Listening and Voice Search: A Happy Tech Couple

April 26, 2018

Voice search is the next big thing in the search industry. This is a pretty universally accepted trend among tech thinkers. With that in mind, it’s a good time to look at your own personal use and your business uses for search and inquire whether or not you are ready. Chances are, you aren’t. We learned more from a recent article in The Next Web, “By 2020 30% of Search Will Be Voice Conducted. Here’s What That Means for Your Business.”

According to the story:

“I would also invest in trying to get clients to review my restaurant on Yelp and Tripadvisor so that when people click through, they will see relevant and recent information on my restaurant. If I were providing services, I would make an effort to get listed in Yelp and Google My Business to increase my chances of showing up.”

Another big way to prepare that experts are recommending is to think about SEO in a totally different way. The way we search through our fingertips and through our voiceboxes are totally different. In short, we tend to say less than we type when searching so SEO will have to be even more precise than before.

However, “Amazon’s Alexa Had a Flaw “That Let Eavesdroppers Listen In” reminds Beyond Search that in order to answer a question, the devices have to listen. Amazon’s Alexa had a “flaw” which allowed third parties to use the device like an old school “bug.” According to the write up, Amazon fixed this problem.

How many other always on listening devices are just listening, analyzing, and sending data into a federated database?

Toss in online search and cross correlation, and one has an intriguing way to gather intelligence.

Stephen E Arnold, April 26, 2018

Terror Database Enriched with Social Media Pix

April 24, 2018

A question is surging through the tech and espionage communities after a recent article that makes some big implications in both worlds. That’s because a company formed by ex-spies is using facial recognition software to create a database of images from social networks like Facebook. This raises a ton of questions, but they all start with the recent Daily Mail piece, “Surveillance Company Run by Ex-Spies is Harvesting Facebook Photos.”

According to the story, the program is called Face-Int and they have a specific goal in mind:

“Its creators say the software could lead to the identification of terror suspects, captured in promotional and other material posted online… “Experts are concerned that the company’s efforts extend beyond this remit, however, and into the political realm…’It raises the stakes of face recognition – it intensifies the potential negative consequences,’ Jay Stanley, senior policy analyst at the American Civil Liberties Union, told Forbes.”

While it is admirable that a company is aiming to help capture terrorists through social media, it leaves one to worry about several things. For starters, it’s pretty safe to assume many terrorists will not appear on social media or, at the least, not without something covering their face. Thus, accuracy becomes a concern. However, the larger concern is that This, however, does not touch upon the greater concern that private, law abiding citizens are also getting funneled into this database. The opportunities for invading one’s privacy is alarmingly high. Time will tell how this shakes out, but we have a hunch the general public will never be told.

Patrick Roland, April 24, 2018

Blockchain: A Database Tooth Fairy?

April 19, 2018

Writer Kai Stinchcombe at Medium understands why so many people want to believe blockchain technology will cure the ills of society, he really does. However, he is compelled to burst that bubble in the piece, “Blockchain Is Not Only Crappy Technology but a Bad Vision for the Future.” Most advocates of Bitcoin and other blockchain products proclaim the value of “a tamper-proof repository not owned by anyone” (his words). That would be great, he acknowledges… but that is not what we have here. He explains:

“You actually see it over and over again. Blockchain systems are supposed to be more trustworthy, but in fact they are the least trustworthy systems in the world. Today, in less than a decade, three successive top bitcoin exchanges have been hacked, another is accused of insider trading, the demonstration-project DAO smart contract got drained, crypto price swings are ten times those of the world’s most mismanaged currencies, and bitcoin, the ‘killer app’ of crypto transparency, is almost certainly artificially propped up by fake transactions involving billions of literally imaginary dollars. Blockchain systems do not magically make the data in them accurate or the people entering the data trustworthy, they merely enable you to audit whether it has been tampered with. A person who sprayed pesticides on a mango can still enter onto a blockchain system that the mangoes were organic. A corrupt government can create a blockchain system to count the votes and just allocate an extra million addresses to their cronies. An investment fund whose charter is written in software can still misallocate funds. How, then, is trust created?”

See the post for more about the technical limits of blockchain technology, as well as Stinchcombe’s philosophy on the role of trust in a connected society. In a nutshell, he thinks we should stop trying to avoid it and start working to build it. Sounds ideal to me.

Cynthia Murrell, April 19, 2018

Blockchain as a CP Delivery System

April 18, 2018

With the rise of Bitcoin’s profile the encryption platform, Blockchain, used to keep things so secret has also seen a rise in its profile. But just like Bitcoin’s scrutiny under the spotlight, Blockchain’s less savory side is being exposed. We learned more from a recent CoinCenter story, defending the encryption, called “Addressing The Concerns of Illicit Images on Public Blockchains.”

According to the well thought out editorial,

“Bitcoin transactions allow one to add to them a short text memo. What some have done is to include encoded text in transaction memo fields and these are recorded in the Blockchain. Some of these encoded surprises on the blockchain include wedding vows, Bible verses, the Bitcoin logo and white paper, and quotes from Nelson Mandela. Unfortunately, some sick individuals have also added encoded images of child abuse.”

This is, however, not a new problem for the dark web. In fact, three years ago Forbes pointed out that Blockchain was a potential safe haven for malware and child abuse. That doesn’t erase the problems, though. The CoinCenter piece points out that a majority of interactions through Blockchain are on the up-and-up and that many legitimate businesses are investigating its uses. So, it’s safe to say this encryption tool is not going anywhere. We just wonder how it can ethically be policed.

Patrick Roland, April 18, 2018

Hyperbolic Reasoning: Smart Software and Blockchain

March 22, 2018

What pairing of words can rival “blockchain” and “artificial intelligence”? I submit that this word duo could become the next peanut butter and jelly, Ma and Pa Kettle, or semantic search. (Yeah, I know “semantic search” is a bit fuzzy, but like smart software and blockchain, marketing and hyperbolic reasoning is mostly unbounded.)

I read “How Blockchain Can Transform Artificial Intelligence.” Now I don’t know what “artificial intelligence” is. I think I understand that blockchain is a distributed database. Blockchain has the charming characteristic of housing malware, stolen videos, and CP (that’s child pornography, I believe).

I agree that a database and data management system are important to many smart software systems. I am not sure that blockchain is the right dog for the Iditarod race, however.

The write up begs to differ. I learned:

By creating segments of verified databases, models can be successfully built and implemented upon only datasets which have been verified. This will detect any faults or irregularity in the data supply chain. It also helps to reduce the stress of troubleshooting and finding abnormal datasets since the data stream is available in segments. Finally, blockchain technology is synonymous with immutability, this means the data is traceable and auditable.

And the article identifies other benefits. But won’t other types of data management systems work as well or better than the much flogged blockchain?

I would suggest that some public blockchains leak information. Furthermore, the blockchain technology can house “attachments”, unwanted fellow travelers accompanying the encrypted data and assorted impedimenta the technology requires.

Some organizations like GSR and Cambridge Analytica prefer to keep their data and access to those data under wraps. The firestorm about Cambridge Analytica’s use of social media data certainly suggests to me that a blockchain approach may not have been an enhancement to the Cambridge Analytica system.

But read the write up. Make your own judgment.

For me, the this plus that approach to buzzwordisms does not convince. The promise— indeed the hope— that zippy technologies will deliver synergies is an example of hyperbolic reasoning.

Stephen E Arnold, March 22, 2018

Schmidt Admits It Is Hard to Discern Between Fact and Fiction

March 15, 2018

One basic research essential is learning how to tell the difference between fact and fiction.  It used to be easier to control and verify news because information dissemination was limited to physical mediums.  The Internet blew everything out of the water and made it more difficult to discern fact and fiction.  Humans can be taught tricks, but AI still has a lot to learn.  The Daily Mail reports that, “Alphabet Chairman Eric Schmidt Admits It Is ‘Very Difficult’ For Google’s Algorithm To Separate Fact From Fiction In Its Search Results.”

Millions of articles and other content is posted daily online.  Google’s job is to sift through it and delivery the most accurate results.  When opposing viewpoints are shared, Google’s algorithm has difficulty figuring out the truth.  Eric Schmidt says that can be fixed with tweaking.  He viewed fact vs. fiction problems as bugs that need repair and with some work they can be fixed.  The article highlights some of the more infamous examples of Google’s failing such as the AutoComplete feature and how conspiracy theories can be regarded as fact.

Search results displaying only hard truth will be as elusive as accurate sentiment analytics.

Schmidt added:

That is a core problem of humans that they tend to learn from each other and their friends are like them.  And so until we decide collectively that occasionally somebody not like you should be inserted into your database, which is sort of a social values thing, I think we are going to have this problem.’

Or we can just wait until we make artificial intelligence smarter.

Whitney Grace, March 15, 2018

Oracle: Sparking the Database Fire

October 3, 2017

Hadoop? Er, what? And Microsoft .SQLServer? Or MarkLogic’s XML, business intelligence, analytics, and search offering? Amazon’s storage complex? IBM’s DB2? The recently-endowed MongoDB?

I thought of these systems when I read “Targeting Cybersecurity, Larry Ellison Debuts Oracle’s New ‘Self-Driving’ Database.”

For me, the main point of the write up is that the Oracle database is coming. There’s nothing like an announcement to keep the Oracle faithful in the fold.
If the write up is accurate, Oracle is embracing buzzy trends, storage that eliminates the guess work, and security. (Remember Secure Enterprise Search, the Security Server, and the nifty credential verification procedures? I do.)
The new version of Oracle, according to the write up, will deliver self driving. Cars don’t do this too well, but the Oracle database will and darned soon.

The 18c Autonomous Database or 18cad will:

  • Fix itself
  • Cost less than Amazon’s cloud
  • Go faster
  • Be online 99.995 percent of the time

And more, of course.

Let’s assume that Oracle 18cad works as described. (Words are usually easier to do than software I remind myself.)

The customers look to be big winners. Better, faster, cheaper. Oracle believes its revenues will soar because happy customers just buy more Oracle goodies.

Will there be  a downside?

What about database administrators? Some organizations may assume that 18cad will allow some expensive database administrator (DBA) heads to roll.
What about the competition? I anticipate more marketing fireworks or at least some open source “sparks” and competitive flames to heat up the cold autumn days.

Stephen E Arnold, October 3, 2017

Short Honk: Database Cost

September 26, 2017

If you want to get a sense of the time and computational cost under the covers of Big Data processing, please, read “Cost in the Land of Databases.” Two takeaways for me were [a] real time is different from what some individuals believe, and [b] if you want to crunch Big Data bring money and technical expertise, not assumptions that data are easy.

Stephen E Arnold, September 26, 2017

AI to Tackle Image Reading

September 11, 2017

The new frontier in analytics might just be pictures. Known to baffle even the most advanced AI systems, the ability to break pictures into recognizable parts and then use them to derive meaning has been a quest for many for some time. It appears that Disney Research in cahoots with UC Davis believe they are near a breakthrough.

Phys.org quotes Markus Gross, vice president at Disney Research, as saying,

We’ve seen tremendous progress in the ability of computers to detect and categorize objects, to understand scenes and even to write basic captions, but these capabilities have been developed largely by training computer programs with huge numbers of images that have been carefully and laboriously labeled as to their content. As computer vision applications tackle increasingly complex problems, creating these large training data sets has become a serious bottleneck.

A perfect example of the application of this is MIT attempts to use AI to share recipes and nutritional information just by viewing a picture of food. The sky is the limit when it comes to possibilities if Disney and MIT can help AI over the current hump of limitations.

Catherine Lamsfuss, September 11, 2017

Blockchain Quote to Note: The Value of Big Data as an Efficient Error Reducer

September 6, 2017

I read “Blockchains for Artificial Intelligence: From Decentralized Model Exchanges to Model Audit Trails.” The foundation of the write up is that blockchain technology can be used to bring more control to data and models. The idea is an interesting one. I spotted a passage tucked into the lower 20 percent of the article which I judged to be a quote to note. Here’s the passage I highlighted:

as you added more data — not just a bit more data but orders of magnitude more data — and kept the algorithms the same, then the error rates kept going down, by a lot. By the time the datasets were three orders of magnitude larger, error was less than 5%. In many domains, there’s a world of difference between 18% and 5%, because only the latter is good enough for real-world application. Moreover, the best-performing algorithms were the simplest; and the worst algorithm was the fanciest. Boring old perceptrons from the 1950s were beating state-of-the-art techniques.

Bayesian methods date from the 18th century and work well. Despite LaPlacian and Markovian bolt ons, the drift problem bedevils some implementations. The solution? Pump in more training data, and the centuries old techniques work like a jazzed millennial with a bundle of venture money.

Care to name a large online outfit which may find this an idea worth nudging forward? I don’t think it will be Verizon Oath or Tronc.

Stephen E Arnold, September 6, 2017

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