The hunter becomes the hunted: Young wildebeest turns tables on cheetah after a surprise attack by world's fastest cat 01-16

The hunter becomes the hunted: Young wildebeest turns tables on cheetah after a surprise attack by world's fastest cat

• In Kenya's Masai Mara, a wildlife photographer snapped these amazing action shots of a female cheetah hunting
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• Malaika, as she's known, spotted a young wildebeest from her vantage point perched atop a safari vehicle
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• However, her attack didn't go as planned when the wildebeest held its ground and the tables were turned
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Wildlife photographer Manoj Shah took these amazing pictures of the action of the female cheetah, known as Malaika, attempting a hunt.

The big cat had spotted the wildebeest from her cheeky vantage point, perched atop a tourist safari vehicle.

Just minutes later, she jumped off the truck and launched into her attack in Kenya's Masai Mara.

Wildlife photographer Manoj Shah took these amazing pictures of the action of the female cheetah, known as Malaika, attempting a hunt.

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From her cheeky vantage point, perched atop a safari vehicle, Malaika spotted the wildebeest in the long grass plains

Manoj said he first noticed the cheetah scanning the bush as he drove up to the site - and knew that she was about to hunt.

'Driving towards the vehicle, I noticed a female cheetah, popularly known Malaika - meaning 'angel' in the local Kiswahili language - looking intently at the line of wildebeest running across the savannah plains,' he explained.

'In places where the grass was tall and ant hills were absent, Malaika cleverly used a tourist vehicle as a vantage point.

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Manoj first noticed the cheetah scanning the bush as he drove towards the site - and he knew that she was about to hunt.

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With her powerful eyesight, she spotted a young wildebeest following its mother - and immediately jumped from the vehicle in its direction.

'Thus she was able to scan vast areas of the Mara with her powerful eyesight.

'Suddenly her eyes gleamed upon noticing a wildebeest youngster closely following its mother.

'Malaika spotted her target, immediately jumped down from the vehicle and hurried through the long grass in the direction of her prey.

'She broke into a fast run when about 70 metres away from her target.' 

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Malaika broke into a fast run about 70 metres from her target, confusing the wildebeest who was then separated from its mother.

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Once she caught up to her target, the cheetah used its front paw (and razor sharp dew claw) to grab hold of the wildebeest.

The young wildebeest became confused and was quickly separated from its mother. He took off, running for his life. 

'While all the big cats are specialist hunters, the cheetah has pushed specialism to an extreme,' Manoj added.

'It is sleek with its trim waist and long slender legs, its deep chest and small head - like a greyhound with a coat of a leopard.

'Catching up with her fleeing target, the cheetah slapped its front paw onto the hind of the wildebeest, grappling it with its razor sharp dew claw.'

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Surprisingly, however, the wildebeest held its ground and turned the tables on the cheetah, who fell to the ground

'The wildebeest faced the cheetah and tried to attack her with its horns,' the photographed said.

'It charged at Malaika and drove her off, the hunter had become the hunted.'

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Make in India discussions at IIM Bangalore 12-14

‘Stop comparing India with China, at least in manufacturing’

At 'Make in India' panel, hosted by IIM Bangalore's PGPEM program, Shivaprasad Naik, Senior Vice President, PVC, Reliance Industries, highlights the differences between the two business models and calls for focus on 'Make for India'

JANUARY 11, 2015: Drawing attention to the dangers of "blindly" comparing the two countries, at least in manufacturing, SS Naik, Senior Vice President, Reliance Industries, emphasized that China's manufacturing sector was driven by global demand while India enjoyed a huge opportunity in the local market.

"We are a population of 1.2 billion. There's huge opportunity here. Yet we import idols for Ganesha Chathurti and diyas for Deepavali from China," he remarked, clarifying that there was no harm in 'Make in India' but manufacturers would certainly do well to first 'Make for India'. "We keep talking of our demographic dividend. We must leverage this demographic dividend by understanding the wants of our aspirational youth and by making products for them," he said.

Ruing the "shortcut" approach to prosperity that India's traders often take, Naik gave the example of the Canton fair, which he said when he last visited in 2008 "startled" him for the large numbers of Indian traders who thronged it. "They purchased everything from toys to tablecloth which they would come back and sell at thrice the price in India, enjoy the profits and go back for the next Canton fair," he exclaimed.

Addressing a packed auditorium at the panel on 'Make in India', hosted by IIMB's Post Graduate Program in Enterprise Management (PGPEM) and moderated by Sushil Vachani, Director, IIM Bangalore, on Sunday (Jan 11), Shivaprasad Naik, along with Arun Chandavarkar, CEO & Joint Managing Director, Biocon, Chris Rao, Vice President, UTC Aerospace System, UTAS, and Ananth Agastya, Executive Director, HAL Management Academy, called for a mindset change among entrepreneurs, bureaucrats and government to address challenges unique to the country like poor infrastructure, power shortage, delayed IP processing, lack of talent and failure to deploy unproductive land for manufacturing.

"Government, industry and labor are the key stakeholders in the 'Make in India' mission," said Ananth Agastya, Executive Director, HAL Management Academy. "The government should show that they mean business by ensuring harassment-free administration, industry must bring in investment in technology and productivity and must stop seeking a protective environment, and distinction between contract labor and organized labor should go," he observed, calling for an Indian philosophy of manufacturing without "blindly aping the rest".

Using the analogy of a 'yagna', Agastya said: "We have made the 'sankalp' which is 'Make in India'. We must now offer 'yantra', 'tantra' and 'mantra' to complete the 'yagna'. We must ask ourselves whether 'Make in India' is measurable, whether we have data on each sub sector, whether our policy makers can be advised on which of these sub sectors are likely to grow so that they can focus on them and whether policy change will attract entrepreneurs to these sub sectors. Academic institutions like IIM Bangalore can develop models for each of these sub sectors. Only then can we say that policy making is driven by analysis."

Listing the pivots to increase the thrust on manufacturing, Arun Chandavarkar, CEO & Joint Managing Director, Biocon, said India must take advantage of the demographic dividend by giving the youth skills and knowledge, ensure good governance and end bureaucratic delays, nurture entrepreneurial culture by taking it from services to manufacturing, bring in global alignment in corporate governance and leverage it to facilitate partnerships and investment. "It is only when we have enablers like talent, skill, infrastructure, guidelines and fiscal policies can we increase manufacturing's contribution to the country's GDP from 17 percent to 25-26 per cent," he said, declaring that "notions which say it is more glamorous to be in services, not in manufacturing must be busted."

Describing 'Make in India' as a relevant mission, Chris Rao, Vice President, UTC Aerospace System, UTAS, said the sector needed to develop a supply chain of vendors, down to tier 4 suppliers, so that the integrators could focus on technology and innovation. "India has huge engineering talent. We see huge opportunity here. What we also need is strong policy support and good government support. Else, Mexico, Brazil, China, Poland, Singapore and Taiwan could beat us in this game," he said, calling for professionally-run industry-focused organizations to create ecosystems that support manufacturing.

Earlier in the day, IIMB Director Sushil Vachani welcomed the distinguished panel. Moderating the discussion, he also took a few questions on new initiatives taken by IIM Bangalore to support entrepreneurial culture and social responsibility among its students.

The panel discussion was followed by an Open House on IIMB's Post Graduate Program in Enterprise Management, which caters to the needs of diverse industries, including manufacturing.

Professor Abhoy Ojha, Chairperson, Post Graduate Program in Enterprise Management (PGPEM), said: "IIM Bangalore designs its programs to cater to management education needs of different domains in India. The Post Graduate Program in Software Enterprise Management was launched in 1998 to partner the software and IT industry in its growth to global prominence by providing world class management education to middle and senior managers. The program has now been re-positioned to cater to the needs of diverse industries, including manufacturing, in Bangalore and neighboring cities. The panel discussion, 'Make in India', provides IIMB an opportunity to engage with captains of the industry to understand the opportunities and challenges of the manufacturing sector and fine tune its offerings to partner with the industry to make Bangalore (and India) the global hub for manufacturing."

About the program:

The Post Graduate Program in Enterprise Management (PGPEM) is a 22-month weekend residential management program. Classes are scheduled on Friday afternoons and Saturdays. The program is designed for the needs of high performing professionals from across industries who want to continue working even as they upgrade their management knowledge and skills. It provides them a strong grounding in general management through the core courses in the first year, and a rich choice of electives in the second year.

Candidates with over 3 years of work experience may apply. Selection is based on CAT/GMAT/GRE score. Those with over seven years of work experience can take the PGPEM entrance exam that will be conducted by IIMB on 8th February, 2015. The last date to apply online is 31st January, 2015. Visitwww.iimb.ernet.in/pgpem for details.

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FBI investigating Central Command Twitter hack 01-13

FBI investigating Central Command Twitter hack

The Twitter account for U.S. Central Command was hacked on Monday, with pro-ISIS messages plastering the account's profile.

The first message was posted at 12:29 p.m. ET, with the words "AMERICAN SOLDIERS, WE ARE COMING, WATCH YOUR BACK. ISIS." and the hashtag "#CyberCaliphate."

The profile's image was replaced with a photo that includes the text "i love you isis." Just before 1 p.m. ET profile and banner images were reverted to their default.

The FBI said on Monday it was working with the Department of Defense to investigate the hacking of the Twitter and YouTube accounts of the U.S. military command that oversees operations in the Middle East.

A screen shot of the Twitter account for the US Military Central Command, which was apparently hacked.

Around 1:09 p.m. ET the Twitter account was suspended.

A YouTube page labeled as belonging to Centcom was also apparently hacked. By 1:30 p.m. ET, that page had been blanked.

"We can confirm that the U.S. Central Command's Twitter and YouTube accounts were compromised earlier today. We are taking appropriate measures to address the matter," a defense official told NBC News.

Later tweets included images of what were apparently spreadsheets labeled as containing the contact info and home addresses of retired U.S. army generals.

Other tweets claimed to include military plans from Pentagon networks. One such image showed a map of China with labels of different military assets. Another supposed Pentagon image featured a map of North Korea with labels for nuclear facilities.

Government officials told NBC News that the Twitter and YouTube accounts are not classified, and that none of the information posted by the hackers was actually classified—the names and contact information are "official use only," they said.

The slides containing information on China and North Korea were not military, the officials told NBC, with some of them coming from MIT.

A U.S. Department of Defense official told NBC News "this is clearly embarrassing, but not a security threat."

Press Secretary Josh Earnest said Monday afternoon the White House was monitoring the incident.

Another message read "ISIS is already here, we are in your PCs, in each military base."

The organization "CyberCaliphate" has previously hacked twitter accounts of U.S. media outlets, including The Albuquerque Journal and Maryland's WBOC 16, but Monday's was the highest-level attack as yet attributed to the group.

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Applications Drive The Biggest Money In Big Data 01-09

Applications Drive The Biggest Money In Big Data

The real money in Big Data has nothing to do with selling Hadoop.

We're still fixating on all the wrong Big Data startups. Hortonworks, one of the primary companies behind Hadoop, recently went public to great fanfare and a $1.2 billion valuation. But Hortonworks and the rest of the so-called Big Data startups are actually some of the least interesting Big Data companies.

In fact, of the current crop of 40 startups valued at more than $1 billion, virtually none of them sell Big Data technology like Hadoop. But all of them make heavy use of data - lots of it - to deliver a wide array of services.

As consultant Peter Goldmacher declared back in 2013, the biggest winners in Big Data are the "business people that have identified opportunities to use data to create new opportunities or disrupt legacy business models." As we enter 2015, expect to see data double the number of billion-dollar startups even as public companies learn to grow through data, as well.

Do-It-Yourself Software Loses Its Luster

It used to be enough for a vendor to ship software and abandon the customer to figure it out (or pay hefty sums of money in consulting fees). SAP, for example, has made billions in revenue by shipping complex software and having customers shell out multiples of the software license fee for high-priced consultants to make sense of its Byzantine software.

That sort of strategy doesn't work very well anymore.

Forget startups for a moment. If we look at the stock prices of various data-related companies, investors are paying a premium for companies like Tableau and Qlik that make data easy to consume:

The companies rising the most include Tableau, Qlik and MicroStrategy, which provide tools to visualize data, while companies that tend to sell infrastructure like IBM and Teradata largely skidded through the year. (In fact, IBM is on its second year as one of the Dow Jones worst performers.)

Data Begets Billions

The analysis isn't perfect, of course. For example, though IBM sells a lot of core infrastructure it also has a Business Intelligence business. Oracle, for its part, plays in many camps, with a strong applications business to make up for its stalling database business.

But where the shift to Big Data really becomes apparent is in the Wall Street Journal's burgeoning billion-dollar startup club. As the Journal's Christopher Mims points out, "2014 was the year tech startup valuations went on a tear without precedent." 

It was also the year that tech startups put data to use at unprecedented levels.

No, not in the old-school Big Data way. When you review most lists of the "top 10 Big Data companies" they focus on those that sell Big Data technology. Among the top-15 most valuable startups, only Cloudera (and maybe Palantir) counts as a Big Data startup in this old sense of the word. 

Source: Wall Street Journal

Comb through the rest of the top-40 most valuable startups and you add MongoDB and Good Data. At face value this seems to suggest that Big Data really isn't that big of a deal.

Back to Goldmacher.

In Goldmacher's world, the "Big winners" in Big Data are "infrastructure providers like the Hadoop vendors and the NoSQL vendors," the "Bigger winners" are "the Apps and Analytics vendors that abstract the complexity of working with very complicated underlying technologies into a user friendly front end."

There's An App For That

But the "Biggest winners," as noted above, are companies like Uber, Stripe and Airbnb that have figured out how to "leverage data as an asset," thereby up-ending old industries and setting themselves apart. Look through the list of the top-40 most valuable startups and nearly all of them have this in common: they understand and leverage Big Data.

As we enter 2015, data will become more important than ever. It won't, however, be easy to track, because there's no meaningful "Big Data" category of vendors. Instead, data will transform industries as diverse as retail and healthcare, crowning multitudes of billion-dollar startups and billion-dollar revenue streams along the way.

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Spark Just Passed Hadoop in Popularity on the Web–Here’s Why 01-09

Spark Just Passed Hadoop in Popularity on the Web–Here’s Why

Interest in Apache Spark surpassed Apache Hadoop for the first time last month, according to Google Trends. While it’s not a definitive statement of Spark’s actual impact on big data processing in the real world, it does indicate the enormous momentum the in-memory analytics software has garnered during a phenomenal run in 2014.

As you can see from the Google Trends graphic–which compares the relative popularity of search terms that people enter and prevalence of news articles about given topics–Apache Spark went from a relative unknown to big data superstar in a matter of months. Coming out of Cal Berkeley’s AMPLab, Spark was just one of a handful of promising distributed computing frameworks at this time last year.

In October Apache Spark (blue line) passed Apache Hadoop (red line) in popularity according to Google Trends

But from January through October of this year, interest in Spark skyrocketed. It went from next to nothing into the most talked-about and search-for big data technology in the land—even bigger than big data’s big daddy, Apache Hadoop.

So why has Spark risen so far and so fast? Spark’s popularity has largely been driven by developers who are tired of the complexity of MapReduce and who want an easier and faster way to build big data applications, primarily for Hadoop.

Setting up data flows is critical in today’s big data analytic apps, and Spark simply makes that task easier. When you get Spark, you get a variety of processing engines, including the Spark SQL capability, Spark Streaming, and the MLlib machine learning library (additional capabilites like GraphX for graph analytics, the SparkR capability for running R-based applications, and hte BlinkDB capability are also in the wings). Moving data from one processing engine to the next is more easily done under Spark than if you had to cobble together multiple Hadoop-based

processing engines, such as MapReduce, Impala, Storm, Mahout, and Giraph.

Spark also has speed on its side. Last month Databricks, the company behind Spark,released benchmark results that demonstrated Spark running three times faster than MapReduce on a 100TB sort workload, using 10 times less computing power. It also out-sorted MapReduce by a factor of four on a 1PB workload, using significantly less hardware. In some instances, Spark can run upwards of 100 times faster than MapReduce applications, Spark backers have claimed.

In the beginning of the year, there were about 200 contributors to Spark, which made it a more active project than Hadoop MapReduce. Since then, more than 100 additional contributors have signed on to help develop Spark.

Where will it go in 2015? Don’t bet against it from continuing the rise. “Spark is a fast moving project,” Databricks Head of Engineering, Ali Ghodsi, told Datanami last month. “It’s actually the most active big data project now out there. There’s a lot happening to it.”

The community of Hadoop software vendors are also increasingly turning to Spark to power big data analytic applications. Platfora, ClearStory Data, and Alpine Data Labs have all committed to using Spark in their Hadoop-based applications, while Trifacta and Paxata are also counting on Spark’s speed to power big data transformation solutions. Datameer is re-architecting its solution with Spark in mind, and Glassbeam, which builds a NoSQL-based product that helps companies make sense of big data generated by devices connected to the Internet of Things (IoT), recently adopted Spark running under Cassandra.

Spark is outpacing Hadoop itself as the hottest big data technology at the moment. The fact that Spark doesn’t need Hadoop creates an interesting tension in the marketplace. The folks at Databricks will tell you that they learned from Hadoop’s early mistakes and are seeking to eliminate much of the complexity that plagues first-gen Hadoop and MapReduce implementations.

Unfortunately, getting Spark running on-premise is still hard, Databricks says. That’s where its Databricks Cloud implementation of Spark comes in handy. And while Databricks Cloud doesn’t use Hadoop, many of its early customers analyze HDFS-resident data.

In many ways, Spark is helping to fulfill the big data promises and dreams of Hadoop and that has forced the Hadoop distributors to take notice.Cloudera was an early supporter of Spark and has been shipping the Spark software with its latest Hadoop distribution CDH 5, since it was in beta over a year ago. MapR Technologies has also supported the entire Apache stack since April.

It took a little longer for Hortonworks to catch the Spark wave. Hortonworks, which sticks closer to the core trunk of open source Hadoop and has openly questioned Spark’s readiness and ability to scale at the high end, started talking about making Spark a first-class citizen on Hadoop 2.0 and YARN during the summer. As it stands, Spark will be fully supported in Hortonworks Data Platform version 2.2, which it unveiled in October and is currently in tech preview.

Hortonworks is fully on board Spark bandwagon now and is ramping up efforts to fully integrate the technology with the rest of the Hadoop stack, which Hortonworks VP of strategic marketing John Kreisa recently described as a “shared vision for Apache Spark on Hadoop.”

“We’ve seen this unbridled excitement around Spark really over the past eight months,” Hortonworks Director of Product Marketing Jim Walker told Datanami recently. “It’s fascinating how quickly this is picking up in the broader enterprise.”

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2015 is getting an extra second and that's a bit of a problem for the internet 01-09

2015 is getting an extra second and that's a bit of a problem for the internet

On June 30th at precisely 23:59:59, the world’s atomic clocks will pause for a single second. Or, to be more precise, they’ll change to the uncharted time of 23:59:60 — before ticking over to the more worldly hour of 00:00:00 on the morning of July 1st, 2015. This addition of a leap second, announced by the Paris Observatory this week, is being added to keep terrestrial clocks in step with the vagaries of astronomical time — in this case, the slowing of the Earth’s rotation. And it's a bit of a headache for computer engineers.

WHAT CAUSES LEAP SECONDS? EARTHQUAKES, TIDAL DRAG, THE WEATHER

Leap seconds are like the Y2K bug in that they threaten to throw out of sync time as measured by computers and time as measured by atomic clocks. But while Y2K was a single instance (computer systems that were used to abbreviating the year to two digits were confused by "2000" and "1900"), the addition of leap seconds are a regular problem. The first was added back in 1972; this year’s will be the 26th, and they're not likely to stop coming. They're also broadly unpredictable: earthquakes, tidal drag, and the weather all affect the rotation of the Earth, and it’s up to the scientists at the International Earth Rotation Serviceto keep an eye on things and call the changes as they come.

Unfortunately, when the last leap second was added back in 2012, more than a few sites had trouble keeping pace. As reported by Phys.org, Foursquare, Reddit, LinkedIn, and StumbledUpon all crashed when the leap second ticked unexpectedly into place. 

In the case of Reddit, the problem was eventually traced back to a Linux subsystem that got confused when it checked the Network Time Protocol only to find an extra second. Speaking to Wired about the problem back in 2012, Linux creator Linus Torvalds commented: "Almost every time we have a leap second, we find something. It’s really annoying, because it’s a classic case of code that is basically never run, and thus not tested by users under their normal conditions."

GOOGLE SOLVES tHE PROBLEM OF THE EXTRA SECOND BY CUTTING IT INTO MILLISECONDS

Instead, companies have been forced to create their own workaround, with Google’s "leap smear" perhaps the best-known example. As the company’s site reliability engineer Christopher Pascoe explained in a blog post, the usual fix is to turn back the clocks by one second at the end of the day, essentially playing that second again. However, says Pascoe, this creates problems: "What happens to write operations that happen during that second? Does email that comes in during that second get stored correctly?" Google’s solution is to cut the extra second into milliseconds and then sprinkle these tiny portions of time into the system imperceptibly throughout the day. "This [means] that when it became time to add an extra second at midnight," says Pascoe, "our clocks [have] already taken this into account, by skewing the time over the course of the day."

COULD WE DETACH OUR CONCEPT OF TIME FROM THE SOLAR DAY?

Of course, not every website or company has the sort of engineering resources needed to implement something like a "leap smear," and when June 30th rolls around in the summer, you can expect to see the odd outage or two. Beyond clever engineering though, there's not much to be done. As The Telegraph reports, there are some factions in the US that would like to drop the leap second altogether, but doing so would mean unmooring our concept of time from one of the most fundamental timescales, the solar day, and setting civil time on a path forever diverging from time as measured by our planet. Would it be worth the trouble? We'll get another chance to find out on June 30th.

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IBM Chip Processes Data Similar to the Way Your Brain Does 01-07

New thinking: IBM has built a processor designed using principles at work in your brain.

IBM Chip Processes Data Similar to the Way Your Brain Does

New thinking: IBM has built a processor designed using principles at work in your brain.

A new kind of computer chip, unveiled by IBM today, takes design cues from the wrinkled outer layer of the human brain. Though it is no match for a conventional microprocessor at crunching numbers, the chip consumes significantly less power, and is vastly better suited to processing images, sound, and other sensory data.

IBM’s SyNapse chip processes information using a network of just over one million “neurons,” which communicate with one another using electrical spikes—as actual neurons do. The chip uses the same basic components as today’s commercial chips—silicon transistors. But its transistors are configured to mimic the behavior of both neurons and the connections—synapses—between them.

The SyNapse chip breaks with a design known as the Von Neumann architecture that has underpinned computer chips for decades. Although researchers have been experimenting with chips modeled on brains—known as neuromorphic chips—since the late 1980s, until now all have been many times less complex, and not powerful enough to be practical (see “Thinking in Silicon”). Details of the chip were published today in the journal Science.

The new chip is not yet a product, but it is powerful enough to work on real-world problems. In a demonstration at IBM’s Almaden research center, MIT Technology Review saw one recognize cars, people, and bicycles in video of a road intersection. A nearby laptop that had been programed to do the same task processed the footage 100 times slower than real time, and it consumed 100,000 times as much power as the IBM chip. IBM researchers are now experimenting with connecting multiple SyNapse chips together, and they hope to build a supercomputer using thousands.

When data is fed into a SyNapse chip it causes a stream of spikes, and its neurons react with a storm of further spikes. The just over one million neurons on the chip are organized into 4,096 identical blocks of 250, an arrangement inspired by the structure of mammalian brains, which appear to be built out of repeating circuits of 100 to 250 neurons, says Dharmendra Modha, chief scientist for brain-inspired computing at IBM. Programming the chip involves choosing which neurons are connected, and how strongly they influence one another. To recognize cars in video, for example, a programmer would work out the necessary settings on a simulated version of the chip, which would then be transferred over to the real thing.

In recent years, major breakthroughs in image analysis and speech recognition have come from using large, simulated neural networks to work on data (see “Deep Learning”). But those networks require giant clusters of conventional computers. As an example, Google’s famous neural network capable of recognizing cat and human faces required 1,000 computers with 16 processors apiece (see “Self-Taught Software”).

Although the new SyNapse chip has more transistors than most desktop processors, or any chip IBM has ever made, with over five billion, it consumes strikingly little power. When running the traffic video recognition demo, it consumed just 63 milliwatts of power. Server chips with similar numbers of transistors consume tens of watts of power—around 10,000 times more.

The efficiency of conventional computers is limited because they store data and program instructions in a block of memory that’s separate from the processor that carries out instructions. As the processor works through its instructions in a linear sequence, it has to constantly shuttle information back and forth from the memory store—a bottleneck that slows things down and wastes energy.

IBM’s new chip doesn’t have separate memory and processing blocks, because its neurons and synapses intertwine the two functions. And it doesn’t work on data in a linear sequence of operations; individual neurons simply fire when the spikes they receive from other neurons cause them to.

Horst Simon, the deputy director of Lawrence Berkeley National Lab and an expert in supercomputing, says that until now the industry has focused on tinkering with the Von Neumann approach rather than replacing it, for example by using multiple processors in parallel, or using graphics processors to speed up certain types of calculations. The new chip “may be a historic development,” he says. “The very low power consumption and scalability of this architecture are really unique.”

One downside is that IBM’s chip requires an entirely new approach to programming. Although the company announced a suite of tools geared toward writing code for its forthcoming chip last year (see “IBM Scientists Show Blueprints for Brainlike Computing”), even the best programmers find learning to work with the chip bruising, says Modha: “It’s almost always a frustrating experience.” His team is working to create a library of ready-made blocks of code to make the process easier.

Asking the industry to adopt an entirely new kind of chip and way of coding may seem audacious. But IBM may find a receptive audience because it is becoming clear that current computers won’t be able to deliver much more in the way of performance gains. “This chip is coming at the right time,” says Simon.

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