Showing posts with label Lessons learned to those traveling at high speed on GKPath. Show all posts
Showing posts with label Lessons learned to those traveling at high speed on GKPath. Show all posts

Sunday, May 30, 2021

g-f(2)301 The big picture of the digital age (5/30/2021), MIT SMR, Digital Fabrication During the COVID-19 Pandemic.




ULTRA-condensed knowledge


A KEY QUESTION about digital fabrication
  • Whether the progress toward increased self-sufficient production made during the COVID-19 crisis can be sustained over the long term. 

1. Lesson learned, Coordination and communication in the virtual R&D process
  • Coordination and communication in the virtual R&D process and among fab labs converting to production operations included regular online meetings along with offline collaborations. 
2. Lesson learned, Forms of distributed R&D and production
  • These forms of distributed R&D and production highlight how innovation and safety can be addressed during a rapidly evolving crisis, even without the structure of a formal organization.
3. Lesson learned, The patterns of self-sufficiency
  • The patterns of self-sufficiency that have emerged during the pandemic reveal how distributed R&D and local production could persist and expand as vital organizational and institutional arrangements in the pandemic recovery. 


Genioux knowledge fact condensed as an image


Condensed knowledge



Lessons learned, Digital Fabrication During the COVID-19 Pandemic

A KEY QUESTION about digital fabrication
  • Whether the progress toward increased self-sufficient production made during the COVID-19 crisis can be sustained over the long term. 

1. Lesson learned, Coordination and communication in the virtual R&D process
  • Coordination and communication in the virtual R&D process and among fab labs converting to production operations included regular online meetings along with offline collaborations. 
2. Lesson learned, Forms of distributed R&D and production
  • These forms of distributed R&D and production highlight how innovation and safety can be addressed during a rapidly evolving crisis, even without the structure of a formal organization.
3. Lesson learned, The patterns of self-sufficiency
  • The patterns of self-sufficiency that have emerged during the pandemic reveal how distributed R&D and local production could persist and expand as vital organizational and institutional arrangements in the pandemic recovery. 

                Category 2: The Big Picture of the Digital Age

                [genioux fact deduced or extracted from MIT SMR]

                This is a “genioux fact fast solution.”

                Tag Lessons learned to those traveling at high speed on GKPath

                Lessons learned, Digital Fabrication During the COVID-19 Pandemic
                • 3 relevant lessons learned (5/30/2021) for those traveling at high speed on GKPath!

                Type of essential knowledge of this “genioux fact”: Essential Analyzed Knowledge (EAK).

                Type of validity of the "genioux fact". 

                • Inherited from sources + Supported by the knowledge of one or more experts + Supported by research.


                Authors of the genioux fact

                Fernando Machuca


                References

                ABOUT THE AUTHORS


                Joel Cutcher-Gershenfeld is a professor at the Heller School for Social Policy and Management at Brandeis University. Alan Gershenfeld is cofounder and president of E-Line Media. Neil Gershenfeld is the director of MIT’s Center for Bits and Atoms.

                Professor
                joelcg@brandeis.edu
                Departments/Programs

                The Heller School for Social Policy and Management
                Degrees

                Massachusetts Institute of Technology, Ph.D.
                Cornell University, B.S.
                Expertise

                Joel has field expertise in social impact enterprises, large-scale systems change, high performance work systems, negotiation and dispute resolution, cyberinfrastructure, labor-management relations, new technology, and related matters. He has led change initiatives at team, enterprise, industry, national, and international levels. As a scholar, Joel has advanced theory and method in industrial relations, negotiations, institutional analysis, organizational behavior, information systems, employment law, cross-cultural studies, and other areas of social science.


                Alan Gershenfeld has spent the last twenty years at the intersection of entertainment, technology, and social entrepreneurship. He is currently President and Cofounder of E-Line Media, a publisher of digital entertainment that engages, educates and empowers— with a core focus on computer and video games. Alan has worked on impact game projects with the Gates Foundation, the MacArthur Foundation, the National Science Foundation, USAID, DARPA, the White House OSTP, the California Endowment, the Cook Inlet Tribal Council, Games for Change, Google, Sesame Workshop, the MIT Center for Bits and Atoms, and the ASU Center for Games and Impact. Prior to E-Line, he was CEO and Cofounder of neomat, a leader in mobile and web community solutions. 


                Prof. Neil Gershenfeld is the Director of MIT's Center for Bits and Atoms, where his unique laboratory is breaking down boundaries between the digital and physical worlds, from pioneering quantum computing to digital fabrication to the Internet of Things. Technology from his lab has been seen and used in settings including New York's Museum of Modern Art and rural Indian villages, the White House and the World Economic Forum, inner-city community centers and automobile safety systems, Las Vegas shows and Sami herds. 
                • He is the author of numerous technical publications, patents, and books including Designing Reality, Fab, When Things Start To Think, The Nature of Mathematical Modeling, and The Physics of Information Technology, and has been featured in media such as The New York Times, The Economist, NPR, CNN, and PBS. 
                • He is a Fellow of the American Association for the Advancement of Science and the American Physical Society, has been named one of Scientific American's 50 leaders in science and technology, as one of 40 Modern-Day Leonardos by the Museum of Science and Industry, one of Popular Mechanic's 25 Makers, has been selected as a CNN/Time/Fortune Principal Voice, and by Prospect/Foreign Policy as one of the top 100 public intellectuals. 
                • He's been called the intellectual father of the maker movement, founding a growing global network of over one thousand fab labs that provide widespread access to prototype tools for personal fabrication, directing the Fab Academy for distributed research and education in the principles and practices of digital fabrication, and chairing the Fab Foundation. 
                • Dr. Gershenfeld has a BA in Physics with High Honors from Swarthmore College, a Ph.D. in Applied Physics from Cornell University, honorary doctorates from Swarthmore College, Strathclyde University and the University of Antwerp, was a Junior Fellow of the Harvard University Society of Fellows, and a member of the research staff at Bell Labs.




                Key “genioux facts”








                By
                Labels: , , , , , , ,

                g-f(2)300 The big picture of the digital age, Untapped free golden knowledge of exceptional quality, Boston Global Forum YouTube channel, 5/30/2021.




                Extra-condensed knowledge


                • THE FUTURE OF AI AND HOW THE DIGITAL WORLD RELATES TO THE PHYSICAL WORLD – PROF. GERSHENFELD’S TALK AT AIWS SUMMIT 2019
                  • Posted on May 27, 2019
                  • On May 15, 2019, at MIT’s Center for Bits and Atoms, Prof. Gershenfeld gave a keynote talk at the AI World Society Summit 2019 about the future of AI and how the digital world relates to the physical world – the boundary between them.
                • VIDEO: Prof Neil Gershenfeld, Director of MIT's Center for Bits and Atoms
                  • 174 views, May 27, 2019
                  • Boston Global Forum YouTube channel
                    • 21 subscribers

                ULTRA-condensed knowledge


                1. Lesson learned, The computers and the capability of the brain
                • Thanks to the advances in computing technology, the computers have caught up to the capability of the brain in terms of the number of operations that can be performed.
                2. Lesson learned, The mother of all AI problems
                • “Literally, the mother of all AI problems is the revolution of AI itself, how intelligence creates intelligence,” said Gershenfeld.
                3. Lesson learned, Where we would be ahead of the scaling curve of AI
                • “We are really living through the third digital revolution”. With digital fabrication, we can digitalize not just the description of a design but also the materials that it is made from, in the same way that living systems are assembled from a small set of amino acids. A problem with today’s AI, Prof Neil Gershenfeld said, is that AI does not have a “body”, and with digital fabrication, we are getting closer to real AI. 
                4. Lesson learned, Challenging fundamental assumptions
                • Digital fabrication is challenging fundamental assumptions about the nature of work, money and government. It is a significant breakthrough and will have a big impact on shaping the future of AI.


                Genioux knowledge fact condensed as an image

                Condensed knowledge



                Untapped free golden knowledge of exceptional quality, Boston Global Forum YouTube channel, 5/30/2021

                1. Lesson learned, The computers and the capability of the brain
                • Thanks to the advances in computing technology, the computers have caught up to the capability of the brain in terms of the number of operations that can be performed.
                2. Lesson learned, The mother of all AI problems
                • “Literally, the mother of all AI problems is the revolution of AI itself, how intelligence creates intelligence,” said Gershenfeld.
                3. Lesson learned, Where we would be ahead of the scaling curve of AI
                • “We are really living through the third digital revolution”. With digital fabrication, we can digitalize not just the description of a design but also the materials that it is made from, in the same way that living systems are assembled from a small set of amino acids. A problem with today’s AI, Prof Neil Gershenfeld said, is that AI does not have a “body”, and with digital fabrication, we are getting closer to real AI. 
                4. Lesson learned, Challenging fundamental assumptions
                • Digital fabrication is challenging fundamental assumptions about the nature of work, money and government. It is a significant breakthrough and will have a big impact on shaping the future of AI.

                              Prof Neil Gershenfeld, Director of MIT's Center for Bits and Atoms




                              Category 2: The Big Picture of the Digital Age

                              [genioux fact deduced or extracted from Boston Global Forum YouTube channel]

                              This is a “genioux fact fast solution.”

                              Tag Lessons learned to those traveling at high speed on GKPath

                              Untapped free golden knowledge of exceptional quality, Boston Global Forum YouTube channel, 5/30/2021

                              • 4 relevant lessons learned (5/30/2021) for those traveling at high speed on GKPath!

                              Type of essential knowledge of this “genioux fact”: Essential Analyzed Knowledge (EAK).

                              Type of validity of the "genioux fact". 

                              • Inherited from sources + Supported by the knowledge of one or more experts + Supported by research.


                              Authors of the genioux fact

                              Fernando Machuca


                              References

                              ABOUT THE AUTHORS


                              Prof. Neil Gershenfeld is the Director of MIT's Center for Bits and Atoms, where his unique laboratory is breaking down boundaries between the digital and physical worlds, from pioneering quantum computing to digital fabrication to the Internet of Things. Technology from his lab has been seen and used in settings including New York's Museum of Modern Art and rural Indian villages, the White House and the World Economic Forum, inner-city community centers and automobile safety systems, Las Vegas shows and Sami herds. 
                              • He is the author of numerous technical publications, patents, and books including Designing Reality, Fab, When Things Start To Think, The Nature of Mathematical Modeling, and The Physics of Information Technology, and has been featured in media such as The New York Times, The Economist, NPR, CNN, and PBS. 
                              • He is a Fellow of the American Association for the Advancement of Science and the American Physical Society, has been named one of Scientific American's 50 leaders in science and technology, as one of 40 Modern-Day Leonardos by the Museum of Science and Industry, one of Popular Mechanic's 25 Makers, has been selected as a CNN/Time/Fortune Principal Voice, and by Prospect/Foreign Policy as one of the top 100 public intellectuals. 
                              • He's been called the intellectual father of the maker movement, founding a growing global network of over one thousand fab labs that provide widespread access to prototype tools for personal fabrication, directing the Fab Academy for distributed research and education in the principles and practices of digital fabrication, and chairing the Fab Foundation. 
                              • Dr. Gershenfeld has a BA in Physics with High Honors from Swarthmore College, a Ph.D. in Applied Physics from Cornell University, honorary doctorates from Swarthmore College, Strathclyde University and the University of Antwerp, was a Junior Fellow of the Harvard University Society of Fellows, and a member of the research staff at Bell Labs.



                              Key “genioux facts”








                              By
                              Labels: , , , , ,

                              Friday, May 28, 2021

                              g-f(2)298 The Big Picture of Business Artificial Intelligence, geniouxfacts, 10 relevant AI lessons learned from CIO (5/28/2021) for those traveling at high speed on GKPath!




                              ULTRA-condensed knowledge


                              1. Lesson learned, The value of using artificial intelligence
                              • Business leaders at every level see the value of using artificial intelligence but using AI well is where the true value lies. According to a Deloitte survey released last summer, 61% of companies expect AI to transform their industry over the next three years.
                              2. Lesson learned, Decisive factors for getting the most out of AI
                              • Companies with effective leaders, a high level of commitment to AI projects, and a clear AI vision and strategy are positioned to benefit the most, according to a McKinsey survey released last November.
                              3. Lesson learned, Focus on business transformation
                              • Today, the story General Electric is more about using AI as part of a transformation of the business itself.
                              4. Lesson learned, Know the limits of AI
                              • If an AI system trained on a specific problem is then applied to a slightly different problem, the results may be suboptimal — or even dangerous.
                              5. Lesson learned, Listen to stakeholders — and customers
                              • For some companies, ensuring AI systems produce useful results requires help beyond the core AI team. 
                              6. Lesson learned, No more proofs of concept
                              • When the technology was brand new, proofs of concept (POCs) made sense. Today, however, there’s less of a need to start your AI journey with experiments, says JJ López Murphy, data and AI technology director at Globant.
                              7. Lesson learned, Mixed teams
                              • “The No. 1 habit of successful companies is using well-mixed teams,” Gartner analyst Whit Andrews says. 
                              8. Lesson learned, Embrace domain expertise
                              • Relying solely on data scientists to surface insights from data is a big mistake, says Halim Abbas, chief AI officer at Cognoa.
                              9. Lesson learned, Realize the value of real-world testing
                              • No battle plan survives contact with the enemy — and no AI system survives contact with the real world. If your company isn’t prepared for this fact, your AI project is doomed before it starts. 
                              10. Lesson learned, Have a higher purpose
                              • As companies compete for scarce AI talent, having meaningful projects can make a big difference. 


                              Genioux knowledge fact condensed as an image


                              Condensed knowledge



                              1. Lesson learned, The value of using artificial intelligence
                              • Business leaders at every level see the value of using artificial intelligence but using AI well is where the true value lies. According to a Deloitte survey released last summer, 61% of companies expect AI to transform their industry over the next three years.
                              2. Lesson learned, Decisive factors for getting the most out of AI
                              • Companies with effective leaders, a high level of commitment to AI projects, and a clear AI vision and strategy are positioned to benefit the most, according to a McKinsey survey released last November.
                              3. Lesson learned, Focus on business transformation
                              • Today, the story General Electric is more about using AI as part of a transformation of the business itself.
                              4. Lesson learned, Know the limits of AI
                              • If an AI system trained on a specific problem is then applied to a slightly different problem, the results may be suboptimal — or even dangerous.
                              5. Lesson learned, Listen to stakeholders — and customers
                              • For some companies, ensuring AI systems produce useful results requires help beyond the core AI team. 
                              6. Lesson learned, No more proofs of concept
                              • When the technology was brand new, proofs of concept (POCs) made sense. Today, however, there’s less of a need to start your AI journey with experiments, says JJ López Murphy, data and AI technology director at Globant.
                              7. Lesson learned, Mixed teams
                              • “The No. 1 habit of successful companies is using well-mixed teams,” Gartner analyst Whit Andrews says. 
                              8. Lesson learned, Embrace domain expertise
                              • Relying solely on data scientists to surface insights from data is a big mistake, says Halim Abbas, chief AI officer at Cognoa.
                              9. Lesson learned, Realize the value of real-world testing
                              • No battle plan survives contact with the enemy — and no AI system survives contact with the real world. If your company isn’t prepared for this fact, your AI project is doomed before it starts. 
                              10. Lesson learned, Have a higher purpose
                              • As companies compete for scarce AI talent, having meaningful projects can make a big difference. 

                                            Category 2: The Big Picture of the Digital Age

                                            [genioux fact deduced or extracted from geniouxfacts]

                                            This is a “genioux fact fast solution.”

                                            Tag Lessons learned to those traveling at high speed on GKPath

                                            10 relevant AI lessons learned from CIO (5/28/2021)
                                            • 10 relevant AI lessons learned from CIO (5/28/2021) for those traveling at high speed on GKPath!

                                            Type of essential knowledge of this “genioux fact”: Essential Analyzed Knowledge (EAK).

                                            Type of validity of the "genioux fact". 

                                            • Inherited from sources + Supported by the knowledge of one or more experts.


                                            Authors of the genioux fact

                                            Fernando Machuca


                                            References


                                            ABOUT THE AUTHORS


                                            Contributing Writer

                                            Maria Korolov has been covering emerging technology and emerging markets for the past twenty years. She has reported from Russia, India, and Afghanistan, and recently returned to the United States after running a news bureau in China for five years



                                            Maria Korolov is a science fiction writer who covers cybersecurity, AI and extended reality as an award-winning tech journalist at her day job. Check out her author page on Amazon or follow her on Twitter, Facebook, or LinkedIn. She is also the publisher of MetaStellar, a new online magazine of speculative fiction.



                                            Key “genioux facts”








                                            By
                                            Labels: , , , , ,
                                            Subscribe to: Posts (Atom)

                                            Featured "genioux fact"

                                            🌟 g-f(2)3607: The Program That Masters the Digital Age — Your Ultimate Navigation System

                                              📚 Volume 21 of the genioux GK Nuggets (g-f GKN) Series: Bite-Sized Transformational Insights for Continuous Learning By  Fernando Machuca...

                                            Popular genioux facts, Last 30 days