Amazon Mechanical Turk is a new Web service that allows .NET software developers to incorporate the power of human decision-making into their automated software systems
I composed this brief introduction to Amazon's crowdsourcing tool, Mechanical Turk (AMT), at the request of a professor who advocates AMT for marketing research.
Amazon Mechanical Turk (https://requester.mturk.com), a crowdsourcing marketplace, adds value by processing work that cannot be computerized.
Typically, these include large-scale [data] projects - think Amazon.com's 500MM product database - which requires some form of human judgment to help digitize, validate, moderate, tag, cleanse, categorize, dedupe, etc...This is accomplished by breaking down the project into micro-tasks, distributing to qualified cloud-based workers, who then deliver the results.
Slides presented at the Mechanical Turk Office Hours on January 20, 2011.
Video of the presentation can be found on the Mechanical Turk blog:
http://mechanicalturk.typepad.com
I composed this brief introduction to Amazon's crowdsourcing tool, Mechanical Turk (AMT), at the request of a professor who advocates AMT for marketing research.
Amazon Mechanical Turk (https://requester.mturk.com), a crowdsourcing marketplace, adds value by processing work that cannot be computerized.
Typically, these include large-scale [data] projects - think Amazon.com's 500MM product database - which requires some form of human judgment to help digitize, validate, moderate, tag, cleanse, categorize, dedupe, etc...This is accomplished by breaking down the project into micro-tasks, distributing to qualified cloud-based workers, who then deliver the results.
Slides presented at the Mechanical Turk Office Hours on January 20, 2011.
Video of the presentation can be found on the Mechanical Turk blog:
http://mechanicalturk.typepad.com
The Internet-of-Things provides us with lots of sensor data. However, the data by themselves do not provide value unless we can turn them into actionable, contextualized information. Big data and data visualization techniques allow us to gain new insights by batch-processing and off-line analysis. Real-time sensor data analysis and decision-making is often done manually but to make it scalable, it is preferably automated. Artificial Intelligence provides us the framework and tools to go beyond trivial real-time decision and automation use cases for IoT.
Why the Internet of Things needs AI & interoperability to succeedNuance Communications
Gartner predicts 5.5 million new ‘things’ will be connected everyday this year. The challenge: non-intuitive interfaces, disconnected systems, and incompatible APIs mean we’ve not yet been able to unleash the greatest potential of this IoT-connected devices ecosystem. That’s why we need to innovate with interoperability in mind.
Artificial Intelligence has the potential to change human work and productivity at a magnitude comparable to the industrialisation. This change is incremental rather than revolutionary.
An Overview of AI on the AWS Platform - February 2017 Online Tech TalksAmazon Web Services
AWS offers a family of intelligent services that provide cloud-native machine learning and deep learning technologies to address your different use cases and needs. For developers looking to add managed AI services to their applications, AWS brings natural language understanding (NLU) and automatic speech recognition (ASR) with Amazon Lex, visual search and image recognition with Amazon Rekognition, text-to-speech (TTS) with Amazon Polly, and developer-focused machine learning with Amazon Machine Learning.
For more in-depth deep learning applications, the AWS Deep Learning AMI lets you run deep learning in the cloud, at any scale. Launch instances of the AMI, pre-installed with open source deep learning engines (Apache MXNet, TensorFlow, Caffe, Theano, Torch and Keras), to train sophisticated, custom AI models, experiment with new algorithms, and learn new deep learning skills and techniques; all backed by auto-scaling clusters of GPU-based instances.
Whether you’re just getting started with AI or you’re a deep learning expert, this session will provide a meaningful overview of how to improve scale and efficiency with the AWS Cloud.
Learning Objectives
• Learn about the breadth of AI services available on the AWS Cloud
• Gain insight into practical use cases for Amazon Lex, Amazon Polly, and Amazon Rekognition
• Understand why Amazon has selected MXNet as its deep learning framework of choice due its programmability, portability, and performance
New Artificial Intelligence and IoT Services (Lex, Polly, Rekognition, Greeng...Amazon Web Services
This talk will recap new AI and IoT services announced or released at re:Invent. In the AI space, Gavin will cover Lex, the same deep learning engine that power Alexa; Polly, a service that turns text into lifelike speech; and Rekognition, a service that makes it easy to add image analysis to your applications. For IoT, he will cover Greengrass, which is software that lets you run local compute, messaging and data caching for connected devices. Also covered will be the 2nd generation AWS IoT Button, and Enterprise Program.
The ppt Sujoy and I made for the Psi Phi ( An Inter School Competition held by our School). Our Topic was Artificial Intelligence.
Credits:
Theme Images from ESET NOD32 (My Antivirus of Choice)
Backgrounds from SwimChick.net (Amazing designs here)
Credits Image from Full Metal Alchemist (One of my favorite Anime).
Boost Customer Experience with UiPath and AWS Contact Center automationCristina Vidu
This session is for users that want to integrate AWS contact center capabilities with UiPath, both to learn the art of the possible and to implement immediately. Users will learn about currently available activity packs and integrations on both the AWS and UiPath sides, hearing directly from experts from each company.
In this session you will hear from UiPath and AWS experts on:
Using the Amazon Connect Native Integration activity pack and setting up a practical example
Setting up authentication and initial configuration on both the UiPath and AWS side
Triggering a UiPath job based on input received using both the Activity Pack and Connector
Setting up a simple solution incorporating Amazon Comprehend
Practical examples of additional workflow actions integrated with both Connect, Comprehend, and other CCI capabilities
Prioritizing and selecting critical use cases to improve self-service and agent assistance
Speakers:
Mo Roy, Sales Engineer @UiPath
Meena Thandavarayan, AI/ML Partner Solutions Architect, Amazon Web Services (AWS)
Boost Customer Experience with UiPath & AWS Contact Center AutomationDiana Gray, MBA
This session is for users that want to integrate AWS contact center capabilities with UiPath, both to learn the art of the possible and to implement immediately. Users will learn about currently available activity packs and integrations on both the AWS and UiPath sides, hearing directly from experts from each company.
In this session you will hear from UiPath and AWS experts on:
Using the Amazon Connect Native Integration activity pack and setting up a practical example
Setting up authentication and initial configuration on both the UiPath and AWS side
Triggering a UiPath job based on input received using both the Activity Pack and Connector
Setting up a simple solution incorporating Amazon Comprehend
Practical examples of additional workflow actions integrated with both Connect, Comprehend, and other CCI capabilities
Prioritizing and selecting critical use cases to improve self-service and agent assistance
The Internet-of-Things provides us with lots of sensor data. However, the data by themselves do not provide value unless we can turn them into actionable, contextualized information. Big data and data visualization techniques allow us to gain new insights by batch-processing and off-line analysis. Real-time sensor data analysis and decision-making is often done manually but to make it scalable, it is preferably automated. Artificial Intelligence provides us the framework and tools to go beyond trivial real-time decision and automation use cases for IoT.
Why the Internet of Things needs AI & interoperability to succeedNuance Communications
Gartner predicts 5.5 million new ‘things’ will be connected everyday this year. The challenge: non-intuitive interfaces, disconnected systems, and incompatible APIs mean we’ve not yet been able to unleash the greatest potential of this IoT-connected devices ecosystem. That’s why we need to innovate with interoperability in mind.
Artificial Intelligence has the potential to change human work and productivity at a magnitude comparable to the industrialisation. This change is incremental rather than revolutionary.
An Overview of AI on the AWS Platform - February 2017 Online Tech TalksAmazon Web Services
AWS offers a family of intelligent services that provide cloud-native machine learning and deep learning technologies to address your different use cases and needs. For developers looking to add managed AI services to their applications, AWS brings natural language understanding (NLU) and automatic speech recognition (ASR) with Amazon Lex, visual search and image recognition with Amazon Rekognition, text-to-speech (TTS) with Amazon Polly, and developer-focused machine learning with Amazon Machine Learning.
For more in-depth deep learning applications, the AWS Deep Learning AMI lets you run deep learning in the cloud, at any scale. Launch instances of the AMI, pre-installed with open source deep learning engines (Apache MXNet, TensorFlow, Caffe, Theano, Torch and Keras), to train sophisticated, custom AI models, experiment with new algorithms, and learn new deep learning skills and techniques; all backed by auto-scaling clusters of GPU-based instances.
Whether you’re just getting started with AI or you’re a deep learning expert, this session will provide a meaningful overview of how to improve scale and efficiency with the AWS Cloud.
Learning Objectives
• Learn about the breadth of AI services available on the AWS Cloud
• Gain insight into practical use cases for Amazon Lex, Amazon Polly, and Amazon Rekognition
• Understand why Amazon has selected MXNet as its deep learning framework of choice due its programmability, portability, and performance
New Artificial Intelligence and IoT Services (Lex, Polly, Rekognition, Greeng...Amazon Web Services
This talk will recap new AI and IoT services announced or released at re:Invent. In the AI space, Gavin will cover Lex, the same deep learning engine that power Alexa; Polly, a service that turns text into lifelike speech; and Rekognition, a service that makes it easy to add image analysis to your applications. For IoT, he will cover Greengrass, which is software that lets you run local compute, messaging and data caching for connected devices. Also covered will be the 2nd generation AWS IoT Button, and Enterprise Program.
The ppt Sujoy and I made for the Psi Phi ( An Inter School Competition held by our School). Our Topic was Artificial Intelligence.
Credits:
Theme Images from ESET NOD32 (My Antivirus of Choice)
Backgrounds from SwimChick.net (Amazing designs here)
Credits Image from Full Metal Alchemist (One of my favorite Anime).
Boost Customer Experience with UiPath and AWS Contact Center automationCristina Vidu
This session is for users that want to integrate AWS contact center capabilities with UiPath, both to learn the art of the possible and to implement immediately. Users will learn about currently available activity packs and integrations on both the AWS and UiPath sides, hearing directly from experts from each company.
In this session you will hear from UiPath and AWS experts on:
Using the Amazon Connect Native Integration activity pack and setting up a practical example
Setting up authentication and initial configuration on both the UiPath and AWS side
Triggering a UiPath job based on input received using both the Activity Pack and Connector
Setting up a simple solution incorporating Amazon Comprehend
Practical examples of additional workflow actions integrated with both Connect, Comprehend, and other CCI capabilities
Prioritizing and selecting critical use cases to improve self-service and agent assistance
Speakers:
Mo Roy, Sales Engineer @UiPath
Meena Thandavarayan, AI/ML Partner Solutions Architect, Amazon Web Services (AWS)
Boost Customer Experience with UiPath & AWS Contact Center AutomationDiana Gray, MBA
This session is for users that want to integrate AWS contact center capabilities with UiPath, both to learn the art of the possible and to implement immediately. Users will learn about currently available activity packs and integrations on both the AWS and UiPath sides, hearing directly from experts from each company.
In this session you will hear from UiPath and AWS experts on:
Using the Amazon Connect Native Integration activity pack and setting up a practical example
Setting up authentication and initial configuration on both the UiPath and AWS side
Triggering a UiPath job based on input received using both the Activity Pack and Connector
Setting up a simple solution incorporating Amazon Comprehend
Practical examples of additional workflow actions integrated with both Connect, Comprehend, and other CCI capabilities
Prioritizing and selecting critical use cases to improve self-service and agent assistance
Boost Customer Experience with UiPath & AWS Contact Center AutomationDiana Gray, MBA
This session is for users that want to integrate AWS contact center capabilities with UiPath, both to learn the art of the possible and to implement immediately. Users will learn about currently available activity packs and integrations on both the AWS and UiPath sides, hearing directly from experts from each company.
In this session you will hear from UiPath and AWS experts on:
Using the Amazon Connect Native Integration activity pack and setting up a practical example
Setting up authentication and initial configuration on both the UiPath and AWS side
Triggering a UiPath job based on input received using both the Activity Pack and Connector
Setting up a simple solution incorporating Amazon Comprehend
Practical examples of additional workflow actions integrated with both Connect, Comprehend, and other CCI capabilities
Prioritizing and selecting critical use cases to improve self-service and agent assistance
Apidays Singapore 2024 - APIs in the world of Generative AI by Claudio Tag, IBMapidays
APIs in the world of Generative AI
Claudio Tag, Chief Architect – IBM Automation – APAC - IBM
Apidays Singapore 2024: Connecting Customers, Business and Technology (April 17 & 18, 2024)
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Check out our conferences at https://www.apidays.global/
Do you want to sponsor or talk at one of our conferences?
https://apidays.typeform.com/to/ILJeAaV8
Learn more on APIscene, the global media made by the community for the community:
https://www.apiscene.io
Explore the API ecosystem with the API Landscape:
https://apilandscape.apiscene.io/
"APIs: the Glue of Cloud Computing"
CloudExpo Europe Keynote - June 22, 2010
The second day of the CloudExpo Europe that was taking place in Prague the 21st and 22nd of June, Steven Willmott, the CEO of 3scale, made a presentation on APIs and their importance for Cloud Computing.
The key highlights of this presentation are:
1. Cloud Computing pushes to the “hyper integration” of the Web and the enabling of key platform to emerge (e.g. the new SkypeKit)…. But not only for computing power
2. Cloud Computing and its different elements fit into an MVC “Cloud Edition” framework thanks to APIs
3. APIs enable Cloud Scale MVC
4. You need to become indispensable in the Value Chain otherwise someone may eat your lunch
5. APIs are key to become indispensable but need to be managed
Amazon subsidiary Alexa.com is leveling the search playing field. For the first time, developers looking to build the next "big thing" in search or an ultra custom search engine have access to the 300 terabytes of Alexa crawl data, along with the utilities to search, process, and publish their own custom subset of the data-all at a reasonable price.
Bridging the Gap Between Real Time/Offline and AI/ML Capabilities in Modern S...Amazon Web Services
Building real-time collaboration applications can be difficult, and adding intelligence to an app to make it stand out remains a challenge. In this session, learn how to build real-time chat serverless apps infused with AWS machine learning (ML) services. We dive into enhancing a real-time chat application with search capabilities, chatroom bots providing automated responses , and on-demand message translation using Amazon AI/ML services.
Creating a World-Class RESTful Web Services APIDavid Keener
Companies like Amazon, Google and Yahoo have published web services API's that empower developers to create mash-ups, add-ons and full-scale applications. The creation of such API's, however, is not exclusively the domain of large, multi-national corporations. Learn how to architect, build and field a well-designed and scalable RESTful web services API that will allow your business to leverage the capabilities of the developer community. This presentation includes real-life examples from the Grab Networks RESTful API, which provides access to information about the hundreds of thousands of news videos available through Grab Networks' distribution network.
Whitepaper: Volume Testing Thick Clients and DatabasesRTTS
Even in the current age of cloud computing there are still endless benefits of developing thick client software: non-dependency on browser version, offline support, low hosting fees, and utilizing existing end user hardware, to name a few.
It's more than likely that your organization is utilizing at least a few thick client applications. Now consider this: as your user base grows, does your think client's back-end server need to grow as well? How quickly? How do you ensure that you provide the correct amount of additional capacity without overstepping and unnecessarily eating into your profits? The answer is volume testing.
Read how RTTS does this with IBM Rational Performance Tester.
AWS January 2016 Webinar Series - Building Smart Applications with Amazon Mac...Amazon Web Services
In this presentation, learn how an end-to-end smart application can be built in the AWS cloud. We will demonstrate how to use Amazon Machine Learning (Amazon ML) to create machine learning models, deploy them to production, and obtain predictions in real-time. We will then demonstrate how to build a complete smart application using Amazon ML, Amazon Kinesis, and AWS Lambda. We will walk you through the process flow and architecture, demonstrate outcomes, and then dive into the code for implementation. In this session, you will learn how to use Amazon ML as well as how to integrate Amazon ML into your applications to take advantage of predictive analysis in the cloud.
Learning Objectives:
Learn about AWS services needed to build smart applications on AWS, e.g. Amazon Kinesis, AWS Lambda, Amazon Mechanical Turk, Amazon SNS
Learn how to deploy such implementation
Get the code on GitHub for you to use immediately
Who Should Attend:
Developers, Engineers, Solutions Architects
Vortrag "Real-World Smart Applications with Amazon Machine Learning" von Alex Ingerman beim AWS Machine Learning Web Day. Alle Videos und Präsentationen finden Sie hier: http://amzn.to/1XP3dz9
Talk given for CTUs Open Informatics Program. Focuses on the shift from Browser focused web pages to APIs and Applications (Apps) - covering trends, business models, architecture and the emerging Internet Operating System
Building Bridges: Merging RPA Processes, UiPath Apps, and Data Service to bu...DianaGray10
This session is focused on the art of application architecture, where we unravel the intricacies of creating a standard, yet dynamic application structure.
We'll explore:
Essential components of a typical application, emphasizing their roles and interactions.
Learn how to connect UiPath RPA Processes, UiPath Apps, and Data Service together to build a stronger app.
Gain insights into building more efficient, interconnected, and robust applications in the UiPath ecosystem.
Speaker:
David Kroll, Director, Product Marketing @Ashling Partners and UiPath MVP
IIBA® Sydney Unlocking the Power of Low Code No Code: Why BAs Hold the KeyAustraliaChapterIIBA
Unlocking the Power of Low Code No Code: Why Business Analysts Hold the Key
Join us for an upcoming virtual event to explore how business analysts can drive low code no code adoption within their organisations. Taking place on Wednesday 29th March at 6pm - 7pm AEDT, this event is a must-attend for Australian businesses looking to simplify processes, reduce costs, and achieve more with less using low code and no code strategies.
According to Gartner, the low code development platform market is predicted to grow at a pace of 23% through 2026, reaching $23.3 billion in revenue. As digital transformation continues to accelerate and skilled developers remain in short supply, the adoption of low code and no code is set to soar in the coming years.
Hear from industry experts from Microsoft Power Platform and Increment as they discuss the latest trends in low code and no code adoption, the benefits of these platforms, and the pivotal role that business analysts play in driving their adoption. Discover how the Business Analyst is uniquely positioned to spearhead the success of low code no code by streamlining operations, automating processes, speeding up time to market, and improving ROI.
Artificial Artificial Intelligence: Using Amazon Mechanical Turk and .NET to Create a…
1. Artificial, Artificial Intelligence Using Amazon Mechanical Turk and .NET to Create a New Breed of Web App Jeff Barr Web Services Evangelist Amazon Web Services NGW012
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5. Web Service Architecture Operating System Libraries / DLLs / Assemblies Application Internet Web Services Application
16. How It Works www.mturk.com Workers Artificial, Artificially Intelligent Software Requester (Developer) Human Intelligence Tasks (HITs) Completed HITs Worker Qualifications
29. Application Flow Load Qualifications Load HITs Any Completed Assignments? Retrieve and Approve Do Local Processing More Work? Y Y Done! Do Local Processing N