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jerryking : albert_einstein   15

Thinking in Levels (How to Dig Deeper And Think Better)
Apr 21, 2018 | Medium | by Thomas Oppong.

Einstein once said, “You can’t solve a problem from the level of thinking that created the problem in the first place“.
*
[JCK: what follows is an example of thinking in layers] The process of thinking involves several levels, but only a few people think beyond the first level.....Thinking in levels can expose flaws in your decision making process, helping you to make choices with little or no blindspots....Robert Sternberg, a professor of psychology and education at Yale University, says that successful people use three kinds of intelligence: analytical, creative, and practical. A successful person, according to Sternberg, uses all three.......Instead of thinking on the fly, you use mental models to analyse every situation before making a choice.

The 3 thinking levels:
** Level 1
Level one thinkers observe, but rarely interpret or analyse what they see.
They take information on the face value. ..First-level thinking is simplistic and superficial, and just about everyone can do it (a bad sign for anything involving an attempt at superiority). All the first-level thinker needs is an opinion about the future, as in “The outlook for the company is favorable, meaning the stock will go up.” ...Most people get stuck at level 1. They take in facts, statistics and information, but never question the reasoning behind them or make the effort analyse what they have seen, read or been taught. They obsessively seek out truth that confirms their worldviews and cling to it with little room for metacognition (thinking about their thinking)..

** Level 2
At this level, you allow yourself to interpret, make connections and meanings. Second-level thinking is deep, complex and convoluted....At the second level, decision makers begin to interpret and analyze the pieces they have observed and put them together to form meaning.
This is the level at which we begin to look for alignments, contrast, repetition or improvements....Level two thinkers synthesis better — build up or connect separate pieces of information to form a larger, more coherent pattern. They are better at reorganizing or rearranging ideas to produce a more comprehensive understanding of the “big picture”.

** Level 3
This is the alpha stage of thinking.
Level 3 thinkers have the capacity to transfer knowledge, i.e., to apply a concept learned in one context to different contexts than the one in which the concept was originally learned.....Level 3 thinkers can view an issue or idea from a variety of viewpoints, standpoints, or positions to gain a more comprehensive and holistic understanding. They generate imaginative ideas, unique perspectives, innovative strategies, or novel (alternative) approaches to traditional practices.
Albert_Einstein  blindspots  books  business_acumen  connecting_the_dots  critical_thinking  decision_making  interpretation  metacognition  questions  thinking  thinking_deliberatively  weaknesses 
10 days ago by jerryking
Opinion | The Secrets of Jewish Genius - The New York Times
By Bret Stephens
Opinion Columnist

Dec. 27, 2019

** “Genius & Anxiety," by Norman Lebrecht.
An erudite and delightful study of the intellectual achievements and nerve-wracked lives of Jewish thinkers, artists, and entrepreneurs between 1847 and 1947. Sarah Bernhardt and Franz Kafka; Albert Einstein and Rosalind Franklin; Benjamin Disraeli and (sigh) Karl Marx — how is it that a people who never amounted even to one-third of 1 percent of the world’s population contributed so seminally to so many of its most pathbreaking ideas and innovations?.....The common answer is that Jews are, or tend to be, smart. When it comes to Ashkenazi Jews, it’s true. “Ashkenazi Jews have the highest average I.Q. of any ethnic group for which there are reliable data,”.....the “Jews are smart” explanation obscures more than it illuminates. Aside from the perennial nature-or-nurture question of why so many Ashkenazi Jews have higher I.Q.s, there is the more difficult question of why that intelligence was so often matched by such bracing originality and high-minded purpose. One can apply a prodigious intellect in the service of prosaic things — formulating a war plan, for instance, or constructing a ship. One can also apply brilliance in the service of a mistake or a crime, like managing a planned economy or robbing a bank.........But...Jewish genius operates differently. It is prone to question the premise and rethink the concept; to ask why (or why not?) as often as how; to see the absurd in the mundane and the sublime in the absurd. Ashkenazi Jews might have a marginal advantage over their gentile peers when it comes to thinking better. Where their advantage more often lies is in thinking different.
Where do these habits of mind come from?

There is a religious tradition that, unlike some others, asks the believer not only to observe and obey but also to discuss and disagree. There is the never-quite-comfortable status of Jews in places where they are the minority — intimately familiar with the customs of the country while maintaining a critical distance from them. There is a moral belief, “incarnate in the Jewish people” according to Einstein, that “the life of the individual only has value [insofar] as it aids in making the life of every living thing nobler and more beautiful.”

And there is the understanding, born of repeated exile, that everything that seems solid and valuable is ultimately perishable, while everything that is intangible — knowledge most of all — is potentially everlasting.
These explanations for Jewish brilliance aren’t necessarily definitive. Nor are they exclusive to the Jews......At its best, the American university can still be a place of relentless intellectual challenge rather than ideological conformity and social groupthink. At its best, the United States can still be the country that respects, and sometimes rewards, all manner of heresies that outrage polite society and contradict established belief. At its best, the West can honor the principle of racial, religious and ethnic pluralism not as a grudging accommodation to strangers but as an affirmation of its own diverse identity. In that sense, what makes Jews special is that they aren’t.

They are representational

The West, however, is not at its best. It’s no surprise that Jew hatred has made a comeback, albeit under new guises. Anti-Zionism has taken the place of anti-Semitism as a political program directed against Jews. Globalists have taken the place of rootless cosmopolitans as the shadowy agents of economic iniquity. Jews have been murdered by white nationalists and black “Hebrews.” Hate crimes against Orthodox Jews have become an almost daily fact of life in New York City. Jews of the late 19th century would have been familiar with the hatreds. Jews of the early 21st century should recognize where they could lead. What’s not secret about Jewish genius is that it’s a terribly fragile flower.
19th_century  20th_century  Albert_Einstein  anti-Semitism  books  Bret_Stephens  capitalization  genius  heresies  high-minded  human_capital  human_intelligence  IQ  Jewish  mental_dexterity  originality  outsiders  purpose  smart_people  talent  think_differently 
7 weeks ago by jerryking
Lost Einsteins: The Innovations We’re Missing -
DEC. 3, 2017 | The New York Times | David Leonhardt.

societies have a big interest in making sure that as many people as possible have the opportunity to become scientists, inventors and entrepreneurs. It’s not only a matter of fairness. Denying opportunities to talented people can end up hurting everyone.

.....Raj Chetty....is a Stanford professor who helps lead the Equality of Opportunity Project.... considered among the most important research efforts in economics today.....The project’s latest paper, out Sunday, looks at who becomes an inventor — and who doesn’t. The results are disturbing....The key phrase in the research paper is “lost Einsteins.” It’s a reference to people who could “have had highly impactful innovations” if they had been able to pursue the opportunities they deserved.....children who excelled in math were far more likely to become inventors. But being a math standout wasn’t enough. Only the top students who also came from high-income families had a decent chance to become an inventor.

This fact may be the starkest: Low-income students who are among the very best math students — those who score in the top 5 percent of all third graders — are no more likely to become inventors than below-average math students from affluent families:

....“There are great differences in innovation rates,” Chetty said. “Those differences don’t seem to be due to innate ability to innovate.” Or as Steve Case — the entrepreneur who’s now investing in regions that venture capital tends to ignore — told me when I called him to discuss the findings: “Creativity is broadly distributed. Opportunity is not.” [or life’s basic truth: Talent is universal, but opportunity is not.]
innovation  equality_of_opportunity  Steve_Case  Albert_Einstein  achievement_gaps  affluence  high-income  low-income  mathematics  capitalization  human_potential  inventions  inventiveness  inventors  creativity  quotes  unevenly_distributed 
december 2017 by jerryking
Flood. Rinse. Repeat: The costly cycle that must end
May 07, 2017 | The Globe and Mail |GLENN MCGILLIVRAY, managing director, Institute for Catastrophic Loss Reduction

Once again, homes located alongside a Canadian river have flooded, affected homeowners are shocked, the local government is wringing its hands, the respective provincial government is ramping up to provide taxpayer-funded disaster assistance and the feds are deploying the Armed Forces.

In Canada, it is the plot of the movie Groundhog Day, or the definition of insanity attributed to Albert Einstein: Doing the same thing over and over again and expecting a different result.....First, a homeowner locates next to the river, oftentimes because of the view (meaning a personal choice is being made). Many of these homes are of high value.

Then the snow melts, the ice jams or the rain falls and the flood comes. Often, as is the case now, the rain is characterized by the media as being incredible, far outside the norm. Then a scientific or engineering analysis later shows that what happened was not very exceptional.

These events are not caused by the rain, they are caused by poor land-use decisions, among other public-policy foibles. This is what is meant when some say there are no such things as natural catastrophes, only man-made disasters.

Finally, the province steps in with disaster assistance then seeks reimbursement from the federal government through the Disaster Financial Assistance Arrangements. In any case, whether provincial or federal, taxpayers are left holding the bag.....So what is the root of the problem? Though complex problems have complex causes and complex solutions, one of the causes is that the party making the initial decision to allow construction (usually the local government) is not the party left holding the bag when the flood comes.

Just as homeowners have skin in the game through insurance deductibles and other measures, local governments need a financial disincentive to act in a risky manner. At present, municipalities face far more upside risk than downside risk when it comes to approving building in high-risk hazard zones. When the bailout comes from elsewhere, there is no incentive to make the right decision – the lure of an increased tax base and the desire not to anger local voters is all too great.

Reducing natural disaster losses in Canada means breaking the cycle – taking a link out of the chain of events that leads to losses.

Local governments eager for growth and the tax revenue that goes with it need to hold some significant portion of the downside risk in order to give them pause for thought.
floods  catastrophes  natural_calamities  design  insurance  public_policy  disasters  relief_recovery_reconstruction  sustainability  municipalities  skin_in_the_game  disincentives  Albert_Einstein  complex_problems  land_uses  moral_hazards  man-made  hazards  downside_risks 
may 2017 by jerryking
Perimeter Institute's formula for a calculated physics reboot - The Globe and Mail
IVAN SEMENIUK
WATERLOO, ONT. — The Globe and Mail
Published Tuesday, Jun. 23, 2015

“We want to reboot physics – globally,” says Neil Turok, Perimeter’s director and the driving force behind Convergence, a four-day physics summit that kicked off here on Sunday. Turok wants to channel the daring originality of the likes of: (a) Albert Einstein’s radical rethinking of gravity that gave us warped space and black holes; and (b), Emmy Noether’s first theorem, a tour de force of abstract reasoning that demonstrates the relationship between forms of symmetry in mathematics and the physical laws that govern the way the universe operates-- to help spark a another revolution.

The meeting’s premise is that theoretical physics has worked itself into the tall weeds, getting more complex and less connected to experiment than it ought to be. To get back out, Dr. Turok says, the field needs ideas as rich and startling as those that came from Einstein, Noether and their peers....The challenge in working with such individuals, says James Forrest, who runs the institute’s academic programs, is “how do you teach physics to the people who are already good at it?” It’s a dilemma universities seldom worry about – but for Perimeter, which aims to optimize the randomness of human brilliance, the question is crucial.

Another way in which the institute has tried to leverage the global talent pool is to bring in more female researchers. Women are conspicuously underrepresented in physics but through a funding stream called the Emmy Noether Circle the institute has significantly boosted its share of young women theorists.
Albert_Einstein  Perimeter_Institute  physics  Colleges_&_Universities  rebuilding  revitalization  reboot  physicists  women  Kitchener-Waterloo  randomness  talent_pools 
june 2015 by jerryking
How Not to Drown in Numbers - NYTimes.com
MAY 2, 2015| NYT |By ALEX PEYSAKHOVICH and SETH STEPHENS-DAVIDOWITZ.

If you’re trying to build a self-driving car or detect whether a picture has a cat in it, big data is amazing. But here’s a secret: If you’re trying to make important decisions about your health, wealth or happiness, big data is not enough.

The problem is this: The things we can measure are never exactly what we care about. Just trying to get a single, easy-to-measure number higher and higher (or lower and lower) doesn’t actually help us make the right choice. For this reason, the key question isn’t “What did I measure?” but “What did I miss?”...So what can big data do to help us make big decisions? One of us, Alex, is a data scientist at Facebook. The other, Seth, is a former data scientist at Google. There is a special sauce necessary to making big data work: surveys and the judgment of humans — two seemingly old-fashioned approaches that we will call small data....For one thing, many teams ended up going overboard on data. It was easy to measure offense and pitching, so some organizations ended up underestimating the importance of defense, which is harder to measure. In fact, in his book “The Signal and the Noise,” Nate Silver of fivethirtyeight.com estimates that the Oakland A’s were giving up 8 to 10 wins per year in the mid-1990s because of their lousy defense.

And data-driven teams found out the hard way that scouts were actually important...We are optimists about the potential of data to improve human lives. But the world is incredibly complicated. No one data set, no matter how big, is going to tell us exactly what we need. The new mountains of blunt data sets make human creativity, judgment, intuition and expertise more valuable, not less.

==============================================
From Market Research: Safety Not Always in Numbers | Qualtrics ☑
Author: Qualtrics|July 28, 2010

Albert Einstein once said, “Not everything that can be counted counts, and not everything that counts can be counted.” [Warning of the danger of overquantification) Although many market research experts would say that quantitative research is the safest bet when one has limited resources, it can be dangerous to assume that it is always the best option.
human_ingenuity  data  analytics  small_data  massive_data_sets  data_driven  information_overload  dark_data  measurements  creativity  judgment  intuition  Nate_Silver  expertise  datasets  information_gaps  unknowns  underestimation  infoliteracy  overlooked_opportunities  sense-making  easy-to-measure  Albert_Einstein  special_sauce  metrics  overlooked  defensive_tactics  emotional_intelligence  EQ  soft_skills  overquantification  false_confidence 
may 2015 by jerryking
Finding gems of insight from customer data
Dec. 16 2013 | The Globe and Mail | by AMANDA HAY.

"Albert Einstein – “If you can’t explain it to a six-year-old, you don’t understand it yourself.” It’s not enough to be able do the calculations, build the models, run the analyses, you have to be able to articulate and justify your methods simply. Clients want insights they can use to generate revenue. Understanding your client’s business is key so that you can communicate with them in meaningful terms."
customer_loyalty  customer_insights  massive_data_sets  Aimia  loyalty_management  data  analytics  Albert_Einstein  insights  Communicating_&_Connecting  storytelling 
december 2013 by jerryking
Einstein’s Secret to Amazing Problem Solving (and 10 Specific Ways You Can Use It)
Einstein is quoted as having said that if he had one hour to save the world he would spend fifty-five minutes defining the problem and only five minutes finding the solution.

The point: before jumping right into solving a problem, we should step back and invest time and effort to improve our understanding of it. Here are 10 strategies to see problems from many different perspectives and to master the most important step in problem solving: clearly defining the problem in the first place!
The Problem Is To Know What the Problem Is

The definition of the problem will be the focal point of all your problem-solving efforts.
1. Rephrase the Problem
2. Expose and Challenge Assumptions
3. Chunk Up
4. Chunk Down. From Engineering school--break a problem into its component sub-systems, solve at that level, and then combine mini solutions.
5. Find Multiple Perspectives
6. Use Effective Language Constructs
7. Make It Engaging
8. Reverse the Problem
9. Gather Facts
10. Problem-Solve Your Problem Statement
Albert_Einstein  creativity  critical_thinking  engineering  lifehacks  Philip_Mudd  problems  problem_definition  problem_framing  problem_solving  thinking  thinking_backwards  tips  uncharted_problems 
january 2012 by jerryking
Charlie Rose's Interview with Ray Dalio
October 20, 2011 | Charlie Rose Show | with Ray Dalio.

CHARLIE ROSE: And you always make a point that you know what you don`t know and that`s equally valuable.

RAY DALIO: More valuable. I want to say that -- so this is the whole philosophy. I -- I so, know that I can be wrong; and look, we all should recognize that we can be wrong. And if we recognize that we`re wrong and we worry about being wrong than what we should do is have a thoughtful dialogue....RAY DALIO: So the way I get to success. The way -- it`s not what I know. I`ve acquired some things that I know along the way and they`re helpful.

(CROSSTALK)

CHARLIE ROSE: It is -- it is -- it`s not what you know but it is --

(CROSSTALK)

RAY DALIO: It`s knowing what I don`t know or worrying that I won`t -- that I`ll be wrong that makes me find --

CHARLIE ROSE: Yes.

RAY DALIO: Well, I want people to criticize my point of view -- I want to hold down.

CHARLIE ROSE: Right.

RAY DALIO: Say I have a -- I think this but I may be wrong. And if you can attack what I`m saying -- in other words stress test what I`m saying -- I`ll learn....CHARLIE ROSE: And you have not been precise, and your assumptions are flawed.

RAY DALIO: Oh it`s so essential, right. There`s -- the -- the number one principle at our place is that if something doesn`t make sense to you, you have the right to explore it, to see if it makes sense.

I don`t want people around who do things that they don`t -- they don`t think makes sense because I`m going to have not-thinking people.

(CROSSTALK)

CHARLIE ROSE: Right.

RAY DALIO: So that they have not only the right, they have obligation. Don`t walk away thinking something`s wrong.

CHARLIE ROSE: Failure teaches you more than success?

RAY DALIO: Of course. One of my favorite books is "Einstein`s Mistakes."

CHARLIE ROSE: Right. And because it showed you that even Einstein, the most brilliant person of the century in common judgment made mistakes?

RAY DALIO: The great fallacy of all -- I think of all of mankind practically -- I mean that`s a big statement -- but the great fallacy is that people know more than what they do and there`s a discovery process and so when you look at -- that`s the process for learning.

The process for learning is to say "I don`t know." Like, I`m -- I`m totally comfortable being incompetent. If I -- if I -- I like being incompetent. I don`t mind being an incompetent. If I don`t -- how -- how much can you be competent about?

And so that whole notion of do you like learning? Do you like finding out what`s true and building on it without an ego? And that becomes the problem. How many statements do you listen to people that begin "I think this, I think that," where they should be asking "I wonder."
Ray_Dalio  interviews  truth-clarity  philanthropy  stress-tests  Charlie_Rose  truth-telling  Bridgewater  hedge_funds  deleveraging  organizational_culture  economics  unknowns  pretense_of_knowledge  Albert_Einstein  mistakes 
january 2012 by jerryking
EINSTEIN'S MISTAKES | Hans C. Ohanian
Although Einstein was the greatest genius of the twentieth century, many of his groundbreaking discoveries were blighted by mistakes, ranging from serious errors in mathematics to bad misconceptions in physics and failures to grasp the subtleties of his own creations. This forensic biography dissects Einstein’s scientific mistakes and places them in the context of his turbulent life and times. In lively, accessible prose, Hans C. Ohanian paints a fresh, insightful portrait of the real Einstein at work, in contrast to the uncritical celebrity worship found in many biographies.

Of the approximately 180 original scientific papers that Einstein published in his lifetime, about 40 are infested with mistakes. For instance, Einstein’s first mathematical proof of the famous formula E = mc2 was incomplete and only approximately valid; he struggled with this problem for many years, but he never found a complete proof (better mathematicians did). Einstein was often lured by irrational and mystical inspirations, but his extraordinary intuition about physics permitted him to discover profound truths despite—and sometimes because of—the mistakes he made along the way. He was a sleepwalker: his intuition told him where he needed to go, and he somehow managed to get there without quite knowing how.

As this book persuasively argues, the defining hallmark of Einstein’s genius was not any special mathematical ability but an uncanny talent to use his mistakes as stepping stones to formulate his revolutionary theories.
Albert_Einstein  books  book_reviews  Bridgewater  groundbreaking  hedge_funds  mistakes  Ray_Dalio 
january 2012 by jerryking
Market Research: Safety Not Always in Numbers | Qualtrics
Author: Qualtrics|July 28, 2010

Albert Einstein once said, “Not everything that can be counted counts, and not everything that counts can be counted.”

Although many market research experts would say that quantitative research is the safest bet when one has limited resources, it can be dangerous to assume that it is always the best option.

we put together a few guidelines for when one research method might be more useful than the other.

Quantitative:
* For trending purposes, i.e. trends in customer feedback
* Need for quick feedback
* Particularly useful when a company wants to determine how to increase market share
* Product feedback for consumer products

Qualitative:
* Help identify non-obvious ways to delight current customers
* Looking for information to grow an existing market or create a new one
* Market research follow-up questions when numeric scales can be misleading
* Messaging validation for products that are new to the market
* Market validation
* Understanding objections and barriers
* Product feedback for enterprise products

In the article, “Market Research: Quantitative or Qualitative,” the writer Diane Hagglund said, “sometimes numbers provide false confidence and obscure real opportunity.” [Definition of overquantification]

She later added in a follow-up article that her market research firm recommends web surveys as good vehicles for quantifying concepts that the researcher is familiar with and wants accurate percentages for each option.

“This is a valuable thing to do, especially for market sizing, external marketing and PR purpose,” Hagglund said. “But for finding out the answers that you don’t really know, start with qualitative research – and by all means do a web survey next to put those percentages in place once you know the statements to put the percentages with.”

In other words, it’s important to quantify your qualitative research and qualify your quantitative research
market_research  market_sizing  overquantification  storytelling  qualitative  quantitative  Scott_Anthony  dangers  research_methods  non-obvious  enterprise_clients  false_confidence  Albert_Einstein  easy-to-measure  delighting_customers  follow-up_questions 
december 2011 by jerryking
Address by Mike Lazaridis, PI Board Chair, to the Public Policy Forum - Perimeter Institute for Theoretical Physics
April 2, 2009 | Address by Mike Lazaridis, PI Board Chair, to the Public Policy Forum

First Principles: The Crazy Business of Doing Serious Science (Paperback)
by Howard Burton (Author) . It's an account of how the Perimeter Institute was built from scratch.

This year’s testimonial dinner was held on April 2, 2009, and honoured several Canadian leaders, including Mike Lazaridis, Founder and Board Chair of Perimeter Institute, who conveyed the importance of long-term thinking by those involved with shaping policy relating to science and technology. The following text, building on those remarks as reported by the national media, shares the messages provided to the PPF.
+++++++++++++++

So imagine this story. A granting council has been tasked with driving the economy, really building commerce and commercializing technology and doing important things for the country. And so, of course, what are they thinking? They’re thinking we need more horses, we need better ways to clean up the streets, and we need to figure out ways to build better stagecoaches and carriages. Now this physicist comes into the room and he sits down. And they ask him, "Dr. Einstein, why are you here?" He says, "Oh, I’d like to have an office and a stipend." "For what?" they want to know. So he explains, "Well, I need a desk and blackboard and maybe a shelf for my books and my papers. And I need a small stipend, so I can go to a few scientific conferences around the world and have a few postdoctoral researchers." They ask, "Why?" And he says: "Well, I have these ideas about light and it’s very complicated, but light can …" And the council members start wondering, "What’s that got to do with horses?"

So, that gentleman actually had to go and get a day job. He went to work at a patent office, where he came up with, a few years later, the four most important papers of all time. Ideas that transformed everything we knew and put mankind in a new direction. He came up with one of the basic ideas leading to quantum technology, when he predicted the quantum properties of light, explaining an observation called the photo-electric effect. He came up with special relativity, a new understanding of space and time. He also discovered that mass and energy are the same thing at a fundamental level. By thinking and calculating the way he did, he came up with E=mc2, the most famous equation of all time. These discoveries, over time, led to nuclear energy, semiconductors, computers, lasers, medical imaging, DVDs and much more. The powerful ideas happened from pure thought and research by someone who basically would have had to give up a comfortable salary at the patent office to take a research or teaching position at a university.

Now let’s fast-forward to today. We have all these issues. We’re running out of energy any way you slice it. And the energy sources that we have today are changing our climate and the environment catastrophically and irreparably. At the same time, we have this enormous need for value creation because our financial system basically ran onto a coral reef. We’re taking on debt to try to get ourselves off the reef, and there’s all this need for value creation and innovation. It’s kind of staring us in the face.

We only have to flashback to that gentleman thinking about light to realize that we need to fund our scientists and our researchers and our students. We not only need to fund them imaginatively, we need to have faith that what they are doing is going to be important in 20, 30, 40 or 50 years from now, and that we haven’t got a chance of understanding its relevance today.

And so we need to be very careful with policy, not to try to put everything in short-term context – not to try to figure out how something is only relevant today – because, if we do, we will make a mistake. We will go the wrong way. We will be investing in horses, carriages, and cleaning manure in the streets instead of fostering the research that can give rise to an idea or super technology that’s going to change the world.

Right now, there is some pandemonium in physics because we are running up against some paradoxes and some data that don’t make any sense. For example, Moore’s Law, which describes the miniaturization of computer chips, will reach its limit in 10 years. Everything we built our telecommunications industry and information age on is going to hit this limit, if we don’t find a new base. We need a new discovery. It’s going to happen, and we need to put major investments in these esoteric studies like quantum computing, quantum information science, quantum gravity, string theory and other areas, because I can guarantee you that one of the discoveries that will emerge is going to solve one of those scientific paradoxes and make sense of that weird data. And when that happens, 20 or 30 years from now, you won’t recognize things.
Albert_Einstein  Blackberry  books  broad-based_scientific_enquiry  first_principle  fundamental_discoveries  Mike_Lazaridis  miniaturization  Moore's_Law  paradoxes  Perimeter_Institute  physicists  public_policy  quantum_computing  RIM  semiconductors 
april 2009 by jerryking

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