Archive for the ‘Technology’ Category
AT&T throttles their “unlimited” customers routinely. (A few years back, a blog reader commented that “We can trust corporations.” I was stunned by the statement, but I realize that he probably meant that we can trust corporations to try to cheat us at every turn and lie repeatedly.”) Chris Welch reports at The Verge:
The Federal Trade Commission is suing AT&T because the second-largest US carrier throttles speeds of its unlimited data customers, a policy that the FTC describes as “deceptive” and “unfair.” In a press release, the FTC said AT&T has “misled millions of its smartphone customers” by slowing down their data speeds after they’ve used up a certain amount of data in a single month. AT&T has failed to make its throttling policies clear enough, according to the complaint. “The issue here is simple: ‘unlimited’ means unlimited,” said FTC Chairwoman Edith Ramirez. The Commission’s filing blasts AT&T for slowing customers down to the point where common tasks — watching video, streaming music, etc. — become “difficult or nearly impossible.”
Lesson to mobile companies from FTC’s 1st data throttling case: If u promise unlimited data, ur on hook to deliver: http://t.co/Q29FL8Am2V
— FTC (@FTC) October 28, 2014
AT&T no longer offers unlimited data plans; the carrier began slowing down speeds for heavy data users in 2011 — and it’s throttled a whole lot of people since then. 3.5 million unique customers have had speeds slowed more than 25 million times, per the FTC’s numbers. AT&T has drawn thousands of complaints over the policy from consumers who feel unlimited data should continue to be free of restrictions. Those complaints have been sent to the FTC, FCC, Better Business Bureau, and AT&T itself. AT&T is by no means alone in slowing down those on unlimited plans, but clearly the FTC isn’t happy with how the carrier has handled things in recent years. Today’s press release says the FTC worked closely with the FCC in piecing together the complaint. In response, AT&T offered the following, strongly-worded statement: . . .
In the meantime, of course, AT&T is one of the telecoms pressuring states to pass laws that make it illegal for municipalities to create gigabit networks for public use: worse than a dog in the manger, a pig in the manger.
Brian Fung also reports on this in the Washington Post:
AT&T broke the law when it slowed down mobile Internet speeds among customers who’ve paid for unlimited data, federal regulators said in a complaint unveiled Tuesday.
As many as 3.5 million individual AT&T customers were hit by the throttling more than 25 million times over the course of several years, the Federal Trade Commission alleges in its suit. In some cases, users’ speeds were cut by more than 90 percent. . .
And Elon Musk warns us that with AI we unleash the demon. Kevin Kelly describes in Wired exactly how the unleashing is being accomplished:
A few months ago I made the trek to the sylvan campus of the IBM research labs in Yorktown Heights, New York, to catch an early glimpse of the fast-arriving, long-overdue future of artificial intelligence. This was the home of Watson, the electronic genius that conquered Jeopardy! in 2011. The original Watson is still here—it’s about the size of a bedroom, with 10 upright, refrigerator-shaped machines forming the four walls. The tiny interior cavity gives technicians access to the jumble of wires and cables on the machines’ backs. It is surprisingly warm inside, as if the cluster were alive.
Today’s Watson is very different. It no longer exists solely within a wall of cabinets but is spread across a cloud of open-standard servers that run several hundred “instances” of the AI at once. Like all things cloudy, Watson is served to simultaneous customers anywhere in the world, who can access it using their phones, their desktops, or their own data servers. This kind of AI can be scaled up or down on demand. Because AI improves as people use it, Watson is always getting smarter; anything it learns in one instance can be immediately transferred to the others. And instead of one single program, it’s an aggregation of diverse software engines—its logic-deduction engine and its language-parsing engine might operate on different code, on different chips, in different locations—all cleverly integrated into a unified stream of intelligence.
Consumers can tap into that always-on intelligence directly, but also through third-party apps that harness the power of this AI cloud. Like many parents of a bright mind, IBM would like Watson to pursue a medical career, so it should come as no surprise that one of the apps under development is a medical-diagnosis tool. Most of the previous attempts to make a diagnostic AI have been pathetic failures, but Watson really works. When, in plain English, I give it the symptoms of a disease I once contracted in India, it gives me a list of hunches, ranked from most to least probable. The most likely cause, it declares, is Giardia—the correct answer. This expertise isn’t yet available to patients directly; IBM provides access to Watson’s intelligence to partners, helping them develop user-friendly interfaces for subscribing doctors and hospitals. “I believe something like Watson will soon be the world’s best diagnostician—whether machine or human,” says Alan Greene, chief medical officer of Scanadu, a startup that is building a diagnostic device inspired by the Star Trek medical tricorder and powered by a cloud AI. “At the rate AI technology is improving, a kid born today will rarely need to see a doctor to get a diagnosis by the time they are an adult.”
Medicine is only the beginning. All the major cloud companies, plus dozens of startups, are in a mad rush to launch a Watson-like cognitive service. According to quantitative analysis firm Quid, AI has attracted more than $17 billion in investments since 2009. Last year alone more than $2 billion was invested in 322 companies with AI-like technology. Facebook and Google have recruited researchers to join their in-house AI research teams. Yahoo, Intel, Dropbox, LinkedIn, Pinterest, and Twitter have all purchased AI companies since last year. Private investment in the AI sector has been expanding 62 percent a year on average for the past four years, a rate that is expected to continue.
Amid all this activity, a picture of our AI future is coming into view, and it is not the HAL 9000—a discrete machine animated by a charismatic (yet potentially homicidal) humanlike consciousness—or a Singularitan rapture of superintelligence. The AI on the horizon looks more like Amazon Web Services—cheap, reliable, industrial-grade digital smartness running behind everything, and almost invisible except when it blinks off. This common utility will serve you as much IQ as you want but no more than you need. Like all utilities, AI will be supremely boring, even as it transforms the Internet, the global economy, and civilization. It will enliven inert objects, much as electricity did more than a century ago. Everything that we formerly electrified we will now cognitize. This new utilitarian AI will also augment us individually as people (deepening our memory, speeding our recognition) and collectively as a species. There is almost nothing we can think of that cannot be made new, different, or interesting by infusing it with some extra IQ. In fact, the business plans of the next 10,000 startups are easy to forecast: Take X and add AI. This is a big deal, and now it’s here.
Around 2002 I attended a small party for Google—before its IPO, when it only focused on search. I struck up a conversation with Larry Page, Google’s brilliant cofounder, who became the company’s CEO in 2011. “Larry, I still don’t get it. There are so many search companies. Web search, for free? Where does that get you?” My unimaginative blindness is solid evidence that predicting is hard, especially about the future, but in my defense this was before Google had ramped up its ad-auction scheme to generate real income, long before YouTube or any other major acquisitions. I was not the only avid user of its search site who thought it would not last long. But Page’s reply has always stuck with me: “Oh, we’re really making an AI.”
I’ve thought a lot about that conversation over the past few years as Google has bought 14 AI and robotics companies. At first glance, you might think that Google is beefing up its AI portfolio to improve its search capabilities, since search contributes 80 percent of its revenue. But I think that’s backward. Rather than use AI to make its search better, Google is using search to make its AI better. Every time you type a query, click on a search-generated link, or create a link on the web, you are training the Google AI. When you type “Easter Bunny” into the image search bar and then click on the most Easter Bunny-looking image, you are teaching the AI what an Easter bunny looks like. Each of the 12.1 billion queries that Google’s 1.2 billion searchers conduct each day tutor the deep-learning AI over and over again. With another 10 years of steady improvements to its AI algorithms, plus a thousand-fold more data and 100 times more computing resources, Google will have an unrivaled AI. My prediction: By 2024, Google’s main product will not be search but AI.
This is the point where it is entirely appropriate to be skeptical. For almost 60 years, AI researchers have predicted that AI is right around the corner, yet until a few years ago it seemed as stuck in the future as ever. There was even a term coined to describe this era of meager results and even more meager research funding: the AI winter. Has anything really changed?
Yes. Three recent breakthroughs have unleashed the long-awaited arrival of artificial intelligence: . . .
This is something that I believe should be stopped. Elizabeth Dwoskin writes at the Wall Street Journal:
A new study found that e-commerce sites vary online pricing depending on whether customers use mobile or desktop devices, iOS or Android, and other factors.
Travel-booking sites Cheaptickets and Orbitz, for instance, charged some users searching hotel rates an average $12 more per night if they weren’t logged into the sites. Travelocity charged users of Apple’s iOS mobile operating system $15 less for hotels than other users. Users of mobile devices who surfed to Home Depot saw products that were roughly $100 more expensive than those offered to desktop-computer users. Expedia and Hotels.com steered users at random to pricier products, according to researchers at Northeastern University’s College of Information science.
For the study, the Northeastern researchers recruited 300 helpers on the task-outsourcing site Amazon Mechanical Turk and noted their experience on different sites. They created hundreds of fake accounts to evaluate the effect of historical clicks and purchases. Did consumers who spent less money in the past get better deals? Were consumers who bought pricey tickets more likely to be charged higher prices? The researchers didn’t examine the impact of overall Web browsing because they didn’t know whether a particular e-commerce site tracked individual visitors as they browsed other sites.
Discriminatory pricing isn’t illegal. It happens all the time when consumers get loyalty cards, coupons, or promotion codes. But consumers have protested when it’s not transparent. How can you shop for the best deal if you don’t know the rules of the game?
Even in the physical world, though, pricing can be less transparent than it appears. Stores may hold flash sales available only to customers who happen to be shopping at the time. They may mail promotion codes and coupons to some people and not others. Is that really so different from what’s happening online? . . .
Later in the article:
Expedia and Hotels.com were researching the impact of pricing on sales by showing different prices to different groups of shoppers, a practice known as A/B testing — essentially conducting market research in real time. Without such testing, Expedia and other vendors have argued, it would be harder for them to run their business.
It’s good to see local governments actually working to serve the public instead of kowtowing to big business. Jason Koebler writes at Motherboard:
At least 20 additional American cities have expressed a formal interest in joining a coalition that’s dedicated to bringing gigabit internet speeds to their residents by any means necessary—even if it means building the infrastructure themselves.
The Next Centuries Cities coalition launched last week with an impressive list of 32 cities in 19 states who recognize that fast internet speeds unencumbered by fast lanes or other tiered systems are necessary to keep residents and businesses happy.
The group includes cities that have built their own municipal broadband networks, cities that want to build their own, and cities that have worked with companies such as Google to bring fiber, gigabit-speed internet to their residents—the idea being that cities that don’t have ultrafast internet can learn how to jump through legislative and logistical hoops from those who have been there before.
The group’s launch event was so successful that Deb Socia, the group’s executive director, says at least 20 more cities have already asked to join, and that she expects the coalition to grow “substantially” in the next couple months.
“It’s already generated a lot of interest in other cities, so it justifies what we’ve been thinking all along—that people really want this,” she told me in a phone interview. “Over the next month or two we’ll formalize it. I think we’ll increase our numbers pretty substantially.”
Socia wouldn’t tell me what cities have expressed interest, because they haven’t formally joined yet.
These new cities would join others such as Chattanooga, Tennessee, and Wilson, North Carolina—two cities that have built their own broadband networks but are hoping to expand them to neighboring communities despite state laws being on the books that prevent them from legally doing so. To circumvent that problem, both cities have filed petitions with the Federal Communications Commission to override state restrictions.
“One of our principles is that communities must enjoy self determination,” she said. “Even if you’re in a city with an anti [municipal broadband] law, we think that decisions are made best when they’re made close to the people who are impacted.”
Socia said she believes that over the last several years, cities have really begun recognizing that if they are unable to offer their residents fast, reliable internet (or if big telecom is unwilling to), their growth and economic prosperity will stagnate. . .
More info here. Cheapest desk in the line is $490.
Induction stovetops don’t get hot—indeed, in looking at them you have no idea whether they’re off or on, and if so, at how high a heat.
Samsung has a range that uses blue LEDs to cast skeumorphic flames around the bottom of the pan, their size showing the level of heat: bigger flame = hotter. Cool, eh?
UPDATE: Reader Chris R from Thailand emailed me the solution. It’s a POODLE attack. He suggested a number of add-ons, two of which I already had, but they were not sufficient:
This I already had: *Adblock Plus**2.6*
This I added: *Adblock Plus Pop-up Addon 0.9.2*
This I added: *No Google Analytics 0.6*
This I already had: *Disconnect* 3.14
This I added: *SSL Version Control 0.2* from Firefox (I think this foils the POODLE attack.)
Once those were in place, the problem cleared. /UPDATE
Original post follows:
I use two browsers so I can flip between them for blogging. I browse in Google Chrome and blog in Firefox.
Over the past several days I’ve noticed that Firefox connection times (for all the little connections that seem to be require for any action) are WAY longer th han they used to be—like, I have to go do something else—and Google Chrome, where I’m now blogging, does not have that problem. I’m on AT&T U-verse. Are they starting to do the “fast lane/slow lane” thing? And Firefox is definitely sloweMaybe it’s Firefox, but the footer message on the screen pops up little messsages like “waiting on www. google.com,” “waiting on 0gravatar.com,” etc. Lots of waiting.
Somehow this reminded me of a piece of IBM folklore, which may well be true. One high-placed marketing guy (and Marketing ran IBM) was looking around the computer room and noticed that most of the (very expensive in monthly lease—IBM didn’t sell computers in those days) tape drives were red lighted (inactive), very few being green-lighted (in use).
The green light read “In Use,” and the red light, naturally enough to the engineering mind, read “Idle.”
The wording on the red lights was quickly changed to “Ready.”