Siemens’s MindSphere: from automation to digitalization

Perhaps the most important component of a successful IoT transformation is building it on a robust platform, because that alone can let your company go beyond random IoT experiments to achieve an integrated IoT strategy that can add new components systematically and create synergistic benefits by combining the various aspects of the program.

A good starting point for discussion of such platforms is a description of the eight key platform components as detailed by IoT Analytics:

  1. “Connectivity & normalization: brings different protocols and different data formats into one ‘software’  interface ensuring accurate data streaming and interaction with all devices.
  2. Device management: ensures the connected ‘things’ are working properly, seamlessly running patches and updates for software and applications running on the device or edge gateways.
  3. Database: scalable storage of device data brings the requirements for hybrid cloud-based databases to a new level in terms of data volume, variety, velocity and veracity.
  4. Processing & action management: brings data to life with rule-based event-action-triggers enabling execution of ‘smart’ actions based on specific sensor data.
  5. Analytics: performs a range of complex analysis from basic data clustering and deep machine learning to predictive analytics extracting the most value out of the IoT data-stream.
  6. Visualization: enables humans to see patterns and observe trends from visualization dashboards where data is vividly portrayed through line-, stacked-, or pie charts, 2D- or even 3D-models.
  7. Additional tools: allow IoT developers prototype, test and market the IoT use case creating platform ecosystem apps for visualizing, managing and controlling connected devices.
  8. External interfaces: integrate with 3rd-party systems and the rest of the wider IT-ecosystem via built-in application programming interfaces (API), software development kits (SDK), and gateways.”

Despite (or because of, the complexity,) I think this is a decent description, because a robust IoT platf0rm really must encompass so many functions. The eight points give a basis for deciding whether what a company hawks as an IoT platform really deserves that title or really constitutes only part of the necessary whole (Aside: it’s also a great illustration of my Essential Truth that, instead of hoarding data as in the past, we must begin to ask “who else can use this data?” either inside the company or, potentially, outside, then use technology such as an IoT platform to integrate all those data uses productively.).

During my recent Barcelona trip (disclaimer: Siemens paid my way and arranged special access to some of its key decision makers, but made no attempt to limit my editorial judgment) I interviewed the company’s Chief Strategy Officer, Dr. Horst J. Kayser, who made it clear (as I mentioned in my earlier post about Siemens) that one of the advantages the company has over pure-play software firms is that it can apply its software offerings internally first and tweak them there, because of its 169-year heritage as a manufacturer, and “sits on a vast program of automation.”

Siemens’s IoT platform, MindSphere  is a collaboration with SAP, using the latter’s vast HANA cloud.  It ties together all components of Siemens’s IoT offerings, including data analytics, connectivity capabilities, developers’ tools, applications and services. MindSphere focuses on monitoring manufacturing assets’ real-time status, to evaluate and use customers’ data, producing insights that can cut production costs, improve performance, and even switch to predictive maintenance. Its Mind Connect Nano collects data from the assets and transferring it to MindSphere.

The “digital twin” is integrated throughout the MindSphere platform. Kayser says that “there’s a digital twin of the entire process, from conception through the manufacturing and maintenance, and it feeds the data back into the model.” In fact,  one dramatic example of the concept in action is the new Maserati Ghibli, created in 16 months instead of 30 — almost 50% less time than for prior models.  Using the Teamcenter PLM software, the team was able to virtually develop and extensively test the car before anything was created physically.

IMHO, Mindsphere and components such as Teamware might really be the key to actualizing my dream of the circular company, in this case with the IoT-based real-time digital twin at the heart of the enterprise — as Kayser said, “everything is done through one consistent data set.)” I hope to explore my concept, and the benefits I think it can produce, more with the Siemens strategists in the future!  I tried the idea out on several of them in Barcelona, and no one laughed, so we’ll see…

As with the company’s rail digitization services that I mentioned in my earlier post, there’s an in-house guinea pig for MindSphere as well: the company’s “Factory of the Future” in Amberg. The plant manufactures Simatic controllers, the key to the company’s automation products and services, to which digitalization is now being added as part of the company’s Industrie 4.0 IoT plan for manufacturing (paralleling GE’s “Industrial Internet.”). As you may be aware, Siemens’s efforts in this area are a subset of a formal German government/industry initiative — I  doubt seriously we’ll see this in the U.S. under Trump.

The results of digitalization at Amberg are astonishing by any measure, especially the ultimate accomplishment: a  99.9988 percent rate (no typo!!), which is even more incredible when you realize this is not mass production with long, uniform production runs: the plant manufactures more than 1,000 varieties of the controllers, with a total volume of 12 million Simatic products each year, or about one per second.  Here are some of the other benefits of what they call an emphasis on optimizing the entire value chain:

  • shorter delivery time: 24 hours from order.
  • time to market reduced by up to 50%.
  • cost savings of up to 25%

Of course there are several other robust IoT platforms, including GE’s Predix and PTC’s Thingworx, but my analysis shows that Mindsphere meets IoT Analytics’ criteria, and, combined with the company’s long background in manufacturing and automation, should make it a real player in the industrial internet. Bravo!

When Philips’s Hue Bulbs Are Attacked, IoT Security Becomes Even Bigger Issue

OK, what will it take to make security (and privacy) job #1 for the IoT industry?

The recent Mirai DDoS attack should have been enough to get IoT device companies to increase their security and privacy efforts.

Now we hear that the Hue bulbs from Philips, a global electronics and IoT leader that DOES emphasize security and doesn’t cut corners, have been the focus of a potentially devastating attack (um, just wonderin’: how does triggering mass epileptic seizures through your light bulbs grab you?).

Since it’s abundantly clear that the US president-elect would rather cut regulations than add needed ones (just announcing that, for every new regulation, two must be cut), the burden of improving IoT security will lie squarely on the shoulders of the industry itself. BTW:kudos in parting to outgoing FTC Chair Edith Ramirez, who has made intelligent, workable IoT regulations in collaboration with self-help efforts by the industry a priority. Will we be up to the security challenge, or, as I’ve warned before, will security and privacy lapses totally undermine the IoT in its adolescence by losing the public and corporate confidence and trust that is so crucial in this particular industry?

Count me among the dubious.

Here’s what happened in this truly scary episode, which, for the first time, presages making the focus of an IoT hack an entire city, by exploiting what might otherwise be a smart city/smart grid virtue: a large installed base of smart bulbs, all within communication distance of each other. The weapons? An off-the-shelf drone and an USB stick (the same team found that a car will also do nicely as an attack vector). Fortunately, the perpetrators in this case were a group of white-hat hackers from the Weizmann Institute of Science in Israel and Dalhousie University in Canada, who reported it to Philips so they could implement additional protections, which the company did.

Here’s what they wrote about their plan of attack:

“In this paper we describe a new type of threat in which adjacent IoT devices will infect each other with a worm that will spread explosively over large areas in a kind of nuclear chain reaction (my emphasis), provided that the density of compatible IoT devices exceeds a certain critical mass. In particular, we developed and verified such an infection using the popular Philips Hue smart lamps as a platform.

“The worm spreads by jumping directly from one lamp to its neighbors, using only their built-in ZigBee wireless connectivity and their physical proximity. The attack can start by plugging in a single infected bulb anywhere in the city, and then catastrophically spread everywhere within minutes, enabling the attacker to turn all the city lights on or off, permanently brick them, or exploit them in a massive DDOS attack (my emphasis). To demonstrate the risks involved, we use results from percolation theory to estimate the critical mass of installed devices for a typical city such as Paris whose area is about 105 square kilometers: The chain reaction will fizzle if there are fewer than about 15,000 randomly located smart lights in the whole city, but will spread everywhere when the number exceeds this critical mass (which had almost certainly been surpassed already (my emphasis).

“To make such an attack possible, we had to find a way to remotely yank already installed lamps from their current networks, and to perform over-the-air firmware updates. We overcame the first problem by discovering and exploiting a major bug in the implementation of the Touchlink part of the ZigBee Light Link protocol, which is supposed to stop such attempts with a proximity test. To solve the second problem, we developed a new version of a side channel attack to extract the global AES-CCM key that Philips uses to encrypt and authenticate new firmware. We used only readily available equipment costing a few hundred dollars, and managed to find this key without seeing any actual updates. This demonstrates once again how difficult it is to get security right even for a large company that uses standard cryptographic techniques to protect a major product.”

Again, this wasn’t one of those fly-by-night Chinese manufacturers of low-end IoT devices, but Philips, a major, respected, and vigilant corporation.

As for the possible results? It could:

  •  jam WiFi connections
  • disturb the electric grid
  • brick devices making entire critical systems inoperable
  • and, as I mentioned before, cause mass epileptic seizures.

As for the specifics, according to TechHive, the researchers installed Hue bulbs in several offices in an office building in the Israeli city of Beer Sheva. In a nice flair for the ironic, the building housed several computer security firms and the Israeli Computer Emergency Response Team.  They attached the attack kit on the USB stick to a drone, and flew it toward the building from 350 meters away. When they got to the building they took over the bulbs and made them flash the SOS signal in Morse Code.

The researchers”were able to bypass any prohibitions against remote access of the networked light bulbs, and then install malicious firmware. At that point the researchers were able to block further wireless updates, which apparently made the infection irreversible. ‘There is no other method of reprogramming these [infected] devices without full disassemble (which is not feasible). Any old stock would also need to be recalled, as any devices with vulnerable firmware can be infected as soon as power is applied.’”

Worst of all, the attack was against Zigbee, one of the most robust and widely-used IoT protocols, an IoT favorite because Zigbee networks tend to be cheaper and simpler than WiFi or BlueTooth.

The attack points up one of the critical ambiguities about the IoT. On one hand, the fact that it allows networking of devices leads to “network effects,” where each device becomes more valuable because of the synergies with other IoT devices. On the other hand, that same networking and use of open standards means that penetrating one device can mean ultimately penetrating millions and compounding the damage.


I’m hoping against hope that when Trump’s team tries to implement cyber-warfare protections they’ll extend the scope to include the IoT because of this specific threat. If they do, they’ll realize that you can’t just say yes cyber-security and no, regulations. In the messy world of actually governing, rather than issuing categorical dictums, you sometimes have to embrace the messy world of ambiguity.  

What do you think?

 

Siemens’s Mobility Services: Trains Become IoT Labs on Wheels

George Stephenson's Killingworth locomotive Source: Project Gutenberg

George Stephenson’s Killingworth locomotive
Source: Project Gutenberg

As those of you who know rail history understand, with Stephenson as your last name, you’re bound to have a strong interest in railroads! Add in the fact that I was associate producer of an award-winning documentary on the subject back in the early 70’s, and it’s no wonder I was hooked when I got a chance to meet with some of Siemens’s top rail executives on my trip to Barcelona last week (Disclaimer: Siemens paid my expenses, but didn’t dictate what I covered, nor did they have editorial review of this piece).

What really excites me about railroads and the IoT is that they neatly encapsulate the dramatic transformation from the traditional industrial economy to the IoT: on one hand, the railroad was perhaps THE most critical invention making possible 19th century industry, and yet it still exists, in recognizable but radically-evolved form, in 2016. As you’ll see below, trains have essentially become laboratories on wheels!

I dwelt on the example of the Union Pacific in my e-book introduction to the IoT, SmartStuff, because to CIO Lynden Tennison was an early adopter, with his efforts focused largely on reducing the number of costly and dangerous derailments, through measures such as putting infrared sensors every twenty miles along the rail bed to spot “hotboxes,” overheating bearings. That allowed an early version of what we now know as predictive maintenance, pulling cars off at the next convenient yard so the bearings could be replaced before a serious problem. Even though the technology even five years ago was primitive compared to today, the UP cut bearing-related derailments by 75%.

Fast-forward to 2016, and Siemens’s application of the IoT to trains through its Mobility Services is yielding amazing benefits: increasing reliability, cutting costs, and even leading to possible new business models. They’ve taken over maintenance for more than 50 rail and transit programs.

While I love IoT startups with a radical new vision and no history to encumber them, Siemens is a beacon to those companies firmly rooted in manufacturing which may wonder whether to incorporate the IoT in their services and strategy. I suspect that its software products are inherently more valuable than competitors from pure-play software firms at commercial launch because the company eats its own dogfood and applies the new technology first to the products it manufactures and maintains — closing the loop.

Several of its executives emphasized that one of the advantages Siemens feels they enjoy is that their software engineers in Munich work in a corner of an old locomotive factory that Siemens still operates, so they can interact with those actually building and maintaining the engines on a daily basis. When it comes to security issues, their experience as a manufacturer means they understand the role of each component of the signaling system. Dr. Sebastian Schoning, ceo of Siemens client Gehring Technologies, which manufactures precision honing tools, told me that it was easier to sell these digital services to its own client base because so much of their current products include Siemens devices, giving them confidence in the new offerings. GE enjoys the same advantages of combining manufacturing and digital services with its Evolution Series locomotives.

The key to Siemens’s Mobility Services is Sinalytics, its platform architecture for data analysis not just for rail, but also for industries ranging from medical equipment to wind farms. More than 300,000 devices currently feed real-time data to the platform,   Consistent with my IoT-centric “Circular Company” vision, Sinalytics capitalizes on the data for multiple uses, including connectivity, data integration, analytics, and the all-important cyber security — they call the result not Big Data, but Smart Data. As with data services from jet turbine manufacturers such as Rolls Royce and GE, the platform also allows merging the data with data from sources such as weather forecasts which, in combination, can let clients optimize operating efficiency on a real-time M2M basis.  

With the new approach, trains become IoT laboratories on wheels, combining all of the key elements of an IoT system:

  • Sensing: there are sensors on the engines and gearboxes, plus vibration sensors on  microphones measure noises from bearings in commuter trains. They can even measure how engine oil is aging, so it can be changed when really needed, rather than on an arbitrary schedule.
  • Algorithms to make sense of the data and act on it. They read out patterns, record deviations & compare them with train control systems or vehicles of the same type.
  • Predictive maintenance replaces scheduled maintenance, dramatically reducing down-time and catastrophic failure.For example: “There’s a warning in one of the windows (of the control center display): engine temperature unusual. ‘We need to analyze the situation in greater depth to know what to do next  — we call it  ‘root cause analysis,” (say) Vice-President for Customer Support Herbert Padinger. ‘We look at its history and draw on comparative data from the fleet as a whole.’ Clicking on the message opens a chart showing changes in temperature during the past three months. The increased heat is gradually traced to a signal assembly. The Siemens experts talk with the customer to establish how urgent the need for action is, and then takes the most appropriate steps.”  He says that temperature and vibration analyses from the critical gearboxes gives Siemens at least three days advance notice of a breakdown — plenty of time for maintenance or replacement.  Predictive maintenance is now the norm for 70-80% of Siemens’s repairs.
  • Security (especially important given all of the miles of track and large crowds on station platforms): it includes video-based train-dispatch and platform surveillance using its SITRAIL D system, as well as cameras in the trains. The protections have to run the gamut from physical attacks to cyber attacks.  For security, the data is shared by digital radio, not networks also shared by consumers.

When operations are digitized, it allows seamlessly integrating emerging digital technologies into the services. Siemens Digital Services also included augmented reality (so repair personnel can see manuals on heads-up displays), social collaboration platforms, and — perhaps most important — 3-D printing-based additive manufacturing, so that replacement parts can be delivered with unprecedented speed. 3-D printing also allows dramatic reduction in parts inventories and allows replacement of obsolete parts that may no longer be available through conventional parts depots or even — get this — to improve on the original part’s function and/or durability, based on practical experience gained from observing the parts in use.  Siemens has used 3-D printing for the past last 3 years, and it lets them assure that they will have replacements for the locomotive’s entire lifespan, which can exceed 30 years.

The results of the new approach are dramatic.

  • None of the Velaro trains that Siemens maintains for several operators have broken down since Sinalytics was implemented. Among those in Spain only 1 has left more than 15 min. behind time in 2,300 trips: .0004%!
  • Reliability for London’s West Coast Mainline is 99.7%

  • Perhaps most impressive, because of the extreme cold conditions it must endure, the reliability rate for the Velaro service in Russia is 99.9%!

Their ultimate goal is a little higher: what Siemens calls (pardon the pun) 100% Railability (TM).

And, consistent with what other companies find when they fully implement not only IoT technology, but also what I like to call “IoT Thinking,” when it does reach those previously inconceivable quality benchmarks, the company predicts that, as the software and sensors evolve, the next stage will be new business models in which billing will be determined by guaranteeing customers availability and performance.

PS: I’ll be posting more about my interviews with Siemens officials and the Gartner event in coming days.

#IoT and Trump’s Election

Posted on 9th November 2016 in government, Internet of Things

I try to keep my politics out of this blog (disclosure: I am an old-fashioned liberal Democrat, who cares about poor, working-class white men AND everyone), but I do feel compelled to bring one little factoid to your attention: a quick review of Google earlier for “Internet of Things” AND Trump revealed absolutely nothing.  As for Obama initiatives in the field, such as the recent Smart Cities contest, you can bet they will be among the first programs axed by executive action. If you didn’t feel compelled to vote, or, even worst, voted for him to “Send Washington a Message,” consider it sent, and I hope you can live with what you have set in process. As ye sow, so shall ye reap.

For everyone else, pray for the future of the world — it’s that dangerous when a narcissist has his finger on the nuclear Button

2nd day liveblogging, Gartner ITxpo, Barcelona

Accelerating Digital Business Transformation With IoT Saptarshi Routh Angelo Marotta
(arrived late, mea culpa)

  • case study (didn’t mention name, but just moved headquarters to Boston. Hmmmmm).
  • you will be disrupted by IoT.
  • market fragmented now.

Toshiba: How is IoT Redefining Relationships Between Customers and Suppliers, Damien Jaume, president, Toshiba Client Solutions, Europe:

  • time of tremendous transformation
  • by end of ’17, will surpass PC, tabled & phone market combined
  • 30 billion connect  devices by 2020
  • health care IoT will be $117 billion by 2020
  • 38% of indiustry leaders disrupted by digitally-enabled competitors by 2018
  • certainty of customer-supplier relationship disruption will be greatest in manufacturing, but also every other market
    • farming: from product procurement to systems within systems. Smart, connected product will yield to integrated systems of systems.
  • not selling product, but how to feed into whole IoT ecosystem
  • security paramount on every level
  • risk to suppliers from new entrants w/ lean start-up costs.
  • transition from low engagement, low trust to high engagement, high trust.
  • Improving efficiencies
  • ELIMINATE MIDDLEMAN — NO LONGER RELEVANT
  • 4 critical success factors:
    • real-time performance pre-requisite
    • robustness — no downtime
    • scalability
    • security
  • case studies: energy & connected home, insurance & health & social care (Neil Bramley, business unit director for clients solutions
    • increase depth of engagement with customer. Tailored information
    • real-time performance is key, esp. in energy & health
    • 20 million smart homes underway in GB by 2020:
      • digitally empowering consumers
      • engaging consumers
      • Transforming relationships among all players
      • Transforming homes
      • Digital readiness
    • car insurance: real-time telematics.
      • real-time telematics data
      • fleet management: training to reduce accidents. Working  w/ Sompo Japan car insurance:
    • Birmingham NHS Trust for health (Ciaron Hoye, head of digital) :
      • move to health promotion paradigm
      • pro-actively treat patients
      • security first
      • asynchronous communications to “nudge” behavior.
      • avoiding hip fractures
      • changing relationship w/ the patient: making them stakeholders, involving in discussion, strategy
      • use game theory to change relationship

One-on-one w/ Christian Steenstrup, Gartner IoT analyst. ABSOLUTE VISIONARY — I’LL BE INTERVIEWING HIM AT LENGTH IN FUTURE:

  • industrial emphasis
  • applications more ROI driven, tangible benefits
  • case study: mining & heavy industry
    • mining in Australia, automating entire value train. Driverless. Driverless trains. Sensors. Caterpillar. Collateral benefits: 10% increase in productivity. Less payroll.  Lower maintenance. Less damage means less repairs.
    • he downplays AR in industrial setting: walking in industrial setting with lithium battery strapped to your head is dangerous.
    • big benefit: less capital expense when they build next mine. For example, building the town for the operators — so eliminate the town!
  • take existing processes & small improvements, but IoT-centric biz, eliminating people, might eliminate people. Such as a human-less warehouse. No more pumping huge amount of air underground. Huge reduction with new system.  Mine of future: smaller holes. Possibility  of under-sea mining.
  • mining has only had incremental change.
  • BHP mining’s railroad — Western Australia. No one else is involved. “Massive experiment.”
  • Sound sensing can be important in industrial maintenance.  All sorts of real-time info. 
  • Digital twins: must give complete info — 1 thing missing & it doesn’t work.
  • Future: 3rd party data brokers for equipment data.
  • Privacy rights of equipment.
  • “communism model” of info sharing — twist on Lenin.

 

Accelerating Digital Transformation with Microsoft Azure IoT Suite (Charlie Lagervik):

  • value networking approach
  • customer at center of everything: customer conversation
  • 4 imperatives:
    • engage customers
    • transform products
    • empower employees
    • optmize operations
  • their def. of IoT combines things/connectivity/data/analytics/action  Need feedback loop for change
  • they focus on B2B because of efficiency gains.
  • Problems: difficult to maintain security, time-consuming to launch, incompatible with current infrastructure, and hard to scale.
  • Azure built on cloud.
  • InternetofYourThings.com

 

Afternoon panel on “IoT of Moving Things” starts with all sorts of incredible factoids (“since Aug., Singapore residents have had access to self=driving taxis”/ “By 2030, owning a car will be an expensive self-indulgence and will no longer be legal.”

  • vehicles now have broader range of connectivity now
  • do we really want others to know where we are? — privacy again!
  • who owns the data?
  • what challenges do we need to overcome to turn data into information & valuable insight that will help network and city operators maximize efficiency & drive improvement across our transportation network?
  • think of evolution: now car will be software driven, then will become living room or office.
  • data is still just data, needs context & location gives context.
  • cities have to re-engineer streets to become intelligent streets.
  • must create trust among those who aren’t IT saavy.
  • do we need to invest in physical infrastructure, or will it all be digital?
  • case study: one car company w/ engine failures in 1 of 3 cars gave the consultants data to decide on what was the problem.

Live Blogging Gartner ITxpo Barcelona!

After a harrowing trip via Air France (#neveragain) I’m in lovely Barcelona, live-blogging Gartner ITxpo courtesy of Siemens — but they aren’t dictating my editorial judgment.

Keynoter is Peter Sondergaard, Sr. VP, Gartner Research:

  • start with high-scale traditional IT structures, but with new emphasis on cloud, etc. IT system now partially inside your org. and part outside.  We are half-way through transition to cloud: half of sales support now through cloud. More financial, HR & other functions. General trend toward cloud, but still some internal processes as necessary. Must clean up traditional inside processes.
    • “Ecosystems are the next evolution of Digital”
    • Must learn to measure your investments in customer experience.
    • Starting to explore VR & AR (personal shout out to PTC & clients such as Caterpillar!!)
    • must understand customer’s intent through advanced algorithms.  Create solutions to problems they don’t even know they have!
  • next domain of new platform: Things:
    • build strategies with two lenses: consumer preferences, AND the enterprise IoT lens.
    • leverage exponential growth in connected things
    • 27445 exabytes of data by 2020!
    • can’t just bolt on new systems on old ones: must rework existing systems to include devices — processes, workflow, much harder (i.e., my circular company paradigm).
  • intelligence: how your systems learn and decide independently
    • algorithms– algorithmic intelligence — drives decisions
    • now, AI, driven by machine learning. Machines learn from experience.
    • information is new code base
    • we will employ people to train things to learn from experience through neural networks
  • ecosystems
    • linear value supply chains transformed to ecosystems through electronic interchange.
    • others can build experiences, etc. that you haven’t thought out through APIs  — my “share data” Essential Truth. APIs implement business policies in the digital world.c
  • customers
    • customer driven

Where to start?

  • 70% of IoT implementation is through new organization within companies!

Now other Gartner analysts chime in:

  • insurance: engage your customers.
  • smart gov: must interact with those who implement. Must re-imaging public involvement sense/engage/interact
  • case study: Deakin University in Australia: digital platforms to enhance student experience.
  • case study: Trenitalia mass transit system switching to predictive maintenance! Huge cost savings. “Experience hands & beginners mind at work” — love that slogan!!!! “Listen to the train instead of scheduling maintenance”
  • blockchain: ecosystem, brilliant in simplicity. All can see transaction but no one can invade privacy. Use to solve many problems: data provenance, land registry, public infrastucture, AI.
  • Woo: use this to TRANSFORM THE WORLD!!!
  • ratz — I was preoccupied at time, they talked about a new mobility system for seniors — re my SmartAging paradigm!!
  • paradigm shift — partnering with competitors (much of what I wrote about in DataDynamite: share data, don’t hoard it!)  Think about Apple & Google driving car companies’ interfaces. “Do you join hands with digital giants or join hands with them?”).
  • ooh, love the digital assistant correcting his presentation. I can only dream of a future where there are millions added to grammar police!