Computational Limits: Just a Reminder to the Cheerleaders for Big Data and Analytics
December 1, 2016
“Let’s index everything” or “Let’s process all the digital data”. Ever hear these statements or something similar? I have. In fact, I hear this type of misinformed blather almost every day. I read “Big Data Coming in Faster Than Biomedical Researchers Can Process It” seems to have figured out that yapping about capture and crunch are spitting out partial truths. (What’s new in the trendy world of fake news?)
The write up points out in a somewhat surprised way:
“It’s not just that any one data repository is growing exponentially, the number of data repositories is growing exponentially,” said Dr. Atul Butte, who leads the Institute for Computational Health Sciences at the University of California, San Francisco.
Now the kicker:
Prospecting for hints about health and disease isn’t going to be easy. The raw data aren’t very robust and reliable. Electronic medical records are often kept in databases that aren’t compatible with one another, at least without a struggle. Some of the potentially revealing details are also kept as free-form notes, which can be hard to extract and interpret. Errors commonly creep into these records. And data culled from scientific studies aren’t entirely trustworthy, either.
Net net: Lots of data. Inadequate resources. Inability to filter for relevance. Failure to hook “data” to actual humans. The yap about curing cancer or whatever disease generates a news release indicates an opportunity. But there’s no easy solution.
The resources to “make sense” of large quantities of historical and real time data are not available. But marketing is easy. Dealing with real world data is a bit more difficult. Keep that in mind if you develop a nifty disease and expect Big Data and analytics to keep the cookies from burning. Sure the “data” about making a blue ribbon batch of chocolate chips is available. Putting the right information into a context at the appropriate time is a bit more difficult even for the cognitive, smart software, text analytics cheerleaders.
Wait. I have a better idea. Why not just let a search system find and discover exactly what you need? Let me know how that works out for you.
Stephen E Arnold, December 1, 2016
Google and Its Search Results: Objective or Subjective
December 1, 2016
I love the Alphabet Google thing. The information I obtain via a Google query is spot on, accurate, perfect, and highly credible. Run the query “dancing with the stars” and what do you get? Substance. Rock solid factoids.
I read “Google Search Results Tend to Have Liberal Bias That Could Influence Public Opinion.” The write up informed me:
After analyzing nearly 2,000 pages, a panel rated 31% pages as liberal as opposed to only 22% that were conservative; the remaining 47% pages were neutral that included government or mainstream news websites.
And the source of this information? An outfit called CanIRank.com. That sounds like a company that would make Ian Sharp sit up and take notice. Don’t remember Ian Sharp? Well, too bad. He founded IP Sharp Associates and had some useful insights about the subjective/objective issues in algorithms.
The methodology is interesting too:
The study conducted by online search marketer CanIRank.com found that 50 most recent searches for political terms on the search engine showed more liberal-leaning Web pages rather than conservative ones.
But the Google insists that is results are objective. But Google keeps its ranking method secret. The write up quotes a computer science professor as saying:
“No one really knows what Google’s search engine is doing,” said Christo Wilson, a Northeastern University computer science professor. “This is a big, complex system that’s been evolving for 15 years.”
Hmm. Evolving. I thought that the Google wraps its 1998 methods and just keeps on trucking. My hunch is that the wrappers which have been added by those trying to deal with the new content and new uses to which the mobile and desktop Web search systems are put are add ons. Think of the customization of a celebrity’s SUV. That’s how Google relevance has evolved. Cool, right?
The write up points out:
Google denies results are politically slanted and says its algorithms use several factors.
My hunch is that CanIRank.com is well meaning, but it may have some biases baked into its study. CanIRank.com, like the Google, is based on human choices. When humans fiddle, subjectivity enters the arena. For real objectivity, check out Google’s translation system which may have created its own inter-lingua. That’s objective as long as one does not try to translate colloquial code phrase from a group of individuals seeking to secure their communications.
Subjective humans are needed for that task. Humans are subjective. So how does the logic flow? Oh, right. Google must be subjective. This is news? Ask Foundem.
Stephen E Arnold, December 1, 2016
Technology and Never: A Risky Proposition
December 1, 2016
I love the capitalist tool. Forbes does the content marketing thing with a soupçon of MBA craziness and the legacy of a once proud business publication. The write up which caught my attention is “Never Acquire Technology You Understand.” The premise strikes me as ill advised.
The premise of the article is that a person with money to invest should seek far out, unproven, unknown, and high risk technologies. I highlighted this statement:
due to a lack of market and technology insight, these decisions turn into a white elephant–the corporate equivalent of the Bridge to Nowhere.
Got that? Here’s a picture to help you out.
Note the role of “waiters”. Apparently below “developers” are folks who serve others and survive on tips and the hope a big break will come with the order. “Waiters” are really the patient ones at the bottom of the pile.
The write up dips into the notion of a “robo advisor.” There’s social media too. The bulk of the write up describes the three types of individuals involved in doing big things via financial technology or betting money on technology horses.
What strikes me is the conclusion of the write up:
Unless you truly and deeply understand the needs of your audience, it’s best to be patient and then apply a rational litmus test to determine the personality you will present to the marketplace. If you are not a rational Waiter, you may end up in the Valley of Technology as a loss-leading Acquirer and Developer.
Wow.
The title says, “Buy stuff you don’t understand.” The conclusion says, “Sit tight.”
Forbes’ editors must have a deeper understanding of logic than I do. I thought that the approach of the smart money folks I used to work with followed some slightly different ideas; for example, diversification, allocation of a specific percentage to higher risk investments, and understand what you are dumping money into.
Errors in search and content processing companies are one example. Think of the dozens of investment firms which do not and did not understand the revenue potential of an information access company. In search, for example, a handful of companies have survived and most of the big name firms gen3rated a payoff when the company was sold to another firm. As standalone businesses, most search and content processing companies have not been home runs. The handful of high fliers has captured headlines due to financial improprieties or allegations of fancy dancing.
MBAs like to make money via flips or deals. Understanding a business is often not a prerequisite. Hey, it’s other people’s money. For those with some money, prudence makes sense. If something cannot be understood, the risks might be high. Do MBAs like wiring, side deals, and crazy double talk to get paid to be wizards?
Do dangerous technologies have a downside? Why not invest in fuel pool cleanups and let me know how that works out for you? You can even lend a hand. Oh, wear protective clothing. Some things which people don’t understand can have non financial consequences.
Stephen E Arnold, December 1, 2016
Could AI Spell Doom for Marketers?
December 1, 2016
AI is making inroads into almost every domain; marketing is no different. However, inability of AI to be creative in true sense may be a major impediment.
The Telegraph in a feature article titled Marketing Faces Death by Algorithm Unless It Finds a New Code says:
Artificial intelligence (AI) is one of the most-hyped topics in advertising right now. Brands are increasingly finding that they need to market to intelligent machines in order to reach humans, and this is set to transform the marketing function.
The problem with AI, as most marketers agree is its inability to imitate true creativity. As the focus of marketing is shifting from direct product placement to content marketing, the importance of AI becomes even bigger. For instance, a clothing company cannot analyze vast amounts of Big Data, decipher it and then create targeted advertising based on it. Algorithms will play a crucial role in it. However, the content creation will ultimately require human touch and intervention.
As it becomes clear here:
While AI can build a creative idea, it’s not creative “in the true sense of the word”, according to Mr Cooper. Machine learning – the driving technology behind how AI can learn – still requires human intelligence to work out how the machine would get there. “It can’t put two seemingly random thoughts together and recognize something new.
The other school of thought says that what AI lacks is not creativity, but processing power and storage. It seems we are moving closer to bridging this gap. Thus when AI closes this gap, will most occupations, including, creative and technical become obsolete?
Vishal Ingole, December 1, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Comprehensive Search System Atlas Recall Enters Open Beta
December 1, 2016
We learn about a new way to search nearly everything one has encountered digitally from TechCrunch’s article, “Atlas Recall, a Search Engine for Your Entire Digital Live, Gets an Open Beta and $20M in Backing.” The platform is the idea of Atlas Informatics CEO, and Napster co-founder, Jordan Ritter, a man after our own hearts. When given funding and his pick of projects, Ritter says, he “immediately” chose to improve the search experience.
The approach the Atlas team has devised may not be for everyone. It keeps track of everything users bring up on their computers and mobile devices (except things they specifically tell it not to.) It brings together data from disparate places like one’s Facebook, Outlook, Spotlight, and Spotify accounts and makes the data available from one cloud-based dashboard.
This does sound extremely convenient, and I don’t doubt the company’s claim that it can save workers hours every week. However, imagine how much damage a bad actor could do if, hypothetically, they were able to get in and search for, say, “account number” or “eyes only.” Make no mistake, security is a top priority for Atlas, and sensible privacy measures are in place. Besides, the company vows, they will not sell tailored (or any) advertising, and are very clear that each user owns their data. Furthermore, Atlas maintains they will have access to metadata, not the actual contents of users’ files.
Perhaps for those who already trust the cloud with much of their data, this arrangement is an acceptable risk. For those potential users, contributor Devin Coldewey describes Atlas Recall:
Not only does it keep track of all those items [which you have viewed] and their contents, but it knows the context surrounding them. It knows when you looked at them, what order you did so in, what other windows and apps you had open at the same time, where you were when you accessed it, who it was shared with before, and tons of other metadata.
The result is that a vague search, say ‘Seahawks game,’ will instantly produce all the data related to it, regardless of what silo it happens to be in, and presented with the most relevant stuff first. In that case maybe it would be the tickets you were emailed, then nearby, the plans you made over email with friends to get there, the Facebook invite you made, the articles you were reading about the team, your fantasy football page. Click on any of them and it takes you straight there. …
When you see it in action, it’s easy to imagine how quickly it could become essential. I happen to have a pretty poor memory, but even if I didn’t, who wants to scrub through four different web apps at work trying to find that one PDF? Wouldn’t it be nice to just type in a project name and have everything related to it — from you and from coworkers — pop up instantly, regardless of where it ‘lives’?
The main Atlas interface can be integrated with other search engines like Google and Spotlight, so users can see aggregated results when they use those, too. Interested readers may want to navigate to the article and view the embedded sales video, shorter than two minutes, which illustrates the platform. If you’re interested in the beta, you can sign up here (scroll down to “When can I start using Atlas?”). Founded in 2015, Atlas Informatics is based in Seattle. As of this writing, they are also hiring developers and engineers.
Cynthia Murrell, December 01, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
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