We realized recently that a lot of people don’t understand very well what Y Combinator does, so I wrote something explaining that in detail. Since YC has been shaped by the needs of hundreds of early stage startups, this should be interesting not just to potential applicants but to anyone curious about startups, because a portrait of YC is in some ways the complement of a portrait of the average startup.
Y Combinator runs two three-month funding cycles a year, one from January through March and one from June through August. We ask the founders of each startup we fund to move to the Bay Area for the duration of their cycle, during which we work intensively with them to get the company into the best shape possible. Each cycle culminates in an event called Demo Day, at which the startups present to an audience that now includes most of the world’s top startup investors. (…)
If the startup either hasn’t decided what to work on or wants to change their idea, then we talk about what the company should do. That usually means satisfying two constraints: something (1) users would want, that (2) the founders of this startup would be good at building. We have these types of conversations surprisingly often. Startups modify or even replace their ideas much more than outsiders realize.
Laws banning texting or talking on a mobile phone while driving don’t reduce car accidents.
“In fact,” concludes the US Highway Loss Data Institute, “[texting] bans are associated with a slight increase in the frequency of insurance claims filed under collision coverage for damage to vehicles in crashes.”
This counter-intuitive revelation comes from a study by the HLDI, which compared insurance-claim data in states that enacted texting bans with the same data in states where no such laws exist. Data from after the bans took affect was also compared to stats before the bans took effect.
Texting bans did not reduce accident rates, and in some states the accident rates increased after the bans went into effect. “In California, Louisiana and Minnesota,” the HDLI reports, “the bans are associated with small but statistically significant increases in collision claims (7.6%, 6.7%, and 8.9%, respectively).”
It has always been tough for literary fiction writers to get their work published by the top publishing houses. But the digital revolution that is disrupting the economic model of the book industry is having an outsize impact on the careers of literary writers.
Priced much lower than hardcovers, many e-books generate less income for publishers. And big retailers are buying fewer titles. As a result, the publishers who nurtured generations of America’s top literary-fiction writers are approving fewer book deals and signing fewer new writers. Most of those getting published are receiving smaller advances.
“Advances are down, and there aren’t as many debuts as before,” says Ira Silverberg, a well-known literary agent. “We’re all trying to figure out what the business is as it goes through this digital disruption.”
Much as cheap digital-music downloads have meant that fewer bands can earn a living from record-company deals, fewer literary authors will be able to support themselves as e-books win acceptance, publishers and agents say.
The world is more complex and less controllable than ‘rational’ planners believe. There are two main reasons for this. First, as behavioural economics tells us, agents - be they individuals, institutions or governments - do not necessarily behave rationally; their responses when confronted by new information or a different set of incentives may be hard to anticipate. Second, as the study of networks shows, our tastes and preferences can be altered directly by the behaviour of others and can change over time. Natural selection is now believed to favour social learning strategies that specify when and whom to copy. It seems that humans are particularly adept at this. (…)
In the late 1990s, a group of epidemiologists, sociologists and physicists analysed a database of individuals and their sexual contacts. The results were published in Nature, one of the world’s leading scientific journals. They found that most people have only a few sexual partners, but that a small number have hundreds or even thousands. The real originality of the paper was its finding that the structure of the pattern of the contacts closely reflected a recently discovered type of network that is described as ‘scale-free’. Such networks are important in the natural sciences, and more of them - at least, good approximations of the scale-free pattern - have been discovered in the human world. The internet, for example, has these properties. A few sites receive a massive number of hits, while most get very few. A whole industry has grown up in American marketing circles trying to find these influential ‘hubs’. (…)
Another important type of network that makes life even more complicated is the ‘small-world’ network. When we delve into the maths, there are considerable similarities between a scale-free and a small-world network. But their basic social structure is different. In the scale-free network, there are a few agents who have huge potential influence. The small world is much more like overlapping sets of ‘friends of friends’. The additional feature is that, while no one has a large number of connections, a few agents may have ‘long-range’ connections to others who are remote from their immediate cliques. However, these individuals may be even harder to identify in practice than the hubs of a scale-free network, precisely because they themselves are not distinguished by having an unusual number of connections.
Rumors of the web’s memory are greatly exaggerated.
Jeffrey Rosen has an engaging piece in the Times about privacy and the web that touches on issues of forgiveness and reputation and how the Internet has basically screwed that up for all of us; the upshot being that because your Facebook profile never really goes away, your sins are plastered on the world’s largest wall for all to see forever. Here’s the thing. They’re probably not. Forever, that is.
A Michigan company announced that for the low, low price of $1.99, you could have a lifetime license to use something you might not have thought you needed - a new punctuation mark.
Japan’s surprise intervention in currency markets has caught some of the world’s largest hedge funds by surprise, with big names suffering sharp reversals as the yen tumbled.
The Japanese currency saw its biggest daily fall this year on Wednesday, dropping more than 3 per cent from a 15-year high of Y82.88 against the dollar after the Japanese ministry of finance said that it had staged an intervention in the market, the first such action by Tokyo in six years.
Three London-based hedge funds suffered on their bullish yen positions, according to people familiar with the funds’ performances. All three funds use computer models to automatically spot and ride market trends, making them vulnerable to unexpected events including surprise action by governments and central banks. Other funds understood to have been hit by the intervention include several large global macro hedge funds and currency trading specialists.
Reverse-engineering the human brain so we can simulate it using computers may be just two decades away, says Ray Kurzweil, artificial intelligence expert and author of the best-selling book The Singularity is Near.
It would be the first step toward creating machines that are more powerful than the human brain. These supercomputers could be networked into a cloud computing architecture to amplify their processing capabilities. Meanwhile, algorithms that power them could get more intelligent. Together these could create the ultimate machine that can help us handle the challenges of the future, says Kurzweil.
related { The Man Who Made a Copy of Himself. A Japanese roboticist is building androids to understand humans–starting with himself. | ieee Spectrum | full story }
Although the audio program Auto-Tune is best known for the singing-through-a-fan, robotic vocal style that has dominated pop radio in recent years with stars like Lady Gaga, T-Pain and countless others, Auto-Tune is in fact widely used in the studio and at concerts to make artists’ sound pitch-perfect.
“Quite frankly, [use of Auto-Tune] happens on almost all vocal performances you hear on the radio,” said Marco Alpert, vice president of marketing for Antares Audio Technologies, the company that holds the trademark and patent for Auto-Tune.
The beauty of Auto-Tune, Alpert said, is that instead of an artist having to sing take after take, struggling to get through a song flawlessly, Auto-Tune can clean up small goofs. (…)
Auto-Tune’s invention sprung from a quite unrelated field: prospecting for oil underground using sound waves. Andy Hildebrand, a geophysicist who worked with Exxon, came up with a technique called autocorrelation to interpret these waves. During the 1990s, Hildebrand founded the company that later became Antares, and he applied his tools to voices.
The recording industry pounced on the technology, and the first song credited (or bemoaned) for introducing Auto-Tune to the masses was Cher’s 1998 hit “Believe.”
Although a success with audio engineers, Auto-Tune remained largely out of sight until 2003 when rhythm and blues crooner T-Pain discovered its voice-altering effects.
Four dozen Prince George’s County police cadets had searched a wooded area in Glenn Dale for the BlackBerry of a woman who had been killed in her Upper Marlboro home. They found nothing.
Five days later, a county homicide detective, Benjamin Brown, the lead investigator into the strangulation of Antoinette Renee Chase, started a weekend night shift by driving back to the area. Brown suspected Chase’s husband but needed evidence before he could put him in handcuffs.
Brown, a Boy Scout leader who attained the rank of Eagle Scout, knows maps and Global Positioning System devices. The day of the slaying, the victim’s BlackBerry had made or received a phone call that placed the device within 200 meters of a particular location in Glenn Dale. Brown plugged longitude and latitude coordinates into his GPS device and identified an area about 300 meters from where the cadets had searched.
Behind a strip shopping mall, the detective inspected another wooded area. Nothing. He retreated to the shopping mall’s asphalt and, using a screwdriver, pried open a heavy metal storm drain cover. Then a second. Then a third. Jackpot.
On a ledge, Brown saw a plastic bag. Inside the bag, he found a purse that belonged to Antoinette Chase. At the bottom of the storm drain, Brown spotted another plastic bag, which had water shoes and work gloves. The shoes were the same size as those worn by Antoinette’s husband, Spencer Ellsworth Chase, according to court testimony. The work gloves contained the DNA of both Chases, according to testimony.
The future of humanity is often viewed as a topic for idle speculation. Yet our beliefs and assumptions on this subject matter shape decisions in both our personal lives and public policy – decisions that have very real and sometimes unfortunate consequences. It is therefore practically important to try to develop a realistic mode of futuristic thought about big picture questions for humanity.
This paper sketches an overview of some recent attempts in this direction, and it offers a brief discussion of four families of scenarios for humanity’s future: extinction, recurrent collapse, plateau, and posthumanity. (…)
Predictability does not necessarily fall off with temporal distance. It may be highly unpredictable where a traveler will be one hour after the start of her journey, yet predictable that after five hours she will be at her destination. The very long-term future of humanity may be relatively easy to predict, being a matter amenable to study by the natural sciences, particularly cosmology (physical eschatology). And for there to be a degree of predictability, it is not necessary that it be possible to identify one specific scenario as what will definitely happen. If there is at least some scenario that can be ruled out, that is also a degree of predictability. (…)
Most differences between our lives and the lives of our hunter-gatherer forebears are ultimately tied to technology, especially if we understand “technology” in its broadest sense, to include not only gadgets and machines but also techniques, processes, and institutions. In this wide sense we could say that technology is the sum total of instrumentally useful culturally-transmissible information. Language is a technology in this sense, along with tractors, machine guns, sorting algorithms, double-entry bookkeeping, and Robert’s Rules of Order. (…)
Supposing that some perceptive observer in the past had noticed some instance of directionality – be it a technological, cultural, or social trend – the question would have remained whether the detected directionality was a global feature or a mere local pattern. In a cyclical view of history, for example, there can be long stretches of steady cumulative development of technology or other factors. Within a period, there is clear directionality; yet each flood of growth is followed by an ebb of decay, returning things to where they stood at the beginning of the cycle. Strong local directionality is thus compatible with the view that, globally, history moves in circles and never really gets anywhere. If the periodicity is assumed to go on forever, a form of eternal recurrence would follow.
It’s 1 p.m. on a Thursday and Dianne Bates, 40, juggles three screens. She listens to a few songs on her iPod, then taps out a quick e-mail on her iPhone and turns her attention to the high-definition television.
Just another day at the gym.
The technology makes the tiniest windows of time entertaining, and potentially productive. But scientists point to an unanticipated side effect: when people keep their brains busy with digital input, they are forfeiting downtime that could allow them to better learn and remember information, or come up with new ideas. (…)
At the University of California, San Francisco, scientists have found that when rats have a new experience, like exploring an unfamiliar area, their brains show new patterns of activity. But only when the rats take a break from their exploration do they process those patterns in a way that seems to create a persistent memory of the experience.
The researchers suspect that the findings also apply to how humans learn.
I wrote a few days ago about the Intel anti-trust settlement with the Federal Trade Commission. Those words stand unchanged but some readers have asked for more so I have given the deal further thought and have what might be a better context in which to place it — Too Big to Fail. This isn’t “too big to fail” in the Bush/Obama big bank context in which failing and stupid institutions are saved at any cost to the public. Intel, in contrast, literally is too big to fail, at least right now.
Everything about the Intel/FTC settlement screams of one thing — Microsoft. Redmond’s multi-year nightmare with the FTC, DoJ, and the attorneys-general of several dozen states wasn’t lost on Intel, which is a more rational company and doesn’t want a Microsoft-like anti-trust experience. Both companies are guilty and both are paying something for that guilt, but Intel clearly wants to avoid the decade of pain and distraction suffered by Microsoft.
For the record, Intel admitted no wrong-doing in the settlement. But they also promised to specifically change their behavior.
What this settlement (and the previous one with AMD) does for Intel is clear the decks for future action. Now Intel can attack new market segments and be aggressive in existing market segments within the rules of the FTC deal.
Microsoft was paralyzed with the FTC breathing down its neck. Intel is not paralyzed.
Roughly $2 billion in payouts and Intel is a free bird — a rich free bird at that — having proved that crime does pay.
We are about to get a very different kind of Internet, one replete with huge potential and danger. The spread of cloud computing will allow much greater personalisation and mobility, constant real time connection and easier collaboration. Cloud computing will give rise to a cloud culture. (…)
In the world of cloud computing our data — emails, documents, pictures, songs — would be stored remotely in a digital cloud hanging above us, always there for us to access from any device we like: computer, television, games console, handheld and mobile, embedded in our kitchen table, bathroom mirror or car dashboard. We should be able to access our data from anywhere, thanks to always on broadband and draw down as much or as little as and when we need. Instead of installing software on our computer we would pay for it only when we needed it.
The most familiar early version of a cloud based service is web mail — Googlemail and hotmail — in which email messages are stored on remote servers which can be accessed from anywhere. Google also provides ways for people to store and then share documents and spreadsheets, so many people can access the same document. Facebook and Twitter are like vast clouds of personal information held in a cloud. Wikipedia is a cloud of self-managed, user generated information. Open source software platforms like Drupal are software clouds which coders can draw down from and add to.
Sharing our programmes and data makes a lot of sense, at least in theory. Pooling storage and software with others should lower the cost. Cloud computing would turn computing power into just another utility that we would access much as we turn on a tap for water.
As computing becomes a utility it will power many more devices, many of them with no user interface, more of them mobile and handheld. The cloud should also encourage collaboration. Different people, using different devices should be able to access the same documents and resources more easily. Work on shared projects will become easier, especially as collaboration software and web video conferencing becomes easier to use. This should allow far more of what Hal Varian, Google’s chief economist calls “combinatorial innovation” as developers mash-up data from different sources, as many people are doing already with Google maps. It is more sensible not to think of the cloud but clouds taking different shapes and forms.
“I don’t believe society understands what happens when everything is available, knowable and recorded by everyone all the time,” he says. He predicts, apparently seriously, that every young person one day will be entitled automatically to change his or her name on reaching adulthood in order to disown youthful hijinks stored on their friends’ social media sites.
Twenty years ago, a green laser would set you back $100,000 and occupy a good-sized dining room table. Today, you can buy a green laser pointer the size of a ball point pen for $15.
These devices create coherent green light in a three step process. A standard laser diode first generates near infrared light with a wavelength of 808nm. This is focused onto a neodymium crystal that converts the light into infrared with a wavelength of 1064nm. In the final step, the light passes into a frequency doubling crystal that emits green light at a wavelength of 532nm.
All this can easily be assembled into a cigar-sized package and powered by a couple of AAA batteries.
The result are devices generally advertised to have a power output of 10mW.
Today, Jemellie Galang and pals from the National Institute of Standards and Technology and the University of Maryland say they’ve found worrying evidence that the output of some green laser pointers is much higher and more insidious. They describe one $15 green laser pointer that actually emits ten times more infrared than green light.
Galang and co are under no illusion as to the potential consequences of this. “This is a serious hazard, since humans or animals may incur significant eye damage by exposure to invisible light before they become aware of it,” they say.
Mysterious and possibly nefarious trading algorithms are operating every minute of every day in the nation’s stock exchanges.
What they do doesn’t show up in Google Finance, let alone in the pages of the Wall Street Journal. No one really knows how they operate or why. But over the past few weeks, Nanex, a data services firm has dragged some of the odder algorithm specimens into the light.
The trading bots visualized in the stock charts in this story aren’t doing anything that could be construed to help the market. Unknown entities for unknown reasons are sending thousands of orders a second through the electronic stock exchanges with no intent to actually trade. Often, the buy or sell prices that they are offering are so far from the market price that there’s no way they’d ever be part of a trade. The bots sketch out odd patterns with their orders, leaving patterns in the data that are largely invisible to market participants.
