Costs of the Cloud
December 15, 2016
The cloud was supposed to save organizations a bundle on servers, but now we learn from Datamation that “Enterprises Struggle with Managing Cloud Costs.” The article cites a recent report from Dimensional Research and cloud-financial-management firm Cloud Cruiser, which tells us, for one thing, that 92 percent of organizations surveyed now use the cloud. Researchers polled 189 IT pros at Amazon Web Services (AWS) Global Summit in Chicago this past April, where they also found that 95 percent of respondents expect their cloud usage to expand over the next year.
However, organizations may wish to pause and reconsider their approach before throwing more money at cloud systems. Writer Pedro Hernandez reports:
Most organizations are suffering from a massive blind spot when it comes to budgeting for their public cloud services and making certain they are getting their money’s worth. Nearly a third of respondents said that they aren’t proactively managing cloud spend and usage, the study found. A whopping 82 percent said they encountered difficulties reconciling bills for cloud services with their finance departments.
The top challenge with the continuously growing public cloud resource is the ability to manage allocation usage and costs,’ stated the report. ‘IT and Finance continue to have difficulty working together to ascertain and allocate public cloud usage, and IT continues to struggle with technologies that will gather and track public cloud usage information.’ …
David Gehringer, principal at Dimensional Research, believes it’s time for enterprises to quit treating the cloud differently and adopt IT monitoring and cost-control measures similar to those used in their own data centers.
The report also found that top priorities for respondents included cost and reporting at 54 percent, performance management at 46 percent, and resource optimization at 45 percent. It also found that cloudy demand is driven by application development and testing, at 59 percent, and big data/ analytics at 31 percent.
The cloud is no longer a shiny new invention, but rather an integral part of most organizations. We would do well to approach its management and funding as we would other resource. The original report is available, with registration, here.
Cynthia Murrell, December 15, 2016
Algorithmic Selling on Amazon Spells Buyer Beware
December 12, 2016
The article on Science Daily titled Amazon Might Not Always Be Pitching You the Best Prices, Researchers Find unveils the stacked deck that Amazon has created for sellers. Amazon rewards sellers who use automated algorithmic pricing by more often featuring those seller’s items in the buy box, the more prominent and visible display. So what is algorithmic pricing, exactly? The article explains,
For a fee, any one of Amazon’s more than 2 million third-party sellers can easily subscribe to an automated pricing service…They then set up a pricing strategy by choosing from a menu of options like these: Find the lowest price offered and go above it (or below it) by X dollars or Y percentage, find Amazon’s own price for the item and adjust up or down relative to it, and so on. The service does the rest.
For the consumer, this means that searching on Amazon won’t necessarily produce the best value (at first click, anyway.) It may be a mere dollar difference, but it could also be a more significant price increase between $20 and $60. What is really startling is that even though less than 10% of “algo sellers,” these sellers account for close to a third of the best-selling products. If you take anything away from this article, let it be that what Amazon is showing you first might not be the best price, so always do your research!
Chelsea Kerwin, December 12, 2016
Google Shifts Development Emphasis to Artificial Intelligence
December 2, 2016
The article on The American Genius titled Google’s Ambitious Plans to Change Every Device on the Planet explains the focus on A.I. innovation by Sundar Pichai, a Google CEO. If you think Google is behind when it comes to A.I., you haven’t been paying close enough attention. Google has dipped its feet in voice recognition and machine translation as well as language understanding, but the next step is Google Home. The article states,
This device seems to be a direct answer to Amazon’s Echo. Google Home isn’t the only product set to launch, however. They also plan to launch a messaging app called Allo. This is likely a direct response to WhatsApp, Kik, and other popular messaging platforms… Google may be hoping Allo is the answer for what this particular platform is lacking. Allo and Google Home will both be powered by a “Google assistant” (a bit like Siri), but in their eyes, more engaging.
So what will the future landscape of A.I. technology look like? Depends on who you believe. Microsoft, Apple, and Amazon can all point to an existing product, but Google can mention AlphaGo, the computer program developed by Google DeepMind, in response. Pichai recognizes that Google must be all about the long game when it comes to A.I., because so far, we have only scratched the surface. What role will Google play in the much-feared A.I. arms race? All we know right now is that more Google is good for Google.
Chelsea Kerwin, December 2, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Emphasize Data Suitability over Data Quantity
November 30, 2016
It seems obvious to us, but apparently, some folks need a reminder. Harvard Business Review proclaims, “You Don’t Need Big Data, You Need the Right Data.” Perhaps that distinction has gotten lost in the Big Data hype. Writer Maxwell Wessel points to Uber as an example. Though the company does collect a lot of data, the key is in which data it collects, and which it does not. Wessel explains:
In an era before we could summon a vehicle with the push of a button on our smartphones, humans required a thing called taxis. Taxis, while largely unconnected to the internet or any form of formal computer infrastructure, were actually the big data players in rider identification. Why? The taxi system required a network of eyeballs moving around the city scanning for human-shaped figures with their arms outstretched. While it wasn’t Intel and Hewlett-Packard infrastructure crunching the data, the amount of information processed to get the job done was massive. The fact that the computation happened inside of human brains doesn’t change the quantity of data captured and analyzed. Uber’s elegant solution was to stop running a biological anomaly detection algorithm on visual data — and just ask for the right data to get the job done. Who in the city needs a ride and where are they? That critical piece of information let the likes of Uber, Lyft, and Didi Chuxing revolutionize an industry.
In order for businesses to decide which data is worth their attention, the article suggests three guiding questions: “What decisions drive waste in your business?” “Which decisions could you automate to reduce waste?” (Example—Amazon’s pricing algorithms) and “What data would you need to do so?” (Example—Uber requires data on potential riders’ locations to efficiently send out drivers.) See the article for more notes on each of these guidelines.
Cynthia Murrell, November 30, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Dark Web Marketplaces Are Getting Customer Savvy
November 17, 2016
Offering on Dark Web marketplaces are getting weirder by the day. Apart from guns, ammo, porn, fake identities, products like forged train tickets are now available for sale.
The Guardian in an investigative article titled Dark Web Departure: Fake Train Tickets Go on Sale Alongside AK-47s reveals that:
At least that’s the impression left by an investigation into the sale of forged train tickets on hidden parts of the internet. BBC South East bought several sophisticated fakes, including a first-class Hastings fare, for as little as a third of their face value. The tickets cannot fool machines but barrier staff accepted them on 12 occasions.
According to the group selling these tickets, the counterfeiting was done to inflict financial losses on the operators who are providing deficient services. Of course, it is also possible that the fake tickets are used by people (without criminalistics inclinations) who do not want to pay for the full fares.
One school of thought also says that like online marketplaces on Open Web, Dark Web marketplaces are also getting customer-savvy and are providing products and services that the customers need or want. This becomes apparent in this portion of the article:
The academics say the sites, once accessed by invitation or via dark-web search engines (there’ll be no hyperlinks here) resemble typical marketplaces such as Amazon or eBay, and that customer service is improving. “Agora was invitation-only but many of these marketplaces are easily accessible if you know how to search,” Dr Lee adds. “I think any secondary school student who knows how to use Google could get access – and that’s the danger of it.
One of the most active consumer group on Dark Web happens to be students, who are purchasing anything from fake certificates to hacker services to improve their grades and attendance records. Educational institutions, as well as law enforcement officials, are worried about this trend. And as more people get savvy with Dark Web, this trend is going to strengthen creating a parallel e-commerce, albeit a dark one.
Vishal Ingole, November 17, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Oh No! The Ads Are Becoming Smarter
November 15, 2016
I love Christmas and subsequent holiday season, although I am tired of it starting in October. Thankfully the holiday music does not start playing until Thanksgiving week, as do the ads, although they have been sneaking into the year earlier and earlier. I like the fact that commercials and Internet ads are inanimate objects, so I can turn them off. IT Pro Portal tells me, however, that I might be in for a Christmas nightmare; “IBM’s Watson Now Used In Native Advertising” or the ads are becoming smarter!
While credit card expenditures, browsing history, and other factors are already used for individualized, targeted ads, they still remain a static tool dependent on external factors. Watson is going to try be tried in the advertising game to improve targeting in native advertising. Watson will add an aesthetic quality too:
The difference is – it’s not just looking at keywords as the practice was so far – it’s actually looking at the ad, determining what it’s about and then places it where it believes is a good fit. According to the press release, Watson “looks at where, why and how the existing editorial content on each site is ‘talking about’ subjects”, and then makes sure best ads are placed to deliver content in proper context.
Another way Watson’s implementation in advertising is “semantic targeting AI for native advertising.” It will work in real-time and deliver more individualized targeted ads, over your recent Amazon, eBay, and other Web site shopping. It is an interesting factor how Watson can disseminate all this information for one person, but if you imagine that the same technology is being used in the medical and law fields, it does inspire hope.
Whitney Grace, November 15, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Big Brother Now in Corporate Avatar
October 31, 2016
Companies in the US are now tracking employee movements and interactions to determine how productive their assets are. Badges created by Humanyze; embedded in employee IDs track these key indicators and suggest appropriate measures to help improve employee productivity.
An article published on Business Insider titled Employees at a dozen Fortune 500 companies wear digital badges that watch and listen to their every move reveals:
Humanyze visualizes the data as webs of social interaction that reveal who’s talking to whom on a by-the-second basis. The goal: Revolutionize how companies think about how they organize themselves.
The badges though only track employees who have explicitly given permission to track their working hours, imagination is the only inhibiting factor that will determine how the meta-data can be used. For instance, as the badges are being embedded into employee IDs (that already have chips), it can also be used by someone with right tools to track the movement of an employee beyond working hours.
Social engineering in the past has been used in the past to breach IT security at large organizations. With Humanyze badges, hackers now will have one more weapon in their arsenal.
One worrisome aspect of these badges becomes apparent here:
But the badges are already around the necks of more than 10,000 employees in the US, Waber says. They’ve led to wild insights. One client moves the coffee machine around each night, so the next morning employees in nearby departments naturally talk more.
The ironic part is, companies are exposing themselves to this threat. Google, Facebook, Amazon are already tracking people online. With services like Humanyze, the Big Brother has also entered the corporate domain. The question is not how the data will be used by hacked; it’s just when?
Vishal Ingole October 31, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Google Cloud, Azure, and AWS Differences
October 18, 2016
With so many options for cloud computing, it can be confusing about which one to use for your personal or business files. Three of the most popular cloud computing options are Amazon Web Services (AWS), Google Cloud Platform, and Microsoft Azure. Beyond the pricing, the main differences range from what services they offer and what they name them. Site Point did us a favor with its article comparing the different cloud services: “A Side-By-Side Comparison Of AWS, Google Cloud, And Azure.”
Cloud computing has the great benefit of offering flexible price options, but they can often can very intricate based on how much processing power you need, how many virtual servers you deploy, where they are deployed, etc. AWS, Azure, and Google Cloud do offer canned solutions along with individual ones.
AWS has the most extensive service array, but they are also the most expensive. It is best to decide how you want to use cloud computing because prices will vary based on the usage and each service does have specializations. All three are good for scalable computing on demand, but Google is less flexible in its offering, although it is easier to understand the pricing. Amazon has the most robust storage options.
When it comes to big data:
This requires very specific technologies and programming models, one of which is MapReduce, which was developed by Google, so maybe it isn’t surprising to see Google walking forward in the big data arena by offering an array of products — such as BigQuery (managed data warehouse for large-scale data analytics), Cloud Dataflow (real-time data processing), Cloud Dataproc (managed Spark and Hadoop), Cloud Datalab (large-scale data exploration, analysis, and visualization), Cloud Pub/Sub (messaging and streaming data), and Genomics (for processing up to petabytes of genomic data). Elastic MapReduce (EMR) and HDInsight are Amazon’s and Azure’s take on big data, respectively.
Without getting too much into the nitty gritty, each of the services have their strengths and weaknesses. If one of the canned solutions do not work for you, read the fine print to learn how cloud computing can help your project.
Whitney Grace, October 18, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Artificial Intelligence Is Only a Download Away
October 17, 2016
Artificial intelligence still remains a thing of imagination in most people’s minds, because we do not understand how much it actually impacts our daily lives. If you use a smartphone of any kind, it is programmed with software, apps, and a digital assistant teeming with artificial intelligence. We are just so used to thinking that AI is the product of robots that we are unaware our phones, tablets, and other mobiles devices are little robots of their own.
Artificial intelligence programming and development is also on the daily task list on many software technicians. If you happen to have any technical background, you might be interested to know that there are many open source options to begin experimenting with artificial intelligence. Datamation rounded up the “15 Top Open Source Artificial Intelligence Tools” and these might be the next tool you use to complete your machine learning project. The article shares that:
Artificial Intelligence (AI) is one of the hottest areas of technology research. Companies like IBM, Google, Microsoft, Facebook and Amazon are investing heavily in their own R&D, as well as buying up startups that have made progress in areas like machine learning, neural networks, natural language and image processing. Given the level of interest, it should come as no surprise that a recent artificial intelligence report from experts at Stanford University concluded that ‘increasingly useful applications of AI, with potentially profound positive impacts on our society and economy are likely to emerge between now and 2030.
The statement reiterates what I already wrote. The list runs down open source tools, including PredictionIO, Oryx 2, OpenNN, MLib, Mahout, H20, Distributed Machine Learning Toolkit, Deeplearning4j, CNTK, Caffe, SystemML, TensorFlow, and Torch. The use of each tool is described and most of them rely on some sort of Apache software. Perhaps your own artificial intelligence project can contribute to further development of these open source tools.
Whitney Grace, October 17, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Microsoft Looks Slightly Desperate Paying People to Use Edge and Bing
September 28, 2016
The article on Business Insider titled Microsoft Will Actually Pay You to Use Its Newest Web Browser shows the evolution of Microsoft’s program from using Bing Rewards to their own Microsoft Rewards. Originally, just using Bing could earn users points towards Starbucks, Amazon, and Hulu, to name a few. Microsoft is now rebranding and expanding the program to incentivize users to spend time on Microsoft Edge, the child of Internet Explorer. The article states,
So long as you’re actively using Microsoft Edge — defined as having the Edge window open and actually using it to browse the web…— you’ll accrue points that can be redeemed for prizes, up to 30 hours’ worth a month. While Windows 10 is on over 350 million active devices, the Edge browser hasn’t quite made the splash that Microsoft had hoped for. Current numbers place Edge usage at just over 4.2% of the overall browser market.
The article makes a point of mentioning that for this program to work for users, they can’t just have Microsoft Edge open. They also must use Microsoft Bing as their default search engine. Without that setup, no points for you. Some users might jump at the chance to get paid for doing practically nothing, but others might be less than willing to expose themselves to being tracked by Microsoft. Still others might wince at the idea of giving up their Google default. Microsoft Edge: the broke person’s Google Chrome.
Chelsea Kerwin, September 28, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
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