Interesting MIT World lecture by Sherry Turkle.

Contemporary science has done a great disservice to Sigmund Freud, suggests Sherry Turkle, who believes the psychoanalytic tradition can teach us much about the often concealed connections between physical objects and our thoughts and feelings. On the occasion of the publication of her latest book, The Inner History of Devices — the third in a trilogy — Turkle speaks of the importance of technology as a subjective tool, as a window into the soul.

When she first arrived at MIT, Turkle relates, colleagues viewed devices like their computers as simply instruments for accomplishing work. Turkle set out on her life’s work to demonstrate that technology serves a much greater purpose in our lives. People turn their devices “into beings, which they animate, anthropomorphize.” Her research and writing involves the ways people invest themselves in physical objects, and how those objects “inflect inner life, relationships, carry ideas, sensibilities and memory.”

Turkle’s latest work, as she describes it, brings together the artful listening of a memoirist, the interpretive skills of a clinician, and the participant observational skills of an ethnographer. Together, these enable her to dig deep into such questions as how cellphones can change people’s sensibilities, what is intimacy without privacy (e.g., texting and Second Life); and how people are starting to add robots as companions to their lives. There is no doubt that technology is “changing our hearts and minds,” and that people increasingly attach “to the inanimate without prejudice.” Whether online or with robotic creatures, “we are lost in cyber intimacies and solitudes, and we often don’t know if we’ve been alone, together, close or distant.”

DailyLit is an interesting idea — books delivered to your phone or email in small daily snippets.

When I mentioned Songsmith the other day, my colleague Tony Hirst reminded me wryly that he had sent me a link about it months ago. And of course he was right. Here it is.

The program works by identifying the 12 standard musical notes in a sung melody, and then feeding those notes into an algorithm that has been trained by listening to 300 songs in varying genres and learning how to identify chords and melody fragments that work well together. The result is a series of musical accompaniments that users can adjust via sliders for "happy factor" and "jazz factor."

"I suspect musicians will argue that this is another step towards homogenized elevator music for all," Peter Bentley, a computer scientist at University College London, told New Scientist. "But I see a big market for this, whether it's liked by musicians or not." We agree, and we think the web is the perfect place to find that market.

Microsoft Research has come up with an ingenious PC application called Songsmith.

Just open up Songsmith, choose from one of thirty different musical styles, and press record. Sing whatever you like – a birthday song for Mom, a love song for that special someone (they’ll be impressed that you wrote a song for them!), or maybe just try playing with your favorite pop songs. As soon as you press “stop”, Songsmith will generate musical accompaniment to match your voice, and play back your song for you. It’s that simple.

Robert Scoble was given a demo by the developers in his Vegas hotel room.

Technology Review has an interesting photographic record of Moore’s Law. It opens with this image (from Texas Instruments).

The first working integrated circuit on germanium was demonstrated by Jack Kilby at Texas Instruments in 1958. This prototype has a transistor (small left dot) attached to two gold wires and a capacitor (middle black dot). The germanium itself, secured on a glass slide, is divided into three resistors by the tabs at the bottom. By showing that all three types of components could work in the same slice of germanium, Kilby offered a way to improve the performance and lower the cost of electronic devices.

Bob Cringely has an excellent and informative piece about our future in a parallel universe. Well, a parallelized universe, anyway.

In [2002], at Intel's developer conference, chief technology officer Pat Gelsinger said, "We're on track, by 2010, for 30-gigahertz devices, 10 nanometers or less, delivering a tera-instruction of performance." That's one trillion computer instructions per second.

But Gelsinger was wrong. Intel and its competitors are still making processors that top out at less than four gigahertz, and something around five gigahertz has come to be seen, at least for now, as the maximum feasible speed for silicon technology.

It's not as if Moore's Law–the idea that the number of transistors on a chip doubles every two years–has been repealed. Rather, unexpected problems with heat generation and power consumption have put a practical limit on processors' clock speeds, or the rate at which they can execute instructions. New technologies, such as spintronics (which uses the spin direction of a single electron to encode data) and quantum (or tunneling) transistors, may ultimately allow computers to run many times faster than they do now, while using much less power. But those technologies are at least a decade away from reaching the market, and they would require the replacement of semiconductor manufacturing lines that have cost many tens of billions of dollars to build.

So in order to make the most of the technologies at hand, chip makers are taking a different approach. The additional transistors predicted by Moore's Law are being used not to make individual processors run faster but to increase the number of processors inside a chip. Chips with two processors–or "cores"–are now the desktop standard, and four-core chips are increasingly common. In the long term, Intel envisions hundreds of cores per device.

But here's the thing: while the hardware problem of overheating chips lends itself nicely to the hardware solution of multicore computing, that solution gives rise in turn to a tricky software problem. How do you program for multiple processors?

Answer: with great difficulty. The big limitation, in other words, may not come from physics but from our inability to write software that can make use of parallel architectures.

I particularly like the crack that most humans couldn’t pass a Turing Test. Also the observation that artificial intelligence makes people stupid.