Which CPU Should You Buy? Comparing Intel Core i5 vs. i7

There’s a wealth of difference between Intel’s Core i5 and Core i7 processors. We outline each CPU and explain what it all means for your next desktop or laptop purchase.
For many consumers who are on the hunt for a new desktop or laptop PC, one of the biggest considerations is the type of processor. Two of the CPUs most often in contention are the Intel Core i5 and Intel Core i7. Discounting Core i3 (mainly found in budget systems) and AMD processors (another story entirely), the difference between Intel Core i5 and Core i7 can seem daunting, especially when the prices seem so close together once they’re in completed systems. We break down the differences for you.
Price and Marketing
Simply put, Core i5-equipped systems will be less expensive than Core i7-equipped PCs. Intel has moved away from the star ratings it used with previous-generation Core processors in favor of a capability-driven marketing message. Essentially, the Core i7 processors have more capabilities than Core i5 CPUs. They will be better for multitasking, multimedia tasks, high-end gaming, and scientific work. Core i7 processors are certainly aimed at people who complain that their current system is “too slow.” Spot-checking a system like the Dell XPS 13 Touch ultrabook, you’ll find the Core i5 to be about $200 less expensive than a similarly equipped Core i7 system.

Core Confusion

For the most part, you’ll get faster CPU performance from Core i7 than Core i5. The majority of Core i7 desktop CPUs are quad-core processors, but so are the majority of Core i5 desktop CPUs. This is not always the case, as there are dual-core mobile Core i7 processors and many dual-core mobile Core i5 CPUs. You might also see the rare six- or eight-core Core i7, but that’s usually found with the desktop-only, top-of-the-line Extreme Edition models.

The Core nomenclature has been used for several generations of CPUs. Nehalem and Westmere use three-digit model names (i.e., Intel Core i7-920), while Sandy Bridge, Ivy Bridge, Haswell, and Broadwell CPUs use four-digit model names (such as the Intel Core i7-5500). Thankfully, unless you’re shopping the used PC market, you’ll find Ivy Bridge processors in closeout systems and budget PCs, while you’ll find Haswell or Broadwell processors in most new PCs. Older-generation Nehalem, Westmere, and Sandy Bridge cores are found in older PCs and generally have lower performance. The essential takeaway is that to get better performance in each generation, buy a processor with a higher model number. For instance, an Intel Core i7-5500U generally has better performance than an Intel Core i5-5200U.

Give Me the Cache

In addition to generally faster base clock speeds, Core i7 processors have larger cache (on-board memory) to help the processor deal with repetitive tasks faster. If you’re editing and calculating spreadsheets, your CPU shouldn’t have to reload the framework where the numbers sit. This info will sit in the cache, so when you change a number, the calculations are almost instantaneous. Larger cache sizes help with multitasking as well, since background tasks will be ready for when you switch focus to another window. On currently available desktop processors, i5 CPUs have 3MB to 6MB of L3 cache, while i7 processors have 4MB to 8MB. Read more of this post

Microsoft unveils de-cluttering option for Office 365 mailboxes

Microsoft today launched Clutter, an email filtering option for Office 365 business customers.

The tool, which Microsoft debuted earlier this year in Outlook Web App (OWA), the browser-based mail client for Exchange, will roll out to Office 365 commercial customers starting today.

Similar to an anti-spam filter, Clutter shunts messages into a segregated folder where they can be ignored or reviewed later. Microsoft defines “clutter” as “lower priority messages” that, while not strictly spam, are either unimportant or useless.

“Clutter removes distractions so you can focus on what matters most,” claimed Brian Shiers, a senior product marketing manager, and Kumar Venkateswar, a senior program manager, in a blog post Tuesday. Shiers and Venkateswar work on the Exchange team.

In practice, Clutter works similarly to a spam filter: Users can drag messages they deem suitable to a same-named folder to “train” the tool to spot like email in the future. “It gets smarter over time, learning from your prior actions with similar messages, and assessing things like the type of content and even how you are addressed in the message,” said Shiers and Venkateswar.

Once enabled in OWA, Clutter appears in other clients linked to that Exchange account, including Outlook on both Windows and OS X desktops and notebooks, and the iPhone and Android OWA apps.

Microsoft powered Clutter with Office Graph, the machine learning engine that also drives Delve, an Office 365 application that attempts to automatically connect users to the most relevant colleagues, files and data.

Employees whose workplaces have adopted Office 365 subscription plans — including Business Premium (12.50peruserpermonth)andEnterpriseE3(20 per user per month) — will be able to call on Clutter; consumers who subscribe to Office 365 Home or Personal will not.

Companies that have opted into Microsoft’s First Release program — corporate early adopters, in other words — will see Clutter today in English-speaking locales; others will be able to access the tool starting later this month, or in the case of non-English languages, once Microsoft wraps up localization.

Computerworld enabled Clutter on an Office 365 Enterprise account through OWA’s Options menu — Microsoft’s recommended method — and a new folder labeled “Clutter” appeared moments later in the desktop Outlook client tied to the account.

There was no immediate evidence that Clutter was doing its job — even though several eligible messages had been dragged to the folder — but Shiers and Venkateswar warned that it would take several days to begin sweeping aside messages. They added that “the more [messages] you move [to the Clutter folder], the faster it will learn.” Read more of this post

This Device Diagnoses Hundreds of Diseases Using a Single Drop of Blood

rHEALTH X1.

rHEALTH X1. XPRIZE Foundation

The digital health revolution is still stuck.

Tech giants are jumping into the fray with fitness offerings like Apple Health and Google Fit, but there’s still not much in the way of, well, actual medicine. The Fitbits and Jawbones of the world measure users’ steps and heart rate, but they don’t get into the deep diagnostics of, say, biomarkers, the internal indicators that can serve as an early warning sign of a serious ailment. For now, those who want to screen for a disease or measure a medical condition with clinical accuracy still need to go to the doctor. Read more of this post

Machine Learning: Optimizing How WindTurbines Work (Video)

October 31, 2014
By Ulrich Kreutzer – Siemens, Pictures of the Future, siemens.com/pof
Wind parks produce their own air circulation dynamics. First row turbines get more wind than those in the middle. They also produce vortices that affect the performance of downstream turbines. Learning software can reduce these effects by optimizing rotor speeds and blade angles. (Image: Vattenfall)

Machine learning helps make complex systems more efficient. Regardless of whether the systems in question are steel mills or gas turbines, they can learn from collected data, detect regular patterns, and optimize their own operations. Researchers at Siemens are demonstrating that continuous learning also allows wind turbines to increase their electricity output.

In his free time Volkmar Sterzing likes to work as a sailing instructor on Lake Starnberg south of Munich. A specialist in machine learning at Siemens Corporate Technology, Sterzing says that: “There are definitely parallels between sailing instruction and the machine learning process we use to optimize products.” Whereas his pupils learn to understand the power of the wind and to intuitively know when and how they have to set their sails, Sterzing studies how complex systems such as wind turbines can independently recognize regular patterns in collected data and thus learn how to optimize their operations.

Read more of this post

Physics Nobel prize goes to scientists who perfected LED light

By Laura Smith-Spark, CNN
October 7, 2014 — Updated 1435 GMT (2235 HKT)

(CNN) — Two scientists in Japan and one at the University of California at Santa Barbara were awarded this year’s Nobel Prize in physics for helping create the LED light, a transformational and ubiquitous source that now lights up everything from our living rooms to our flashlights to our smart phones.

The awarding committee said the trio’s work is in keeping with the spirit of Alfred Nobel, the founder of the prize, because LED lights save on energy, last long and are environmentally-friendly because they don’t contain mercury.

They “hold great promise for increasing the quality of life for over 1.5 billion people around the world who lack access to electricity grids,” the awarding committee said.

Specifically, Isamu Akasaki, Hiroshi Amano and Shuji Nakamura were honored for inventing the blue light emitting diode.

Red and green diodes had been around for years. But when the three created the blue diodes in the early 1990s, only then could the white lamps that glow from every corner of our world be created.

For 30 years, scientists had tried to create the blue diode.

“They triggered a fundamental transformation of lighting technology,” the committee said. “They succeeded where everyone else failed.”

LED lights last longer and are more efficient than regular light bulbs and fluorescent lamps.

Medicine Nobel Prize goes for work on cells that form brain’s GPS system

Not prepared for it

Nakamura, a scientist at the University of California, Santa Barbara, said by phone that receiving the news that he had won the Nobel prize was “unbelievable.”

Akasaki and Amano are affiliated with Nagoya University in Japan.

Amano was on a flight when the committee tried to call him so was not able to hear the news in advance of the news conference, the committee said.

Staffan Normark, permanent secretary of the Royal Swedish Academy of Sciences, said that Nakamura and Akasaki had been thrilled to learn they were prize winners.

“I think they were not prepared for it. They had not been waiting up all day and all night for this call,” he said.

The three winners will share the 8 million Swedish kronor ($1.2 million) attached to the prize.

Last year’s physics prize went jointly to Francois Englert of Belgium and Peter Higgs of the United Kingdom for the theory of how particles acquire mass. Their theoretical brilliance was borne out when researchers confirmed the existence in 2012 of the Higgs boson, or “God particle.”

The Nobel prizes in chemistry, literature and economic sciences will be announced later this week, as will the Nobel Peace Prize.