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

How Data Science Pervades

May 2, 2017

We think Information Management may be overstating a bit with the headline, “Data Science Underlies Everything the Enterprise Now Does.”  While perhaps not underpinning quite “everything,” the use of data analysis has indeed spread throughout many companies (especially larger ones).

Writer Michael O’Connell cites a few key developments over the last year alone, including the rise of representative data, a wider adoption of predictive analysis, and the refinement of customer analytics. He predicts, even more, changes in the coming year, then uses a hypothetical telecom company for a series of examples. He concludes:

You’ll note that this model represents a significant broadening beyond traditional big data/analytics functions. Such task alignment and comprehensive integration of analytics functions into specific business operations enable high-value digital applications ranging far beyond our sample Telco’s churn mitigation — cross-selling, predictive and condition-based maintenance, fraud detection, price optimization, and logistics management are just a few areas where data science is making a huge difference to the bottom line.

See the article for more on the process of turning data into action, as illustrated with the tale of that imaginary telecom’s data-wrangling adventure.

Cynthia Murrell, May 2, 2017

Comprehensive, Intelligent Enterprise Search Is Already Here

February 28, 2017

The article on Sys-Con Media titled Delivering Comprehensive Intelligent Search examines the accomplishments of World Wide Technology (WWT) in building a better search engine for the business organization. The Enterprise Search Project Manager and Manager of Enterprise Content at WWT discovered that the average employee will waste over a full week each year looking for the information they need to do their work. The article details how they approached a solution for enterprise search,

We used the Gartner Magic Quadrants and started talks with all of the Magic Quadrant leaders. Then, through a down-selection process, we eventually landed on HPE… It wound up being that we went with the HPE IDOL tool, which has been one of the leaders in enterprise search, as well as big data analytics, for well over a decade now, because it has very extensible platform, something that you can really scale out and customize and build on top of.

Trying to replicate what Google delivers in an enterprise is a complicated task because of how siloed data is in the typical organization. The new search solution offers vast improvements in presenting employees with the relevant information, and all of the relevant information and prevents major time waste through comprehensive and intelligent search.

Chelsea Kerwin, February 28, 2017

Google Shoots for Star Status in the Cloud Space

February 21, 2017

Competition continues in the realm of cloud technology. Amigo Bulls released an article, Can Google Cloud Really Catch Up With The Cloud Leaders?, that highlights how Google Cloud is behind Amazon Web Services and Microsoft Azure. However, some recent wins for Google are also mentioned. One way Google is gaining steam is through new clients; they signed Spotify and even some of Apple’s iCloud services are moving to Google Cloud. The article summarizes the current state,

Alphabet Inc’s-C (NSDQ:GOOG) Google cloud has for a long time lived in relative obscurity. Google Cloud results do not even feature on the company’s quarterly earnings report the way AWS does for Amazon (NSDQ:AMZN) and Azure for Microsoft (NSDQ:MSFT). This appears somewhat ironic considering that Google owns one of the largest computer and server networks on the planet to handle tasks such as Google Search, YouTube, and Gmail. Further, the Google Cloud Platform is actually cheaper than offerings by the two market leaders.

Enterprise accounts with legacy systems will likely go for Microsoft as a no-brainer given the familiarity factor and connectivity. Considering the enterprise sector will make up a large portion of cloud customers, Amazon is probably Google’s toughest competition. Spotify apparently moved to Google from Amazon because of the quality tools, including machine-learning, and excellence in customer service. We will continue following whether Google Cloud makes it as high in the sky as its peers.

Megan Feil, February 21, 2017

Hewlett Packard Enterprise Releases Q4 Earnings of First Year After Split from HP

January 30, 2017

The article on Business Insider titled Hewlett Packard Enterprise Misses Its Q4 Revenue Expectations But Beats on Profit discusses the first year of HPE following its separation from HP. The article reports fiscal fourth quarter revenue of $12.5B, just short of the expected $12.85B. The article provides all of the nitty gritty details of the fourth quarter segment results, including,

Software revenue was $903 million, down 6% year over year, flat when adjusted for divestitures and currency, with a 32.1% operating margin. License revenue was down 5%, down 1% when adjusted for divestitures and currency, support revenue was down 7%, up 1% when adjusted for divestitures and currency, professional services revenue was down 7%, down 4% adjusted for divestitures and currency, and software-as-a-service (SaaS) revenue was down 1%, up 11% adjusted for divestitures and currency.

Additionally, Enterprise Services revenue was reported as $4.7B, down 6% year over year, and Enterprise Group revenue was down 9% at $6.7B. Financial Services revenue was up 2% at $814M.  According to HPE President and CEO Meg Whitman, all of this amounts to a major win for the standalone company. She emphasized the innovation and financial performance and called FY16 a “historic” year for the company.

Chelsea Kerwin, January 30, 2017

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

Facebook AI pro Throws Shade at DeepMind Headquarters

November 29, 2016

An AI expert at Facebook criticizes Google’s handling of  DeepMind, we learn in Business Insider’s article, “Facebook’s AI Guru Thinks DeepMind is Too Far Away from the ‘Mothership’.” Might Yann LeCun, said guru, be biased? Nah. He simply points out that DeepMind’s London offices are geographically far away from Google’s headquarters in California. Writer Sam Shead, on the other hand, observes that physical distance does not hamper collaboration the way it did before this little thing called the Internet came along.

The article reminds us of rumors that Facebook was eying DeepMind before Google snapped it up. When asked, LeCun declined to confirm or deny that rumor. Shead tells us:

LeCun said: ‘You know, things played out the way they played out. There’s a lot of very good people at DeepMind.’ He added: ‘I think the nature of DeepMind eventually would have been quite a bit different from what it is now if DeepMind had been acquired by a different company than Google.

Google and Facebook are competitors in some areas of their businesses but the companies are also working together to advance the field of AI. ‘It’s very nice to have several companies that work on this space in an open fashion because we build on each other’s ideas,’ said LeCun. ‘So whenever we come up with an idea, very often DeepMind will build on top of it and do something that’s better and vice versa. Sometimes within days or months of each other we work on the same team. They hire half of my students.

Hooray for cooperation. As it happens, London is not an arbitrary location for DeepMind. The enterprise was founded in 2010 by two Oxbridge grads, Demis Hassabis and Mustafa Suleyman, along with UCL professor Shane Legg. Google bought the company in 2014, and has been making the most of their acquisition ever since. For example, Shead reminds us, Google has used the AI to help boost the efficiency of their data-center cooling units by some 40%. A worthy endeavor, indeed.

Cynthia Murrell, November 29, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph

Big Data Teaches Us We Are Big Paranoid

November 18, 2016

I love election years!  Actually, that is sarcasm.  Election years bring out the worst in Americans.  The media runs rampant with predictions that each nominee is the equivalent of the anti-Christ and will “doom America,” “ruin the nation,” or “destroy humanity.”  The sane voter knows that whoever the next president is will probably not destroy the nation or everyday life…much.  Fear, hysteria, and paranoia sells more than puff pieces and big data supports that theory.  Popular news site Newsweek shares that, “Our Trust In Big Data Shows We Don’t Trust Ourselves.”

The article starts with a new acronym: DATA.  It is not that new, but Newsweek takes a new spin on it.  D means dimensions or different datasets, the ability to combine multiple data streams for new insights.  A is for automatic, which is self-explanatory.  T stands for time and how data is processed in real time.  The second A is for artificial intelligence that discovers all the patterns in the data.

Artificial intelligence is where the problems start to emerge.  Big data algorithms can be unintentionally programmed with bias.  In order to interpret data, artificial intelligence must learn from prior datasets.  These older datasets can show human bias, such as racism, sexism, and socioeconomic prejudices.

Our machines are not as objectives as we believe:

But our readiness to hand over difficult choices to machines tells us more about how we see ourselves.

Instead of seeing a job applicant as a person facing their own choices, capable of overcoming their disadvantages, they become a data point in a mathematical model. Instead of seeing an employer as a person of judgment, bringing wisdom and experience to hard decisions, they become a vector for unconscious bias and inconsistent behavior.  Why do we trust the machines, biased and unaccountable as they are? Because we no longer trust ourselves.”

Newsweek really knows how to be dramatic.  We no longer trust ourselves?  No, we trust ourselves more than ever, because we rely on machines to make our simple decisions so we can concentrate on more important topics.  However, what we deem important is biased.  Taking the Newsweek example, what a job applicant considers an important submission, a HR representative will see as the 500th submission that week.  Big data should provide us with better, more diverse perspectives.

Whitney Grace, November 18, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph

Quote to Note: Enterprise Search As a Black Hole

October 19, 2016

Here’s a quote to note from “Slack CEO Describes Holy Grail of Virtual Assistants.” Slack seeks to create smart software capable of correlating information from enterprise applications. Good idea. The write up says:

Slack CEO Stewart Butterfield has an audacious goal: Turning his messaging and collaboration platform into an uber virtual assistant capable of searching every enterprise application to deliver employees pertinent information.

Got it. Employees cannot locate information needed for their job. Let me sidestep the issue of hiring people incapable of locating information in the first place.

Here’s the quote I noted:

And if Slack succeeds, it could seal the timeless black hole of wasted productivity enterprise search and other tools have failed to close.

I love the “timeless black hole of wasted productivity of enterprise search.” Great stuff, particularly because outfits like Wolters Kluwer continue to oscillate between proprietary search investments like Qwant.com and open source solutions like Lucene/Solr.

Do organizations create these black holes or is software to blame? Information is a slippery fish, which often find “timeless black holes” inhospitable.

Stephen E Arnold, October 19, 2016

Is Resting Data Safe Data?

August 2, 2016

Have you ever wondered if the data resting on your hard drive is safe while you are away from your computer?  Have you ever worried that a hacker could sneak into your system and steal everything even when the data is resting (not actively being used)?  It is a worry that most computer users experience as the traverse the Internet and possibly leaving themselves exposed.  Network World describes how a potential upgrade could protect data in databases, “ A New Update To The NoSQL Database Adds Cryptsoft Technology.”

MarkLogic’s NoSQL database version nine will be released later in 2016 with an added security update that includes Cryptsoft’s KMIP (Key Management Interoperability Protocol). MarkLogic’s upgrade will use the flexibility, scalability, and agility of NoSQL with enterprise features, government-grade security, and high availability.  Along with the basic upgrades, there will also be stronger augmentations to security, manageability, and data integration. MarkLogic is betting that companies will be integrating more data into their systems from dispersed silos.  Data integration has its own series of security problems, but there are more solutions to protect data in transition than at rest, which is where the Cryptsoft KMIP enters:

“Data is frequently protected while in transit between consumers and businesses, MarkLogic notes, but the same isn’t always true when data is at rest within the business because of a variety of challenges associated with that task. That’s where Cryptsoft’s technology could make a difference.  Rather than grappling with multiple key management tools, MarkLogic 9 users will be able to tap Cryptsoft’s embedded Key Management SDKs to manage data security from across the enterprise using a comprehensive, standards-compliant KMIP toolkit.”

Protecting data at rest is just as important as securing transitioning data.  This reminds me of Oracle’s secure enterprise search angle that came out a few years ago.  Is it a coincidence?

 

Whitney Grace, August 2, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph

 

Next Page »

  • Archives

  • Recent Posts

  • Meta