad Rutter
6. Could YOU beat Watson?
http://www.youtube.com/watch?v=qpKoIfTu
krA&feature=related
7. Purpose of Watson
• Idea formed during IBM top executives
brainstorming publicity stunts
• Deep Blue– chess supercomputer defeated Garry
Kasparov
• IBM’s previous most advanced machine was slow
and inaccurate
• Overall goal: “to create a new generation of
technology that can find answers from data more
effectively than current search engines”
8. Technology
• Question-answering Technology
• Deep understanding of natural language.
– Process and answer complex questions
that have puns, irony, and/or riddles
9.
10. Technology
• Computer running Software called Deep QA
• Runs on cluster of Power 750 computers
– ten racks holding 90 servers, for a total of 2880
processor cores running DeepQA software and
storage
– Holds approximately one million books worth of
information
19. Words from John Kelly, Director of IBM Research:
“I want to create something that I can
take into every other retail industry, in
the transportation industry, you name
it.”
“Any place where time is critical and you need to
get advanced state-of-the-art information to the
front decision-makers. Computers need to go
from just being back-office calculating machines
to improving the intelligence of people making
decisions.”
20. Beyond Jeopardy
• Medical Assistant: Memorial Sloan Kettering
Cancer Center Partnership (March 2012)
– Clinicians will “teach” Watson to review
oncological case histories and come up with
best diagnosis and treatment
21.
22. Managerial Purposes
• Financial Assistant: Working with Citi Bank
– Help analyze customer needs
– Process financial, economic, product, and client
data
– Help financial professionals make better decision
• Could IBM Watson rival complex derivatives on the
trade floor?
24. Advantages
• Provides Services that revolve around the
new, digital world
• Gives immediate answers instead of
search results
• Healthcare uses
– Diagnosis
– Information Warehouse
• Efficiency and Organization
25. Disadvantages
• Cannot read PET and CT scans to identify tumors
• Questions asked must be in text
• Less human effort
– Too reliant upon technology
– Less personal interaction between doctors and
patients
• Not cognitive
– Only manipulates symbols
• Limits understanding and reasoning behind decisions
26. Competition
• Thus far there are no other computers that are near the
performance level of Watson
• Microsoft and GE announced plans to create something
similar to use in the healthcare industry
– Aim to use analytics, high performance software
technologies to deliver patient outcomes and clinical
applications
27. Applications to SIT
• New technology for a business’ Decision Making
Processes
– Organizational structure may shift based on
allocation of decision making
• Potentially eliminates the needs/advantages of
Virtual Teams (especially in healthcare)
• Changes Knowledge Management Processes
28. Discussion Question #1
• What do you think about the future of
this product, and the potential to have a
super computer with voice recognition
software? Could this lead to an
iRobot/personal assistant?
30. Discussion Question #3
• If you were a manager at a business, would you
trust using Watson with decision making, or do you
feel human decision making still is a more reliable
source?
