http://www.eejournal.com/article/sunshine-changing-the-world/
NovaSolix is a silicon valley startup developing a process to manufacture solar panels that use carbon nanotubes as antennas – combined with nanoscale rectifiers – to generate power from a much broader swath of the solar energy spectrum than conventional PV cells. The company claims that 80-90% efficiency may be possible. They are also working to develop a process to manufacture the panels on a substrate of glass, thus dramatically reducing the cost compared with silicon-based PV technology.
If the company is successful in hitting their efficiency and cost targets, they could quite literally change the world. The economics and practicality of solar versus other forms of energy is already at a tipping point, so tiny changes in the cost-per-watt of deploying solar can have massive effects on the economics of energy. Changes of the magnitude NovaSolix envisions could slam a brick on that balance scale, completely transforming the energy landscape (and wiping out entire major industries in the process).
In order to harness the full spectrum of visible and infrared light, we need antennas of varying lengths. NovaSolix is working to create just the right mix of manufacturing variation in their carbon nanotubes to give the optimal distribution of antenna lengths. The carbon nanotube antennas are “grown” between electrical contacts, and they create diodes at the interface point. Each successful nanotube pair creates an antenna and a full-wave rectifier. NovaSolix has now successfully created demo wafers, and the IV curve of the resulting devices is interesting. Conventional PV cells have a fairly flat IV curve, with current remaining relatively constant and voltage increasing proportional to output. The nanotube antennas, however, produce a more linear IV curve, which should allow for a simpler controller than conventional PV cells, as well as greater immunity to partial shading effects.
NovaSolix is currently doing wafer fabrication in the Stanford Nanofabrication Facility and growing carbon nanotubes in their own labs. Their plan is to work toward a small-volume production capability with a “boutique” version of the technology aimed at specialty markets where power-per-area is the critical factor. This includes portable applications such as solar aircraft, wearables, and satellites. This production will be done using primarily older-generation semi-automated IC fabrication equipment. NovaSolix can see bringing the cost per watt down from $10 to around $1 with this approach.
AI moves on past games…
https://theconversation.com/no-more-playing-games-alphago-ai-to-tackle-some-real-world-challenges-78472
The game of Go provided a nicely constrained development platform for optimising these learning algorithms. But many real world problems are messier than this, and have less opportunity for the equivalent of self-play (for instance self-driving cars).So are there problems to which the current algorithms can be fairly immediately applied?
One example may be optimisation in controlled industrial settings. Here the goal is often to complete a complex series of tasks while satisfying multiple constraints and minimising cost.
As long as the possibilities can be accurately simulated, these algorithms can explore and learn from a vastly larger space of outcomes than will ever be possible for humans. Thus DeepMind’s bold claims seem likely to be realised, and as the company says, we can’t wait to see what comes next.
Ubiquitous solar faster than you can imagine…
https://m.imgur.com/r/Futurology/2rWxy
If you trade energy complex you might wanna understand this…
Leading researchers on whether AI is near or far… great read
http://spectrum.ieee.org/computing/software/humanlevel-ai-is-right-around-the-corner-or-hundreds-of-years-away
Artificial intelligence is progressing rapidly, and its impact on our daily lives will only increase. Today, there are still many things humans can do that computers can’t. But will it always be that way? Should we worry about a future in which the capabilities of machines rival those of humans across the board? For IEEE Spectrum’s June 2017 special issue, we asked a range of technologists and visionaries to weigh in on what the future holds for AI and brainlike computing.
The limits of silicon have not been reached quite yet.
Today, an IBM-led group of researchers have detailed a breakthrough transistor design, one that will enable processors to continue their Moore’s Law march toward smaller, more affordable iterations. Better still? They achieved it not with carbon nanotubes or some other theoretical solution, but with an inventive new process that actually works, and should scale up to the demands of mass manufacturing within several years
You can imagine that FinFET is now turned sideways, and stacked on top of each other,” says Khare. For a sense of scale, in this architecture electrical signals pass through a switch that’s the width of two or three strands of DNA.
“It’s a big development,” says Hutcheson. “If I can make the transistor smaller, I get more transistors in the same area, which means I get more compute power in the same area.” In this case, that number leaps from 20 billion transistors in a 7nm process to 30 billion on a 5nm process, fingernail-sized chip. IBM pegs the gains at either 40 percent better performance at the same power, or 75 percent reduction in power at the same efficiency.
J
Can Watson disrupt medicine…?
https://www.forbes.com/sites/timworstall/2017/06/04/milton-friedman-told-us-the-answer-decades-ago-now-itll-probably-be-ibms-watson/#28b00be11bce
Physician specialty groups have created “societies” to provide education, establish clinical guidelines and handle public relations. These range from the Society of Surgical Oncology to the group that represents me and my ear, nose and throat colleagues, the American Academy of Otolaryngology-Head and Neck Surgery. They are also lobbyists, charged with maximizing the incomes of member doctors by influencing pricing decisions made by the Centers for Medicare and Medicaid Services. Those prices become the benchmarks for private health insurance companies, too.
There are so many specialty organizations because each develops authority over a niche market and vigorously guards its turf. Imagine building a house by allowing each workman to do his own thing. The plumber would put a sink in every room. The electrician would install chandeliers on every ceiling. The carpenter would panel every room in luxurious wood. That’s how health care works.
Deep thinking…
https://www.theguardian.com/books/2017/jun/04/deep-thinking-where-machine-intelligence-ends-human-creativity-begins-garry-kasparov-review
Garry Kasparov is arguably the greatest chess player of all time. From 1986 until his retirement in 2005, he was ranked world No 1. He is also a leading human rights activist and is probably close to the top of Vladimir Putin’s hitlist, not least because he tried to run against him for the Russian presidency in 2007. But for people who are interested only in technology, Kasparov is probably best known as the first world champion to be beaten by a machine. In 1997, in a famous six-game match with the IBM supercomputer Deep Blue, he lost 3½-2½.
The passage of time has mellowed Kasparov and his reflections on the match and its outcome are more thoughtful, measured and insightful than I had expected from the opening chapters of the book. His initial thoughts about the implications of AI seemed banal and predictable. “Romanticising the loss of jobs to technology,” he writes on page 42, “is little better than complaining that antibiotics put too many gravediggers out of work.” The transfer of labour from humans to our inventions “is nothing less than the history of civilisation”. And the early Kasparov sounds like a technological determinist on steroids. “Even if it were possible to mandate slowing down the development and implementation of intelligent machines,” he writes, “it would only ease the pain for a few for a little while and make the situations worse for everyone in the long run.” And so on.
Yet by the end of the book, he has arrived at a more enlightened view of machine intelligence than most people in the tech industry, who are obsessed with machines that will replace people. Kasparov was an early enthusiast for chess-playing computers and indeed did much to foster the technology that enables every child nowadays to learn to play against a grandmaster-level virtual opponent. In the end, the technology he inspired defeated him. But the message he bears is that the really intelligent approach is not to rail against the machine for being better than we are at some things, but to celebrate its capacity to augment our human capabilities. And therein lies the beginning of wisdom in these matters.
• Deep Thinking by Garry Kasparov is published by John Murray (£20). To order a copy for £17 go to bookshop.theguardian.com or call 0330 333 6846. Free UK p&p over £10, online orders only. Phone orders min p&p of £1.99
Ibjjf worlds… it’s the super bowl for jiujiteiros
So for us bjj guys, this is super bowl weekend. Ibjjf worlds is happening at Long Beach. I’m not competing. I am a masters competitor. But I’m cheering for my guys! I’m calling Dominique Bell as brown belt adult heavy weight worlds champion.
http://www.flograppling.com/article/56195-dominique-bell-comic-artist-and-former-soldier-turned-gold-medal-machine#.WTMVhFQpCf0
The exponential race…
This is good race commentary. And important to understand. But this is a long race…
Google Is Already Late to China’s AI Revolution – WIRED https://apple.news/A8flImUxTRAyf5GyBrNZTQQ
Disruptions to come. More study…
https://static1.squarespace.com/static/585c3439be65942f022bbf9b/t/591a2e4be6f2e1c13df930c5/1494888038959/RethinkX+Report_051517.pdf
We are on the cusp of one of the fastest, deepest, most consequential disruptions of transportation in history. By 2030, within 10 years of regulatory approval of autonomous vehicles (AVs), 95% of U.S. passenger miles traveled will be served by on-demand autonomous electric vehicles owned by eets, not individuals, in a new business model we call “transport- as-a-service” (TaaS). The TaaS disruption will have enormous implications across the transportation and oil industries, decimating entire portions
of their value chains, causing oil demand and prices to plummet, and destroying trillions of dollars in investor value — but also creating trillions of dollars in new business opportunities, consumer surplus and GDP growth.
The disruption will be driven by economics. Using TaaS, the average American family will save more than $5,600 per year in transportation costs, equivalent to a wage raise of 10%. This will keep an additional $1 trillion
per year in Americans’ pockets by 2030, potentially generating the largest infusion of consumer spending in history.