Announcing three new Gigaom Change 2016 speakers fifianahutapea.blogspot.com

Join us in Austin for Gigaom Change where we will explore the impact of seven technologies that will change the way you do business forever.

Over an immersive two and a half days, we will cover Artificial Intelligence, Virtual + Augmented Reality, Robotics, Nanotechnology, Cybersecurity, 3D+ Printing, and Human-Machine Interfaces to understand how these technologies are transforming industry, and why this all matters.

Helping bridge the gap between today’s business operations and tomorrow’s demanding expectations, our carefully curated league of 20+ innovative speakers will showcase how business leaders can stop wondering what the future will bring, and instead start building for it.

We’re excited to announce three new speakers added to our lineup for Gigaom Change 2016!

As Chief Technology Officer and Global Head of HP Labs, Shane Wall drives the company’s technology vision and strategy, new business incubation and the overall technical and innovation community. Joining our 3D+ panel, Wall will provide real insights into how 3D printing is going to transform and disrupt manufacturing, supply chains, even whole economies … in other words, how it’s literally going to change the way we live.

As CEO of Fetch Robotics — delivering advanced robots for the logistics industry — Melonee Wise is an industry expert who will speak to the state of robotics today and the need + potential for the entire industry to transform to meet demand for faster, more personalized logisitics/ops delivery using “collaborative robotics”.

Taking a place on the Human-Machine interface panel is David Rose, an award-winning entrepreneur, author, and instructor at the MIT Media Lab. His research focuses on making the physical environment an interface to digital information. David holds patents for photo sharing, interactive TV, ambient information displays, and medical devices. His work has been featured at the MoMA, covered in The New York Times, WIRED, The Economist, and parodied on the Colbert Report.

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These speakers join an extraordinary group of 20+ global experts we’re lining up for Gigaom Change 2016 including:

Speaking on the subject of nanotechnology is Dr. Heike Riel, IBM Fellow & Director Physical Sciences Department, IBM Research. Dr. Riel’s work focuses on advancing the frontiers of information technology through the physical sciences. Her research interests include nanoscale materials and novel device concepts for applications in electronics, optoelectronics, energy harvesting and cognitive computing.

Discussing the subject of robotics is Rodolphe Gelin, EVP Chief Scientific Officer, Aldebaran. Rodolphe Gelin has worked for decades in the field of robotics, focusing primarily on developing mobile robots for service applications to aid the disabled and elderly. Most notably, he heads the Romeo2 project, a large-scale effort to create a humanoid personal assistant and companion robot.

Addressing human-machine interface is Mark Rolston, Cofounder & Chief Creative Officer, argodesign. Mark Rolston is a renowned designer who focuses on groundbreaking user experiences and addresses the modern challenge of design beyond the visible artifact – in the realm of behavior, the interaction between human and machine, and other unseen elements.

Speaking on the subject of virtual & augmented reality is Jacquelyn Ford Morie Ph.D., Founder and CEO of All These Worlds LLC and Founder & CTO of The Augmented Traveler Corp. Dr. Jacquelyn Ford Morie is widely known for using technology such as Virtual Reality (VR) to deliver meaningful experiences that enrich people’s lives.

Discussing the subject of artificial intelligence is Rob High, IBM Fellow, Vice President and Chief Technology Officer of IBM Watson. Rob High has overall responsibility to drive Watson technical strategy and thought leadership. As a key member of the Watson Leadership team, Rob works collaboratively with the Watson engineering, research, and development teams across IBM.

Addressing nanotechnology is Dr. Michael Edelman, Chief Executive Officer of Nanoco. Through his work with Nanoco, Dr. Edelman and his team have developed an innovative technology platform using quantum dots that are set to transform lighting, bio-imaging, and much more. Using real insights and examples, Edleman will share how this technology is currently disrupting entire industries.

On the artificial intelligence panel, Manoj Saxena, Executive Chairman of CognitiveScale and a founding managing director of The Entrepreneurs’ Fund IV, a $100m seed fund, will address the cognitive computing space; specifically, a new class of machine intelligence powered software that revolutionizing customer engagement, decision-making and productivity via complex, multi-structured Dark Data.

And last but not least, our opening night keynote speaker will be internet/ethernet pioneer Robert Metcalfe, Professor of Innovation, Murchison Fellow of Free Enterprise at The University of Texas.

Join us and 300+ visionary leaders along with 20+ global experts for the Gigaom Change 2016 Leader’s Summit on September 21-23 in Austin, Texas to explore some of the highly disruptive ways seven key technologies are shifting enterprise business.

Tickets are on sale now! This event will sell out, so get your tickets now.

If you are interested in sharing your work either on the stage or demonstrated in the venue, please contact us asap at change@gigaom.com as we’re finalizing things now.

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Logmein to acquire GoTo family of products from Citrix fifianahutapea.blogspot.com

Back in November, Citrix announced that it would spin out the GoTo family of products (see Citrix to spin out Goto products, will cut ‘investment’ in Podio). Today, the other shoe has fallen, with remote access software company LogMeIn announcing that it will acquire the kit-and-kaboodle from Citrix.

The deal has been approved by both companies, and will be structured as a ‘reverse Morris Trust’ which is a simultaneous spin out and merger, which will lead to a zero tax hit for Citrix.

The combined company should have revenues of over $1 billion.

It seems that the CEO of LogMeIn, Bill Wagner, believes in the synergies between a remote access software company and collaborative communications like the GoTo family, including GoToMeeting, GoToAssist, GoToMyPC, GoToTraining, GoToWebinar, Grasshopper and OpenVoice. Which, once upon a time, remote access software company Citrix also believed in. But now LogMeIn will be taking another run at that. (Or maybe there’s more synergy between companies that use capital letters to create HardToType company names?)

Not part of the deal is the somewhat-orphaned work media product, Podio, which is has been folded into the Cloud products at Citrix, like ShareFile. Citrix declared that it was decreasing its investments in that product in November, but not closing it down. In March, development for Podio was moved to Raleigh North Carolina.

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Apple services are growing, hardware slowing fifianahutapea.blogspot.com

Apple posted quarterly results, and received a standing ovation: the stock rose 7% at the opening this morning.

What’s intriguing is that the numbers show lower sales of iPhone (down 15% compared to last year), Mac (down 10.5%), and iPad (down 8.3%). But Apple has pulled off some hand jive, and drawn attention to what may be the future of its growth engine: services.

In the release, Luca Maestri — Apple’s CEO — wrote ‘our Services business grew 19 percent year-over-year and App Store revenue was the highest ever, as our installed base continued to grow and transacting customers hit an all-time record’.

As I mentioned earlier this week (see What’s going on in Phoneland?), the market had already priced in the negatives coming in Apple’s quarterly results. As others — like Chris O’Brien — have pointed out, Apple has done a great job managing the expectations of Wall Street, and drawing the analysts’ attention to the figures Apple wants us to pay attention to. And the trend in services, and the growing margins in iPad sales, are the figures that are causing the stock to soar.

Tim Cook stated that the services side at Apple is on track to be ‘the size of a Fortune 100 company next year’.

So, once again the maturation theme is front and center: Apple’s sales of new hardware is dropping, but with a huge installed base, what can Apple do to make money? Sell — or more aptly, rent — services to all those folks with iPhone, iPads, and Macs. (Oh, and Watches, but that’s too tiny to matter, and might never.) So if Apple can continue to grow services to the installed base — plus get some additional boost in iPhone sales in the fall when new models come out — the company will remain a Wall Street darling.

Relative to enterprise sales, the better margins in iPads has got to be a proxy for increased sales in the enterprise based on the new larger iPad Pro. But, at present, Apple doesn’t have much of a story for enterprise services. Maybe it’s time to the company to revisit the plan to buy Dropbox or Box, and replace/rework iCloud (iCloud Pro?) with a cloud file sync-and-share solution –including a deep integration with Apple’s productivity suite — that makes more sense for the enterprise?

 

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What’s going on in Phoneland? fifianahutapea.blogspot.com

Connecting the dots on some news stories from Phoneland.

First, the CEO of Ericsson has been sacked:

Kim McLaughlin, Ericsson Ousts Vestberg as CEO After Turnaround Plans Stall

Vestberg’s departure caps a turbulent period for Ericsson, which is cutting jobs while battling fierce competition from from Huawei Technologies Co. and Nokia Oyj. The company said last week it would accelerate cost cuts after reporting four straight quarters disappointing revenue and profit. Vestberg has faced questions on probes into alleged corruption in Asia and Europe, and last week the company rejected a report in Swedish media that it may be inflating sales by booking revenue before some clients are invoiced.

As usual, that’s the proximate cause, but the deep structure is that 4G tech has been rolled out worldwide already, and no one’s buying much these days.

With much of the so-called fourth-generation networks already built in the U.S. and China, Vestberg had vowed to improve profitability, but the stock has declined since reaching a more than seven-year high in April last year.

Vestberg had carved out new business units targeting media and enterprise customers to get back to growth, while investing in a next generation of so-called 5G wireless technology, which represents the next wave of spending at Ericsson’s telecom carrier customers. However, he refrained from big, dramatic moves like Nokia’s purchase of Alcatel-Lucent SA, opting instead for a partnership with Cisco Systems Inc. for Internet products like routers.

So, he’s out for thinking small bore, and we’re seeing the hiccups from the 4G/5G transition in Phoneland.

Second story: Steven Russolillo says that Apple is ripe for a Rally, despite the fact that market watchers are negative on the giant:

Much of the bearish thesis is due to weakening iPhone sales, which account for more than half of revenue. The iPad isn’t selling as well as it used to and the jury is out on the Apple Watch. Tech investors are allergic to anemic growth, which explains why the tech-heavy Nasdaq has lagged behind the Dow industrials and S&P 500.

Still, Apple has been punished more than enough. The iPhone slump appears priced in. And while the next iPhone, expected later this year, likely won’t be a significant upgrade, there is optimism that sales growth will soon bounce back. Analysts forecast iPhone unit sales will rise 5% for fiscal 2017, which ends next September.

The real question is not about stock price (or profits, either, with $10.52 billion in the March quarter), but about consumer buying behavior. Will we have to wait for a new mobile device — like AR/VR goggles? — before there is another huge surge in consumer demand for mobile? Watches aren’t the future, but goggles will be, I bet. Not a 2016 trend, though. Maybe 2017?

The third and last data point for today: Aaron Pressman digs into AT&T’s efforts to convince Wall Street its wireless business is healthy. His argument reviews the standard argument that postpaid subscribers — the ones signed up for monthly accounts — are generally considered to be better sources of reliable revenue than prepaid subscribers, who generally ‘spend less for service, buy cheaper phones, and tend to defect to other carriers more frequently’.

The bottom line is that so far this year, AT&T’s postpaid subscribers grew only 1% while prepaid subscriptions increased 21%. That’s disturbing to Wall Street, based on the ruling assumption that postpaid customers are preferable.

Thus, Stephens has been trying to push some new math on the analysts. In essence, his argument is that the best customers in prepaid are actually a lot better—and more profitable—than the worst customers in postpaid.

The average service revenue AT&T collected from postpaid customers who have left—and who mostly had not upgraded to smartphones yet—was only $35, he said during a conference call with analysts on Thursday afternoon. But the new prepaid customers signing up with Cricket are bringing in “closer to a $41, $42” of average revenue. Additionally, it costs less to acquire a new prepaid customer and less to provide them with customer service, he noted.

“So from that standpoint, the economics are better, and it is being shown in our margins,” Stephens told analysts, pointing out that while total wireless revenue was down slightly, profit margins were at record highs.

So AT&T has landed in a different dimension, where the economics are reversed, with T-Mobile and others screwing up the numbers for postpaid, while the supposedly poor prepaid sector looks good. However, this may be only true for a short transient period.

And the back office transitions around cable and internet, suggest other churn as the world is turning:

The telco is shedding expensive-to-maintain cable TV customers at its U-Verse unit while adding less costly satellite TV customers for DirecTV. AT&T is dropping broadband Internet customers who connect via older DSL lines while trying to add fiber optic broadband customers. And it’s trying to move corporate customers from traditional managed networks to cheaper virtualized networks. If all of the transitions succeed, both revenue and profits should grow.

Putting all the dots together? The consolidation in Phoneland is accelerating. Old technology is maturing, while new technologies and business models are only slowly emerging, which is leading to the downdraft at Ericsson, and financial analyst disdain for Apple and AT&T. The slowing rate of purchasing — by telcos and consumers, both — is leading to consolidation, the classic market maturation that comes right before a new era of breakthroughs and growth. But those breakthroughs won’t be in 2016.

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Rob High talks Artificial Intelligence with Gigaom fifianahutapea.blogspot.com

Rob High is an IBM Fellow, Vice President and Chief Technology Officer, IBM Watson. He has overall responsibility to drive Watson technical strategy and thought leadership. As a key member of the Watson Leadership team, Rob works collaboratively with the Watson engineering, research, and development teams across IBM.

Rob High will be speaking on the subject of artificial intelligence at Gigaom Change Leaders Summit in Austin, September 21-23rd. In anticipation of that, I caught up with him to ask a few questions about AI and it’s potential impact on the business world.

Byron Reese: Do you feel like we are on the path to building an AGI and if so, when do you think we will see it?

Rob High: Cognitive technologies, like Watson, apply reasoning techniques to domain-specific problems in things like Healthcare, Finance, Education, and Legal — anywhere there is an overwhelming amount of information that, if processed, can substantially improve the decisions or outcomes in that domain. For example, the work we’ve done with Oncologists to help them identify the most appropriate treatments for their cancer patients is based on having assessed what makes the patient unique; standard of care practices and clinical expertise that has been used to train the system; and the available clinical literature that can help doctors make better decisions. This helps to democratize that expertise to a wide swath of other doctors who do not have the benefit of having seen the thousands of patients that major cancer centers like Memorial Sloan Kettering or MD Anderson see.

The types of artificial intelligence used in these systems are spectacular in that they are able draw inferences from literature written in natural language, and to be taught how to interpret the meaning in that language as it applies to bringing the right information at the right time to the doctor’s fingertips. Unlike Artificial General Intelligence, our goal is to amplify human cognition — not to do our thinking for us, but to do the necessary research so that we can do our thinking better.

What do you make of all of the angst and concern being talked about in terms of why we should perhaps fear the AGI?

The concept of a machine-dominated world is inspired more by Hollywood and science fiction writers rather than technologists and AI researchers. IBM has been firmly committed to responsible science and ethical best practices for over a hundred years – it’s embedded in our DNA. Our focus is on applying cognitive computing to amplifying human cognitive processes, not on replacing them.

The reality is AI and cognitive technologies will help mankind better understand our world and make more informed decisions. Cognitive computing will always serve to bolster, not replace, human decision-making, working side-by-side with humans to accelerate and improve our ability to act with confidence and authority. The industries where Watson is being applied today – healthcare, law, financial services, oil & gas – exist to benefit people working in those industries.

For example, Watson augments a doctor’s abilities by aggregating and producing the best available information to inform medical decisions and democratizing expertise. But it’s the human doctor who takes the information Watson produces and combines it with their own knowledge of a patient and the complex issues associated with each diagnosis. Ultimately, the doctor makes the recommendation, informed by Watson, and the patient makes the decision – so there will always be a complementary relationship between human and machine.

Do you think computers can or will become conscious?

Today, we are making significant advances in integrating embodied cognition into robotics through Watson and that remains a primary focus. Our technology currently allows robots to – like humans – show expression, understand the nuances of certain interactions and respond appropriately. There’s still a need to teach robots certain skills, like the skill of movement, the skill of seeing, the skill of recognizing the difference between a pot of potatoes that are boiling versus a pot of potatoes that are boiling over.

However, we do believe that we’re only in the first few years of a computing era that will last for decades to come. We are currently assessing what’s doable, what’s useful and what will have economic interest in the future.

Great. We’ll leave it there. Thank you for taking the time to talk today.

Rob High will be speaking on the subject of artificial intelligence at Gigaom Change Leaders Summit in Austin, September 21-23rd.

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Slack invests in ecosystem of bot companies fifianahutapea.blogspot.com

Slack has announced $2 million in funding for bot startups in its Slack Fund, that has been passed out to 11 new companies and 3 existing investments. The list, as reported by Techcrunch:

Abacus is intelligent expense reporting software that brings report creation and approvals right into Slack.

Automat is making it easier for anyone to build a bot that passes the Turing Test. Automat is in private beta today.

Birdly connects Slack and Salesforce so that anyone can access the information they need about a given account.

Butter.ai is a personal assistant that makes all of your company knowledge easily accessible. Butter is in private beta.

Candor, Inc. aims to improve working relationships through radically candid feedback. Candor’s Slack app is not generally available yet today.

Growbot lets you encourage and commend your teammates for a job well done with a helpful bot.

Konsus gets you 24/7 access to on-demand freelancers to help you get the job done, all via Slack.

Lattice helps you establish goals, OKRs weekly check-in and continuous feedback with your Slack team.

Myra Labs helps you build amazing bots with an API that provides machine learning modules out of the box. Myra is in private beta.

Sudo is a bot that manages your CRM, taking all of the pain of manual data entry away from the sales rep. Sudo is in private beta.

Wade & Wendy are two intelligent recruiting assistants. Wade is a career advocate who helps find you opportunities and Wendy helps recruiting teams to source candidates. Wade and Wendy aren’t live yet, but you can sign up for their waitlist.

Previously funded

Awesome.ai helps team stay in sync, find clarity and reflect on what’s important.

Begin is a bot that helps improve your focus and efficiency, keeping you on top of all of your work.

Howdy is a friendly, trainable bot that powers teams by automating common tasks.

Bots are a very hot area right now, part of a growing trend toward contextual conversation in enterprise work technologies (see Contextual conversation: Work chat will dominate collaboration) and in the consumer sector, in open messaging apps.

I will be developing a report on Chat, Bots, and the Future of Work Communications in the fall, based on research launching soon. This trend interacts with the rise of AI, and spoken communications, and even the rise of augmented and virtual reality.

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GigaOm Research on Blockchain and Healthcare, IoT, Insurance and Beyond fifianahutapea.blogspot.com

https://ben554.typeform.com/to/MBD5sV (click to contact GigaOm regarding participation in our research)

There is a tremendous amount of growing interest in blockchain in recent months and GigaOm is currently exploring the business implications of this trend across a number of verticals. While most of the current activity is in the finance or fintech sector, there is growing interest in blockchain’s impact on the IoT, healthcare, sharing economy and beyond. Smart contracts, pseudonymous identity management, transparency and cryptographic security are features that have applications well beyond banking. The most obvious use case of distributed, cryptographic ledger data systems in finance is to make more efficient clearing mechanisms for financial transactions. Securities and banking transactions depend on clearninghouses that can authenticate users on each end of a transaction and enable the transfer of funds or completion of the transaction, but this takes up to three days in most cases. Blockchain transactions can automate this type of transaction and cut out the costs of the middlemen who currently handle the bulk of global financial transactions. A great deal of startup activity in the fintech arena is focusing on mobile money and remittances as well as large collaborative intiatives with the largest banks to build private blockchains (or permissioned blockchains) that are closed networks rather than the standard open or public blockchain. With the growth in prevalence of security breaches across the economy, it is no wonder that many other verticals are beginning to pay close attention to developments in blockchain and how it can be used to improve data management, transparency and certifying provenance of goods or that they are not counterfeit, and address the challenges of un-interoperable technology systems. Furthermore, at GigaOm we are looking at new business models that blockchain is going to enable in the coming years.

We are currently taking a close look at healthcare, insurance and the IoT as the next generation of blockchain startups and applications beyond finance. Healthcare is rife with interoperability challenges that stand in the way of coordinating patient care, patient safety and very onerous administrative costs or waste. Companies such as Gem, a blockchain startup, are heavily focused on data management systems using blockchain that can connect diverse datasets across the silos as well as guarantee authenticity of data. The blockchain can be used to create a type of universal record with a timestamp, a library that enables data retrieval across diverse databases. This will become exceedingly valuable as precision medicine and the explosion of sensors, wearables and mHealth apps proceeds. The current health systems and the legacy health IT players quite simply are not well designed to manage the volume and types of data that are being generated today. This stands in the way of realizing the goals of precision medicine in a scalable, pragmatic manner anytime soon. Blockchain and APIs may enable a post-EHR layer of applications to enhance the functionality of current EHRs and make care coordination and population health management much easier to accomplish but this will take several years to become mainstream.

IBM and others major IT vendors are collaborating with the Linux Foundation around the open source Hyperledger Project to accelerate innovation in the blockchain arena. Much of this is driven by growth in the internet of things (IoT) and the need to manage data and services across devices in this ecosystem. Smart contracts can enable micro-payments for services rendered by IoT devices or those monitored by sensors. The security concerns that the IoT raises are also important features of blockchain data management. Alternative versions of blockchain applications such as Tangle are being developed to bring the cloud closer to the devices powering the IoT. New business models are utilizing smart contracts in the context of micro-grids and solar power to enable P2P sharing of energy and payment systems.

More authentic sharing economies may emerge at the nexus of blockchain and insurance. If efficiencies can be realized to authenticate users and incidents, these may enable new forms of insurance for users of AirBnB as one example, but entirely new forms of insurance that involve crowdfunding and matching funding with needs much in the way that Uber and AirBnB do with taxis and apartments. We are also beginning to see microloans of insurance. The authentication and provenance functionalities of blockchain will have robust use cases in mitigating insurance fraud. In healthcare alone Medicare fraud is a major source of lost revenue for the public sector and source of waste.

GigaOm is conducting original research into this rapidly changing space and are looking for companies to work collaboratively on this syndicated report with us that explores the innovative use cases of blockchain. If your company has a strong interest in this work and would like to share your insights or actual applications we would be happy to discuss collaboration in the coming weeks.

For information on how to collaborate in our research click: https://ben554.typeform.com/to/MBD5sV

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Ran Zilca on Millennials Think About Work Too Much fifianahutapea.blogspot.com

Ran Zilca of Happify ran a study on Millennials that reveals them to be work-obsessed, bed-loving, and irreligious [emphasis mine].

When asked what they are grateful for, people typically respond with the things they personally recognize as important — what they appreciate and value. Gratitude text can therefore provide a glimpse into the fundamental life priorities of individuals. In our study, 276,296 Happify users (30.7% of them in the age range of 25–34) responded to a gratitude exercise where they were asked to “jot down three things that happened today or yesterday that made you feel grateful.” Users were directed to think of a broad range of possibilities: “It could be something someone did for you, something you did for yourself, or just the simple fact that the sun was shining.”

Across all ages, the most common topics were related to “spending quality time with family and friends.” Yet the topics for which Millennials specifically expressed the most gratitude were different: “positive interactions with colleagues,” “having a low-stress commute,” “getting a new job,” “being satisfied with an existing job,” “sleeping,” and “relaxing in bed.”

Four out of these six topics were career related and had to do with the process of finding a job or with daily work experiences, and the remaining two topics were related to time spent in bed. Since the gratitude question specifically asked about things that happened today or yesterday, we can fairly confidently say that the unique things characterizing positive Millennial experiences take place at work or in bed.

The two topics of gratitude that were far less common for Millennials were “religious events,” a positive event that happened at church or a church event like singing in the choir, and “friends and family,” a topic that was among the most common for users of other ages.

Millennials are career-wacked drones that apparently live to work and sleep, and they lack the grounding of sociality and spirituality, alas.

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Originally published at www.stoweboyd.com.

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Review: SmartDraw Helps to Tame Wild IoT Networks fifianahutapea.blogspot.com

With the rabid adoption of IoT (Internet of Things) devices across the enterprise and the ensuing infrastructure changes, comes unmitigated complexity. Many network managers, let alone their superiors and subordinates, are having difficulty wrapping their heads around the inherent complexity of the modern, IoT-enabled, network.

San Diego based SmartDraw Software has heard the cries of the IoT besieged and has built a tool that brings simplicity to the diagramming process. What’s more, the company has introduced SmartDraw Cloud as a companion product (or alternative) to the company’s desktop based SmartDraw 2016 Business Edition.

Simply put, network diagrams, org charts, office layouts, floorplans, decision matrices and flow charts are the fodder of business and excel at serving as a visual representation of conceptual ideas, which go a long way towards getting buy-in on most any project. The importance of bringing simple understanding to complex infrastructures becomes obvious when you realize that some decision makers need to see it to believe it.

SmartDraw’s goal with SmartDraw Cloud is to empower those that must explain. SmartDraw Cloud brings a new paradigm to the diagramming market, something akin to “diagramming as a service” and, at only $12.95 per month, ithas become a budget friendly alternative to expensive tools such as Microsoft Visio. As a cloud offering, the product brings the full feature set of SmartDraw 2016 Business Edition to more than just the traditional Windows desktop. SmartDraw Cloud runs on OSX, IOS, Android, Linux and pretty much any OS that can launch a modern browser, such as Edge, IE 10+, Safari, Firefox, Chrome or Opera.

Hands on with SmartDraw Cloud:

Beyond the aforementioned IoT and network diagramming capabilities, there are literally thousands of different use cases for SmartDraw. The product offers 70 different categories of drawings, with some 4,500 templates and 34,000 symbols to help users get started. SmartDraw Cloud gives most anyone the ability to draw most anything. That said, the product really shines when it comes to diagramming complex concepts. For those in the world of IT, SmartDraw can become an indispensable companion for building network diagrams, IoT maps, flow charts, and decision trees,  all of which are used extensively by the majority of tech savvy businesses.

Getting Started:

Diving into SmartDraw first takes making a decision, which basically comes down to choosing what iteration of the product to use. However, there is one caveat, if you purchase the $297 Windows version of SmartDraw 2016 Business edition, you will automatically get a full year of the Cloud service as well. With that in mind, it may make the most sense to start out with the cloud-based offering and then decide if a desktop version is warranted. Either way, SmartDraw does offer a 7-day free trial of the product for those investigating its capabilities.

Using the cloud iteration of SmartDraw proves to be a very simple process, it just takes logging into the cloud app at https://cloud.smartdraw.com, and the user is presented with the GUI, which is almost indistinguishable from the desktop version of the product. That means users can switch back and forth from the desktop and cloud version with relative ease. All of the menus, icons, templates and other elements are virtually identical between the cloud and desktop iterations of the product.

Creating a Networking / IoT Diagram:

The GUI makes creating any diagram amazingly simple. For example, creating a network diagram means navigating down to the Network Design document menu and then choosing the type of network diagram desired (Network or Rack). Fifteen example network diagrams are also offered, giving a neophyte user a head start on building a new network diagram.

For this example, I chose the Enterprise Network template, which then launched another browser window with the diagram editing screen and a sample network design, fully populated with symbols and connections. The design GUI offers a variety of tools, making it easy to change any element on the screen, add effects, create text and so forth. A tabbed interface on the left allows users to choose device images from a “SmartPanel” which supports full drag-and-drop capabilities.

Drag and drop is something not normally found in a browser-based application. Thousands of symbols are available, including all different types of PCs, routers, switches, firewalls, servers and so forth. The GUI also includes a handy tool, which allows a user to search for symbols, allowing normally unrelated symbols to be added to a diagram being created, such as a landscape element like a lamppost or a tree being added to a diagram for IoT networking equipment to indicate where a sensor, IP/WiFi security camera or other device is located. Just by using the drag and drop capabilities, along with symbols from the libraries, an informative network diagram can be completed in just minutes.

All symbols contained within the diagram can be linked, grouped, have text added to, resized, and even have hyperlinks to other diagrams associated with them. Line drawing proves very easy, where by selecting the line tool, lines can be connected between symbols.

Once the diagram is ready, it can be shared with others by simply clicking the share icon. The diagram can be shared as a view only element (which does not require the recipients to have SmartDraw) and is fully viewable in any browser. If the diagram is shared with a “View and Edit” status, recipients can modify and re-share the diagram. Sharing is accomplished using an emailed link to the diagram.

Creating a Flowchart:

Flowcharts are often the primary fodder behind any type of business process, especially those that involve IT operations. Here, SmartDraw excels in its ability to quickly create flowcharts that have logical progressions and incorporate the Boolean logic that can drive decisions. The product comes prepopulated with flowchart templates, as well as examples that speed design, allowing those creating the charts to focus on critical logic and not the mechanics of graphical design. That said, users can still create attractive, professional-looking flowcharts that are easy to modify and expand as time goes on or processes change.

For example, starting a flowchart based upon the flowcharting template consists of little more than selecting the appropriate visual objects and then adding instructions or text. The product’s “SmartPanel” provides numerous visual examples, along with relevant descriptions, which are easy to select, use and understand. Flowcharts can be built in a matter of minutes and delivered to those looking to achieve the given result. SmartDraw’s real strength here comes in the forms of ease of use and speed, trumping competing products by allowing users to build a flowchart in a matter of minutes, instead of the hours it normally takes using other tools.

Visualizing Data: 

SmartDraw also includes the ability to quickly create infographics. Here, the product is loaded with templates and charts that can enable a user to build an infographic for most any situation. Population templates, process/cycle infographic templates, World Data Map templates, and dozens of others are readily available, allowing users to simple plug in collected data and create a professional looking graphical representation of that data.

The product also bundles in several charts, which can be inserted in diagrams. Those charts include the basics, such as bar charts, pie charts and so forth, as well as more advance 3D charts, which give a little more life to the pedestrian data that network managers may be reporting on. Most notable for the IT management realm is the “Relative Value Chart”, which makes it much easier to visualize cost comparisons when calculating critical IT budget elements, such as ROI and TCO. Timeline, Spheres, and Venn infographics are well represented by the GUI, making it a simple chore of selecting what graphic a user needs to use and then just populating the data.

Engineering and CAD:

While SmartDraw makes no boisterous claims that the product can replace multi-thousand-dollar design packages, such as AutoCAD, MATLAB and others, the product sure goes a long way towards covering the basics by providing several engineering templates that can be used to create electrical wiring diagrams, industrial automation designs, and even architectural blueprints. Users can quickly layout floor plans, office buildings, circuit panels and several other CAD/CAM type diagrams with relative ease. The included tools and wizards take a lot of the guesswork out of what are normally complex designs and can expand IT’s ability to be part of the design process. What’s more, a short learning curve and ample integrated help makes what may seem at first impossible, an achievable goal for individuals without any prior CAD/CAM experience.

But Wait, There’s More:

At the risk of sounding like a late night infomercial, there is much more to SmartDraw than the above examples. The product includes templates and examples to build cause & effect diagrams, decision trees, emergency & disaster planning diagrams, flyers & certificates, forms, project management charts, mind maps, org charts, process documentation, schedules, strategic plans and much more.

However, the products core strength lies with more than just countless charts, templates and graphical design tools. The real strength comes from the ease of use associated with created those complicated visual representations. A chore that was once only in the realm of professional graphic artists, that could take days or even weeks to deliver attractive visual representations of complex data sets.

One would be remiss if they did not mention SmartDraw’s primary competitor, Visio. SmartDraw offers several advantages over Visio, starting with the availability of SmartDraw Cloud and ending with ease of use. In between those two comparative bookends lies features such as the ability to share diagrams with others (who lack any type of diagramming package) and the automation that SmartDraw offers in the form of intelligently connected objects. For those comparison shopping, SmartDraw offers the Visio Filter, which imports native Visio drawings into SmartDraw, without losing any content, making it easy to play around with SmartDraw’s feature set, without having to recreate Visio drawings from scratch.

Once you add the cloud-based version of SmartDraw to the mix, you wind up with a real winner, at least when it comes to visualizing most anything you can imagine. For a visual tour of SmartDraw’s capabilities, please visit this companion slideshow over at eWeek.

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Paving the Road for Digital Transformation fifianahutapea.blogspot.com

Countless CEOs, CFOs, CIOs, and the whole c-suite in general are discussing the merits of digital transformation, a process (and ideology) that promises to re-invent how businesses actually conduct business. For the uninitiated, MITSloan defines digital transformation is all about the use of technology to radically improve the performance or reach of enterprises. While that definition may fit into a catch all of what information technology is all about, there is a lot more to digital transformation than meets the eye.

Simply put, the pathway to digital transformation is beset by all sorts of challenges, something that is aptly spelled out in Altimeter’s State of Digital Transformation report, which points out major challenges consisting of changing the company culture, fostering cooperation between departments, and securing the appropriate resources to succeed. While those elements in themselves are considerable challenges, numerous fortune 5000s have successfully achieved the nirvana of digital transformation, but at great cost.

While much of that cost can be attributed to business realignment, training and organizational structure changes, the simple fact of the matter is that digital transformation all comes down to having the proper infrastructure in place and the tools to leverage, manage and optimize that infrastructure. What’s more, the actually technological process behind digital transformation can be both helped and hampered by the distributed nature of today’s networks, meaning that public, private, and hybrid cloud technologies can bring both benefits and complications to digital transformation.
Some business, such as AirBnB and Uber, brought digital transformed their business models by eschewing privately owned infrastructure and fully leveraging the ideology of hosted infrastructure, such as the PaaS (Platforms as a Service) model.

That said, other businesses are still very much leveraging in house solutions to achieve digital transformation, take for instance Caterpillar, which is developing ways to sell data, and not just “things”.  Regardless of the basic infrastructure in use, one of the goals of digital transformation is to bring “data and things” together, to build an intelligent internet of things (IoT), and that means bringing full visibility to IoT, as well as data. A concept that Joshua Dobies, VP Product Marketing at Riverbed, has much to say about.

In an interview with GigaOM, Dobies said “the world of digital transformation powered by optimization.” A fact well illustrated by all of the moving parts involved with tying various micro-services, cloud resources, and application foundations together. Dobies added “overcoming latency and the physical distances is one of the biggest challenges facing those interested in digital transformation.” Dobies makes a good point, if the various pieces of an application are logically distant, application performance will suffer appreciably, perhaps destroying the end user experience and effectively putting a nail in the digital transformation coffin.

Dobies also said “Many businesses have failed to achieve their goals of digital transformation, simply because they did not properly address infrastructure issues before hand.” Dobies’ comments lead to an unmistakable conclusion – digital transformation should never be an organic process, it is something that takes proper planning and creating a foundation (read infrastructure) that can successfully integrate all of the moving pieces into a cohesive, manageable solution.

Simply put, digital transformation take tenacity, persistence, planning, and the appropriate technology to be successful. Riverbed offers an excellent take on the challenges of visibility and digital transformation in the form of a post on the company’s website.

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Dr. Michael Edelman talks quantum dots with Gigaom fifianahutapea.blogspot.com

Dr. Michael Edelman joined Nanoco in 2004, led the initial fund–raising and spun Nanoco out of the University of Manchester. Prior to Nanoco, Michael held a number of executive roles including responsibility for licensing the technology developed by GE/Bayer joint venture, Exatec LLP, Vice President and Managing Director at yet2.com , Commercial Director at Colloids Ltd and Business Manager at Brunner Mond & Co ltd., Michael started his career with ICI, has a Ph.D. in organo–metallic chemistry from the University of Sussex, UK, and undergraduate degree in classics and chemistry from Tufts University, Boston, MA, USA.

Dr. Michael Edelman will be speaking at Gigaom Change Leaders Summit in Austin, September 21-23rd. In anticipation of that, I caught up with him to ask a few questions.

Byron Reese: Tell me the first time you ever heard about Nanotechnology?

Dr. Michael Edelman: Oh gosh, probably in the late eighties. And in the late eighties, we weren’t really calling it nanotechnology then, we were calling it colloidal chemistry, which is chemistry on a very small scale and then the nano name took off. Nanotechnology has been around for thousands of years, starting off with some of the early pigments and dyes used by Greeks and Romans to paint pots. So it’s not a new concept, chemists, physicists have been working on these sorts of technologies for a very very long time, and typically what we mean by nanotechnology is materials, things under 75 to 100 nanometers. You are looking at working with sizes 10,000 times smaller than the width of a human hair. So pretty small.

Wow us a little bit with some of the science fictiony things we may live to see that nano is going to enable.

With Nanoco, my company, we play in the area of florescent semi-conductors called quantum dots. What’s unique about these materials and nanomaterials in general, is that they start to behave in weird and wonderful ways when they get very small.

And the amazing thing that our materials do is they fluoresce, they give off very, very bright, different colored light; red, green, blue, orange, yellow, whatever color you want. And that color is strictly dependent on the size of the nanocrystal. We are manufacturing these nanocrystals with a diameter between one and ten nanometers which is ten to one hundred atoms across.

We accurately manufacture these materials, growing these crystals of one, two, three, five, seven nanometers. It would be as if you had a very tiny golf ball with a diameter of one nanometer, and you expanded it. The chemical makeup is the same, but the mass is changing and this changes the electronic properties, which in turn changes the optical properties or color of light emitted.

When you have a material that lights up very brightly with only tiny amounts of energy, people start getting excited. We can bind specific anti-bodies to the quantum dots and use them to more accurately image and diagnose cancer. They absorb energy so they can also be used very effectively as new generations of solar cells.

So the ‘wow factor’ for the materials, these quantum dots, is that it’s a true platform technology that can be used across a number of different and unrelated end use applications from cancer imaging to next generation displays.

I get excited because it is very infrequent that you see a true platform technology. It is a word that is overused today. People talk about platform technologies all the time, but when you see a material that actually can be used in a number of unrelated sectors its tremendous.

Dr Nigel Pickett, our CTO and co-founder and I started Nanoco in the UK, in a converted men’s bathroom at the University of Manchester and have grown very successfully since then.

So you’ve actually expanded into the woman’s bathroom at this point?

[laughing] We’re actually much bigger. HP started in a garage and we started in the toilet.

Well you’ve got no place to go but up from there.

Well it was a big toilet.

In what sense are quantum dots quantum?

Because you get what we call a ‘sized quantization effect’ which is where the electronic properties of the semiconductor materials are changed, meaning the band gap of the material can be altered by changing the size. That is the quantum effect.

And how will they be used in quantum computing?

Our main focus today for these materials is on things that require enhanced color, so as a company we are not working on quantum computing. The folks working on quantum computing, using more traditional semiconductor technology, use molecular beam epitaxy to grow these quantum dots on wafers. That is the area that’s focused on the quantum computing.

We are essentially chemists and we are making these quantum dots in chemical reactors. In essence we are high-tech cooks, we add ingredients, we stir those ingredients and we heat them. How we do it is fairly sophisticated but the advantage of this is that the finished product is very cost effective to make, so we can apply these onto TVs today. Those TVs are at a price point that you and I can buy. Whereas quantum computing today is not there yet.

So where are you from a commercial standpoint with your technology?

The technology right now is getting launched into the marketplace. The Company has signed a number of deals, and probably [the one] that we’re known for is with Dow Chemical. Dow has built a large facility in South Korea to service the display industry, mainly the Korean TV giants. And the first products coming online are products from Samsung. You can go to Best Buy today and buy a new Samsung TV with enhanced color that comes from quantum dot technology. The first market to take off is the display market, and in the display market the first products are the high end color enhanced 4K displays. We are talking about LCD TV’s and LCD is the predominant display technology out there with about 240 million LCD TVs being sold each year. We’re helping the LCD technology, which has been around for a number of years, evolve and continue to get better.

Likewise, for lighting systems we have developed some products that we launched earlier in the year into horticultural lighting. What we’re doing is tuning the LED light with the quantum dots, so the light emits specific wavelengths that promote specific plant growth.

Looking forward in the next two or three years, what are some breakthroughs our readers should just keep an eye out for in the news?

The televisions are here now, they are getting rolled out and you are going to see a lot more of them. [Also] light and different types of light sources using quantum dots are here and you are going to see more quantum dot based lighting.

What I am excited about, if I look three to five years down the road, is the use of these materials in biological imaging and life science applications. Because our materials are all heavy metal free, [they can be used in the body] to very accurately image and diagnose cancer at an early stage, at a very sensitive level. You can tag specific anti-bodies onto these quantum dots of whatever color, and manipulate the size so they can get through the cell walls. Then they can bind specifically to a cancer that you are targeting. This, to me, is amazing.

Thank you so much for your time. I look forward to discussing this further in September.

Michael Edelman will be speaking on the subject of nanotechnology at Gigaom Change Leaders Summit in Austin, September 21-23rd.

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Teach Millennials How to Be Managed By You fifianahutapea.blogspot.com

This article is the fifth in a series of six. It is excerpted from Not Everyone Gets a Trophy: How to Manage the Millennials by Bruce Tulgan

Set Clear Ground Rules Up Front

Managers tell me every day that Millennials fail to meet a lot of unspoken expectations about behavior in the workplace. I have an idea: Speak them!

One credit union manager was telling me about a young employee who routinely came to work late and then made lots of personal calls on his cell phone throughout the workday. “Do I really need to tell him, ‘Come to work on time, and it’s not good to make so many personal calls all day long’?” Yes! You have to tell him, up front and every step of the way.

You have to figure out what your expectations are and then speak up. Set ground rules. Maybe there are corporate policies in place already. But often there are no concrete policies to regulate important intangibles like attitude, tone of voice, and other subtleties of professionalism in the workplace. You may need to figure out these ground rules on your own. You may need to say, “Whenever you are working with me, on any task, for any period of time, these are MY ground rules.” Then lay out your ground rules in no uncertain terms, and make it clear they are deal breakers for you: you can’t work with someone who doesn’t follow these ground rules.

Leverage the Power of High-Structure, One-on-One Meetings

Remember that Millennials have grown up hyper-scheduled. They thrive on that kind of structure, and they thrive on one-on-one attention. One of the most effective ways to help your young employees learn to be managed by you is to schedule regular discussions with each of them about their work.
At first, err on the side of meeting more often with each person—every day, every other day, or once a week. Start by evaluating what time will best work for you: What time will fit your regular schedule and needs? Then communicate with each Millennial the expectation that you will meet regularly one-on-one at a regular time.

Making a plan with your young employee to meet one-on-one at a regular time and place is a huge commitment for both of you. It is a powerful statement that you care enough to spend time setting this person up for success. When you follow through and spend that time, you are creating a constant feedback loop for ongoing short-term goal setting, performance evaluation, coaching, troubleshooting, and regular course correction.

Spell out how long you expect each meeting to last (my advice is to keep them to fifteen or twenty minutes). Don’t ever let these meetings become long or convoluted. Make it clear that your meetings will follow a fast and tidy agenda, preferably the same basic format every time. Start each meeting by reviewing the agenda. Whenever possible, present an agenda in writing that you can both follow. These meetings should be cordial but all business. This is not the time for chitchat.

Like everything else, this dynamic process will change over time, and your approach will have to change with each young employee you meet with regularly. For each of your employees, you’ll have to figure out how often to meet, how much time to spend at each meeting, what format to use, and what topics to cover. And remember: you’ll have to make adjustments over time.

No matter how well things seem to be going, you still need to verify that things are indeed going as well as you think. If they are, make sure that Millennial knows just how many points she is scoring today.

Create an Upward Spiral of Continuous Improvement

Managers often tell me they have a hard time talking to Millennials about failures great and small. “When they make a mistake, you hesitate to tell them because they take it so hard,” I was told by a partner at a prestigious law firm. “They seem to take it personally, like you are breaking their heart. I want to say, ‘Don’t feel bad. Just go back and make these changes, and then next time try to remember to do it properly in the first place.’ That seems pretty basic.” It is pretty basic.

When it comes to addressing Millennials’ performance problems, the most common mistake managers make is soft-pedaling honest feedback or withholding it altogether. Sometimes managers take back incomplete work and finish it themselves or reassign it. Other times the problems are not addressed at all, and the work product remains substandard. Millennials are left to fail unwittingly or improve on their own impulse and initiative. As one Millennial put it, “What do you want me to do, scream it? Beg for it? Help! Help me get it right. Help me do it faster. Help me do it better. Help me improve.”

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About the Author

Bruce Tulgan is an adviser to business leaders all over the world and a sought-after keynote speaker and seminar leader. He is the founder and CEO of RainmakerThinking, Inc., a management research and training firm, as well as RainmakerThinking.Training, an online training company. Bruce is the best-selling author of numerous books including Not Everyone Gets a Trophy (Revised & Updated, 2016), Bridging the Soft Skills Gap (2015), The 27 Challenges Managers Face (2014), and It’s Okay to be the Boss (2007). He has written for the New York Times, the Harvard Business Review, HR Magazine, Training Magazine, and the Huffington Post. Bruce can be reached by e-mail at brucet@rainmakerthinking.com; you can follow him on Twitter @BruceTulgan, or visit his website.

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Agile DevOps: A Path to the Common Ground of Productivity fifianahutapea.blogspot.com

 

Agility has become the buzz word around the enterprise. whether it is agility around storage, networking, cloud operations, or most any other IT service is not really the point here, it all comes down to agility as an ideology.

Take for example the burgeoning data analytics market, which is driven by big data and business intelligence, where implementing agile ideologies could be the secret to success. After all, an agile business needs to be able to react to trends and discoveries to remain competitive, and waiting on analytics does not bode well for those looking to make intelligent decisions as quickly as possible.

In other words, best of breed analytics solutions must bridge the gap between data science and production to unify development and deployment into an agile methodology. With that in mind, Florian Douetteau, CEO of Dataiku, has put together an interesting guidebook that discusses how to achieve that level of synergy to build a data project that embodies the ideologies of agility.

Douetteau has identified the key strategies that illustrate how to bring agility to a data science project, those strategies include adopting:

–              Consistent Packaging and Release

–              Continuous Retraining of Models

–              Multivariate Optimization

–              Functional Monitoring

–              Roll-Back Strategy

–              IT Environment Consistency

–              Failover Strategies

–              Auditability and Version Control

–              Performance and Scalability

Ultimately, the goal here is to bring agility to the data team, where a data science team and IT production can work hand in hand to deliver results in an agile fashion.

In an Interview with GigaOM, Douetteau offered additional advice, he said “One of the most valuable tips I can offer is that IT should provide a common platform, which gives users across the different groups access to the tools and technologies they are familiar with. Ideally, visual drag and drop tools for should be provided for less technical team members, while the ability to code, should be provided for advanced members. What’s more, monitoring, security options and role based administration tools should be made available to those responsible of deployments.”

Nonetheless, previous attempts to achieve the goal of agile decision making has been an almost impossible task, thanks to the silos surrounding data science development and the deployment of operational applications that can illustrate results.

Douetteau says “the biggest challenge of most data science projects is getting everyone on the same page in terms of business goals, technical requirements, project challenges, and responsibilities. More often than not, there is a disconnect between the worlds of development and production. Some teams may choose to re-code everything in an entirely different language while others may make changes to core elements, such as testing procedures, backup plans, and programming languages.”

It is that isolationism that prevents many data science projects from becoming an overall success, and worse yet, lead to incorrect conclusions and assumptions. Much of the blame can be placed upon the waterfall development ideologies of the past, which have hampered the adoption of agility in the area of data sciences.

Douetteau adds “preventing failures takes a manager who is willing to act as tech stack and programming language dictator, who will force the team into a fixed technology for a solution. That manager should also ensure that team members adopt a big picture approach, where they are able to help each other complete tasks outside of their comfort zone. Individual silos of knowledge will hinder a team’s effectiveness, and collaboration is the key to success.”

For enterprises to truly become agile, they must eschew those waterfall development processes and switch to agile methods across the board. However, data science projects seem to be the most opportune place to start in today’s on demand, instant results world.

Douetteau adds “Providing a platform that caters to all members of the team promotes collaboration and communication, two elements that are essential to the success of any devops/data analysis project that involve multiple departments.”

What’s more, the lessons learned on data science projects can be readily applied to other areas of IT and business operations, making agile an achievable goal, as long as you know where to start.

Douetteau says “Finding a common ground between your data team and IT department will undoubtedly ease the process of creating a data product for your organization.  If all of your teams are aligned from the start of a project, each department knows their role and what technologies they are familiar with and specialize in to accomplish the task. Data scientists can build a solution and the IT department can deploy it.   Once a best practices procedure is established it can be reproduced and your organization can more quickly and effectively make use of new predictive data opportunities… making your organization truly agile”

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Manoj Saxena talks Artificial Intelligence with Gigaom fifianahutapea.blogspot.com

Manoj Saxena is the executive chairman of CognitiveScale and a founding managing director of The Entrepreneurs’ Fund IV, a $100m seed fund focused exclusively on the cognitive computing space. Saxena is also a Special Advisor to IBM senior leadership where he focuses on operationalizing IBM’s $100m Watson Cloud Ecosystem Fund and making side-by-side investments with the TEF IV fund.

Saxena is also the chairman of two other startups in the cognitive computing space, WayBlazer and SparkCognition.

Prior to joining TEF, Saxena was general manager, IBM Watson, where his team built the world’s first cognitive systems in healthcare, financial services, and retail. He received the IBM Chairman’s award for Watson commercialization and helped with the formation of Watson Business Group in January 2014 with a $1B investment from IBM.

Saxena will be speaking on the subject of artificial intelligence at Gigaom Change Leaders Summit in Austin, September 21-23rd. In anticipation of that, I caught up with him to ask a few questions about AI and it’s potential impact on the business world.

Byron Reese: How intelligent do you think a computer can become?

Manoj Saxena: I think they can become super intelligent. They already are. In certain areas, they have far exceeded human brain capacity. Now they are super intelligent, they are not super conscious. So I separate intelligence from awareness and consciousness. So I think intelligence is here, has been here for decades. And you know with the advent of cheaper computing power in the cloud and more access to cloud through mobile, I think that intelligence is going to get more and more pervasive and will basically be woven into all aspects of our life. You know, how we work, how we live and how we play is all going to be changed through computer intelligence surrounding us. I actually talked about this notion of as a species Homo Sapiens are dead. Homo Digitus is the future because we will be surrounded by intelligence and amplified and augmented by intelligence.

Do you believe that in AGI, general intelligence is possible to build?

I think it is possible but we are probably at least 40 or 50 years away from it. You know artificial general intelligence which essentially you could argue that you know parts of it. Google, you could argue as the beginning of an AGI kind of like a mega brain or Watson in certain domain is the beginning of an AGI but through AGI covering all forms of human knowledge and human pursuits, I’ve read a study on it that even if you ask the specialist in the AI field, the average response was that we are looking at 2050 or 2060 by the time we will attain AGI. I think the most exciting part is not AGI but ASI, Artificial Specific Intelligence.

How so?

Well I think a little bit of AI can go a long way. There were few big revelations when I was running IBM Watson. First, you don’t need to build an AGI to drive humanity forward or to transform businesses. A little bit of AI when applied to targeted consumer engagement or industry specific business processes can have exponentially huge impact. The second insight I had when I was running Watson is, the real interesting part about AI and machine intelligence is not asking the question of a machine, but it’s the machine telling you what question to ask. You know there is three types of information in this world: there is stuff you know, there is stuff you know you don’t know, and there is stuff you don’t know that you don’t know. The real interesting part of machine intelligence is the third bucket where the machine taps you on the shoulder and says, hey you got to check this out.

I don’t want to get bogged down in definitions or anything, but can you please explain the distinction between machine intelligence, artificial intelligence and cognitive computing?

Yeah. So artificial intelligence is sort of the uber category. Artificial intelligence is like saying ‘software’. It’s the broadest definition which includes multiple types of technologies and techniques: machine learning is one, computer vision is another one, and cognitive computing is yet another one. There are many other types of AI. So at a top level, AI is the super category and then within that, machine intelligence is application of AI where machines start learning and start getting smarter on their own. So it could be a thermostat, it could be a traffic light or it could be a mobile app. Any of these can get smarter. Cognitive computing is that specific part of AI that relates to mimicking the human brain in terms of how we understand, reason, decide, and learn as a human being.

And recently, you know Stephen Hawking has mentioned that AGI may be an existential threat. Elon Musk says things like, maybe we are just a boot loader for the machine intelligence and that’s the next step in evolution. Bill Gates is concerned about what a general intelligence could do. I would ask two questions. One, why do you think that so many obviously very smart people are worried about it and second, do you share that worry?

I think there is some truth to that worry that I share. But I also think there are other scenarios that are in my opinion overhyped and overinflated in terms of machines as the new digital overlords.

[CALL IS LOST. AFTER RECONNECTING:]

My car’s system is kind of acting up here. This is a good example of why I am not too worried about machines being our own overlords because you can’t even get the damn phone to work in your car or your autocorrect to work on your cell phone as someone said. Having said that, today we already are at a point where machines are running our lives. There are millions of us that entrust our lives to computers today by allowing a computer to land our plane and seem very comfortable doing so. And that will slowly expand that we could only get more prevalent as we start giving more and more trust to machines. Robotic surgeries of eyes or blood vessels are other good examples.

On the other hand, there is a lot that we don’t know about how the human brain works and it will be hard to replicate that in a machine. There is much to be learned around our own consciousness, compassion and instincts work for example so in that sense we are very far away from the worry of a new digital race of computers.

What is needed for sure are some general principles and governance by which we as a race put this powerful technology to work for the betterment of society. I am currently engaged in some discussions with industry and local leaders around AI ethics and moral responsibilities to prevent both real and perceived threats from an AI apocalypse.

So what are you trying to do with CognitiveScale?

What we focus CognitiveScale on is deep practical applications of machine learning in industry. So what CognitiveScale builds is the notion of industry digital brains. They have taken AI and applied it into three verticals in commerce, in healthcare and in wealth management. We call it health, wealth and commerce. We are using AI to transform how patients manage chronic conditions and chronic diseases. We are using AI to manage how shoppers are experiencing their journey with the retailer and how financial advisors and investment advice is being delivered to end users. So we focus on transforming the experience of a user through a mobile phone or a browser that creates an experience like that of the traffic and map application Waze.

Waze is a good example of an existing cognitive app. You know it’s an app that is able to source a lot of data both structured data and unstructured data and it’s an app that guides you through the journey and optimizes your experience and outcomes. It knows you, it knows what’s around you and it gets you to your destination in the most efficient fashion. So what CognitiveScale is doing is they are building products for health, wealth and commerce that create a Waze-like experience that lets a patient manage their diabetes or their cancer or their obesity by guiding them through their journey. It lets a shopper manage the journey of shopping for an event and it helps a financial client manage the journey of investment advice because we believe that patient shoppers and financial clients, they all go through a journey and these applications take a regular mobile app and they put a little digital brain behind it and those applications start acting like Waze.

And where are you in your product lifecycle?

CognitiveScale has launched two products. One is called Engage for the customers, the other is called Amplify for business processes. So Engage transforms how a customer experiences the company and Amplify makes every employee your smartest employee. They are about a 100 people and they have been in existence for about 3 years. They have 20 customers and global brands you know everything from Barclays to Nestle to Macy’s to Dow, Eli Lilly, MD Anderson. So they’ve got a tremendous technology and client proof points and have a very strong deal pipeline. Off to a good start but much more needs to be done.

Do you believe that computers will become conscious?

Well yes and no. So, yes but it depends on how you define consciousness. So with consciousness, there are two problems. One is, there is no consciousness detector today. So we don’t really have a model that says, okay what’s the level of consciousness in a particular human being. Now there are some models that are based on anatomy like doctors use to know if you are comatose or not or behavioral people use to figure out whether you are mentally capable or not but there is no proper sort of a continuous consciousness detector that we can use to measure a person’s or a computer’s consciousness or lack of it. So one is a problem of measurement.

And second is a problem of applicability because only, I think, 5% of the human brain is used around consciousness or consciousness-related activities and it may very well be that consciousness may be outmoded and may be outdated by computers that get super intelligent and are able to do tasks much more efficiently and maybe the relevance of what consciousness is needed for is a lot more limiting.

For example, how does it matter for a computer or when does it matter if the computer can sense the pain of a young wife who lost her husband, or if the computer can sense the joy and laughter of a child on a beach, or why someone would throw themselves in front of a running train to save a baby, right? So these are the kinds of things while they are important, they may not be as relevant in the grander scheme of things for the progress of humanity with machine intelligence. So those are the two issues. Therefore, in part yes, you could say the computers will get self-aware but I think unless we have a proper consciousness detector, it will be very hard to formally answer the questions if computers can become conscious.

What is your take on the Chinese room problem, which argues that computers can’t really ever be truly intelligent? [Note, this is a classic argument against the possibility of a general AI put forth by the philosopher John Searle. It is worth looking up in Wikipedia. But the basic idea is that because a computer is completely mechanistic, it simply follows programming. No matter how clever it looks, it doesn’t really understand anything.]

I think there is a lot of truth to that statement as long as you assume that computers are being built on the Von Neumann architecture. Under the present architecture the Chinese room problem that you are talking about is true. You can say the computer is only parsing things together. However, if you look at evolution of quantum computers, [it might be different.] When you ask a current computer what is 1 plus 1, it will get you 2. When you ask a quantum computer what is 1 plus 1, it will take all numbers on the right and all numbers on the left and it will give you all kinds of answers. So it won’t just add up 1 plus 1, it will add up 1 plus 5, five million plus 3 and on both sides and then it picks a particular quantum event. So a lot of theories [suggest] that the human mind is a quantum machine, and that the reason we make connections across things which may not have any logic to it. There is a big stream of expertise and thinking that believes that the human mind operates not like a traditional computer but more like a quantum computer. So if you took that approach then I think the answer could be, ‘yes AGI is possible.’

Great. We’ll leave it there. Thank you for taking the time to talk today.

Manoj Saxena will be speaking on the subject of artificial intelligence at Gigaom Change Leaders Summit in Austin, September 21-23rd.

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Does Blockchain hold the key to the distributed patient data dilemma? fifianahutapea.blogspot.com

By now most readers have probably heard of blockchain through tech blogs and major cover stories from the likes of The Economist over the past year. The financial sector has rapidly accelerated engagement with blockchain through a growing number of consortia and fintech startup initiatives. As the foundation for bitcoin, blockchain’s distributed, cryptographic ledger provides a novel data structure and capabilities that could offer a wide number of benefits beyond existing technologies over the coming decade.

The discourse on blockchain is exploding, as are the critiques. But many of us can’t help but feel that blockchain, in an ever evolving manner, is here to stay and is likely going to become the next layer of the internet that will dramatically improve security of data that is flowing in our transactional economy. Quite simply, we need blockchain’s cryptographic security and distributed data structure to deal with the wealth of data that is coming from the citizen-end of the spectrum.

Not least in the healthcare sector, where patient data is spread across an increasingly fragmented set of repositories. Healthcare’s interoperability challenge may only grow worse for the medium term as the growth of data from beyond the electronic health records (EHRs) due to wearables, smartphone apps and sensors in the home become more mainstream.

We see a number of bottlenecks arising out of this inability to integrate non-EHR data into records and become actionable intelligence for clinicians. This partially accounts for the lack of stickiness of most wearables as the data collected is locked in apps and fails to provide actionable feedback to those whom need it most.

A great deal of health data is locked in silos and under-utilized in both the diagnostic process and more broadly in medical research. Blockchain is one of several solutions that are only going to grow in importance, due to its distributed and traceable nature.

Meanwhile, healthcare is reaching an epic number of data security breaches over the past year including entire hospitals taken hostage by ransomware. With blockchain we may get a twofer by giving patients more control over whom they can share data with in clinical research, for example, while also maintaining higher levels of security.

Blockchain’s smart contract capabilities might also enable sharing economies for medical technology such as MRIs, expensive machinery that sometimes goes idle and could take advantage of the IoT and blockchain and enable new business models around scheduling and local options for consumers.

Blockchain has also recently been used to help fund novel HIV research. UBS, the bank, donated code to Finclusion Systems for a platform that will launch HealBond, a “smart bond” amounting to $10B deployed in a more efficient manner to fund research for HIV cures.

As healthcare slowly enters the API economy beyond siloed EHRs we may eventually see the post-EHR based on distributed databases and more patient-centric controls. Blockchain will likely play a major supporting role in this gradual transition that values data liquidity vs. data capture, patient-centric vs. vendor-centric solutions that we find in our current health IT ecosystem.

This will be good news for consumers and those interested in wellness, but this won’t happen overnight. We may also need to approach blockchain with the openness that typically hasn’t greeted “the new” in technology in the past. Play and experimentation will be needed to change entrenched ways.

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Will the robots take all the jobs? fifianahutapea.blogspot.com

This article is part of a continuing series leading up to Gigaom Change, which will be held in September in Austin, Texas.

Humans have always had a love/hate relationship with labor saving devices. Generally speaking, the owner of the device loves it and the person put out of work by it hates it. This tension periodically takes the form of violent rejection of industrial technology in all of its forms.

The cotton gin “did the work of twenty men” which meant that after it was installed, one fella loved it, but the nineteen newly-unemployed workers probably shook their fists at the infernal gin, wishing all manner of evil to befall that Eli Whitney troublemaker.

While this “technological unemployment” has been cited as the cause of our economic woes for two centuries, the issue has taken on a new since of urgency as their has emerged a general fear that the wave of technical innovation we are currently in will capsize the economy and produce a new category of workers: The permanently unemployed.

Is this another example of the “boy who cried ‘no jobs’?” or are we witnessing a true transformation in our economic world?

The question is fundamentally unknowable because it hinges on three independent factors, each of which is also unknowable.

The three factors are:

1) How many jobs will the robots/AI really take?
2) How quickly will that happen?
3) What new jobs will be created along the way?

Let’s dive in:

The tipping point of widespread permanent unemployment is thought by many to be the driverless car taking all the jobs away from the truck drivers:

Self-Driving Trucks Are Going to Hit Us Like a Human-Driven Truck

One Oxford study claims that 47% of US jobs could vanish in 20 years. While consulting giant McKinsey & Company says 45% of all work activities could be automated right now.

But at the same time, there is a chorus of voices urging calm and pointing out that in spite of radical transformations of virtually every industry, the US has maintained near-full employment. How can this be?

Technology has created more jobs than it has destroyed, says 140 years of data

Two interesting questions that need to be addressed when approaching these issues are:

1) Why are there still good-paying jobs in the West? Why hasn’t mechanization put everyone out of work?

Bring on the robots, please!

2) A century ago, Keynes predicted that in the future, due to labor-saving devices, we will only work 15 hours. Why hasn’t this in fact happened?

How to relax and start loving the robots

The widespread fear of substantial, permanent joblessness has caused the topic of a universal basic income to move to the mainstream. How would this work?

We talked to five experts about what it would take to actually institute Universal Basic Income

Finally, it may simply be that in a post-scarcity world, “working for a living” just doesn’t have the moral imperative that it used to. We might regard what Buckminster Fuller had to say on the topic:

“We should do away with the absolutely specious notion that everybody has to earn a living. It is a fact today that one in ten thousand of us can make a technological breakthrough capable of supporting all the rest. The youth of today are absolutely right in recognizing this nonsense of earning a living. We keep inventing jobs because of this false idea that everybody has to be employed at some kind of drudgery because, according to Malthusian Darwinian theory he must justify his right to exist. So we have inspectors of inspectors and people making instruments for inspectors to inspect inspectors. The true business of people should be to go back to school and think about whatever it was they were thinking about before somebody came along and told them they had to earn a living.”

Robotics, and its impact on business, will be one of seven topic areas covered at the Gigaom Change Leader’s Summit in September in Austin. Join us.

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US Judge confuses privacy and security, concludes that you should have neither fifianahutapea.blogspot.com

Senior U.S. District Judge Henry Coke Morgan Jr. a federal judge for the Eastern District of Virginia has ruled that the user of any computer which connects to the Internet should not have an expectation of privacy because computer security is ineffectual at stopping hackers.

The ruling made on June 23^rd was reached in one of the many cases resulting from the FBI’s infiltration of PlayPen, a hidden child exploitation site on the Tor network. After taking control of the site, the FBI kept it up and running, using it to plant malware on visitors’ computers, gathering identifying information that was used to enable prosecution.

JCM ruled that the FBI’s actions in hacking visitors’ computers did not violate Fourth Amendment protections and did not require a warrant, stating that the “Defendant here should have been aware that by going [on-line] to access Playpen, he diminished his expectation of privacy.”

JCM offered as an analogy a previous case (Minnesota v. Carter 525 U.S. 83 – 1998) which ruled that a police officer looking through broken window blinds does not violate anyone’s Fourth Amendment rights, so hacking a computer does not either.

“Just as the area into which the officer in Carter peered - an apartment - usually is afforded Fourth Amendment protection, a computer afforded Fourth Amendment protection in other circumstances is not protected from Government actors who take advantage of an easily broken system to peer into a user's computer. People who traverse the Internet ordinarily understand the risk associated with doing so.”

JCM notes that in 2007 the Ninth Circuit found that connecting to a network did not eliminate the reasonable expectation of privacy in one’s computer, but takes the position that in the last nine years things have changed enough to render this position outdated.

“Now, it seems unreasonable to think that a computer connected to the Web is immune from invasion. Indeed, the opposite holds true: in today's digital world, it appears to be a virtual certainty that computers accessing the Internet can - and eventually will - be hacked.”

As justification for this opinion, JCM cites the Ashley Madison hack and a Pew Research Center study on privacy and information sharing as evidence of the acceptance that hacking is inevitable. The Pew study looked at American’s attitudes to sharing personal information in return for receiving something of perceived value. Although the focus of the Pew report was on privacy and not security it did report that focus group participants “worried about hackers”. However, these concerns were expressed exclusively in terms of a hacker’s ability to gain access to personal data from compromised business computer systems, not personal systems in the home.

Judge Coke Morgan’s level of technical understanding appears to be highly selective. The same judge who ruled on a patent case between Vir2us, INC. and INVINCEA, INC. over competing claims covering advanced anti-malware products, fails to acknowledge that anti-malware products continue to advance. In offering that “Terrorists no longer can rely on Apple to protect their electronically stored private data, as it has been publicly reported that the Government can find alternative ways to unlock Apple users’ iPhones.” He ignores the level of expertise needed to identify the exploit that was used to access the phone used by one of the San Bernardino attackers, or that the hack in question was only applicable to the now superseded iPhone 5C. While it may be possible to unlock older iPhones running back-level OS releases lacking the most up-to-date security features, Apple continues to develop new hardware-based security features and works to fix security vulnerabilities as it finds them. While it is reasonable to claim that many computers are vulnerable to attack, in suggesting that this means it is “a virtual certainty that [all] computers accessing the Internet can – and eventually will – be hacked” or that there is nothing that can be done to mitigate this risk, JCM is either being deliberately disingenuous or is failing in his analysis.

Describing the ruling as “dangerously flawed” EFF Senior Staff Attorney Mark Rumold wrote “The implications for the decision, if upheld, are staggering: law enforcement would be free to remotely search and seize information from your computer, without a warrant, without probable cause, or without any suspicion at all.” But holds out that the ruling is “incorrect as a matter of law, and we expect there is little chance it would hold up on appeal.”

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