Salesforce Einstein and Enterprise AI

May 5, 2017

One customer-relationship-management (CRM) firm is determined to leverage the power of natural language processing within its clients’ organizations. VentureBeat examines “What Salesforce Einstein Teaches Us About Enterprise AI.” The company positions its AI tool as a layer within its “Clouds” that brings the AI magic to CRM. They vow that the some-odd 150,000 existing Salesforce customers can deploy Einstein quickly and easily.

Salesforce has invested much in the project, having snapped up RelatelQ for $390 million, BeyondCore for $110 million, Predicition IO for $58 million, and MetaMind for an undisclosed sum. Competition is fierce in this area, but the company is very pleased with the results so far. Writer Mariya Yao cites Salesforce chief scientist Richard Socher as she examines:

The Salesforce AI Research team is innovating on a ‘joint many-task’ learning approach that leverages transfer learning, where a neural network applies knowledge of one domain to other domains. In theory, understanding linguistic morphology should also accelerate understanding of semantics and syntax.

In practice, Socher and his deep learning research team have been able to achieve state-of-the-art results on academic benchmark tests for main entity recognition (identifying key objects, locations, and persons) and semantic similarity (identifying words and phrases that are synonyms). Their approach can solve five NLP tasks — chunking, dependency parsing, semantic relatedness, textual entailment, and part of speech tagging — and also builds in a character model to handle incomplete, misspelled, or unknown words.

Socher believes that AI researchers will achieve transfer learning capabilities in more comprehensive ways in 2017 and that speech recognition will be embedded in many more aspects of our lives. ‘Right now, consumers are used to asking Siri about the weather tomorrow, but we want to enable people to ask natural questions about their own unique data.’

That would indeed be helpful. The article goes on to discuss the potentials for NLP in the enterprise and emphasizes the great challenge of implementing solutions into a company’s workflow. See the article for more discussion. Based in San Francisco, Salesforce was launched in 1999 by a former Oracle executive.

Cynthia Murrell, May 5, 2017

Revealing the Google Relevance Sins

May 2, 2017

I was surprised to read “Google’s Project Owl”. Talk about unintended consequences. An SEO centric publication reported that Google was going to get on the stick and smite fake news and “problematic content.” (I am not sure what “problematic content” is because I think a person’s point of view influences this determination.”

The write up states in real journalistic rhetoric:

Project Owl is Google’s internal name for its endeavor to fight back on problematic searches. The owl name was picked for no specific reason, Google said. However, the idea of an owl as a symbol for wisdom is appropriate. Google’s effort seeks to bring some wisdom back into areas where it is sorely needed.

Right, wisdom. From a vendor of content wrapped in pay to play advertising and “black box” algorithms which mysteriously have magical powers on sites like Foundem and the poor folks who were trying to make French tax forms findable.

My view of the initiative and the real journalistic write up is typical of what folks in Harrod’s Creek think about Left Coast types:

  1. The write up underscores the fact that Google’s quality function, which I wrote about in my three Google monographs, does not work. What determines the clever PageRank method? Well, a clever way to determine a signal of quality. Heh heh. Doesn’t work.
  2. Google is now on the hook to figure out what content is problematic and then find a way to remove that content from the Google indexes. Yep, not one index, but dozens. Google Local (crooked shops, anyone), YouTube (the oodles of porn which is easily findable by an enterprising 12 year old using the Yandex video search function), news (why are there no ads on Google News? Hmmm.), and other fave services from the GOOG.
  3. Relevance is essentially non existent for most queries. I like the idea of using “authoritative sources” for obscure queries. Yep, those Lady Gaga hits keep on rocking when a person searches for animal abuse and meat dresses.

Let me boil this down.

If a person relies on a free, ad supported Web search system for information, you may be getting a jolt from which your gray matter will not recover.

What’s the fix? I know the write up champions search engine optimization and explaining how to erode relevance for a user’s online query. But I am old fashioned. Multiple sources, interviews, reading of primary sources, and analytical thinking.

Hey, boring. Precision and recall are sure less fun than relaxing queries to amp up the irrelevance output.

Tough.

Stephen E Arnold, May 2, 2017

Search Pinterest Pictures Without Pinterest

April 25, 2017

Pinterest is the beloved social media network, where users can post pictures, make comments, get decorating ideas, and recipes.  However, Recode tells us about a new implausible Google Chrome extension: “Pinterest Will Now Let You Search For Products Using Any Image You Find Online-Without Visiting Pinterest.”  Pinterest just launched a new Google Chrome extension that allows users to save images seen online as they browse.  The extension will work like this:

The new tool lets you select an item in any photograph online, and ask Pinterest to surface similar items using its image recognition software.  For example: If you see an image of sunglasses you like on Nordstrom.com, you could use the extension to browse similar glasses from Pinterest without ever leaving Nordstrom’s website.  If you click on one of the search results, you’ll then be taken to Pinterest.

Pinterest wants to leverage itself as an image search engine for all images, in real life and on the Internet.  Evan Sharp, Pinterest co-founder, said that users, should not “..have to put their thoughts into words to find great ideas.”  Visual search technology already exists, but only on Pinterest’s Web site.

Whitney Grace, April 25, 2017

The Big Dud

April 24, 2017

Marketers often need a fancy term periodically to sell technologies to large companies. Big Data and Hadoop was one such term. After years of marketing, adopters are yet to see any results, let alone any ROI.

Datamani recently published an article titled Hadoop Has Failed Us, Tech Experts Say in which the author says:

Many companies still run mainframe applications that were originally developed half a century ago. But thanks to better mousetraps like S3 (for storage) and Spark (for processing), Hadoop will be relegated to niche and legacy statuses going forward.

One of the primary concerns with Hadoop is that only handful of people know how to play it. For data scientists to make head and tail out of data, precise data queries and mining needs to be done. The dearth of experts, however, is hampering efforts of companies who want to make Big Data work for them. Other frameworks are trying to overcome problems put forth by Hadoop, but many companies have already adopted it and are stuck with it. And just like many fads, Big Data might fade into oblivion.

Vishal Ingole, April 24, 2017

ScyllaDB Version 3.1 Available

March 8, 2017

According to Scylla, their latest release is currently the fastest NoSQL database. We learn about the update from SiliconAngle’s article, “ScyllaDB Revamps NoSQL Database in 1.3 Release.” To support their claim, the company points to a performance benchmark test executed by the Yahoo Cloud Serving Benchmark project. That group compared ScyllaDB to the open source Cassandra database, and found Scylla to be 4.6 times faster than a standard Cassandra cluster.

Writer Mike Wheatley elaborates on the product:

ScyllaDB’s biggest differentiator is that it’s compatible with the Apache Cassandra database APIs. As such, the creators claims that ScyllaDB can be used as a drop-in replacement for Cassandra itself, offering users the benefit of improved performance and scale that comes from the integration with a light key/value store.

The company says the new release is geared towards development teams that have struggled with Big Data projects, and claims a number of performance advantages over more traditional development approach, including:

*10X throughput of baseline Cassandra – more than 1,000,000 CQL operations per second per node

*Sub 1msec 99% latency

*10X per-node storage capacity over Cassandra

*Self-tuning database: zero configuration needed to max out hardware

*Unparalleled high availability, native multi-datacenter awareness

*Drop-in replacement for Cassandra – no additional scripts or code required”

Wheatley cites Scylla’s CTO when he points to better integration with graph databases and improved support for Thrift, Date Tiered Compaction Strategy, Large Partitions, Docker, and CQL tracing. I notice the company is hiring as of this writing. Don’t let the Tel Aviv location of Scylla’s headquarters stop from applying you if you don’t happen to live nearby—they note that their developers can work from anywhere in the world.

Cynthia Murrell, March 8, 2016

Upgraded Social Media Monitoring

February 20, 2017

Analytics are catching up to content. In a recent ZDNet article, Digimind partners with Ditto to add image recognition to social media monitoring, we are reminded images reign supreme on social media. Between Pinterest, Snapchat and Instagram, messages are often conveyed through images as opposed to text. Capitalizing on this, and intelligence software company Digimind has announced a partnership with Ditto Labs to introduce image-recognition technology into their social media monitoring software called Digimind Social. We learned,

The Ditto integration lets brands identify the use of their logos across Twitter no matter the item or context. The detected images are then collected and processed on Digimind Social in the same way textual references, articles, or social media postings are analysed. Logos that are small, obscured, upside down, or in cluttered image montages are recognised. Object and scene recognition means that brands can position their products exactly where there customers are using them. Sentiment is measured by the amount of people in the image and counts how many of them are smiling. It even identifies objects such as bags, cars, car logos, or shoes.

It was only a matter of time before these types of features emerged in social media monitoring. For years now, images have been shown to increase engagement even on platforms that began focused more on text. Will we see more watermarked logos on images? More creative ways to visually identify brands? Both are likely and we will be watching to see what transpires.

Megan Feil, February 20, 2017

 

Google Battling Pirates More and More Each Year

February 10, 2017

So far, this has been a booming year for  DMCA takedown requests, we learn from TorrentFreak’s article, “Google Wipes Record Breaking Half Billion Pirate Links in 2016.” The number of wiped links has been growing rapidly over the last several years, but is that good or bad news for copyright holders? That depends on whom you ask. Writer Ernesto reveals the results of TorrentFreak’s most recent analysis:

Data analyzed by TorrentFreak reveals that Google recently received its 500 millionth takedown request of 2016. The counter currently [in mid-July] displays more than 523,000,000, which is yet another record. For comparison, last year it took almost the entire year to reach the same milestone. If the numbers continue to go up at the same rate throughout the year, Google will process a billion allegedly infringing links during the whole of 2016, a staggering number.

According to Google roughly 98% of the reported URLs are indeed removed. This means that half a billion links were stripped from search results this year alone. However, according to copyright holders, this is still not enough. Entertainment industry groups such as the RIAA, BPI and MPAA have pointed out repeatedly that many files simply reappear under new URLs.

Indeed; copyright holders continue to call for Google to take stronger measures. For its part, the company insists increased link removals is evidence that its process is working quite well. They issued out an update of their report, “How Google Fights Piracy.” The two sides remain deeply divided, and will likely be at odds for some time. Ernesto tells us some copyright holders are calling for the government to step in. That could be interesting.

Cynthia Murrell, February 10, 2017

Tips for Better Search Results

February 2, 2017

Want to be an expert searcher? Gizbot shares some tips, complete with screenshots, in their brief write-up, “Here are 5 Tricks To Get Better Google Search Results.” Writer Sneha Saha begins:

To get any information about anything is easy. Just type the keywords on the Google Search engine and you are done. Rather you might just get information that is far more than what you would actually need. However, getting more information than you require is also a little annoying. Searching for the accurate information among the numerous links that Google provides you with is surely a tough task. We at GizBot have come up with a list of effective methods to try out to search the most accurate information on Google in just a few clicks.

Here are the five tricks: Search for synonyms using a tilde symbol; Use an asterisk in place of any word you cannot remember; Include “or” when confused between two options; Use “intitle” to find keywords within a title or “inurl” to find keywords within a URL; Narrow results by including a date range in your query. See the post for details on any of these search tips.

Cynthia Murrell, February 2, 2017

Google and the Cloud Take on Corporate Database Management

February 1, 2017

The article titled Google Cloud Platform Releases New Database Services, Fighting AWS and Azure for Corporate Customers on GeekWire suggests that Google’s corporate offerings have been weak in the area of database management. Compared to Amazon Web Services and Microsoft Azure, Google is only wading into the somewhat monotonous arena of corporate database needs. The article goes into detail on the offerings,

Cloud SQL, Second Generation, is a service offering instances of the popular MySQL database. It’s most comparable to AWS’s Aurora and SQL Azure, though there are some differences from SQL Azure, so Microsoft allows running a MySQL database on Azure. Google’s Cloud SQL supports MySQL 5.7, point-in-time recovery, automatic storage resizing and one-click failover replicas, the company said. Cloud Bigtable is a NoSQL database, the same one that powers Google’s own search, analytics, maps and Gmail.

The Cloud Bigtable database is made to handle major workloads of 100+ petabytes, and it comes equipped with resources such as Hadoop and Spark. It will be fun to see what happens as Google’s new service offering hits the ground running. How will Amazon and Microsoft react? Will price wars arise? If so, only good can come of it, at least for the corporate consumers.

Chelsea Kerwin, February 1, 2017

Fight Fake News with Science

February 1, 2017

With all the recent chatter around “fake news,” one researcher has decided to approach the problem scientifically. An article at Fortune reveals “What a Map of the Fake-News Ecosystem Says About the Problem.” Writer Mathew Ingram introduces us to data-journalism expert and professor Jonathan Albright, of Elon University, who has mapped the fake-news ecosystem. Facebook and Google are just unwitting distributors of faux facts; Albright wanted to examine the network of sites putting this stuff out there in the first place. See the article for a description of his methodology; Ingram summarizes the results:

More than anything, the impression one gets from looking at Albright’s network map is that there are some extremely powerful ‘nodes’ or hubs, that propel a lot of the traffic involving fake news. And it also shows an entire universe of sites that many people have probably never heard of. Two of the largest hubs Albright found were a site called Conservapedia—a kind of Wikipedia for the right wing—and another called Rense, both of which got huge amounts of incoming traffic. Other prominent destinations were sites like Breitbart News, DailyCaller and YouTube (the latter possibly as an attempt to monetize their traffic).

Albright said he specifically stayed away from trying to determine what or who is behind the rise of fake news. … He just wanted to try and get a handle on the scope of the problem, as well as a sense of how the various fake-news distribution or creation sites are inter-connected. Albright also wanted to do so with publicly-available data and open-source tools so others could build on it.

Albright also pointed out the folly of speculating on sources of fake news; such guesswork only “adds to the existing noise,” he noted. (Let’s hear it for common sense!) Ingram points out that, armed with Albright’s research, Google, Facebook, and other outlets may be better able to combat the problem.

Cynthia Murrell, February 1, 2017

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