25 Years of IBM Patent Leadership

IBM inventors received a record-breaking 9,043 U.S. patents during 2017—the 25th consecutive year that IBM has topped the annual list of patent recipients. IBM‘s patents in 2017 included more than 1,900 cloud patents, 1,400 in artificial intelligence (AI) and over 1,200 in the area of cybersecurity. IBM also received patents in the areas of blockchain and quantum computing. IBM‘s India inventors contributed over 800 patents to this record tally, making us the second highest contributor after the US region

It is a winning streak that began just after the advent of the PC and when the world wide web debut to the public. In the history of the technology there is virtually no one that has lead technology in any area for 25 years. IBM has gone from 20,000 patents in 1992 to producing more that a 1,00,000 patents in 25 years period so thought of sharing some insight into it.

The more than 105,000 inventions from IBM during its 100-plus-year history—from FORTRAN to relational databases to the Universal Product Code—are transforming the world. Also you can see smart glasses for the visually-impaired; a technology for securing credit card transactions; a carbon nanotube that’s 50,000 times thinner than human hair; and systems for predicting car traffic before it starts and earthquakes before they strike – Breakthrough after breakthrough.

Sample Patents:
Here are some of the interesting Patents from IBM in 2017:

  • Cloud resources : A system that uses unstructured data about world or local events to forecast cloud resource needs.
  • Self-driving vehicles: A machine-learning system that can shift control between a human driver and autonomous vehicle when there’s an emergency.
  • Blockchain: A method that uses blockchain technology to reduce the number of steps involved in settling transactions between multiple business parties.
  • AI speech: A system that can help artificial intelligence analyze and mirror a user’s speech patters to improve communication between AI and humans.
  • Cybersecurity: Technology that enables AI systems to turn the table on hackers by baiting them into email exchanges and websites that expend their resources and frustrate their attacks.

What takes to innovate?
We tend to think of innovation as a single event—a flash of genius followed by a revolutionary product or service. But the truth is that the road to any significant discovery is a long and twisted path. The inventors take some of the already established ideas and come up with something novel. Do watch the following video that shows the process and importance of Patenting.

Advertisements

Whats new in IBM InfoSphere Information Server 11.7 – Part 3

In my last blog, we discussed about Information Governance Catalog (IGC). In this blog I wish to touch upon some new features of Information Governance that were introduced along with the new look and feel with  IBM InfoSphere Information Server version 11.7.

Enterprise Search

Social Collaboration
InfoSphere Information Server also brought social collaboration to the domain of Information Governance. When you browse your data, sometimes you would want to know what other experts think about critical assets such as reports, source files, and more.. Now it is possible, as you can rate an asset on a scale of one to five stars, and you can leave a comment with a couple of words. This enables all members of your organization to collaborate and share their expertise right where it’s needed. Also remember that the more popular the asset is, the higher is its position on the search results list.

Searching for assets
With 11.7, Searching for assets has become very easy. You don’t need to know anything about the data in your enterprise to explore it. Let’s assume that you want to find information about bank accounts, simply type ‘bank account’ in the search field in enterprise search, and that’s it. The search engine looks for the information in all asset types. It takes into account factors like text match, related assets, ratings and comments, modification date, quality score, and usage. And if  you already familiar with your organization and looking for something more specific, then you just open the catalog with your data, and select asset types that you want to browse. To narrow down search results, apply advanced filters like creation and modification dates, stewards, labels, or custom attributes.

Unstructured data sources
The data in your enterprise consists of databases, tables, columns, and other sources of structured data. What about email messages, word-processing documents, audio or video files, collaboration software, or instant messages? They are also a very valuable source of information. To support a unified approach to enterprise information management, IBM StoredIQ can now be set up to synchronize data with IBM Information Governance Catalog. So now you can classify such information in IGC too.

Exploring Relationships
Data in large organizations can be very complex, and assets can be related to one another in multiple ways. To understand these complex relations better, explore them in a graphical form by using graph explorer. This view by default displays all relationships of one asset that you select. But this is just the starting point, as you can further expand relationships of this asset’s relationships in the same view. Having all this information in one place in a graphical format makes it a lot easier to dig into the structure of your data. Each relationship has direction and name. You’ll be surprised when you discover how assets are connected!

To have a look at the new Information Governance Catalog, view this video.

 

Whats new in IBM InfoSphere Information Server 11.7 – Part 2

DataStage Flow Designer

As promised in the last blog, here are a few more changes that came with InfoSphere Information Server 11.7. DataStage Flow Designer is the new web based user interface for IBM’s flagship data integration component IBM DataStage. It can be used to create, edit, load, and run DataStage jobs. But unlike the current DataStage Designer, it does not require any installation on a Microsoft Windows client environment and therefore is immediately available and easily accessible once DataStage is being installed. Moreover, you do not need to migrate jobs to a new location in order to use the new web-based IBM DataStage Flow Designer user interface. Any existing DataStage jobs can be rendered in IBM DataStage Flow Designer, avoiding complex, error-prone migrations that could lead to costly outages.

DataStage Flow Designer
DataStage Flow Designer

Here are few of it’s features.

  • Search and Quick Tours: Quickly find any job using the built-in search feature.  For example, you can search for job name, description or timestamp to find what you are looking for very quickly. Also you can familiarize yourself with the product by taking the built in quick tour. You can also watch the “Create your first job” video on the welcome page.
  • Automatic metadata propagation: Making changes to a stage in a DataStage job can be time consuming because you have to go to each subsequent stage and redo the change. DataStage Flow Designer automatically propagates the metadata to subsequent stages in that flow, increasing productivity.
  • Highlighting of all compilation errors: Today, the DataStage thick client identifies compilation errors one at a time. Big jobs with upwards of 30 or 50 stages have a difficult time on compile, because errors are highlighted one stage at a time. DataStage Flow Designer highlights all errors and gives you a way to see the problem with a quick hover over each stage, so you can fix multiple problems at once before re-compiling.

In summary, the new browser-based DataStage® Flow Designer is geared for data engineers, but is versatile and accessible to all business users. This cognitive designer features an intuitive, modern, and security-rich browser-based interface. Users can access the DataStage Flow Designer and quickly address their data transformation or preparation needs, without having to rely on a Windows™ desktop environment. Do watch the following video on IBM DataStage Flow Designer.

To know more, please visit the IBM Knowledge Center.
There is a lot more in IBM InfoSphere Information Server 11.7. So stay tuned.

Whats new in IBM InfoSphere Information Server 11.7 – Part 1

IBM® InfoSphere® Information Server V11.7 was released last week. And in next couple of blogs, I wish to share how 11.7 is a major milestone for Governance functionality. First let’s look at the changes from a very high level before going closer.

At a Glance
IBM® InfoSphere® Information Server V11.7 accelerates the delivery of trusted and meaningful information to your business with enhanced automation and new design and usage experiences:

Enterprise Search
Enterprise Search
  • New Enterprise smart search to discover and view enterprise information
  • Automated data discovery and classification powered by machine learning
  • Policy-and-business-classification-driven data quality evaluation
  • New browser-based cognitive design experience for data engineers
  • New and expanded Hadoop data lake and cloud capabilities and connectivity
  • Single and holistic catalog view of information across the information landscape, enabling users to derive insight through a knowledge graph

Unified Governance

Now let’s get into some details. InfoSphere® Information Server V11.7 introduces the unified governance platform, a fabric that supports Data Governance Objectives throughout analytics lifecycle. Unified Governance focuses on the following themes and capabilities to construct a data foundation for the enterprise.

  • Auto Discovery and Classification: For data in traditional repositories or in the modern Hadoop data lakes the ability to catalog data accurately and quickly with minimal user intervention is a key requirement all modern enterprises have. Auto Discovery provides the user with the ability to point to a data source and ingest metadata from that data source and Auto Classification is an optional feature used after discovery which conducts data profiling and quality analysis.
  • Auto Quality Management : Data Quality is a key component of Data Governance. Automation rules provide a way to associate evaluation of data quality with business classification of data and also provide a way to automate data quality evaluation. It will help lower the cost of quality evaluation significantly.
  • Enterprise Search – An enterprise wants to leverage data. A lot of data does not get used simply because there is no good way to find it. The Knowledge Graph is a self-service user experience which provides information with insight to the business user. This allows a CDO to improve the use of data in business decisions with a high level of confidence that it is governed data. Starting with a simple keyword search, a user can leverage context of the data and use social collaboration to narrow down data to be used for analytics or business decision making.
  • Customizable User Experience : This release introduces the ability for an enterprise to customize their users experience based on roles and allows a user to customize their experience suited to their personal preference.
  • Metadata Integration from StoredIQ into IGC enabling organizations to govern all their information assets (structured and unstructured) in a centralized repository. This is critical to support customers needs for GDPR.

Watch the following 2 minute video on Unified Governance:

This release introduces key technological innovations as well open source technology. Also there has been a tremendous change in the DataStage Designer. I will share that in the upcoming blog. So stay tuned.

Information Governance – Revisited

IIGIt has been more than 5 years that I wrote on Information governance. Over the period of last 5 years some areas of Information Governance became more matured and I thought of re-visiting this topic. In a simple analogy, what library do for books, Data governance does for data. It organizes data, makes it simple to access the data, gives means to check for validity/ accuracy of data and makes it understandable to all who need it.  If Information Governance in place, organizations can use data for generating insights and also they are equipped for  regulatory mandates (like GDPR).

There are six sets of capabilities that make up the Information Management & Governance component:

  1. Data Lifecycle Management is a discipline that applies not only to analytical data but also to operational, master and reference data within the enterprise.  It involves defining and implementing policies on the creation, storage, transmission, usage and eventual disposal of data, in order to ensure that it is handled in such a way as to comply with business requirements and regulatory mandates.

2. MDM: Master and Entity Data acts as the ‘single source of the truth’ for entities – customers, suppliers, employees, contracts etc.  Such data is typically stored outside the analytics environment in a Master Data Management (MDM) system, and the analytics environment then accesses the MDM system when performing tasks such as data integration.

3. Reference Data is similar in concept to Master and Entity Data, but pertains to common data elements such as location codes, currency exchange rates etc., which are used by multiple groups or lines of business within the enterprise.  Like Master and Entity Data, Reference data is typically leveraged by operational as well as analytical systems.  It is therefore typically stored outside the analytics environment and accessed when required for data integration or analysis.

4. Data Catalog is a repository that contains metadata relating to the data stored in the Analytical Data Lake Storage repositories.  The catalog maintains the location, meaning and lineage of data elements, the relationships between them and the policies and rules relating to their security and management .  The catalog is critical for enabling effective information governance, and to support self-service access to data for exploration and analysis.

5. Data Models provide a consistent representation of data elements and their relationships across the enterprise.  An effective Enterprise Data Model facilitates consistent representation of entities and relationships, simplifying management of and access to data.

6. Data Quality Rules describe the quality requirements for each data set within the Analytical Data Lake Storage component, and provides measures of data quality that can be used by potential consumers of data to determine whether a data set is suitable for a particular purpose.  For example, data sets obtained from social media sources are often sparse and therefore ‘low quality’ but that does not necessarily disqualify a data set from being used.  Provided a user of the data knows about its quality, they can use that knowledge to determine what kinds of algorithms can best be applied to that data.

 

A World with Watson

An year back I wrote my first blog about Watson. I have been closely following what’s happening with Watson. Here are some facts on Watson and what user’s of Watson are speaking about it.

 

Quick Facts About Watson:

  • By the end of this year, Watson will touch one billion people in some way
  • Watson can “see,” able to describe the contents of an image. For example, Watson can identify melanoma from skin lesion images with 95 percent accuracy, according to research with Memorial Sloan Kettering.
  • Watson can “hear,” understanding speech including Japanese, Mandarin, Spanish, Portuguese, among others.
  • Watson can “read” 9 languages.
  • Watson can “feel” impulses from sensors in elevators, buildings, autos and even ball bearings.
  • Watson has been trained on 8 types of cancers, with plans to add 6 more this year.
  • Beyond oncology, Watson is in use by nearly half of the top 25 life sciences companies, major manufacturers for IoT applications, retail and financial services firms, and partners like GM, H&R Block and SalesForce.com.
  • At IBM, there are more than 1,000 researchers focused solely on artificial intelligence

But perhaps more important than what Watson can do, it is what people, businesses and institutions of all sizes are doing with Watson. See what some IBM Watson users are saying.
Watson
What IBM and Watson has been at the leading edge of is providing enterprise grade, commercially ready cognitive services, fully integrated with a top notch cloud and many other services from analytics to support and sales & marketing.”  — André M. König, Co-Founder @ Opentopic Inc. This quote was included in Mr. König’s article “Watson is a Joke?” featured on LinkedIn.

All of us involved in training Watson… are absolutely convinced that this technology will become an indispensable part of a doctor’s armamentarium to care for patients.” — Mark G. Kris, MD, lead physician of the Memorial Sloan-Kettering-IBM Watson collaboration. Dr. Kris’s quote was featured in a June 25, 2017 article in the American Society of Clinical Oncology entitled “How Watson for Oncology is Advancing Personalized Patient Care.”

But, the probably more exciting part about it is in 30 percent of patients Watson found something new. And so that’s 300-plus people where Watson identified a treatment that a well-meaning, hard-working group of physicians hadn’t found.” Dr. Norman “Ned” Sharpless, director of the Lineberger Comprehensive Cancer Center at the University of North Carolina at Chapel Hill and recent presidential appointee as director of the National Cancer Institute.
Dr. Sharpless’ made these comments in a “60 Minutes” segment that aired on October 2016 and again on June 25, 2017. The segment can be viewed here.

30 minutes is down to 8 minutes to screen a patient…That coordinator can now spend that valuable time gained … in educating the patient on why it’s important for her to be in that clinical trial, helping to break down other barriers.”  Dr. Tufia Haddad, MD, Breast Medical Oncologist, Mayo Clinic, made these comments during an AI in Healthcare panel during HIMSS 2017, reported here.

We could have individually looked at the 1,500 proteins and genes but it would have taken us much longer to do so.  IBM Watson for Drug Discovery, with its robust knowledge base, was able to rapidly give us new and novel information we would not otherwise have had.” – Robert Bowser, PhD, director of the Gregory W. Fulton ALS Research Center at Barrow Neurological Institute and one of the nation’s leading ALS researchers. Quote is from a press release announcing the recent Society for Neuroscience study findings.

[With Watson], we’re seeing some really tremendous efficiencies gained in the drilling business – [including] an 80 percent reduction in the geoscience research time we need to actually design our wells. That means geoscience searchers are doing geoscience not looking out for more data.” -Peter Coleman, CEO and Managing Director for Woodside [source:  Investor Briefing, March 7, 2017]

[Watson services] was a wake-up call for us – that cognitive solutions are real and powerful. We felt that IBM had, by far, the largest lead in terms of where cognitive was going and that the Watson team would be in the best position to help our business users.” -Ryan Bartley, Head of Applied Innovation at Staples [source: IBM Watson blog, February 10, 2017]

It’s not man versus machine—they very much work hand and hand. Our analysts continue to play a critical role in evaluating a cyber security incident, while Watson for Cyber Security enforces their decisions and validates what they are sharing with the customer at risk. It enables security analysts to deliver faster and more accurate details on a breach, so we may better protect our customers.” – Ronan Murphy, CEO, Smarttech (source: Press Release, May 11, 2017)