Valentin Heun (PTC): One Reality - A 3rd generation AR User Interface

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This document discusses augmented reality and its potential to weave technology into everyday life seamlessly. It begins by introducing PTC's Reality Lab team and their work on AR. It then discusses how AR can enhance spatial learning and object recognition like the human brain. The document advocates that AR interfaces that leverage spatial knowledge can reduce cognitive load. It presents a vision for AR integrating various domains like robotics, big data, knowledge graphs and more. The conclusion is that combining AR, VR and other technologies spatially through cross-domain experiences could usher in an era where one unified reality replaces separate technological spheres.

Technology

Valentin Heun
PTC Reality Laboratory
Team:
Anna Fuste, Hisham Bedri, Christian Vazquez, Benjamin Reynolds

“A Human Modem”
James Heppelmann, President & CEO PTC

Dorsolateral
Prefrontal
Cortex
(DLPFC)
Hippocampus
Inferior
Parietal Lobe
(IPL)
Parahippocampal
Cortex (PHC)
Cerebellum
(CB)
Active Spatial LearningObject Recognition
Modem Data Processing Units

Modem Data Throughput
Terminal Desktop Paradigm AR
Spatial LearningObject Recognition

“Overall, our review provides strong
evidence that spatial knowledge of
controls and data enables rapid
interaction and information retrieval, and
allows users to focus more of their
cognitive resources on the task at hand,
rather than on the interface.“
Scarr, J., Cockburn, A. and Gutwin, C., 2013.
Supporting and exploiting spatial memory in user interfaces.
Foundations and Trends in Human–Computer Interaction, 6(1),
pp.1-84.

“The most profound technologies are
those that disappear. They weave
themselves into the fabric of everyday
life until they are indistinguishable
from it.”
The Computer for the 21st Century
Mark Weiser

Everyday Life
Active Spatial LearningObject Recognition

2 Fabric
AR UI for various Technological Domains

Many Separated Realities
TechnologyPhones
AR
VR
Screens
Desktop
Electronics
Electronics
Robotics
Mobile
Mixed
AI
On-Site
Remote
transportation
home
industry
nature

3 Weaving
seamless, spatial, cross domain ux - one reality

Spatial Programming + AR + 3D-Tele-Pres.

In this chapter, we take bold step and propose the unthinkable: The genesis of a Customizable Mind Machine. Thought that stems from the mind is deeply seated in a biological framework of neurons. The biological origin lies in the marvel of evolution over the eons and refined ever so fast, faster than in the prior centuries. Three (a, b and c), triadic objects are ceaselessly at work. At a personal level (a) Mind, knowledge and machines have been intertwined like inspiration, words and language since the dawn of the human evolution and more recently (b) technology, manufacturing and economics have formed a web for (c) wealth, global marketing and insatiable needs of humans and civilization. These triadic cycles of nine essential objects of human existence are spinning quicker and quicker every year. The Internet offers the mind no choice but to leap and soar over history and over the globe. Alternatively, human mind can sink deeper and deeper into ignorance and oblivion. More recently, the Artificial Intelligence at work in the Internet had challenged the natural intelligence at the cognizance level in the mind to find its way to breakthroughs and innovations. We integrate functions of the mind with the processing of knowledge in the hardware of machines by freely traversing the neural, mental, physical, psychological, social, knowledge, and computational spaces. The laws of neural biology and mind, laws of knowledge and social sciences and finally the laws of physics and mechanics, in each of the spaces are unique and executed by distinctive processors for each space. Much as mind rules over matter, the triad of mind, space and time creates a human-space that rules over the Relativistic-space of matter, space and time. Keywords—Mind, Knowledge, Machines, Technology, Human Needs, Knowledge Windows, Perceptual Spaces

Computing for Human Experience [v3, Aug-Oct 2010]

Artificial Intelligence Institute at UofSC

This is a version of series of talks given at NCSA-UIUC's director seminar, IBM Almaden, HP Labs, DERI-Galway, City Univ of Dublin, and KMI-Open University during Aug-Oct 2010 (replaces earlier keynote version). It deals with couple of items of the vision outlined at http://bit.ly/4ynB7A A video of this presentation: http://www.ncsa.illinois.edu/News/Video/2010/sheth.html Link to this talk as http://bit.ly/CHE-talk

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Romissaa ali Esmail/ faculty of dentistry/Al-Azhar university

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Smart Data - How you and I will exploit Big Data for personalized digital hea...

Amit Sheth

Amit Sheth's keynote at IEEE BigData 2014, Oct 29, 2014. Abstract from: http://cci.drexel.edu/bigdata/bigdata2014/keynotespeech.htm Big Data has captured a lot of interest in industry, with the emphasis on the challenges of the four Vs of Big Data: Volume, Variety, Velocity, and Veracity, and their applications to drive value for businesses. Recently, there is rapid growth in situations where a big data challenge relates to making individually relevant decisions. A key example is personalized digital health that related to taking better decisions about our health, fitness, and well-being. Consider for instance, understanding the reasons for and avoiding an asthma attack based on Big Data in the form of personal health signals (e.g., physiological data measured by devices/sensors or Internet of Things around humans, on the humans, and inside/within the humans), public health signals (e.g., information coming from the healthcare system such as hospital admissions), and population health signals (such as Tweets by people related to asthma occurrences and allergens, Web services providing pollen and smog information). However, no individual has the ability to process all these data without the help of appropriate technology, and each human has different set of relevant data! In this talk, I will describe Smart Data that is realized by extracting value from Big Data, to benefit not just large companies but each individual. If my child is an asthma patient, for all the data relevant to my child with the four V-challenges, what I care about is simply, “How is her current health, and what are the risk of having an asthma attack in her current situation (now and today), especially if that risk has changed?” As I will show, Smart Data that gives such personalized and actionable information will need to utilize metadata, use domain specific knowledge, employ semantics and intelligent processing, and go beyond traditional reliance on ML and NLP. I will motivate the need for a synergistic combination of techniques similar to the close interworking of the top brain and the bottom brain in the cognitive models. For harnessing volume, I will discuss the concept of Semantic Perception, that is, how to convert massive amounts of data into information, meaning, and insight useful for human decision-making. For dealing with Variety, I will discuss experience in using agreement represented in the form of ontologies, domain models, or vocabularies, to support semantic interoperability and integration. For Velocity, I will discuss somewhat more recent work on Continuous Semantics, which seeks to use dynamically created models of new objects, concepts, and relationships, using them to better understand new cues in the data that capture rapidly evolving events and situations. Smart Data applications in development at Kno.e.sis come from the domains of personalized health, energy, disaster response, and smart city.

Deep LearningShaikh Shahzad

Principles for reducing extraneous processing edlt 520Hector

Artificial Intelligence Research Topics for PhD Manuscripts 2021 - Phdassistance

PhD Assistance

Imagine a world where knowledge isn’t limited to humans!!! A world in which computers will think and collaborate with humans to create a more exciting universe. Although this future is still a long way off, Artificial Intelligence has made significant progress in recent years. In almost every area of AI, such as quantum computing, healthcare, autonomous vehicles, the internet of things, robotics, and so on, there is a lot of research going on. So much so that the number of annual Published Research Papers on Artificial Intelligence has increased by 90% since 1996. Ph.D. Assistance serves as an external mentor to brainstorm your idea and translate that into a research model. Hiring a mentor or tutor is common and therefore let your research committee know about the same. We do not offer any writing services without the involvement of the researcher. Learn More: https://bit.ly/2Sdlfn4 Contact Us: Website: https://www.phdassistance.com/ UK NO: +44–1143520021 India No: +91–4448137070 WhatsApp No: +91 91769 66446 Email: info@phdassistance.com

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