Scripts and Rules: The Future Is Not Fully Automatic

September 24, 2018

I wanted to capture an item of information which may be lost in the flood of marketing craziness. The subject is smart software, autonomous systems, and why humans may have to push buttons and turn knobs.

The write up is “Deep Learning Is Inferior to Scripting for Teaching Robots.” The main idea, as I understood the article, is that creating useful robots (hardware and software) may benefit from old school methods.

The method is for one or more smart humans to create data sets and train robots. But the humans are not out of a job. The robots have to be retrained with more rules, updated rules, and fresh data sets.

The article points out:

They [A. Rupam Mahmood, Dmytro Korenkevych, Gautham Vasan, William Ma and James Bergstra] conclude that deep learning lags behind the traditional way of training robots with scripts ‘by a large margin in some tasks, where such solutions were well established or easy to script‘. However, RL was ‘more competitive’ in complex tasks (for instance, docking to a charging station). The report also shows that the RL algorithms need careful tuning to their variables before being useful for any task – but after tuning, those same variables were applicable across a range of tasks.

In short, autonomous methods are not as efficient as humans doing the rule work and creating scripts or training sets.

The point is an important one. Smart software is not the cost and accuracy silver bullet that marketers have described as a reality.

I am not disputing that for certain specific operations on bounded data smart software can be magical.

But bootstrapping intelligence and learning with zeros and ones has not yet docked at the port, unloaded, and moved the goods to the user.

Stephen E Arnold, September 24, 2018

Two Internets: Preparing for a Google Centric Walled Garden

September 24, 2018

In my “The Google Legacy” I included a diagram which showed a diagram of a Google centric Internet. Here’s a diagram from that monograph written in 2004:

walled garden

This is an old diagram. To modernize it, we need to add more closed systems such as a Russian Internet, an EU Internet, and maybe an Amazon Internet.

The idea is that information flows into a Google construct. Users use the system. Think of the diagram as illustrating an Internet which is, in effect, inside Google.

I thought about this now 15 year old diagram when I read “Former Google CEO Predicts the Internet Will Split in Two and One Part Will Be Led by China.” The write up reports:

If you think of China as like ‘Oh yeah, they’re good with the Internet,’ you’re missing the point. Globalization means that they get to play too. I think you’re going to see fantastic leadership in products and services from China. There’s a real danger that along with those products and services comes a different leadership regime from government, with censorship, controls, etc.

The subtext, of course, is that Google wanted China to change, a laughable moment like solving death.

Today Google finds itself faced with losing its walled garden. Think of the problem as AMP and online advertising under pressure from outsiders. These are people who can withdraw cash from an ATM but not understand its plumbing.

I interpreted the remark in the context of “The Google Legacy.”

  1. Two Internets means that Google will have to find a way to be a big dog in the other Internets which are likely to try and exclude the Silicon Valley scooter riders
  2. An explanation of why Google’s smart search system has to be given some special training
  3. A signal that Google will change, maybe taking another step down the road that Hewlett Packard followed. (Remember HP owned AltaVista? I do.)

To sum up, I think more allegedly helpful insights are revealing more than than paying for coffee with a mobile phone.

Stephen E Arnold, September 24, 2018

The Semantic Web: Technology Roadkill or a Roadside Snack?

September 24, 2018

I spotted a quote to note. Here it is:

The Semantic Web is as dead as last year’s roadkill.

The statement appears in “Whatever Happened to the Semantic Web?” The write up provides a run through of the starts and stops associated with making the Web into a more organized place.

I would point out that the state of the Semantic Web can be glimpsed in the TweetedTimes’ auto generated list of articles called “Semantic Search.” The collection of items focuses on a range of topics, but the thrust seems to be getting traffic for a Web site; for example, “How to Optimize Content for Semantic SEO.”

If you are an adherent of the Semantic Web, check out the included footnotes. I would point out that the Google has a number of Guha patents in its portfolio. I think the Semantic Web may be of interest to some at the online ad search giant.

Guha’s patents plus the work by Alon Halevy may suggest some interesting use cases for the mark up, triplet, smart agent system and methods.

Stephen E Arnold,  September 24, 2018

Smart Software and Clever Humans

September 23, 2018

Online translation works pretty well. If you want 70 to 85 percent accuracy, you are home free. Most online translation systems handle routine communications like short blog posts written in declarative sentences and articles written in technical jargon just fine. Stick to mainstream languages, and the services work okay.

But if you want an online system to translate my pet phrases like HSSCM or azure chip consultant, you have to attend more closely. HSSCM refers to the way in which some Silicon Valley outfits run their companies. You know. Like a high school science club which decides that proms are for goofs and football players are not smart. The azure chip thing refers to consulting firms which lack the big time reputation of outfits like Bain, BCG, Booz, etc. (Now don’t get me wrong. The current incarnations of these blue chip outfits is far from stellar. Think questionable practices. Maybe criminal behavior.) The azure chip crowd means second string, maybe third string, knowledge work. Just my opinion, but online translation systems don’t get my drift. My references to Harrod’s Creek are geocoding nightmares when I reference squirrel hunting and bourbon in cereal. Savvy?

I was, therefore, not surprised when I read “AI Company Accused of Using Humans to Fake Its AI.” The main point seems to be:

[An[ interpreter accuses leading voice recognition company of ripping off his work and disguising it as the efforts of artificial intelligence.

There are rumors that some outfits use Amazon’s far from mechanical Turk or just use regular employees who can translate that which baffles the smart software.

The allegation from a former human disguised as smart software offered this information to Sixth Tone, a blog publishing the article:

In an open letter posted on Quora-like Q&A platform Zhihu, interpreter Bell Wang claimed he was one of a team of simultaneous interpreters who helped translate the 2018 International Forum on Innovation and Emerging Industries Development on Thursday. The forum claimed to use iFlytek’s automated interpretation service.

Trust me, you zippy millennials, smart software can be fast. It can be efficient. It can be less expensive than manual methods. But it can be wrong. Not just off base. Playing a different game with expensive Ronaldo types.

Why not run this blog post through Google Translate and check out the French or Spanish the system produces? Better yet, aim the system as a poor quality surveillance video or a VoIP call laden with insider talk between a cartel member and the Drug Llama?

Stephen E Arnold, September 23, 2018

HSSCM Methods: Hey, Enough of This Already

September 22, 2018

I read an allegedly “real journalism” story called “Google Suppresses memo Revealing Plans to Closely Track Search Users in China.” I won’t call attention to the split infinitive, which is not popular among the sensitive set.

And now to the “real” story:

The write up reveals that allegedly Google’s high school science club management methods include forcing employees to “delete a confidential memo circulating insight the company.”

But here’s the juicy bit:

The memo, authored by a Google engineer who was asked to work on the project, disclosed that the search system, codenamed Dragonfly, would require users to log in to perform searches, track their location — and share the resulting history with a Chinese partner who would have “unilateral access” to the data.

Okay, now that’s management: Confidential material circulating. Info must be deleted. Data from the alleged memo gets leaked to a “real” news outfit.

The reaction is classic HSSCM: Anger, possible governance goofs, and saying one thing and maybe, just maybe, doing something else.

Well, the HSSCM method includes what the write up says is an interesting angle:

Google reportedly maintains an aggressive security and investigation team known as “stopleaks,” which is dedicated to preventing unauthorized disclosures. The team is also said to monitor internal discussions.

I particularly like the phrase “moral agency.”

Hey, hey, the HSSCM method means that the science club sets the rules. “Moral agency?” Can that be measured in mendacity?

Stephen E Arnold, September 22, 2018

Modern Journalism: Fact or Fiction or Something Quite New

September 21, 2018

I read the information on this New York Times’ Web page. The intent is to explain how the NYT can learn a “secret” from a helpful reader. I noted this statement:

Each tip, be it from a submission or from a source, is rigorously vetted and probed.”

I find that interesting. I wonder how the anonymous editorial about the “soft” revolt within President Donald Trump’s staff was verified.

Probably not important. “Real” journalists do not have to reveal sources when a secret tip is rigorously vetted and probed.

From my vantage point in Harrod’s Creek, where real journalism is embodied in the local newspaper, the difference between reality and fiction is blurred. It is not thinking here; it is bourbon that does the trick.

Stephen E Arnold, September 21, 2018

Amazon: Device Proliferation and One Interesting Use Case

September 21, 2018

The technology “real news” channels are stuffed with Amazon gizmo news. Interesting stuff if one considers that these devices may snap into the eCommerce company’s policeware subsystems.

Here in Harrod’s Creek, we noted one announcement almost lost in the flood of device announcements. “Skype Calling Coming to Amazon Alexa Devices Later This Year” indicates that the tension between the two companies may be lessening. Years ago Microsoft had database envy generated by the eCommerce giant’s innovations in data management and data wrangling. Then there were the skirmishes over staff and office space.

If the information in the ZDNet “real news” write up is accurate, this statement may be more interesting than using an Alexa gizmo as a telephone:

Alexa users will be able to make outgoing Skype voice and video calls, accept incoming Skype calls and make SkypeOut calls to most phone numbers around the world, according to Microsoft officials. Users will be able to say “Alexa, call Jimmy on Skype,” or to say “Alexa, answer” when a Skype call comes in.

But the “real news” continues with an admission from the author:

I have to admit at this point I am kind of lost as to how Microsoft hopes to differentiate and position Cortana. Granted, Microsoft execs said they want Cortana not to be just about convenience, but about built-in assistance, but Skype is a Microsoft service….

From my vantage point in Harrod’s Creek, the tie up in voice may be more than a test. In fact, the deal may signal another victim of the Amazon strategy. Microsoft may be losing without knowing that it is in a fight.

Stephen E Arnold, September 21, 2018

Deep Learning Helps Bing Spotlight Aggregate Breaking News

September 20, 2018

News aggregators sift through the vast number of news stories out there to focus on the content users want to see (and lead to filter bubbles, but that is another topic.) Now, Microsoft has built an aggregator for breaking content right into its browser. VentureBeat reports, “Bing Spotlight Uses AI to Highlight Developing News Stories.” Writer Kyle Wiggers informs us:

“A spokesperson told VentureBeat via email that Bing Spotlight is an ‘evolving feature,’ and that the team will evaluate options based on feedback. Bing Spotlight spots trending topics with the help of deep learning algorithms that ingest millions of search queries and news articles every day. Leaning on a web graph of ‘hundreds of millions’ of websites, it factors in signals such as browser logs, the number of publishers covering a story, and how prominently each publisher featured their respective stories on their sites.’ Articles have to be ‘original, readable, newsworthy, and transparent’ before they’re considered for a top spot, and must demonstrate ‘sound journalistic practices’ such as identify sources and authors, giving attribution, and labeling opinion and commentary.”

Wiggers reproduces a diagram that illustrates the sections of a Spotlight results page—a carousel at the top revolves through related stories; a section titled Perspectives offers various points of view on the topic; the Rundown presents the story’s development over time; and, of course, there’s a section that shares related social media posts. ­­­Notably, this development comes on the heels of a similar move from Google—that company recently retooled their Google News app for smartphones. I suppose all users must do is decide who they want assembling their news for them.

Cynthia Murrell, September 20, 2018

Google: Stomping Out Bad Music Types

September 20, 2018

Google has a lot of content to lord over. And with that responsibility comes the need to police that content when it is misused. Perhaps nowhere does this happen more often than YouTube. While they have clever tools for finding rule breakers, sometimes it fails. We learned more from a recent ARS Technica story, “Google: Sorry, Professor, Old Beethoven Recordings on YouTube Copyrighted.”

According to the story:

“ContentID is a system, developed by YouTube, which checks user-uploaded videos against databases of copyrighted content in order to curb copyright infringement. This system took millions of dollars to develop and is often pointed to as a working example of upload filters by rights holders and lawmakers who wish to make such technology mandatory for every website which hosts user content online.”

Despite following copyright laws, the author (also a music teacher) had several musical pieces removed from the platform, despite being public domain. Maybe the problem isn’t within the code of YouTube’s software, but rather its parent company’s loose attitude toward the topic. Take, for example, the time they recently tried to patent a public domain algorithm. We think that maybe the problem isn’t all digital, but the smash-and-grab mentality of Google.

Patrick Roland, September 20, 2018

IBM Lock In Approach Modified and Given New Life

September 20, 2018

I read “Alphabet Backs GitLab’s Quest to Surpass Microsoft’s GitHub.” The write up explains that Microsoft bought GitHub. Google invests in GitLab. Plus:

It’s the latest major deal in the so-called DevOps market. Broadcom Inc. agreed to buy CA Technologies for $19 billion earlier this year; Atlassian Corp. bought OpsGenie Inc. for $295 million; and Salesforce Inc. spent $6.5 billion to purchase MuleSoft Inc.

From my point of view, these are open source oriented deals.

These deals are part of a revitalization of the old school IBM type of vendor lock in. The way that once worked was:

Buy our big iron

Use our software

Use our preferred partners


Good luck getting those mainframe puppies to behave.

Now the trajectory is to embrace open source, support anyone who codes something semi useful, add proprietary bits, and lock in the platform users.

In short, the lock in play is undergoing a renascence.

How about that open source credo? But where’s Amazon? If you want our take on Amazon’s tactics, contact benkent2020 at yahoo dot com and ask about our for fee briefing on this subject.

Stephen E Arnold, September 20, 2018

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