Thursday, February 3, 2022

g-f(2)891 THE NEW WORLD NEWS (2/3/2022), geniouxfacts, 10 Golden Knowledge (GK) Containers on Artificial Intelligence (AI)


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10 Golden Knowledge (GK) Containers on AI


The main objective of this "genioux fact" is to discover 10 rare containers of golden knowledge (GK) in the Artificial Intelligence (AI). 

  1. The state of AI ethics: The principles, the tools, the regulationsGeorge Anadiotis, February 3, 2022, VentureBeat.
    • A definition that seems to have garnered some consensus is that AI ethics is a system of moral principles and techniques intended to inform the development and responsible use of artificial intelligence technologies.
    • If this definition seems ambiguous to you, you aren’t alone. 
    • The Montreal AI Ethics Institute (MAIEI) is an international nonprofit organization democratizing AI ethics literacy. It aims to equip citizens concerned about artificial intelligence to take action, as its founders believe that civic competence is the foundation of change.
    • The institute’s State of AI Ethics Reports, published semi-annually, condense the top research & reporting around a set of ethical AI subtopics into one document. As the first of those reports for 2022 has just been released, VentureBeat picked some highlights from the almost 300 page document to discuss with Gupta.
      • AI ethics: Privacy and security, reliability and safety, fairness and inclusiveness, transparency and accountability
      • Too many AI principles, not enough tools
      • Bridging the gap via regulation
      • Is AI ethics regulation the end-all?
  2. The brain’s secret to life-long learning can now come as hardware for artificial intelligencePurdue University, February 3, 2022, ScienceDaily.
    • As companies use more and more data to improve how AI recognizes images, learns languages and carries out other complex tasks, a recent article shows a way that computer chips could dynamically rewire themselves to take in new data like the brain does, helping AI to keep learning over time.
    • When the human brain learns something new, it adapts. But when artificial intelligence learns something new, it tends to forget information it already learned.
    • "The brains of living beings can continuously learn throughout their lifespan. We have now created an artificial platform for machines to learn throughout their lifespan," said Shriram Ramanathan, a professor in Purdue University's School of Materials Engineering who specializes in discovering how materials could mimic the brain to improve computing.
    • Toward building a brain in chip form
      • The hardware is a small, rectangular device made of a material called perovskite nickelate, which is very sensitive to hydrogen. Applying electrical pulses at different voltages allows the device to shuffle a concentration of hydrogen ions in a matter of nanoseconds, creating states that the researchers found could be mapped out to corresponding functions in the brain.
  3. DeepMind claims its new code-generating system is competitive with human programmersKyle Wiggers, February 2, 2022, VentureBeat.
    • DeepMind — the AI lab backed by Google parent company Alphabet — claims to have improved upon Codex in key areas with AlphaCode, a system that can write “competition-level” code. In programming competitions hosted on Codeforces, a platform for programming contests, DeepMind claims that AlphaCode achieved an average ranking within the top 54.3% across 10 recent contests with more than 5,000 participants each.
    • DeepMind principal research scientist Oriol Vinyals says it’s the first time that a computer system has achieved such a competitive level in all programming competitions.
    • Machine programming is by no stretch a solved science, and DeepMind admits that AlphaCode has limitations. For example, the system doesn’t always produce code that’s syntactically correct for each language, particularly in C++. AlphaCode also performs worse at generating challenging code, such as that required for dynamic programming, a technique for solving complex mathematical problems.
  4. Report: 79% of ML teams say they ‘lack access’ to data needed to identify bias and ethics issues, VB Staff, February 3, 2022, VentureBeat.
    • A new report from Arize AI illustrates that the day-to-day reality for data scientists and machine learning (ML) engineers is painful and slow, speaking to a distinct need for better ways to collaborate and understand where and why problems are emerging. In all, 48.6% of data scientists say their jobs are more difficult after COVID-19. More than one in four (26.2%) data scientists and ML engineers admit that it takes them one week or more to detect and resolve an issue with ML models. 
    • One of the survey’s biggest findings documents a concerning chasm between business and technical teams. Eighty-seven percent of data scientists and ML engineers report that they encounter issues with business executives not being able to quantify the ROI of ML initiatives, at least sometimes. Additionally, more than half (52.3%) also report that business executives simply don’t understand machine learning. Likely contributing to this disconnect is the fact that “sharing data with others on the team” and “convincing stakeholders when a new model is better” remain issues at least sometimes for over 80% of ML practitioners. To solve these issues, ML practitioners would likely be well-served by initiatives to increase internal ML literacy and quantify AI ROI by tying ML model performance metrics to key business metrics. 
  5. How Google uses artificial intelligence In Google SearchBarry Schwartz, February 3, 2022, Search Engine Land.
    • From RankBrain, Neural Matching, BERT and MUM - here is how Google uses AI for understanding language for query, content and ranking purposes.
    • As Google continues to leverage more artificial intelligence and machine learning in Google Search, one may wonder in what ways does AI and machine learning help Google Search perform its daily tasks. Since 2015, when Google introduced its first AI into search named RankBrain, Google has continued to deploy AI systems to better understand language and thus improve the search results Google presents to its searches.
    • As explained above, Google uses RankBrain, neural matching, and BERT in most queries you enter into Google Search, but Google also has core updates. The Google broad core updates that Google rolls out a few times per year is often noticed by site owners, publishers, and SEOs more than when Google releases these larger AI-based systems.
    • Google told us they do have other machine learning systems in Google Search. “RankBrain, neural matching, and BERT are just some of our more powerful and prominent systems,” Google said. Google added, “there are other AI elements that can impact core updates that don’t pertain to those specific three AI systems.”
  6. New computational tool predicts cell fates and genetic perturbations, Greta Friar, February 3, 2022, MIT News.
    • Biological systems tend to be harder to forecast, but MIT professor of biology Jonathan Weissman, postdoc Xiaojie Qiu, and collaborators at the University of Pittsburgh School of Medicine are working on making the path taken by cells as predictable as the arc of a ball. Rather than looking at how cells move through space, they are considering how cells change with time.
    • Weissman, Qiu, and collaborators Jianhua Xing, professor of computational and systems biology at the University of Pittsburgh School of Medicine, and Xing lab graduate student Yan Zhang have built a machine learning framework that can define the mathematical equations describing a cell’s trajectory from one state to another, such as its development from a stem cell into one of several different types of mature cell. The framework, which they call "dynamo," can also be used to figure out the underlying mechanisms — the specific cocktail of gene activity — driving changes in the cell. Researchers could potentially use these insights to manipulate cells into taking one path instead of another, a common goal in biomedical research and regenerative medicine.
  7. DeepMinds’s new ‘AlphaCode’ can program at a competitive level, Abner Li, February 3, 2022, 9To5Google.
    • DeepMind’s latest real-world application of machine learning is AlphaCode. Alphabet’s AI lab today announced a system that “writes computer programs at a competitive level.”
    • DeepMind has a mission to “solve intelligence” and its latest effort is meant to move beyond solving “relatively simple maths and programming problems.”  
    • AlphaCode leverages deep learning models to excel at tasks that require “critical thinking, logic, algorithms, coding, and natural language understanding” to excel at competitive programming, something that DeepMind says is “beyond the capabilities of existing AI systems.”
    • The system specifically uses “large-scale transformer models (that have recently shown promising abilities to generate code) with large-scale sampling and filtering.”
    • Human participants in these challenges are “ranked mainly based on how many problems they solve.” DeepMind used 10 existing competitions hosted on Codeforces to test AlphaCode. It achieved an “estimated rank within the top 54%” of human participants, or the level of a median competitor.
  8. This PR Firm Took Artificial Intelligence Mainstream, Gary Drenik, February 3, 2022, Forbes.
    • A small Israeli-born artificial intelligence company named Albert had suddenly emerged as a driving force behind this conversation, getting in before Salesforce had a chance to utter the word “Einstein” at its annual Dreamforce conference and AI was still a sparkle in Oracle’s eye. Behind Albert was New York City-based PR and Communications agency Channel V Media.
    • I spoke with Kieran Powell, partner at Channel V Media, about how Channel V Media has carved out a niche by focusing on companies’ narratives as a first step to transforming them into vocal market influencers.
  9. Worldwide Artificial Intelligence in Medical Imaging Industry to 2026 - Increasing Burden of Chronic Diseases is Driving Growth, Cision, February 3, 2022, yahoo!finance.
    • The report titled “Global Artificial Intelligence in Medical Imaging Market: Size, Trends & Forecast with Impact of COVID-19 (2022-2026)”, provides an in-depth analysis of the global artificial intelligence in the medical imaging market by value, by image acquisition technology, by AI technology. by clinical application, by end-user, and by region etc. The report provides a regional analysis of the AI in the medical imaging market, including the following regions: North America, Europe, Asia Pacific (China and Rest of Asia Pacific), and Rest of World. The report also provides a detailed analysis of the COVID-19 impact on the global AI in the medical imaging market.
    • The global AI in medical imaging market has increased during the years 2019-2021. The projections are made that the market would rise in the next four years i.e. 2022-2026 tremendously. 
  10. (AI) Artificial Intelligence in Drug Discovery Market to Rise at 33.9% CAGR, to Reach USD 5,558.0 Million by 2029: Polaris Market Research, GetNews, February 3, 2022, Digital Journal.
    • According to the latest research study, the report predicts the global size & share of Artificial Intelligence in Drug Discovery Market to reach around USD 5,558.0 Million by 2029 from USD 626.6 Million in 2021. The global Artificial Intelligence in Drug Discovery Market is anticipated to register a significant CAGR of 33.9% by 2029.


Genioux knowledge fact condensed as an image



Extra-condensed knowledge



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Ultra condensed golden knowledge (GK) juices for those who got the "g-f superpower" g-f(2)850



The “g-f superpower”


  • The “g-f superpower” is the superpower of becoming a fast and successful learner. g-f(2)837
  • An ultra-condensed golden knowledge (GK) juice for those who obtained the "g-f superpower" consists of a single sentence. A click on the link that accompanies the phrase takes you to the container of golden knowledge. g-f(2)850




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Essential FACT 5: Becoming a fast and successful learner is a superpower g-f(2)837



This "genioux fact" (g-f(2)837) is an ultra-condensed knowledge juice, extracted from more than 836 "genioux facts". The "genioux facts" most relevant to the juice appear as links.

  • To keep pace with change and avoid disruption, people must become fast and successful learners, infinite learners—those who not only enjoy learning but feel a constant need to acquire new skills.
  • Foundational FACT: Golden Knowledge (GK) opens the way to staggering opportunities, risks and challenges.
  • Obsolesce FACTOR: GK can be obsolete in some degree fast because GK of exceptional quality is produced daily.
  • Essential FACT: The essential problem with the digital age is that the rate at which GK is appropriated is much slower than the rate at which new GK is created.
  • Essential fact about pleasure: Learning is the greatest of all pleasures.
  • Essential fact about eternal youth: Keep learning to stay young forever.
  • The list of most relevant Essential FACTS:
    • g-f(2)771 Lighthouse of the big picture of the digital age (12/30/2021), Essential FACT 1: The fabulous treasure must be known to all
    • g-f(2)772 Lighthouse of the big picture of the digital age (12/30/2021), Essential FACT 2: The New World must be known to all
    • g-f(2)773 Lighthouse of the big picture of the digital age (12/31/2021), Essential FACT 3: GK for you to conquer the New World
    • g-f(2)778 Lighthouse of the big picture of the digital age (1/1/2022), Essential FACT 4: In the New World, the game is transformation
    • Essential FACT 5: Becoming a fast and successful learner is a superpower




Condensed knowledge






Some relevant characteristics of this "genioux fact"

  • Category 2: The Big Picture of the Digital Age
  • [genioux fact deduced or extracted from geniouxfacts]
  • This is a “genioux fact fast solution.”
  • Tag Opportunities those travelling 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.


References


“genioux facts”: The online programme on MASTERING “THE BIG PICTURE OF THE DIGITAL AGE”, g-f(2)891, Fernando Machuca, February 3, 2022, blog.geniouxfacts.comgeniouxfacts.comGenioux.com Corporation.


ABOUT THE AUTHORS


PhD with awarded honors in computer science in France

Fernando is the director of "genioux facts". He is the entrepreneur, researcher and professor who has a disruptive proposal in The Digital Age to improve the world and reduce poverty + ignorance + violence. A critical piece of the solution puzzle is "genioux facts"The Innovation Value of "genioux facts" is exceptional for individuals, companies and any kind of organization.




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g-f(2)778 Lighthouse of the big picture of the digital age (1/1/2022), Essential FACT 4: In the New World, the game is transformation

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