This blog is for the open exchange of ideas relating to IBM Systems, storage and storage networking hardware, software and services.
(Short URL for this blog: ibm.co/Pearson )
Tony Pearson is a Master Inventor, Senior IT Architect and Event Content Manager for [IBM Systems for IBM Systems Technical University] events. With over 30 years with IBM Systems, Tony is frequent traveler, speaking to clients at events throughout the world.
Lloyd Dean is an IBM Senior Certified Executive IT Architect in Infrastructure Architecture. Lloyd has held numerous senior technical roles at IBM during his 19 plus years at IBM. Lloyd most recently has been leading efforts across the Communication/CSI Market as a senior Storage Solution Architect/CTS covering the Kansas City territory. In prior years Lloyd supported the industry accounts as a Storage Solution architect and prior to that as a Storage Software Solutions specialist during his time in the ATS organization.
Lloyd currently supports North America storage sales teams in his Storage Software Solution Architecture SME role in the Washington Systems Center team. His current focus is with IBM Cloud Private and he will be delivering and supporting sessions at Think2019, and Storage Technical University on the Value of IBM storage in this high value IBM solution a part of the IBM Cloud strategy. Lloyd maintains a Subject Matter Expert status across the IBM Spectrum Storage Software solutions. You can follow Lloyd on Twitter @ldean0558 and LinkedIn Lloyd Dean.
Tony Pearson's books are available on Lulu.com! Order your copies today!
Safe Harbor Statement: The information on IBM products is intended to outline IBM's general product direction and it should not be relied on in making a purchasing decision. The information on the new products is for informational purposes only and may not be incorporated into any contract. The information on IBM products is not a commitment, promise, or legal obligation to deliver any material, code, or functionality. The development, release, and timing of any features or functionality described for IBM products remains at IBM's sole discretion.
Tony Pearson is a an active participant in local, regional, and industry-specific interests, and does not receive any special payments to mention them on this blog.
Tony Pearson receives part of the revenue proceeds from sales of books he has authored listed in the side panel.
Tony Pearson is not a medical doctor, and this blog does not reference any IBM product or service that is intended for use in the diagnosis, treatment, cure, prevention or monitoring of a disease or medical condition, unless otherwise specified on individual posts.
The developerWorks Connections platform will be sunset on December 31, 2019. On January 1, 2020, this blog will no longer be available. More details available on our FAQ.
Well, it's Tuesday again, and you know what that means? IBM Announcements! There were lots of announcements today, so I have split this up into two posts. One for the Tape and Cloud announcements, and the other for the Spectrum Storage family.
IBM TS7700 Virtual Tape System
IBM TS7700 release 4.1.1 now supports seven- and eight-way grids with approved RPQs. Before this, grids could only have up to six TS7700 systems connected together.
IBM also plans to extend the capacity of the TS7760 base frame to over 600 TB, and to extend the capacity of a fully configured TS7760 system to over 2.45 PB, before compression, by supporting 8 TB disk drives. This is a huge increase over the 4TB and 6TB drives used today.
IBM offers the IBM Cloud Object Storage System in three ways: as software, as pre-built systems, and as a cloud server on IBM Bluemix (formerly known as SoftLayer).
For those not familiar with IBM Cloud Object Storage (IBM COS), consider it "Valet Parking" for your storage. In a valet parking environment, you have valet parking attendants that drive the cars, parking garages that hold the cars, and a manager that oversees the operation. With IBM COS, you have Accesser® nodes that receive and retrieve your data like valet parking attendants, you have Slicestor® nodes that store your objects like cars in a parking garage, and you have IBM COS Manager to oversee the operation.
Today, IBM announced new HDD options for their S01, S03 and S03 models of Slicestor nodes. These are all 7200 rpm, 3.5-inch Nearline drives, at capacities of 4 TB, 6 TB, 8 TB and 10 TB.
In addition, a short-range 40 GbE SFP+ transceiver is available for ordering on IBM Cloud Object Storage Accesser models A00, A01, and A02, and IBM Cloud Object Storage Slicestor models S01 and S02. This improves the performance of data transfer between the Accesser nodes and the Slicestor nodes. Think of it like shortening the distance valet parking attendants have to drive your car to the garage and run back.
I have been presenting Cloud Storage for nearly 10 years now. People are often shocked to learn that most of the major cloud providers -- including Amazon, Google, Microsoft -- do not offer "Data at Rest" encryption on their storage offerings.
Why not? Because it would mean investing in Self-Encrypting Drives, Key management software, and other related technology to make it happen. Instead, Cloud Service Providers (CSPs) expect you to encrypt the data in software. Most users encrypt data before it lands on the cloud, but what if you create the data in the cloud?
IBM solved this by offering IBM Cloud Object Storage in its IBM Cloud (formerly known as SoftLayer). It has integrated encryption software that takes care of this for you.
This new product, IBM Multi-Cloud Data Encryption V1.0, enables you to encrypt files, folders, and volumes in any cloud while maintaining local control of encryption keys. It integrates with IBM Security Key Lifecycle Manager (SKLM). This is designed to allow you to move cipher data between clouds that are running Multi-Cloud Data Encryption without decrypting and re-encrypting the data.
For example, you can use IBM Multi-Cloud Data Encryption to protect your data on Amazon, Google or Microsoft, then later realize that you can save a ton of money moving to IBM Cloud instead, and you are now able to move the data over seamlessly!
(Back in 2010, I poked fun at EMC with my post [VPLEX: EMC's Latest Wheel is Round]. I pointed out that EMC's announcement of "new features" that already existed in IBM's SAN Volume Controller. Oops! They did it again!)
Basically, Dell EMC is working on a new "2 Tiers" approach that combines high-performance flash tier with high-capacity object storage. Guess what? IBM already offers this! Why wait?
IBM Spectrum Scale, formerly known as the General Parallel File System (GPFS), supports POSIX, HDFS, OpenStack Swift, Amazon S3, NFS, SMB and iSCSI protocols.
Spectrum Scale can provide this front-end abstraction layer between flash and object storage, including IBM Cloud Object Storage system and IBM Bluemix (formerly SoftLayer) cloud services.
But why limit yourself to just two tiers? IBM Spectrum Scale can also support 15K, 10K and 7200 RPM spinning disk drive tiers, as well as virtual or physical tape tier, the ultimate low-cost high-capacity tier!
Several years ago, IBM coined the phrase "FLAPE" to discuss the two-tier approach of combining Flash with Tape using Spectrum Scale as the front-end abstraction layer.
Perhaps we should call combinations of Flash and Object "FLobject" storage? If the name catches on, you read it here first!
IBM is in a transition from being a "Systems, Software and Services" company, to become the leading "Cognitive Solutions and Cloud Platform" company. IBM has been in this transformation for the past three years or so, and [over 40 percent of its revenue] now comes from these strategic initiatives.
The purpose of AI and cognitive systems developed and applied by the IBM company is to augment human intelligence. Our technology, products, services and policies will be designed to enhance and extend human capability, expertise and potential. Our position is based not only on principle but also on science.
Cognitive systems will not realistically attain consciousness or independent agency. Rather, they will increasingly be embedded in the processes, systems, products and services by which business and society function -- all of which will and should remain within human control.
For cognitive systems to fulfill their world-changing potential, it is vital that people have confidence in their recommendations, judgments and uses. Therefore, the IBM company will make clear:
When and for what purposes AI is being applied in the cognitive solutions we develop and deploy.
The major sources of data and expertise that inform the insights of cognitive solutions, as well as the methods used to train those systems and solutions.
The principle that clients own their own business models and intellectual property and that they can use AI and cognitive systems to enhance the advantages they have built, often through years of experience. We will work with our clients to protect their data and insights, and will encourage our clients, partners and industry colleagues to adopt similar practices.
The economic and societal benefits of this new era will not be realized if the human side of the equation is not supported. This is uniquely important with cognitive technology, which augments human intelligence and expertise and works collaboratively with humans.
Therefore, the IBM company will work to help students, workers and citizens acquire the skills and knowledge to engage safely, securely and effectively in a relationship with cognitive systems, and to perform the new kinds of work and jobs that will emerge in a cognitive economy.
This week, I was reminded that back in 2011, Watson beat two human players, Ken Jennings and Brad Rutter on the TV game show "Jeopardy!" On his last response, Ken wrote "I for one welcome our new computer overlords." With IBM investing heavily in Cognitive Solutions, should people be worried, or welcome the new technology?
Back in 1950, Isaac Asimov proposed "Three laws of robots":
A robot may not injure a human being or, through inaction, allow a human being to come to harm.
A robot must obey orders given it by human beings except where such orders would conflict with the First Law.
A robot must protect its own existence as long as such protection does not conflict with the First or Second Law.
Let's take a look at how Artificial Intelligence has been represented in the movies over the past few decades. I have put these in chronological order when they were initially released in the United States.
(FCC Disclosure and Spoiler Alert: I work for IBM. This blog post can be considered a "paid celebrity endorsement" for cognitive solutions made by IBM. While IBM may have been involved or featured in some of these movies, I have no financial interest in them. I have seen them all and highly recommend them. I am hoping that you have all seen these, or at least familiar enough with their plot lines that I am not spoiling them for you.)
2001: A Space Odyssey
Back in 1968, Stanley Kubrick and Arthur C. Clarke made a masterpiece movie about a mysterious obelisk floating near Jupiter. To investigate, a crew of human beings takes a space ship managed by a sentient computer named [HAL-9000].
(Many people thought HAL was a subtle reference to IBM. Stanley Kubrick clarifies:
"By the way, just to show you how interpretation can sometimes be bewildering: A cryptographer went to see the film, and he said, 'Oh. I get it. Each letter of HAL's name is one letter ahead of IBM. The H is one letter in front of I, the A is one letter in front of B, and the L is one letter in front of M.'
Now this is a pure coincidence, because HAL's name is an acronym of heuristic and algorithmic, the two methods of computer programming...an almost inconceivable coincidence. It would have taken a cryptographer to have noticed that."
Source: The Making of 2001: A Space Odyssey, Eye Magazine Interview, Modern Library, pp. 249)
The problem arises when HAL-9000 refuses commands from the astronauts. The astronauts are not in control, HAL-9000 was given separate orders from ground control back on earth, and it has determined it would be more successful without the crew.
In 1973, Michael Crichton wrote and directed this movie about an amusement park with three uniquely themed areas: Medieval World, Roman World, and Westworld. Robots are used to staff the parks to make them more realistic, interacting with the guests in character appropriate for each time period.
A malfunction spreads like a computer virus among the robots, causing them to harm or kill the park's guests. Yul Brenner played a robot called simply "the Gunslinger". Equipped with fast reflexes and infrared vision, the Gunslinger proves especially deadly!
(Michael Crichton also wrote "Jurassic Park", which had a similar story line involving dinosaurs with catastrophic results!)
Last year, HBO launched a TV series called "Westworld", based on the same themes covered in this movie. The first season of 10 episodes just finished, and the next season is scheduled for 2018.
Directed by Ridley Scott, this 1982 movie stars Harrison Ford as Rick Deckard, a law enforcement officer. Rick is tasked to hunt down and "retire" four cognitive androids named "replicants" that have killed some humans and are now in search of their creator, a man named J. F. Sebastian.
(I enjoy the euphemisms used in these movies. Terms like kill, murder or assassinate apply to humans but not machines. The word "retire" in this movie refers to destruction of the robots. As we say in IBM, "retirement is not something you do, it is something done to you!")
Destroying machines does not carry the same emotional toll as killing humans, but this movie explores that empathy. A sequel called "Blade Runner 2049" will be released later this year.
In 1983, Matthew Broderick plays David, a young high school student who hacks into the U.S. Military's War Operation Plan Response (WOPR) computer. The WOPR was designed to run various strategic games, including war game simulations, learning as it goes. David decides to initiate the game "Global Thermonuclear War", and the military responds as if the threats were real.
Can the computer learn that the only way to win a war is not to wage it in the first place? And if a computer can learn this, can our human leaders learn this too?
In this series of movies, a franchise spanning from 1984 to 2009, the US Military builds a defense grid computer called [Skynet]. After cognitive learning at an alarming rate, Skynet becomes self-aware, and decides to launch missiles, starting a nuclear war that kills over 3 billion people.
Arnold Schwarzenegger plays the Terminator model T-800, a cognitive solution in human form designed by Skynet to finish the job and kill the remainder of humanity.
In this 2004 movie, Will Smith plays Del Spooner, a technophobic cop who investigates a crime committed by a cognitive robot.
(Many people associate the title with author Isaac Asimov. A short story called "I, Robot" written by Earl and Otto Binder was published in the January 1939 issue of 'Amazing Stories', well before the unrelated and more well-known book 'I, Robot' (1950), a collection of short stories, by Asimov.
Asimov admitted to being heavily influenced by the Binder short story. The title of Asimov's collection was changed to "I, Robot" by the publisher, against Asimov's wishes. Source: IMDB)
Del Spooner uncovers a bigger threat to humanity, not just a single malfunctioning robot, but rather the Virtual Interactive Kinesthetic Interface, or simply VIKI for short, a cognitive solution that controls all robots. VIKI interprets Asimov's three laws in a manner not originally intended.
In this 2015 movie, Domhnall Gleeson plays Caleb, a 26 year old programmer at the world's largest internet company. Caleb wins a competition to spend a week at a private mountain retreat. However, when Caleb arrives he discovers that he must interact with Ava, the world's first true artificial intelligence, a beautiful robot played by Alicia Vikander.
(The title derives from the Latin phrase "Deus Ex-Machina," meaning "a god from the Machine," a phrase that originated in Greek tragedies. Sources: IMDB)
Nathan, the reclusive CEO of this company, relishes this opportunity to have Caleb participate in this experiment, explaining how Artificial Intelligence (AI) will transform the world.
(The three main characters all have appropriate biblical names. Ava is a form of Eve, the first woman; Nathan was a prophet in the court of David; and Caleb was a spy sent by Moses to evaluate the Promised Land. Source: IMDB)
The premise is based in part on the famous [Turing Test], developed by Alan Turing. This is designed to test a machine's ability to exhibit intelligent behavior equivalent to, or indistinguishable from, that of a human.
Movies that depict the bad guys as a particular nationality, ethnicity or religion may be offensive to some movie audiences. Instead, having dinosaurs, monsters, aliens or robots provides a villain that all people can fear equally. This helps movie makers reach a more global audience!
Of course, if robots, androids and other forms of Artificial Intelligence did exactly what humans expect them to, we would not have the tense, thrilling action movies to watch on the big screen.
This is not a complete list of movies. Enter in the comments below your favorite movie that features Artificial Intelligence and why it is your favorite!
(As IBM is focused on its transformation from a "Systems, Software and Services" company to a "Cognitive Solutions and Cloud Platform" company, it seems appropriate to highlight my 1,000 blog post on the concept of cognitive solutions.)
A lot of people ask me to explain what exactly does IBM mean by "cognitive", which is a fair question. Let's start with the [Dictionary definition]:
of or relating to cognition; concerned with the act or process of knowing, perceiving, etc.
of or relating to the mental processes of perception, memory, judgment, and reasoning, as contrasted with emotional and volitional processes.
What exactly does IBM mean by Cognitive? IBM has taken this definition, and focused on four key strategic areas:
In the summer of 1981, I spent a summer debugging a "Pascal" compiler at the University of Texas at Austin. I wasn't told that was what I was doing. Rather, I was tasked with writing sample Pascal programs that would demonstrate the features and capabilities of the language.
Every day, I would come up with a concept of a program, punch up the cards, run it through the CDC hopper, and verify that it would work properly. If I didn't have it working by lunch, I would take it to the "help desk", they would look it over, and tell me how to fix it after I got back.
Most of the time, it was a mistake in my software. A few times, however, it was a flaw in the compiler itself. My programs were basically test cases, and the Pascal Compiler development team was fixing or enhancing the compiler code every time I had a problem.
Compilers basically work by parsing the program text, looking for fixed keywords that are entered in a specifically prescribed order to make sense. Other keywords may represent data types, variables, constants or pre-defined macros.
But compilers are not cognitive. Cognitive solutions can understand natural language, and have to handle all the ambiguity of words not being in the correct order, or different words having different meanings.
As an Electrical Engineer, I had to take many classes on classical analog signal processing. In fact, all computers have some amount of analog components, where threshold processing is used to differentiate a zero (0) from a one (1).
For example, if a "zero" value was represented by 1 volt, and a "one" value by 5 volts, then you can set a threshold at 3 volts. Any voltage less than 3 would be considered a "zero" value, and anything 3 volts or greater a "one" value.
But threshold processing is not cognitive. Cognitive solutions also use thresholds, but their thresholds are dynamically determined, through advanced analytics and statistical mathematical models, and may adjust up and down as needed, based on machine learning over time.
IBM Research is proud to have developed the world's most advanced caching algorithms for its storage systems. Cache memory is very fast, but also very expensive, so offered in limited quantities. Caching algorithms decide which blocks of data should remain in cache, and which should be kicked out.
Ideally, a block in read cache would be kicked out precisely after the last time it was read, with little or no expectation for being read again anytime soon. Likewise, a block in write cache would be destaged to persistent storage precisely after the last time it was updated, with little or no expectation for being updated again anytime soon.
Traditional approach is "Least Recently Used" or [LRU]. Cache entries that were read recently or updated recently, would be placed on the top of the list, and the least referenced would be at the bottom of the list. When space is needed in cache, the entries at the bottom of the list would be kicked out.
IBM's [Adaptive Cache Algorithm outperforms LRU]. For example, on a workstation disk drive workload, at 16MB cache, LRU delivers a hit ratio of 4.24 percent while ARC achieves a hit ratio of 23.82 percent, and, for a SPC1 benchmark, at 4GB cache, LRU delivers a hit ratio of 9.19 percent while ARC achieves a hit ratio of 20 percent.
But caching algorithms, including IBM's Adaptive Cache, are not cognitive. These algorithms respond pragmatically based on the current state of the cache. Cognitive solutions learn, and improve with usage. This is often referred to as "Machine Learning".
The human-computer interface (HCI) has much room for improvement in a variety of areas.
Take for example a snack vending machine. In college, we had assignments to simulate the computing logic of these. We had to interact with the buyer, receive coins entered into the slot--nickels, dimes and quarters representing 5, 10 and 25 cents--determine a total monetary balance, and then dispense snacks of various prices and return an appropriate amount of change, if any. There is even a [greedy algorithm] designed to optimize how the change is returned.
But vending machines are not cognitive. Like the caching algorithms, vending machines interact based on fixed programmatic logic, treating all buyers in the same manner. Cognitive solutions can interact with different users in different ways, customized to their needs, and these interactions can improve over time, based on machine learning.
IBM is exploring the use of Cognitive Solutions in a variety of different industries, from Healthcare to Retail, Financial Services to Manufacturing, and more.