Once Again, Moore's Law is Toast

As reported at The Motley Fool, Intel’s latest 10-K / annual report filing would seem to suggest that the ‘Tick-Tock’ strategy of introducing a new lithographic process note in one product cycle (a ‘tick’) and then an upgraded microarchitecture the next product cycle (a ‘tock’) is going to fall by the wayside for the next two lithographic nodes at a minimum, to be replaced with a three element cycle known as ‘Process-Architecture-Optimization’.

Intel’s Tick-Tock strategy has been the bedrock of their microprocessor dominance of the last decade. Throughout the tenure, every other year Intel would upgrade their fabrication plants to be able to produce processors with a smaller feature set, improving die area, power consumption, and slight optimizations of the microarchitecture, and in the years between the upgrades would launch a new set of processors based on a wholly new (sometimes paradigm shifting) microarchitecture for large performance upgrades. However, due to the difficulty of implementing a ‘tick’, the ever decreasing process node size and complexity therein, as reported previously with 14nm and the introduction of Kaby Lake, Intel’s latest filing would suggest that 10nm will follow a similar pattern as 14nm by introducing a third stage to the cadence.

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2nd link.

Intel's Annual Report (PDF).

Moore's Law is Dead: Get Over it

Next month, the worldwide semiconductor industry will formally acknowledge what has become increasingly obvious to everyone involved: Moore's law, the principle that has powered the information-technology revolution since the 1960s, is nearing its end.

A rule of thumb that has come to dominate computing, Moore's law states that the number of transistors on a microprocessor chip will double every two years or so — which has generally meant that the chip's performance will, too. The exponential improvement that the law describes transformed the first crude home computers of the 1970s into the sophisticated machines of the 1980s and 1990s, and from there gave rise to high-speed Internet, smartphones and the wired-up cars, refrigerators and thermostats that are becoming prevalent today.

None of this was inevitable: chipmakers deliberately chose to stay on the Moore's law track. At every stage, software developers came up with applications that strained the capabilities of existing chips; consumers asked more of their devices; and manufacturers rushed to meet that demand with next-generation chips. Since the 1990s, in fact, the semiconductor industry has released a research road map every two years to coordinate what its hundreds of manufacturers and suppliers are doing to stay in step with the law — a strategy sometimes called More Moore. It has been largely thanks to this road map that computers have followed the law's exponential demands.

Not for much longer. The doubling has already started to falter, thanks to the heat that is unavoidably generated when more and more silicon circuitry is jammed into the same small area. And some even more fundamental limits loom less than a decade away. Top-of-the-line microprocessors currently have circuit features that are around 14 nanometres across, smaller than most viruses. But by the early 2020s, says Paolo Gargini, chair of the road-mapping organization, “even with super-aggressive efforts, we'll get to the 2–3-nanometre limit, where features are just 10 atoms across. Is that a device at all?” Probably not — if only because at that scale, electron behaviour will be governed by quantum uncertainties that will make transistors hopelessly unreliable. And despite vigorous research efforts, there is no obvious successor to today's silicon technology.

The industry road map released next month will for the first time lay out a research and development plan that is not centred on Moore's law. Instead, it will follow what might be called the More than Moore strategy: rather than making the chips better and letting the applications follow, it will start with applications — from smartphones and supercomputers to data centres in the cloud — and work downwards to see what chips are needed to support them. Among those chips will be new generations of sensors, power-management circuits and other silicon devices required by a world in which computing is increasingly mobile.

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Ambient Computing: Marc Andreessen's Vision of the Internet of Things 2.0

The hype around the Internet of Things has been rising steadily over the past five years. In tech analyst Gartner's Hype Cycle for Emerging Technologies report in 2015, the IoT is at the peak of "inflated expectations", particularly for areas like the smart home, which involve controlling your lights, thermostat or TV using your mobile phone.

But the era of sensors has only just dawned, according to renowned technology investor and internet pioneer Marc Andreessen. In 10 years, he predicts mobile phones themselves could disappear.

"The idea that we have a single piece of glowing display is too limiting. By then, every table, every wall, every surface will have a screen or can project," he told the Telegraph. "Hypothetically you walk upto a wall, sit at a table and [talk to] an earpiece or eyeglasses to make a call. The term is ambient or ubiquitous computing."

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China to Invest $47 Billion Over 5 Years to try to Become 3rd Largest Computer Chipmaker

China's Tsinghua Unigroup Ltd plans to invest 300 billion yuan ($47 billion) over the next five years in a bid to become the world's third-biggest chipmaker, the chairman of the state-backed technology conglomerate said on Monday.

Chairman Zhao Weiguo also told Reuters in an interview in Beijing that the company controlled by Tsinghua University, which counts President Xi Jinping among its alumni, was in talks with a U.S.-based company involved in the chip industry.

A deal could be finalized as early as the end of this month, he said. He declined to give more details but said buying a majority stake was unlikely as it was too "sensitive" for the U.S. government.

"If you can't be the top-three giant, it will be very hard to develop your business in the chip industry," Zhao said, citing reports that China imported more chips than crude oil every year.

"The next five years is key... There is an enormous market out there."

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Program Anomaly Detection Approach Detectiion Software Prototype Developed at Virginia Tech

Imagine millions of lines of instructions. Then try and picture how one extremely tiny anomaly could be found in almost real-time and prevent a cyber security attack.

Called a "program anomaly detection approach," a trio of Virginia Tech computer scientists has tested their innovation against many real-world attacks.

One type of attack is when an adversary is able to remotely access a computer, bypassing authentication such as a login screen. A second example of attack is called heap feng shui where attackers hijack the control of a browser by manipulating its memory layout. Another example of attack is called directory harvesting where spammers interact with vulnerable mail servers to steal valid email addresses.

The prototype developed by the Virginia Tech scientists proved to be effective and reliable at these types of attacks with a false positive rate as low as 0.01 percent.

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Extraordinary Claim: More Computer Use in School Doesn't Improve Student Learning

Investing heavily in school computers and classroom technology does not improve pupils' performance, says a global study from the OECD.

The think tank says frequent use of computers in schools is more likely to be associated with lower results.

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Moore's Law: Stick a Fork in it! Its Done!

It may be time for another revision to Moore's Law, if Intel's recent troubles keeping pace are any indication.

In a conference call on Wednesday, Intel confirmed that its upcoming generation of processors, codenamed Cannonlake, will not launch until the second half of 2017 -- nearly three years after the previous generation was made available. To bridge the gap, Intel plans to launch the third iteration of its current-generation processors, codenamed Kaby Lake, in the second half of 2016.

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We've already broken the 18 month cycle.  We've already slipped to 30 months and counting for the next iteration.  The Singularity, sir; its done.

 

Ikea's Concept Kitchen Gets the Robopocalypse Cooking

If this is the Ikea version of the 'kitchen table,' what's the high end look like?  Will you have to assemble this one?  Will all the computer chips and screws actually be included?  Or will you have to run to the store ten times to get every last missing piece?  Will the assembly instructions be so simple only an idiot would be able to understand them?  Finally, and most importantly, will it fall apart when the cat jumps on the table???

Using Digital Enhancement to Study Prehistoric Rock Art

An assessment of methods for the digital enhancement of rock paintings: the rock art from the precordillera of Arica (Chile) as a case study

Authors:

Cerrillo-Cuenca et al

Abstract:

The digital tracing of rock art is becoming a standard for archaeologists working in this field of research. The lack of specific software for this task has resulted in archaeologists either using solutions that are not statistically robust enough or working with overly generic fields of image analysis. This paper will assess the application of three techniques for digital tracing: Principal Components Analysis, K-means, and Decorrelation Stretch. In addition to these techniques of image analysis, this paper will also explore three selective techniques that classify or enhance pigmentation. These analyses have been implemented in a software package called PyDRA (developed by one of the authors, ECC). This software makes use of several scientific libraries for the digital analysis of an image.

As a case study, we chose three rock art sites located between 3100 and 3500 m above sea level in the precordillera of Arica, the northern region of Chile. All of the paintings are located inside rock shelters that are easily accessible; however, we lack a systematic recording for analysing these sites. Pampa El Muerto 14 and Mullipungo 1 were recorded through direct tracings between 1980 and 1990. The Lupica 1 site was identified only in 2013 and has not been recorded until now. Due to the advancement of technology in the years since the 1980s, we have been able to compare the proficiency of different digital and statistical techniques. Our study uses the most adequate parameters and enables us to trace the paintings digitally without actually handling the surface of the rock.

Robopocalypse Comes for the Game of 'Go'

Computers are rapidly beginning to outperform humans in more or less every area of endeavor. For example, machine vision experts recently unveiled an algorithm that outperforms humans in face recognition. Similar algorithms are beginning to match humans at object recognition too. And human chess players long ago gave up the fight to beat computers.

But there is one area where humans still triumph. That is in playing the ancient Japanese game of Go. Computers have never mastered this game. The best algorithms only achieve the skill level of a very strong amateur player which the best human players easily outperform.

That looks set to change thanks to the work of Christopher Clark and Amos Storkey at the University of Edinburgh in Scotland. These guys have applied the same machine learning techniques that have transformed face recognition algorithms to the problem of finding the next move in a game of Go. And the results leave little hope that humans will continue to dominate this game.

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Alva Noë: Worry About the Singularity When Machines Match the Agency and Awareness of Amoeba

One reason I'm not worried about the possibility that we will soon make machines that are smarter than us, is that we haven't managed to make machines until now that are smart at all. Artificial intelligence isn't synthetic intelligence: It's pseudo-intelligence.

This really ought to be obvious. Clocks may keep time, but they don't know what time it is. And strictly speaking, it is we who use them to tell time. But the same is true of Watson, the IBM supercomputer that supposedly played Jeopardy! and dominated the human competition. Watson answered no questions. It participated in no competition. It didn't do anything. All the doing was on our side. We played Jeapordy! with Watson. We used "it" the way we use clocks.

Philosophers and biologists like to compare the living organism to a machine. And once that's on the table, we are lead to wonder whether various kinds of human-made machines could have minds like ours, too.

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Deep Mind Project at Google Unveils Neural Turing Machines

Neural Turing Machines

Authors:

Graves et al

Abstract:

We extend the capabilities of neural networks by coupling them to external memory resources, which they can interact with by attentional processes. The combined system is analogous to a Turing Machine or Von Neumann architecture but is differentiable end-to-end, allowing it to be efficiently trained with gradient descent. Preliminary results demonstrate that Neural Turing Machines can infer simple algorithms such as copying, sorting, and associative recall from input and output examples.

pop sci write up.

HP Announces 3d Printer, Scanner+

HP today announced a new 3D printing technology called Multi Jet Fusion that it said will enable mass production of parts with a technology traditionally reserved for rapid prototyping.

The new industrial 3D printer, about the size of a washing machine, is 10 times faster and 50% less expensive than current systems on the market, HP said. The printer can also use a myriad of colors and materials.

The company also announced Sprout, a new immersive computing platform that combines a 23-in touch screen monitor and horizontal capacitive touch mat with a scanner, depth sensor, hi-res camera, and projector in a single desktop device.

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DOOM! DOOM! DOOM! One in Three Jobs to be Lost to Robopocalypse by 2025

Gartner sees things like robots and drones replacing a third of all workers by 2025, and whether you want to believe it or not, is entirely your business.

This is Gartner being provocative, as it is typically is, at the start of its major U.S. conference, the Symposium/ITxpo.

Take drones, for instance.

"One day, a drone may be your eyes and ears," said Peter Sondergaard, Gartner's research director. In five years, drones will be a standard part of operations in many industries, used in agriculture, geographical surveys and oil and gas pipeline inspections.

"Drones are just one of many kinds of emerging technologies that extend well beyond the traditional information technology world -- these are smart machines," said Sondergaard.

Smart machines are an emerging "super class" of technologies that perform a wide variety of work, both the physical and the intellectual kind, said Sondergaard. Machines, for instance, have been grading multiple choice for years, but now they are grading essays and unstructured text.

This cognitive capability in software will extend to other areas, including financial analysis, medical diagnostics and data analytic jobs of all sorts, says Gartner.

"Knowledge work will be automated," said Sondergaard, as will physical jobs with the arrival of smart robots.

"Gartner predicts one in three jobs will be converted to software, robots and smart machines by 2025," said Sondergaard. "New digital businesses require less labor; machines will be make sense of data faster than humans can."

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Intel has Developed RealSense: a 3d Scanner Built Into a Tablet

Intel has been working on a 3D scanner small enough to fit in the bezel of even the thinnest tablets. The company aims to have the technology in tablets from 2015, with CEO Brian Krzanich telling the crowd at MakerCon in New York on Thursday that he hopes to put the technology in phones as well.

"Our goal is to just have a tablet that you can go out and buy that has this capability," Krzanich said. "Eventually within two or three years I want to be able to put it on a phone."

Krzanich and a few of his colleagues demonstrated the technology, which goes by the name "RealSense," on stage using a human model and an assistant who simply circled the model a few times while pointing a tablet at the subject. A full 3D rendering of the model slowly appeared on the screen behind the stage in just a few minutes. The resulting 3D models can be manipulated with software or sent to a 3D printer.

"The idea is you go out, you see something you like and you just capture it," Krzanich explained. He said consumer tablets with built in 3D scanners will hit the market in the third or fourth quarter of 2015, with Intel also working on putting the 3D scanning cameras on drones.

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heh.  Betcha this or a version after gets banned from art galleries.  

Steps to the Robopocalypse: NHTSA Moving Forward With Vehicle-To-Vehicle Communication

NHTSA has released an advanced notice of proposed rulemaking into the technology, alongside a report detailing comprehensive research into the subject. It includes analysis of the agency's research findings in areas including technical feasibility, privacy and security, as well as preliminary estimates on costs and safety benefits. Privacy and security issues will be of concern to many—particularly unease over how far vehicle data might be shared—but the agency's main concern is safety.

"Safety is our top priority," explains U.S. Transportation Secretary Anthony Foxx, "and V2V technology represents the next great advance in saving lives." The technology isn't about helping people survive accidents, an area which automakers continually strive to improve, but helping them avoid crashes altogether. Cars using vehicle-to-vehicle communication technology can be in constant communication with those nearby, sharing data on vehicle position and speed, proximity and whether any other obstacles in the nearby area pose a threat.

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Robo Brain: the Cloud Machine Learning for the Robopocalypse

Robo Brain – a large-scale computational system that learns from publicly available Internet resources – is currently downloading and processing about 1 billion images, 120,000 YouTube videos, and 100 million how-to documents and appliance manuals. The information is being translated and stored in a robot-friendly format that robots will be able to draw on when they need it.

To serve as helpers in our homes, offices and factories, robots will need to understand how the world works and how the humans around them behave. Robotics researchers have been teaching them these things one at a time: How to find your keys, pour a drink, put away dishes, and when not to interrupt two people having a conversation. This will all come in one package with Robo Brain.

"Our laptops and cell phones have access to all the information we want. If a robot encounters a situation it hasn't seen before it can query Robo Brain in the cloud," said Ashutosh Saxena, assistant professor of computer science at Cornell University. Saxena and colleagues at Cornell, Stanford and Brown universities and the University of California, Berkeley, say Robo Brain will process images to pick out the objects in them, and by connecting images and video with text, it will learn to recognize objects and how they are used, along with human language and behavior.

If a robot sees a coffee mug, it can learn from Robo Brain not only that it's a coffee mug, but also that liquids can be poured into or out of it, that it can be grasped by the handle, and that it must be carried upright when it is full, as opposed to when it is being carried from the dishwasher to the cupboard.

Saxena described the project at the 2014 Robotics: Science and Systems Conference, July 12-16 in Berkeley, and has launched a website for the project at http://robobrain.me

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The Limits of the Limits for Processors

Limits on fundamental limits to computation

Author:

Markov

Abstract:

An indispensable part of our personal and working lives, computing has also become essential to industries and governments. Steady improvements in computer hardware have been supported by periodic doubling of transistor densities in integrated circuits over the past fifty years. Such Moore scaling now requires ever-increasing efforts, stimulating research in alternative hardware and stirring controversy. To help evaluate emerging technologies and increase our understanding of integrated-circuit scaling, here I review fundamental limits to computation in the areas of manufacturing, energy, physical space, design and verification effort, and algorithms. To outline what is achievable in principle and in practice, I recapitulate how some limits were circumvented, and compare loose and tight limits. Engineering difficulties encountered by emerging technologies may indicate yet unknown limits.

pop sci write up of the same.

Memristers Finally Here? HP to Ship in 2016?

A replacement for the ordinary transistor may make it to market by the end of this decade, an event that will herald a radical redesign of traditional computer architectures. The memristor, the subject of much study over the last six years, could become the basic building block for an array of new devices—from the sensors and memory chips being built into the "Internet of Things" (connected, sensor-embedded devices) to the giant computers used for big data applications by scientists, engineers and Wall Street.

[...]

The industry has several goals in making the shift. Memristors can vastly improve energy efficiency of electronic components, and are better able to cope with the floods of data expected from the Internet of Things, which monitor or control equipment or systems in factories, office buildings or homes. Essential to their development is a continuation of the exponential growth in computing power and storage density that has seen prices plunge over the past 40 years. For similar reasons, IBM has just announced it will spend $3 billion to pursue experimental "post-silicon" architectures and chips, predicting a fundamental revamping of existing systems in 10 years.

These changes will produce a fundamental overhaul of computer operating systems to accommodate hardware that no longer differentiates between dynamic memory and long-term storage. Bresniker sees the change as an opportunity to jettison layers of cumbersome operating system code that was previously adopted to accommodate the limitations of older hardware.

HP's current development timetable has memristors going into the earliest stage of production in 2015 and launching as DIMMs (dual in-line memory modules) for computer memory in 2016. The operating system for “The Machine” will go into wider public beta testing in 2017, and the new architecture is intended to be integrated into actual products in 2019. Even if none of this pans out, Bresniker believes the attempt is worth it: "Each of the elements is interesting…[on its own]. Pulling out that copper and dropping in that piece of fiber will be more efficient, even with a traditional computing and memory regime all around it…. We need a replacement memory technology. If it does nothing else than drop in where my DIMMs drop in today, that will be a useful thing."

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New Technique Allows Quantum Computers to be Booted in 5 Minutes

Press the start button, switch on the monitor, grab a cup of coffee and off you go. That is pretty much how most us experience booting up a computer. But with a quantum computer the situation is very different. So far, researchers have had to spend hours making dozens of adjustments and fine calibrations in order to set up a chip with just five quantum bits so that it can be used for experimental work. (One quantum bit or 'qubit' is the quantum physical equivalent of a single bit in a conventional computer). Any small errors in the adjustment and calibration procedure and the chip would not work.

The problem is that, not unlike musical instruments, quantum computers react to small changes in the local environment. If, for example, it is a little warmer or a little colder or if the ambient air pressure is a little higher or a little lower than the day before then the complex network of qubits will no longer function – the computer is detuned and has to be readjusted before it can be used. 'Up until now, experimental quantum physicists have had to sit down each day and see how conditions have changed compared to the day before. They then had to remeasure each parameter and carefully recalibrate the chip,' explains Professor Wilhelm-Mauch, Professor for Theoretical Quantum and Solid-State Physics at Saarland University. Only a very small error rate of less than 0.1 percent is permissible when measuring ambient conditions. Frank Wilhelm-Mauch explains this sensitivity thus: 'That means that an error can occur in only one in a thousand measurements. If just two in a thousand measurements are in error, the software will be unable to correct for the errors and the quantum computer will not operate correctly.' With around 50 different parameters involved in the calibration process, one begins to get an idea of the sheer effort involved in calibrating a quantum computer.

Working together with his doctoral student, Wilhelm-Mauch began to consider a fundamentally new approach to the problem. 'We asked ourselves the question: Why is it necessary each and every day to understand how conditions differ from those of the day before?' The answer we eventually came up with was that it isn't necessary. What's important is that the setup procedure produces the right results. Why it produces the right results is not so relevant.' It was this pragmatic approach that underlay the work carried out by Wilhelm-Mauch and Egger. 'For the calibration procedure we used an algorithm from engineering mathematics, strictly speaking from the field of civil and structural engineering, as that's another area in which experiments are costly,' explains Professor Wilhelm-Mauch.

Using this technique, the two theoreticians were able to reduce the calibration error rate to below the required 0.1 percent threshold, while at the same time speeding up the calibration process from six hours to five minutes. The Saarbrücken methodology, which goes under the name Ad-HOC (Adaptive Hybrid Optimal Control), has now been subjected to rigorous testing by a group of experimental physicists from the University of California in Santa Barbara. Their experimental work is published in the issue of Physical Review Letters that also contains the Saarbrücken paper.

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