Here are the first three:

1. Radio-frequency emissions from cell phones, laptops and other electronics can occur at the same frequencies used by aircraft communication, navigation and surveillance radio receivers. These emissions could cause fluctuations in navigation readouts, problems with other flight displays, and interference with air traffic communications.

2. It’s less risky to let passengers use portable electronics (with the exception of cell phones) at cruising altitudes above 3,000 kilometers because the flight crew would have more time to diagnose and address any possible interference than they would during takeoff or landing.

3. Because passengers bring such a variety of portable electronics onboard in so many different states of function or disrepair, the FAA can’t assure that none of them will interfere with flight instrumentation. The agency thus tells carriers to prohibit their use completely during critical phases of flight.

James Fallows, please take note.

A wise move, considering what the company’s prototype Android handset looked likebefore the debut of the iPhone, and what the first Android smartphone — the HTC Dream — looked like when it finally arrived at market.

And add “what today’s Android phones look like”.

He is my hero, as he is to many others on this planet. So much has been said about him in last few hours. Much more is going to be said in years to come. I will only quote himself in this post.

Do you want to spend the rest of your life selling sugared water or do you want a chance to change the world?
- A comment he made in persuading John Sculley to become Apple’s CEO, as quoted in Odyssey : Pepsi to Apple : A Journey of Adventure, Ideas, and the Future (1987) by John Sculley and John A. Byrne

“The cure for Apple is not cost-cutting. The cure for Apple is to innovate its way out of its current predicament.” [Apple Confidential: The Real Story of Apple Computer Inc., May 1999]

Remembering that I’ll be dead soon is the most important tool I’ve ever encountered to help me make the big choices in life. Because almost everything – all external expectations, all pride, all fear of embarrassment or failure – these things just fall away in the face of death, leaving only what is truly important. Remembering that you are going to die is the best way I know to avoid the trap of thinking you have something to lose. You are already naked. There is no reason not to follow your heart. … stay hungry, stay foolish.
– Stanford commencement speech 2005

“Your work is going to fill a large part of your life, and the only way to be truly satisfied is to do what you believe is great work. And the only way to do great work is to love what you do. If you haven’t found it yet, keep looking. Don’t settle. As with all matters of the heart, you’ll know when you find it. And, like any great relationship, it just gets better and better as the years roll on. So keep looking until you find it. Don’t settle.”
– Stanford commencement speech 2005

“Picasso had a saying: ‘Good artists copy, great artists steal.’ We have always been shameless about stealing great ideas…I think part of what made the Macintosh great was that the people working on it were musicians, poets, artists, zoologists and historians who also happened to be the best computer scientists in the world.”
– 1994

Q: There’s a lot of symbolism to your return. Is that going to be enough to reinvigorate the company with a sense of magic?
“You’re missing it. This is not a one-man show. What’s reinvigorating this company is two things: One, there’s a lot of really talented people in this company who listened to the world tell them they were losers for a couple of years, and some of them were on the verge of starting to believe it themselves. But they’re not losers. What they didn’t have was a good set of coaches, a good plan. A good senior management team. But they have that now.” [BusinessWeek, May 25, 1998]

As Walt Mossberg put it:

Steve Jobs’s resignation as chief executive officer of Apple is the end of an extraordinary era, not just for Apple, but for the global technology industry in general.

Most people are lucky if they can change the world in one important way, but Jobs, in multiple stages of his business career, changed global technology, media and lifestyles in multiple ways on multiple occasions.

He did it because he was willing to take big risks on new ideas, and not be satisfied with small innovations fed by market research. He also insisted on high quality and had the guts to leave out features others found essential and to kill technologies, like the floppy drive and the removable battery, he decided were no longer needed. And he has been a brilliant marketer, personally passionate about his products.

A lot of people are saying that Tim Cook might be good leader, but it seems everyone agrees that Jobs left a shoe no one can fit in.

Nicholas Thompson at New Yorker said:

The big question now is whether Tim Cook, Jobs’s successor, can succeed. I’m sure he’s good, and the people around him are good too. But he won’t do as well, for at least one reason. Steve Jobs built a cult of personality that gave him power. Many of Apple’s future fights will be about content. Which tech companies will get the rights to show what things, in what ways, on their devices? Jobs had a power that Cook could not possibly have here, just because he was Jobs. He could summon anyone he wanted to meet with him; he could get journalists to write whatever he wanted them to write; and, if he and Apple threatened to screw you over, you had to believe them.

All best wishes to Steve. Like many in entertainment industry say: great legends die young. He is not exactly young, and he is not dying, yet. He is a legend.

Our society has become more and more unequal.

When so much income goes to the top, the middle class doesn’t have enough purchasing power to keep the economy going without sinking ever more deeply into debt — which, as we’ve seen, ends badly. An economy so dependent on the spending of a few is also prone to great booms and busts. The rich splurge and speculate when their savings are doing well. But when the values of their assets tumble, they pull back. That can lead to wild gyrations. Sound familiar?

The economy won’t really bounce back until America’s surge toward inequality is reversed.

Earlier this month I derided HP, at least on the consumer side of things, as being essentially a printer company which liked to pretend it was more for the sake of impressing its shareholders. Instead of being an active participant in the PC market, it sells Windows-based PCs manufactured by a third party which have no connection to HP itself beyond the logo on the minitower. Instead of having its own role in the MP3 player market years ago, it literally licensed the iPod from Apple in a move which took HP nowhere. And instead of trying to be a player in the smartphone and tablet market, it bought a dying company like Palm and rebranded it as an HP product while giving Rubinstein a bit of funding so he could carry out his failed webOS experiment a bit longer. HP could brag to its shareholders that it was making bold moves in the mobile device market, just like it could pretend it was a real computer maker. But now the computers, the smartphones, the tablets, the in-house mobile operating system are all being tossed out.

So what’s really going on? Sounds like HP has reached a point where it’s ready to admit that its consumer-level forte really does consist primarily of peripherals like printers and scanners (I’ve got a very pleasing HP laser printer sitting right here, lest ye think I’m some kind of HP hater). That means the pretend-businesses like tablets, and the disconnected businesses like PCs had to go. Of course this could just be a matter of HP clearing the decks so it can make another pointless acquisition and pretend to be moving into yet another trendy market. But really, with smartphones and tablets and even computers and laptops now off HP’s roster, what’s left to move into? Sounds like maybe, for the first time in a long time, HP has decided that honesty about what it really is as a consumer company is the best policy. 

Can Math Beat Financial Markets?

Mathematical models help assess risk, but woe betide those who think math can predict stock market gains and losses

By David Biello | Tuesday, August 16, 2011 |13

MARKET MATH: Can mathematical models predict financial market fluctuations?Image: © iStockphoto.com

Wall Street’s wild swings last week helped skew both retirement portfolios and mathematical models of the financial markets. After all, a standard Gaussian function—a bell curve—would predict that such extreme dips and rises would be exceedingly rare and not prone to following one after the other on succeeding days.

Gaussian functions might be able to describe the distribution of grades in a big college class, with most students getting, say, B–/C+, and enable you to predict how many students will get A’s or fail. But evidently, they do a poor job at explaining steep fluctuations in stock prices, although some economists and modelers think they are the best tool available to describe financial markets.

So can any math accurately describe market behavior and enable you to beat it? To find out, Scientific American spoke with statistical physicist H. Eugene Stanley of Boston University, a proponent of applying the approaches and concepts of physics to economics.

[An edited transcript of the interview follows.]

Can mathematical models beat markets?
They haven’t yet. Science is about empirical fact. There is no question that optimistic people think they can beat the market, but they don’t do it consistently with mathematical models. No model can consistently predict the future. It can’t possibly be.

So what can math predict?
What you can do is predict the risk of a given event. The risk just means the chance that something bad will happen, for example. That you can do with increasing accuracy because we have more and more data. It’s like insurance companies: they cannot tell you when you are going to die, but they can predict the risk that you will die given the right information. You can do the same thing with stocks. If you lose less, you get ahead of those who lose more.

Why do economists and “quants”—those who use quantitative analysis to make financial trades—have such faith in their mathematical models then?
If they’re just to reduce risk, then they’re very valuable. If you’re worried, for example, about the segment of the Chinese economy that deals with steel, you make a model of what that whole market is all about and then you see if we did this what would likely happen. They’re right some of the time. It’s better than nothing.

But when they have excessive faith in these models, it’s not justified. Math starts with assumptions; the real world does not work that way. Economics, which calls itself a science, too often doesn’t start with looking at empirical facts in any great detail. Fifteen years ago even the idea of looking at huge amounts of data did not exist. With a limited amount of data, the chance of a rare event is very low, which gave some economists a false sense of security that long-tail events did not exist.

Why do you argue that financial markets are ruled not by Gaussian functions but by power laws—relations in which the frequency of one event varies as a power of some attribute of that event and are generally more L-shape than bell shape?
For anything that is random and fluctuating, like a financial market, a Gaussian function is a wonderful way to make a histogram of the outcome. If the things that fluctuate are not correlated at all with one another, then it’s demonstrable that a Gaussian function is the correct histogram.

The catch is: in a financial market, everything is correlated. The proof of that is that if the stock market were Gaussian, then you’d never have a flash crash. A Gaussian crash would be an event that goes out to maybe five standard deviations [that is, a rarity on par with one part in two million]. In markets, this is simply not true. There are events that are 100 standard deviations. Every economist knows for sure that these rare events occur and cannot be described by a Gaussian function. The question is: What are you going to do about it?

Power laws are simply way more accurate. If you don’t know the risk, you are not going to make the right decision, and the economy is at risk from these big fluctuations. It’s no surprise when they come. The only reason you have to wait awhile is because they are rare. Knowing that they will happen forces anyone prudent to have a plan for what to do if it happens.

The idea that it would be a power law that describes all the events, the tails and the middle is really a major contribution. It allows one to quantify risk. You can read off a plot of the law the numerical chance for a downturn of any given size. It’s very small for something that is 100 standard deviations out but not so small for something that is 10 standard deviations out. In fact, the S&P 500 fluctuations—which if they were Gaussian, would pretty much be constrained to plus or minus five standard deviations—you find, in a 10-year period, the number of events that exceed five standard deviations is not just one, it’s 64. And the number that exceeds 10 standard deviations is eight, and there was one event that exceeded 20 standard deviations. It looks like a power law, and that’s what it is demonstrated to be when every trade of every stock is analyzed.

There are an awful lot of rare events and they’re all ignored. This is not the best way I want my retirement funds invested.

Are algorithm-based trading programs causing these fluctuations, like in the “flash crash” in 2010, when the Dow Jones Industrial Index momentarily dropped roughly 1,000 points in minutes?
There is no question that a huge percentage of trades are done electronically by algorithms. Of course, the flash crash was triggered by that. But we had problems before [algorithm-based trading programs]. We’ve had lots of crashes.

The speed of a flash crash is vastly greater than the speed of crashes before. Things move fast because everybody knows everything all the time. In that sense, it’s not the algorithm-based trading that moves the markets, it’s that the information is so instantaneous.

Does this understanding of financial markets suggest anything about how to invest, like when to buy or sell?
It can’t predict the future. The key thing is that it tells you not to listen to those who tell you now is the time to buy or sell if their advice is based on something wrong, as it sometimes is.

Is this all a result of the interlinked global financial system?
I believe so. The finances of every country are interlinked to the finances of every other country and, because they are interlinked, if one key players goes down then the other players know things aren’t going to be as good. A useful analogy is coupled networks, which are far more susceptible to a cascade of failures than uncoupled networks.

Is there a remedy for preventing markets from affecting one another?
It would be nice if there were, but the system is going to be more fragile because it is so interlinked. Maybe something like a circuit breaker, something that slows trading down? There are two answers to that: one is that [a circuit breaker] is good and allows people to cool off, to realize the economy is still there. The opposite view is that we just pick up where we left off.

For something like the flash crash, you might try it out. If you lose five to 10 percent in the space of an hour, then you stop the market. Of course, stopping the market at a low point could do the opposite and convince everyone something bad is happening.

Can anything predict the market?
Let me tell you a story: two to the power of 10 is 1,024. One way to predict the market is to call up 1,024 trading places and tell half of them by week’s end the market will be up and the other half that the market will be down. At the end of the week, forget about the half that knows you were wrong. Keep doing that for 10 weeks and, at the end, you will have called the market correctly for one person who will think you are a genius.

The economy is a very complex system—like the weather—that we understand bits of. You sure as heck can’t decide on a Monday whether the weather will be nice on the coming weekend. No one can predict where the market will be at the end of the week.