The document discusses capturing real world activities and interactions to simulate them in virtual worlds. It suggests using a hybrid method combining qualitative and quantitative data collection. Specifically, it recommends using sensors to capture movement and audio data, as well as developing ontologies to represent qualitative details. The goal is to recognize activities and analyze workflows to improve training and performance in high-risk environments like trauma centers.
The Impact of VR and AR on Medical Research and HealthcareStanford University
The Impact of VR and AR Technologies on Medical Research and Healthcare
Walter Greenleaf, PhD
Virtual Human Interaction Lab | Stanford University
Although entertainment, social connection, and gaming will drive the initial adoption of Virtual Reality and Augmented Reality technology, the deepest and most significant impact of the next generation of VR/AR technology will be to enhance clinical care and to improve personal health and wellness.
We know from decades of clinical research that VR/AR technology can provide breakthrough solutions that address the most difficult problems in healthcare - ranging from mood disorders such as Anxiety and Depression to PTSD, Addictions, Autism, Cognitive Aging, Stroke Recovery and Physical Rehabilitation, to name just a few.
VR technology also improved clinical measurements and assessments, can greatly improve medical training such as surgical skill training and procedure planning. Personal health and wellness will be improved by using VR to promote healthy lifestyles and to reduce stress and anxiety. As the cost of healthcare rises, VR technology can serve as an effective telemedicine platform to reduce costs of care delivery, and improve clinical efficiency.
This presentation will provide an overview of how VR technology will impact medicine, clinical care, and personal health and wellness, and how it will help to facilitate the shift of medicine to direct personal care.
Semantic, Cognitive, and Perceptual Computing – three intertwined strands of ...Amit Sheth
Keynote at Web Intelligence 2017: http://webintelligence2017.com/program/keynotes/
Video: https://youtu.be/EIbhcqakgvA Paper: http://knoesis.org/node/2698
Abstract: While Bill Gates, Stephen Hawking, Elon Musk, Peter Thiel, and others engage in OpenAI discussions of whether or not AI, robots, and machines will replace humans, proponents of human-centric computing continue to extend work in which humans and machine partner in contextualized and personalized processing of multimodal data to derive actionable information.
In this talk, we discuss how maturing towards the emerging paradigms of semantic computing (SC), cognitive computing (CC), and perceptual computing (PC) provides a continuum through which to exploit the ever-increasing and growing diversity of data that could enhance people’s daily lives. SC and CC sift through raw data to personalize it according to context and individual users, creating abstractions that move the data closer to what humans can readily understand and apply in decision-making. PC, which interacts with the surrounding environment to collect data that is relevant and useful in understanding the outside world, is characterized by interpretative and exploratory activities that are supported by the use of prior/background knowledge. Using the examples of personalized digital health and a smart city, we will demonstrate how the trio of these computing paradigms form complementary capabilities that will enable the development of the next generation of intelligent systems. For background: http://bit.ly/PCSComputing
An Overview of VR Technology and Smulation in Healthcare
Walter Greenleaf, PhD
Virtual Human Interaction Lab | Stanford University
The onrushing wave of Virtual Reality and Augmented Reality technology will profoundly impact healthcare.
Working in concert with data analytics provided by wearable technology, VR and AR technology will shift the locus of clinical care from the hospital and the clinic to the home and workplace, and through improved analytics enable personalized medicine.
We know from decades of clinical research that VR/AR technology can provide breakthrough solutions that address the most difficult problems in healthcare - ranging from mood disorders such as anxiety and depression to PTSD, addictions, autism, cognitive aging, stroke recovery, and physical rehabilitation, to name just a few.
Individualized health and wellness protocols/treatment plans can be enhanced by using VR and AR to promote adherence and to encourage healthy lifestyles.
As the cost of healthcare rises, VR and AR technology can serve as an effective telemedicine platform to reduce costs of care delivery and improve clinical efficiency.
The Impact of VR and AR on Medical Research and HealthcareStanford University
The Impact of VR and AR Technologies on Medical Research and Healthcare
Walter Greenleaf, PhD
Virtual Human Interaction Lab | Stanford University
Although entertainment, social connection, and gaming will drive the initial adoption of Virtual Reality and Augmented Reality technology, the deepest and most significant impact of the next generation of VR/AR technology will be to enhance clinical care and to improve personal health and wellness.
We know from decades of clinical research that VR/AR technology can provide breakthrough solutions that address the most difficult problems in healthcare - ranging from mood disorders such as Anxiety and Depression to PTSD, Addictions, Autism, Cognitive Aging, Stroke Recovery and Physical Rehabilitation, to name just a few.
VR technology also improved clinical measurements and assessments, can greatly improve medical training such as surgical skill training and procedure planning. Personal health and wellness will be improved by using VR to promote healthy lifestyles and to reduce stress and anxiety. As the cost of healthcare rises, VR technology can serve as an effective telemedicine platform to reduce costs of care delivery, and improve clinical efficiency.
This presentation will provide an overview of how VR technology will impact medicine, clinical care, and personal health and wellness, and how it will help to facilitate the shift of medicine to direct personal care.
Semantic, Cognitive, and Perceptual Computing – three intertwined strands of ...Amit Sheth
Keynote at Web Intelligence 2017: http://webintelligence2017.com/program/keynotes/
Video: https://youtu.be/EIbhcqakgvA Paper: http://knoesis.org/node/2698
Abstract: While Bill Gates, Stephen Hawking, Elon Musk, Peter Thiel, and others engage in OpenAI discussions of whether or not AI, robots, and machines will replace humans, proponents of human-centric computing continue to extend work in which humans and machine partner in contextualized and personalized processing of multimodal data to derive actionable information.
In this talk, we discuss how maturing towards the emerging paradigms of semantic computing (SC), cognitive computing (CC), and perceptual computing (PC) provides a continuum through which to exploit the ever-increasing and growing diversity of data that could enhance people’s daily lives. SC and CC sift through raw data to personalize it according to context and individual users, creating abstractions that move the data closer to what humans can readily understand and apply in decision-making. PC, which interacts with the surrounding environment to collect data that is relevant and useful in understanding the outside world, is characterized by interpretative and exploratory activities that are supported by the use of prior/background knowledge. Using the examples of personalized digital health and a smart city, we will demonstrate how the trio of these computing paradigms form complementary capabilities that will enable the development of the next generation of intelligent systems. For background: http://bit.ly/PCSComputing
An Overview of VR Technology and Smulation in Healthcare
Walter Greenleaf, PhD
Virtual Human Interaction Lab | Stanford University
The onrushing wave of Virtual Reality and Augmented Reality technology will profoundly impact healthcare.
Working in concert with data analytics provided by wearable technology, VR and AR technology will shift the locus of clinical care from the hospital and the clinic to the home and workplace, and through improved analytics enable personalized medicine.
We know from decades of clinical research that VR/AR technology can provide breakthrough solutions that address the most difficult problems in healthcare - ranging from mood disorders such as anxiety and depression to PTSD, addictions, autism, cognitive aging, stroke recovery, and physical rehabilitation, to name just a few.
Individualized health and wellness protocols/treatment plans can be enhanced by using VR and AR to promote adherence and to encourage healthy lifestyles.
As the cost of healthcare rises, VR and AR technology can serve as an effective telemedicine platform to reduce costs of care delivery and improve clinical efficiency.
Knowledge Will Propel Machine Understanding of Big DataAmit Sheth
Preview video: https://youtu.be/4e0dtV7CTWM
CCKS Keynote, August 2017: http://www.ccks2017.com/?page_id=358
SEAS Summer School, July 2017
https://sites.google.com/view/seasschool2017/talks
Related paper: http://knoesis.org/node/2835
CCKS Conf had over 500 attendees- some photos: https://photos.app.goo.gl/5CdlfAX1uYwvgqsQ2
Presentation of Hexoskin Validation for KHealth's Dementia Project
The paper is available at: http://www.knoesis.org/library/resource.php?id=2155
Citation for the paper: T. Banerjee, P. Anantharam, W. L. Romine, L. Lawhorne, A. Sheth, 'Evaluating a Potential Commercial Tool for Healthcare Application for People with Dementia' in Proc. of the Intl Conf on Health Informatics and Medical Systems (HIMS), Las Vegas, July 27-30, 2015.
Iotswc2016 - Microsoft - Healthcare track - lombardi - KHAREallo75
KHARE is a rehabilitation solution to speed up the recovery process for injured people: using Kinect, Microsoft Band and an IoT architecture on Azure, the human telemetry supports physiatrists and neuroscience researchers in tracking movements of exercises and predicting rehab trends. The body telemetry of a patient allows for experimentation with new rehabilitation modalities using mirror neurons.
* This is the presentation made at IoT Solution World Congress (IOTSWC) 2016 in the healthcare track
Challenges in deep learning methods for medical imaging - PubricaPubrica
1. Broad between association cooperation.
2. Need to Capitalize Big Image Data.
3. Progression in Deep Learning Methods.
4. Black-Box and Its Acceptance by Health Professional.
5. Security and moral issues.
6. Wrapping up.
Continue Reading: https://bit.ly/37zT2ur
Reference: https://pubrica.com/services/physician-writing-services/clinical-litearture-review-for-an-evidence-based-medicine/
Why Pubrica?
When you order our services, Plagiarism free|on Time|outstanding customer support|Unlimited Revisions support|High-quality Subject Matter Experts.
Contact us :
Web: https://pubrica.com/
Blog: https://pubrica.com/academy/
Email: sales@pubrica.com
WhatsApp : +91 9884350006
United Kingdom: +44- 74248 10299
Fairness in Search & RecSys 네이버 검색 콜로키움 김진영Jin Young Kim
검색 및 추천 시스템의 사회적 역할이 커지면서, 그 결과의 공정성 역시 최근 관심사로 대두되었다. 본 발표에서는 검색 및 추천시스템의 공정성 이슈 및 그 해법을 다룬다. 공정한 검색 및 추천 결과를 정의하는 다양한 방법, 공정성의 결여가 미치는 자원 배분 및 스테레오타이핑 문제, 그리고 검색 및 추천시스템 개발의 각 단계별로 어떤 해결책이 있는지를 최신 연구 중심으로 살펴본다. 마지막으로 실제 공정한 시스템 개발을 위한 실무적인 고려사항을 다룬다.
Machine learning is permeating nearly every industry – from retail and financial services to entertainment and transportation. And, while it's been slow to make its way into healthcare, machine learning stands to transform this space, too… positioning us to better diagnose, predict outcomes, provide follow-up care, and tailor treatments.
In this webinar, PointClear Solutions' Michael Atkins discusses the current state of machine learning in healthcare and what we can expect in the near future:
• What is machine learning and how is it being used today?
• What are some of the risks and obstacles we face in implementing this new technology?
• Looking into the future, what role will machine learning play in transforming healthcare?
• How can my company prepare for machine learning?
New Directions for Virtual Worlds for HealthParvati Dev
Keynote presented at Games for Health, Boston, for the Virtual Worlds and Social Games Day, May 25th. (First three slides are to introduce the pre-conference. Rest are my talk.)
Information security risk assessment under uncertainty using dynamic bayesian...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Abstract: http://j.mp/1MhWWei
Healthcare applications now have the ability to exploit big data in all its complexity. A crucial challenge is to achieve interoperability or integration so that a variety of content from diverse physical (IoT)- cyber (web-based)- and social sources, with diverse formats and modality (text, image, video), can be used in analysis, insight, and decision-making. At Kno.e.sis, an Ohio Center of Excellence in BioHealth Innovation, we have a variety of large, collaborative healthcare/clinical/biomedical projects, all involving domain experts and end-users, and access to real world data that include: clinical/EMR data (of individual patients and that related to public health), data from a variety of sensors (IoT) on and around patients measuring real-time physiological and environmental observations), social data (Twitter, Web forums, PatientsLikeMe), Web search logs, etc. Key projects include: Prescription drug abuse online-surveillance and epidemiology (PREDOSE), Social media analysis to monitor cannabis and synthetic cannabinoid use (eDrugTrends), Modeling Social Behavior for Healthcare Utilization in Depression, Medical Information Decision Assistant and Support (MIDAS) with application to musculoskeletal issues, kHealth: A Semantic Approach to Proactive, Personalized Asthma Management Using Multimodal Sensing (also for Dementia), and Cardiology Semantic Analysis System (with applications to Computer Assisted Coding and Computerized Document Improvement).
This talk will review how ontologies or knowledge graphs play a central role in supporting semantic filtering, interoperability and integration (including the issues such as disambiguation), reasoning and decision-making in all our health-centric research and applications. Additional relevant information is at the speaker’s HCLS page. http://knoesis.org/amit/hcls
Developing soft computing techniques to structured information extraction from unstructured and semi-structured data.
Integrating records for the same entity from multiple web sources using ontologies. Analyzing the information in social networking websites .
For details :
http://www.sonatech.ac.in/research/web-services-development.php
What leads to ultimate happiness? Is it real relationships that are true and meaningful, on which we can count or is it virtual ones which do not exist in real life, and takes us far away from the reality that we live in.
Francesco D'Orazio - Everything you know about virtual worlds is WRONG - Meta...Francesco D'Orazio
Patterns and challenges in the evolution of immersive entertainment.
Plus, all the wrongest things you could possibly say at a virtual worlds conference.
Virtual Relationship Vs Real RelationshipManish Kumar
What is Virtual Relationship?
What is Real Relationship?
Advantages of Virtual and Real Relationship ,
Disadvantages of Virtual and Real Relationship ,
Virtual Person, Real Person, Hybrid Person,
Conclusion
A definition of virtual world asset classes, the virtual worlds ecosystem and the attendant accounting, valuation, taxation and legal issues that arise in virtual world economics.
Audio: http://feeds.feedburner.com/BroaderPerspectivePodcast
Knowledge Will Propel Machine Understanding of Big DataAmit Sheth
Preview video: https://youtu.be/4e0dtV7CTWM
CCKS Keynote, August 2017: http://www.ccks2017.com/?page_id=358
SEAS Summer School, July 2017
https://sites.google.com/view/seasschool2017/talks
Related paper: http://knoesis.org/node/2835
CCKS Conf had over 500 attendees- some photos: https://photos.app.goo.gl/5CdlfAX1uYwvgqsQ2
Presentation of Hexoskin Validation for KHealth's Dementia Project
The paper is available at: http://www.knoesis.org/library/resource.php?id=2155
Citation for the paper: T. Banerjee, P. Anantharam, W. L. Romine, L. Lawhorne, A. Sheth, 'Evaluating a Potential Commercial Tool for Healthcare Application for People with Dementia' in Proc. of the Intl Conf on Health Informatics and Medical Systems (HIMS), Las Vegas, July 27-30, 2015.
Iotswc2016 - Microsoft - Healthcare track - lombardi - KHAREallo75
KHARE is a rehabilitation solution to speed up the recovery process for injured people: using Kinect, Microsoft Band and an IoT architecture on Azure, the human telemetry supports physiatrists and neuroscience researchers in tracking movements of exercises and predicting rehab trends. The body telemetry of a patient allows for experimentation with new rehabilitation modalities using mirror neurons.
* This is the presentation made at IoT Solution World Congress (IOTSWC) 2016 in the healthcare track
Challenges in deep learning methods for medical imaging - PubricaPubrica
1. Broad between association cooperation.
2. Need to Capitalize Big Image Data.
3. Progression in Deep Learning Methods.
4. Black-Box and Its Acceptance by Health Professional.
5. Security and moral issues.
6. Wrapping up.
Continue Reading: https://bit.ly/37zT2ur
Reference: https://pubrica.com/services/physician-writing-services/clinical-litearture-review-for-an-evidence-based-medicine/
Why Pubrica?
When you order our services, Plagiarism free|on Time|outstanding customer support|Unlimited Revisions support|High-quality Subject Matter Experts.
Contact us :
Web: https://pubrica.com/
Blog: https://pubrica.com/academy/
Email: sales@pubrica.com
WhatsApp : +91 9884350006
United Kingdom: +44- 74248 10299
Fairness in Search & RecSys 네이버 검색 콜로키움 김진영Jin Young Kim
검색 및 추천 시스템의 사회적 역할이 커지면서, 그 결과의 공정성 역시 최근 관심사로 대두되었다. 본 발표에서는 검색 및 추천시스템의 공정성 이슈 및 그 해법을 다룬다. 공정한 검색 및 추천 결과를 정의하는 다양한 방법, 공정성의 결여가 미치는 자원 배분 및 스테레오타이핑 문제, 그리고 검색 및 추천시스템 개발의 각 단계별로 어떤 해결책이 있는지를 최신 연구 중심으로 살펴본다. 마지막으로 실제 공정한 시스템 개발을 위한 실무적인 고려사항을 다룬다.
Machine learning is permeating nearly every industry – from retail and financial services to entertainment and transportation. And, while it's been slow to make its way into healthcare, machine learning stands to transform this space, too… positioning us to better diagnose, predict outcomes, provide follow-up care, and tailor treatments.
In this webinar, PointClear Solutions' Michael Atkins discusses the current state of machine learning in healthcare and what we can expect in the near future:
• What is machine learning and how is it being used today?
• What are some of the risks and obstacles we face in implementing this new technology?
• Looking into the future, what role will machine learning play in transforming healthcare?
• How can my company prepare for machine learning?
New Directions for Virtual Worlds for HealthParvati Dev
Keynote presented at Games for Health, Boston, for the Virtual Worlds and Social Games Day, May 25th. (First three slides are to introduce the pre-conference. Rest are my talk.)
Information security risk assessment under uncertainty using dynamic bayesian...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Abstract: http://j.mp/1MhWWei
Healthcare applications now have the ability to exploit big data in all its complexity. A crucial challenge is to achieve interoperability or integration so that a variety of content from diverse physical (IoT)- cyber (web-based)- and social sources, with diverse formats and modality (text, image, video), can be used in analysis, insight, and decision-making. At Kno.e.sis, an Ohio Center of Excellence in BioHealth Innovation, we have a variety of large, collaborative healthcare/clinical/biomedical projects, all involving domain experts and end-users, and access to real world data that include: clinical/EMR data (of individual patients and that related to public health), data from a variety of sensors (IoT) on and around patients measuring real-time physiological and environmental observations), social data (Twitter, Web forums, PatientsLikeMe), Web search logs, etc. Key projects include: Prescription drug abuse online-surveillance and epidemiology (PREDOSE), Social media analysis to monitor cannabis and synthetic cannabinoid use (eDrugTrends), Modeling Social Behavior for Healthcare Utilization in Depression, Medical Information Decision Assistant and Support (MIDAS) with application to musculoskeletal issues, kHealth: A Semantic Approach to Proactive, Personalized Asthma Management Using Multimodal Sensing (also for Dementia), and Cardiology Semantic Analysis System (with applications to Computer Assisted Coding and Computerized Document Improvement).
This talk will review how ontologies or knowledge graphs play a central role in supporting semantic filtering, interoperability and integration (including the issues such as disambiguation), reasoning and decision-making in all our health-centric research and applications. Additional relevant information is at the speaker’s HCLS page. http://knoesis.org/amit/hcls
Developing soft computing techniques to structured information extraction from unstructured and semi-structured data.
Integrating records for the same entity from multiple web sources using ontologies. Analyzing the information in social networking websites .
For details :
http://www.sonatech.ac.in/research/web-services-development.php
What leads to ultimate happiness? Is it real relationships that are true and meaningful, on which we can count or is it virtual ones which do not exist in real life, and takes us far away from the reality that we live in.
Francesco D'Orazio - Everything you know about virtual worlds is WRONG - Meta...Francesco D'Orazio
Patterns and challenges in the evolution of immersive entertainment.
Plus, all the wrongest things you could possibly say at a virtual worlds conference.
Virtual Relationship Vs Real RelationshipManish Kumar
What is Virtual Relationship?
What is Real Relationship?
Advantages of Virtual and Real Relationship ,
Disadvantages of Virtual and Real Relationship ,
Virtual Person, Real Person, Hybrid Person,
Conclusion
A definition of virtual world asset classes, the virtual worlds ecosystem and the attendant accounting, valuation, taxation and legal issues that arise in virtual world economics.
Audio: http://feeds.feedburner.com/BroaderPerspectivePodcast
Understanding The Pattern Of RecognitionRahul Bedi
Pattern recognition is identifying patterns and regularities in data through algorithms and mathematical models. It’s a field that has revolutionized the way we process and make decisions based on data. Contact EnFuse Solutions today and discover how pattern recognition can transform your business. For more information visit here: https://www.enfuse-solutions.com/
Machine learning applications nurturing growth of various business domainsShrutika Oswal
Machine learning is a science in which machines are becoming smarter and helping humans to make the best decisions based on previous data recommended practices. This technique is not new but is occupying fresh momentum. Machine Learning Algorithm learns from the previous records and analyses the data. Without any human interrupt, it will generate its own recommendation. A machine will add that recommendation as experience in its database and use it for further processing. In short, the machine learns from its own experience and gives you better and better output.
Machine learning is an iterative process as the more data added to machines learn from fresh feeds of data and then independently adapt new features to handle new data without constant human intervention. Machine learning was earlier used to predict what’s happing with the business but now the machine learning algorithm will suggest what action needs be taken by moving our business forward.
This PowerPoint presentation presents the results of a literature survey of machine learning applications nurturing the growth of various business domains. More specifically, it gives a brief introduction of Machine Learning, four major types of Machine Learning, enhancement in various business domains by the use of various machine learning algorithms.
What are Cognitive Applications? What is exciting about them? They represent a whole new way of human computer interaction and acting on data insights. Introducing IBM Watson and how to develop Cognitive applications. AI, Machine Learning compared and contrasted.
How AI will change the way you help students succeed - SchooLinksKatie Fang
In this presentation, we are going to uncover
1) why there's so much hype about AI/Machine Learning (and what these things really are)
2) Whirlwind tour of machine learning/statistics techniques and what they mean for counselors
3) Optimism for what the future brings - data as your friend rather than something to be managed.
If you have heard about machine learning and want to try out some of it, please check this out. In this article I am just trying to jot down few basics and must know stuff to kick start in this field. The objective of this compilation; to trigger the interest in this field of data analytics and to demystify the abstract concept. This article is not for the advanced data scientists, this is for the beginners or those who want a quick refresher.
As a speaker at San Jose Hadoop Summit 2015, presented the principles for Self Evolving Models for Dynamic System Accuracy.The theme of the topic is streaming and machine learning.
[moved to my rekhajoshm official slideshare account; with side effects of loss of stats]
HadoopSummit'2015:Self Evolving Models for Dynamic System AccuracyRekha Joshi
As a speaker at San Jose Hadoop Summit 2015, presented the principles for Self Evolving Models for Dynamic System Accuracy.I talked about self evolving model for dynamic system accuracy on big data ecosystem.The theme of the topic is streaming and machine learning.
[moved from my peas2bees unofficial slideshare account; with side effects of loss of stats]
Why Google defined a new discipline to help humans make decisions.docxgauthierleppington
Why Google defined a new discipline to help humans make decisions
Machine-learning systems are only as smart as their training data. So Google formalized the marshaling of hard and soft sciences that go into its decisions.
By Ciara Byrne
Cassie Kozyrkov is Google’s first-ever chief decision officer. She has already trained 17,000 Googlers to make better decisions by augmenting data science with psychology, neuroscience, economics, and managerial science. Now Google wants to share this new discipline–which it calls Decision Intelligence Engineering–with the world.
At Google, the need for someone like Kozyrkov stemmed from the company’s adoption of machine-learning technology across an array of products and services to make decisions reliably and at massive scale. A Machine Learning model which decides if a photo of an animal is a cat, can trigger actions accordingly: If it’s a cat, do A. If it’s not a cat, do B. And it can do it over and over without ongoing human involvement.
The problem is that an algorithm which learns from examples–in this case, photos of animals which are labeled as cats or not cats–is only as good as the examples it’s trained on. If the human being training the algorithm sometimes labels rabbits as cats, the algorithm will make bad decisions as efficiently as it does good ones. And the more sophisticated machine-learning applications get, the more opportunity there is for humans to introduce subtle problems into the final results.
Google needed a decision-making framework which enabled individual humans, groups of humans, and machines to make wise decisions. Such a process didn’t yet exist. So the company decided to build it.
DECISION INTELLIGENCE ENGINEERING
The well-established academic field of decision science covers the psychology, neuroscience, and economics of how human beings make decisions–but it doesn’t encompass the engineering perspective and the scale of automated decision-making. Likewise, data science doesn’t cover how humans think through a decision.
“A lot of the training that data scientists have assumes that the decision maker knows exactly what they need and the question and problem are framed perfectly,” says Kozyrkov. “The data scientist goes off and collects the data in service of that question, and answers it, or builds the machine learning system to implement it.”
That ideal scenario is all too rare in the real world. While working with Google’s data-science consulting arm, Kozyrkov often saw executives make decisions that were steered by unconscious bias rather than by the data itself.
Kozyrkov’s graduate training spans psychology, neuroscience, and statistics. Instead of just training decision-makers in data science, she set out to draw on the behavioral sciences to help them to make truly data-driven decisions. This means framing a decision effectively–often before looking at any data at all.
HOW TO DECIDE
The first step in Google’s framework asks decision-makers to determine how they will mak.
A look at metrics and analytics in Second Life from an educational perspective. This was initially presented at the Immersive Education Symposium at Boston College in January, 2008.
Hardware landscape from computer vision to wearable sensors, and a light intro for UX requirements to ensure adherence and engagement.
At the intersection of new sensors, big data, deep learning, gamification, behavioral medicine and human factors.
Applications benefiting from "quantitative sensorimotor training", "precision exercise", "precision physiotherapy" or whatever you are calling this, include weight and strength training, powerlifting, bodybuilding, martial arts, yoga, dance, musical instrument training, post-surgery rehabilitation for ACL tears, etc.
Alternative download link:
https://www.dropbox.com/s/wcfrzdjkn58xjdq/physio_pipeline_hw.pdf?dl=0
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.
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
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
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.
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.
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.
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/
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.
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.
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.
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.
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.
3. A model of the real world.. IT MAY BE ARGUED THAT ACTIVITIES, INTERACTIONS AND COGNITION IS WHERE THE BIGGEST BANG FOR THE BUCK IS….
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8. Capturing Interactions…. Detailed But Human Intensive and Can miss Dynamic Events Data Driven Too Coarse Not cognitively grounded Laxmisan et al. 2007 Malhotra et al. 2007 Alwan et al. 2006 Ostbye et al. 2003
29. Methodology For Choosing Exercises Cognitive task analysis Suturing->{setting the needle->passing suture->tying} Matching observational Parameters in the real world And virtual world Monitor progress through mechanism that work in an ambient manner Adapt gaming scores to our needs
In 1960, Rudolf E. Kalman published his famous paper describing a recursive solution to the discrete linear filtering problem. The Kalman filter addresses the general problem of trying to estimate the state x of a discrete-time controlled process that is governed by the linear stochastic difference equation, with a measurement z. The Kalman filter estimates a process by using a form of feedback control: the filter estimates the process state at some time and then obtains feedback in the form of (noisy) measurements. As such, the equations for the Kalman filter fall into two groups: time update equations and measurement update equations. The time update equations are responsible for projecting forward the current state and error covariance estimates to obtain the a priori estimates for the next time step. The measurement update equations are responsible for the feedback, i.e. for incorporating a new measurement into the a priori estimate to obtain an improved a posteriori estimate. If the process to be estimated or the measurement relationship to the process is non-linear, a filter that linearizes about the current mean and covariance will be needed. This filter is referred to as an extended Kalman filter.
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