CTOvision.com

Context for the CTO, CIO, CISO and Data Scientist

Our Latest Posts

Funny But Sad: Survey shows most people know nothing about technology

Dear CTOvision readers. You know we love you and I hope it doesn’t seem like I’m pandering to you when I say you are the smart ones who will lead us all to a better/brighter future. I have always believed that and now I have some statistics that back this up.

The stats below are from a somewhat unscientific survey. The coupons website Vouchercloud.com  published a study that showed 2,392 men and women a series of technical and non-technical terms and then were asked to pick from three possible definitions.

Here are some of the results of this survey:

  • 11% believed that HTML is a sexually transmitted disease.
  • 27% believed that a gigabyte is an insect in South America
  • 23% thought that MP3 is a robot found in Star Wars
  • 15% said that software is comfortable clothing
  • 12% believe that USB is an acronym for a European country
  • 18% believe that Blu-ray is a marine animal
  • 42% thought that a motherboard is the deck of a cruise ship.

The good news is that 61% signaled that they believe having a good knowledge of today’s technology is important.

Do I believe this survey? Not really. The results are probably in part due to people giving flippant answers while trying to quickly click through a survey. But hey we technologists need to laugh too so I wanted to share it. And it is a good excuse for me to say something I really believe. CTOvision readers are smarter than most everyone else.

For more see: VoucherCloud Study

Analysts, Tools, and Complexity

complexityCTOs and analysts of all stripes know that understanding the problem they are trying to solve should precede selecting analytical tools. Yet this is far more difficult than it seems, particularly as the variety of problems we come across multiply. One of the major stumbling blocks for analysis in particular is terminological fuzziness. We often (wrongly) treat terms like “uncertain,” “difficult,” and “complex” as interchangeable — when, as economist Scott Page points out, the differences between them are instructive. Page has a useful distinction between all of these that can help us match tool to problem. And by going through his schema, I hope to convince you that there may be more possible dimensions to analytics than tools fielded by current market leaders imply.

Say we have a problem that involves trying to find the best solution from a range of alternatives. Are we able to consider each solution simultaneously and rank them? If so, analysis should be simple — with one gigantic caveat. Generally, the problem here is uncertainty about the solutions themselves. We have a state of belief about what to do, but are we sure we correctly understand the nature of the solutions? In this situation, the best thing to do is to gather more information about the problem and potential solutions. Tools that help reveal patterns, connections, and inferences make the choices we face seem much less daunting, particularly when they can ingest and analyze large and/or unstructured data and guide our intuition.  And contrary to Chris Anderson’s famous column, it’s here where computational tools most approximate the traditional idea of the scientific method. We have a defined question, we want to test the potential explanations/solutions, and we use tools to investigate. When we get the information we need, we’re that much closer to making the right choice. We can’t completely eliminate uncertainty about explanations/alternatives, but we can at least reduce it.

What if the problem is too many potential solutions to evaluate at once? Then it becomes a question of difficulty. Here we move more to the algorithmic and artificial intelligence-centric aspect of analytical tools. With a defined problem, problem function to optimize, and set of problem constraints, we search a solution space in a structured manner with algorithms that will find the best solution and prune away ones we don’t want.  When tractable, these problems take the form of things like the classic Knight’s Tour problem solved with divide-and-conquer algorithms. Often we’ll have to rely on problem-specific heuristics to either find a solution (admissible heuristics) or at least find it some of the time (inadmissible heuristic). Many real-world problems outside of computer science textbooks require algorithms that make very little assumptions about the nature of the problem.  These are all usually combinations of random search of the solution space and iterative hill-climbing/improvement towards better solutions.  Some academics within my school (George Mason University) have developed useful tools for deploying these metaheuristic algorithms to solve problems.

Before I continue, I’d like to make the point that both of these formulations of the problem makes one big assumption about the problem: the fitness landscape of potential solutions is fixed. Peaks and valleys don’t really change too much. For example, say the company is uncertain about what market to choose in the first example. It has some some rough ideas to evaluate, and it uses data science tools to gather information on the problem. The decision is made, and then it’s on to the next problem. Or perhaps a government agency is having a difficult time finding the best way to deal with an job shop scheduling problem. It uses Ant Colony Optimization to find an acceptable answer.  Sure, the problem itself may change, requiring either information-gathering or solution search to be redone. But we can find optimal or at least satisfactory solutions for discrete instances of each problem as they come.

The last kind of problem, however, is very different. Here the problem isn’t really that we have a lack of information or that moving through the range of options is very difficult. Consider that every year, you have to organize a family gathering. Different groups of your extended family have varying preferences about where to go. You have to find a destination that satisfies them all. Unfortunately, each previous vacation (and their level of satisfaction with it) influences their preferences in the current planning round. If your cousin Frank didn’t like the last choice, he’ll be that much more likely to dislike your current idea. To make matters worse,  maybe there was something about the last vacation that put Frank and your wife’s sister Paula at loggerheads, souring both on the previous vacation simply because it caused a flare-up. Whether or not you make a good choice is dependent on whether or not you can predict something the family aggregate will like.

There’s so many dimensions to the problem, and what qualifies as a good solution evolves in time. There’s also a high degree of randomness involved — there are obviously qualitative patterns that re-occur in your vacation satisfaction outcome, but sometimes there can be instances where the outcome is a complete surprise. And because each variable in the problem is so highly interconnected, there may be unintended consequences to seemingly benign choices. You have a feeling that there are a couple of key dynamics driving the problem. It could be, for example, that your in-laws and your side of the family have a finite tolerance for how long they interact with each other, and that a  resort/cruise vacation creates a situation that pushes them beyond their maximum tolerance level. You may not be able to increase their tolerance for each other, but you could design a vacation that doesn’t, more often than not, push them past a critical tolerance value. Don’t put them on a cruise ship, maybe give them more free time so they won’t see each other as much. But how would you find that out?

I spend a lot of time on this precisely because this is a kind of problem that standard conceptions of analytic decision tools often neglect. What you really need is a way to experiment on the problem. You could collect a lot of data and discover some interesting patterns that would tell you what kinds of outcomes you want to explain. But what you need is a way to experiment to figure out combinations of variables are causing the patterns and how altering some parameters might change the way the problem evolves. And since there isn’t necessarily a hard dependent variable –> independent variable setup, you have to think about multi causal dynamics and relationships. You could conduct some experiments, but the family fights that might result could leave you sleeping on the couch for the foreseeable future.

CTOs and analysts should look more at tools like NetLogo and other lightweight simulation environments that can easily and intuitively demonstrate dynamics of problems. These tools can be calibrated to existing data and validated against the observed patterns (like, for example, the aggregate vacation satisfaction levels). These tools, however, require some programming knowledge and lack the point-and-click usability of data science tools produced by companies like the many we track here at CTOvision (see our special report on analytical tools). What would make a difference, as my GMU colleague David Masad argues, would be modeling tools that could ingest large quantities of data, run algorithms, and automatically generate a model environment and detailed behavior specifications. That way, model behavior would be automatically calibrated to data and decision makers could just play around with model settings and see what happens.

The academic and research communities currently have the tools to deal with complex problems. But while the analyst community has tools to deal with uncertainty and difficulty, integrated and user-friendly tools to deal with complexity are far and few between. The company that produces tools capable of combining all three problem-solving methods — reducing uncertainty with knowledge discovery, finding optimal model behaviors and settings by cutting through difficulty, and allowing decisionmakers to explore and experiment on complexity — could very well produce the analyst community’s killer app.

DARPA Official: Human-Robot Teams Key to Disaster Response

DARPA is advancing the science of robot-human teams that can be deployed to respond to natural disasters and other events deemed too dangerous for first responders.

from American Forces Press Service News Feed

DARPA Official: Human-Robot Teams Key to Disaster Response

By Cheryl Pellerin
American Forces Press Service

WASHINGTON, Feb. 6, 2014 – In the future, when an earthquake or tsunami strikes a populated area or a terrorist attack decimates a city, teams of disaster experts partnered with robots — whose skills are being honed in rigorous competitions funded by the Defense Advanced Research Projects Agency — may be the first responders.

Launched in October 2012, the DARPA Robotics Challenge has held two of three competitions -– a virtual event in June 2013 and a live two-day event held Dec. 20-21 at the Homestead-Miami Speedway in Florida.

The first competition tested software teams’ ability to guide a simulated robot through three sample tasks in a virtual environment. In December, teams had to guide their robots through as many as eight individual physical tasks that tested robot mobility, manipulation, dexterity, perception and operator-control mechanisms.

During the finals, to be held sometime in the next 12-18 months, human-robot teams will attempt a circuit of consecutive physical tasks with degraded communications between the robots and their operators. The winning team will receive a $2 million prize.

“Over a period of less than three years,” program manager Dr. Gill Pratt wrote in the January-February edition of The Bulletin of Atomic Scientists, “DARPA expects the field of robotics to undergo a historic transformation that could drive innovation in robots for defense, health care, agriculture and industry.”

Pratt has a doctorate in electrical engineering and computer science from the Massachusetts Institute of Technology and is a professor at the Franklin W. Olin College of Engineering in Needham, Mass. He’s also the DARPA Robotics Challenge program manager in DARPA’s Defense Sciences Office.

Having people and robots work together in teams is essential to robot success in disaster response, Pratt told American Forces Press Service during a recent interview at DARPA headquarters in Arlington, Va.

“For the foreseeable future, our robots are not going to have anywhere near the intelligence they require to do even small parts of missions on their own,” he said. “They’re going to require a human being to figure out what the plan is, to figure out what the contingencies are [and] to understand the situation.”

What robots can do, Pratt explained, is contribute sensing and physical effects at a distance from a human controller, operating in a dangerous environment while a human operator stays back where it’s safe and directs the action.

“Together, working as a team,” he added, “they can be more effective than either one of them working by themselves.”

DARPA officials know this from their own experiences.

In the days after 9/11, DARPA sent to New York City robots whose development the agency had funded. But those robots found no survivors, Pratt recalled in an analytic piece published Dec. 3 in The Bulletin of Atomic Scientists.

DARPA tried again in March 2011 in the deadly aftermath of a magnitude 9.0 earthquake centered 81 miles off the coast of the city of Sendai on the eastern coast of Honshu Island, Japan.

A subsequent 49-foot tsunami killed more than 19,000 people, destroyed or damaged more than a million buildings and shut down power in and flooded Tokyo Electric Power Co.’s Fukushima Daiichi nuclear plant, melting the reactor cores of operating units 1, 2 and 3, and damaging unit 4.

Japanese officials declared a nuclear emergency later that day and evacuated people initially within 1.2 miles of the plant and later within 12 miles.

Humanitarian assistance and disaster relief is a primary DOD mission, Pratt wrote in the Dec. 3 Bulletin, and as the disaster unfolded in Japan, “DARPA officials contacted researchers who had designed robots for the Three Mile Island and Chernobyl disasters and coordinated with companies that DARPA had funded to develop other robots.”

Each company already was making plans to send its robots and training personnel to Japan, he added, and others around the world sent robots as well, but it took weeks for power-plant personnel to complete training they needed to operate the robots.

By then, Pratt said, “the golden hours for early intervention to mitigate the extent of the disaster had long since passed.”

Even with progress made in the DARPA Robotics Challenge and elsewhere in the industry, Pratt said, “We don’t know how to make [robots] intelligent enough to do sophisticated tasks, [but] we do know how to make them do … very specific subtasks.”

These days in a laboratory, he explained, a robot can be told to open a door and the robot will use its visual sensors to locate the door, compare that image against a library of different handles it’s been programmed to recognize, turn the door handle and pull the door open.

“At the DARPA Robotics Challenge, we were trying to be successful with that out in the field, where lighting conditions are varied, where the location you’re looking at the door from changes all the time, there are shadows, there are other things in front of the door,” Pratt said. “We were trying to make it robust to all those changes, and that’s really where the state of the art is now.”

Most of the challenge tasks were on a slope that started out easy and went to medium and then hard, he said. The challenge began with 16 robot teams and ended with eight robot teams qualifying to receive DARPA funding for the finals event.

Pratt said most differences seen in the robots’ performances were differences of software capabilities. But it wasn’t that the robot hardware was more capable in some cases, he said, adding that most of the robots were quite good at the tasks “and, in fact, did better than we had expected them to.” The software differentiation was mostly in how well the teams handled the communications degradation inserted into the challenge, Pratt said.

“Some teams did very well and [their] robot had enough subtask autonomy that it was able to do some meaningful work while communications was poor. Other teams … could only really control the robot well when the communications quality was higher,” he explained.

“The key to robustness is feedback, and the key to feedback in a robot is the ability to perceive the environment well,” Pratt said.

Looking toward the DARPA Robot Challenge finals, Pratt said, officials learned in the December trials that the robots were about 20 percent more capable mechanically than expected, so they will raise the bar accordingly for the finals.

The plan is to make the tasks more difficult and more authentic than they were in the trials, he said.

“My thought right now, and this is subject to change,” Pratt added, “is [to] take the eight different tasks we had as separate events in the trials and … combine them into an integrated task where the robot has to respond to a situation,” chaining together capabilities it demonstrated in the trials.

Finals officials will tell the teams much less than they were told before the trials so the setup will be a surprise to all entrants. And Pratt said they’re planning to degrade communications more than they did during the trials.

“We’re going to have the comms go black and dead for significant lengths of time and … see whether the robots can continue to execute some of these subtasks on their own … because we know those kinds of dropouts are quite common in the austere environments we care about,” he said.

Also in the finals, the robots won’t use safety harnesses as they did in the December trials.

“If the robot falls down, it must first not be damaged so badly that it can’t continue to work,” Pratt said. “But even more difficult, it needs to be able to get itself back up, even if it falls down on rough terrain. We think those behaviors are absolutely essential for true work in austere environments.”

DARPA officials aren’t sure yet what the finals scenario will include, but it will focus more on disaster response than on trying to save injured people.

“Trying to affect the properties so the disaster doesn’t get worse is part one, trying to save human beings who are hurt or even recover them if they were killed is part two, and part three is how to remediate the disaster and make the site good again for use,” he said. “The DARPA Robotics Challenge is really focused on the first one.”

Pratt said DARPA expects roughly a dozen teams to participate in the finals, including the top eight teams from the December trials that are in contract negotiations with DARPA to receive $1 million for development this year, and other teams from around the world that will fund their own software development.

After the finals, when the winner walks away with $2 million, the technology still won’t be quite ready for commercialization.

“The technology will be ready for commercialization if a market can be found in the commercial world for it,” Pratt said. “What many people don’t realize is that the defense market is a very small fraction of the size of the commercial market.”

He added, “After we show the feasibility of things, after we provide the spark to start it, then we need to enter a phase where the costs get driven down. And the commercial world typically is very, very good for that.”

MegaTrend Update: Dramatic and broad shifts in models due to software ("software eats the world")

We have been tracking this since Marc Andreessen called the trend out in 2011 (see “Why Software is Eating the World“) and are especially interested in how the trend will impact the world of the enterprise.

We think this trend will continue, since it is being fed by growing proliferation of smart phones with increasingly powerful processors and faster/more reliable bandwidth. Penetration of the trend into other industries will threaten many business models. Who is next? Seems like education. Then healthcare. Then perhaps the government contracting world (we have previously written about software eating the government contracting world and DoD command and Control). We will keep tracking these trends.

What industries are being consumed by this trend? Here is a list:

Domain

Examples

Books

Amazon

News

Google, Twitter, Facebook,

Sales

eBay, Craigslist

Telecom

Skype

Entertainment

Netflix, iTunes, Spotify, Rovio

Recruiting

LinkedIn

IT Infrastructure

Amazon, Google, Microsoft, IFTTT

Business Software

Salesforce.com, Privia

Marketing

Google, Groupon, Foursquare

Knowledge

RapGenius

Robotics

Anki

A full list of what we regard as the most virtuous and disruptive technologies in enterprise IT is available at our CTOvision Company Guides.

Other Resources:

How Google Fiber Could Upset The Entire Broadband Industry

Gain Decision Advantage With Innovative Enterprise Software

 

The Guide To Professional Hadoop Solutions For The Enterprise

hadoopsolutions I’ve known Kevin Smith of Novetta Solutions for years and have been a huge fan of both his ability to write about technology and his ability to field enterprise grade solutions that really work. He knows real enterprise solutions require focused planning, solid designs and an attitude of enterprise-focused teamwork. He is the kind of author that writes well because he writes frequently and writes relevant because he fields real solutions.

This makes anything Kevin collaborates on to write a good project. His latest book is written with Boris Lublinsky (principle architect at Nokia and author of 70 other publications) and Alexey Yakubovich (a Hadoop architect). Together they have collaborated on “Professional Hadoop Solutions“, a great “how-to” book and guide for the systems architect.

I am particularly impressed with the security chapter of this book. There are many challenges in the security environment related to Hadoop deployments and it is important for architects to know both the history and status of core Hadoop in this regard. There are configuration steps that can be taken that greatly reduce security risks and this book can guide you through ways to optimize your clusters in this regard. For those requiring real industrial strength security you will want solutions like Sentry on the latest distribution from Cloudera as well as their enterprise management tools and of course commercial support. But if you are just looking to scope out the kinds of issues you will need to deal with you will find a great introduction to security in this book.

My recommendation: Add Professional Hadoop Solutions to your library. It is a great read that will give you lots of food for thought and help you speed your deployment.

Related Reading:

CTO Guide to the Business of Artificial Intelligence

CTOvision Guide To The Cybersecurity Technology Marketplace

Why Cybersecurity is Looking to AI to Mitigate Business Risks

Working in Cybersecurity: Life on the front lines, in the C-suite, and everywhere in-between

The Need for A Strategic Pivot in DoD R&D

This CTOvision Pro produced analysis focuses on the technological needs for DoD in order to ensure a modern infrastructure while enhancing DoD ability to defend itself. It specifically calls for a shift in R&D spending in DoD.

The Need For A Strategic Pivot in DoD R&D: A concept piece for enhancing DoD cyber security posture

Speeding technology acquisition is a key goal of the department’s “Strategy for Operating in Cyberspace” and we found strong support for this tenant throughout our study.  There is wide-spread agreement that technology innovation is at the forefront of national security and that DoD must enhance its ability to speed its acquisition processes, especially in support of cyber operations. We have found, however, a significant difference in what is being called for in technology innovation and what is being done. The department is investing R&D in cyber projects for defense and offense, but these activities too frequently assume a high degree of customization will be allowed before systems will be fielding into DoD. This runs contrary to the stated cyber strategy, which seeks to replicate the dynamism of the private sector to harness the power of emerging computing concepts. DoD must be willing to sacrifice and defer customization to achieve speedy incremental improvements. Remaining wed to expensive long-term customization activities is a key reason why much of the department still operates on an operating system that is over a decade old and now unsupported by the vendor community. We believe a strategic pivot of DoD R&D spending on IT can mitigate this and other weaknesses and turn our IT infrastructure into a much more resilient one.

 

The Pivot: Shift Cyber R&D To The Tracking And Influencing Of Commercial IT.

The information technology in use in DoD today is based on commercial off the shelf IT. Commercial IT is now in use globally, and it is also produced globally. It ubiquitous, intertwined, and so powerful and contributes so much to humanity that it is being invested in and improved upon everywhere. IT is no longer solely under the control of any one organization or even any one nation. The globe’s IT is moving by autonomous market driven forces and an advancement of science.

This means a system of techno-assemblages so complex that no one individual or group could possibly understand and never control is now forming the basis of DoD’s infrastructure. Enhancing our trust in our IT and mitigating threats to resilience will require new approaches. No longer can we invest as if we can shape an understandable stand-alone system that can be evaluated in isolation. We must invest in ways that recognize the limits of our influence and focus on those prioritized factors we can change.

This calls for a pivot in our cyber related R&D. We must pivot our R&D to raise our awareness of where the cyber market is going and focus investment on the things we can influence.

 

We Recommend the Following Guidance in Execution of this Pivot:

Technology developments, including developments in Hardware, Software, and Concepts, are moving so fast that a greater apportionment of resources must be spent on tracking both the capabilities of existing IT and the mega trends of the IT industry. Under existing policies and acquisition regulations, procurements are to be conducted in ways that take into account “market assessments” but in practice it has become impossible for any procurement official to understand current capabilities in the IT marketplace, let alone coming changes to the market. It has become intractable to optimize evaluations of engineering trades in procurements. Traditionally R&D is focused on creating capabilities far into the future but pivoting to studies closer to the present will aid in the continuous procurement decisions DoD professionals must make every day. Additionally, R&D focused on IT mega trends that we can hardly influence will also inform procurement strategies and decisions since items being planned for today must be relevant and resilient in a future being impacted by these mega trends.

R&D should also accelerate our wisdom on creation of new solutions from existing hardware and software. This is a pivot from an approach that seeks to focus R&D on creation of new hardware and software. The pivot is towards influencing things we can influence. For example, our study revealed eight new technology requirements that we believe will make significant, positive change in the resilience of DoD systems, and each of these eight could be more rapidly fielded by R&D focused on development of systems based on existing IT. None of the below require new science. All can be based on capabilities the IT industry provides today.

Technology

Benefit
Cyber “Thin Line” providing survivable out of band C2 including ability to reach into IT industry while in attack Enhanced deterrent, resiliency, recovery
Non-signature based detection of threats Detect while under attack vice after
Secure collaborative environments with visualizations spanning all cyber mission areas Link communities of interest together enabling more rapid coordination of action
M&S tools for cyber mission rehearsal, exercise planning, mission planning Enhanced mission effectiveness
Enhanced COA development, BDA, Situational Awareness and C2 tools Enhanced mission effectiveness
Enhanced Root of Trust, including purge to zero state and BIOS attestation Increased system resiliency, recovery, restoration after attack
Integrated Automation Suites including continuous vulnerability assessment and mitigation Support to automated hygiene, enhanced defense and more rapid restoration after attack.
Technology for cyber audit and forensics, including reverse engineering tools Assessment of damage from attacks and continuous hygiene monitoring

 

More CTOvision Reporting:

For more on these topics see the CTOvision Guide to National Security Technology and

Haystax Technology (@HaystaxTech) Names Advisory Board Members (including @BobGourley and @BobFlores)

Editor’s note: I’m very proud to be serving on the Haystax Technology advisory board. This firm is absolutely one to watch. For more see Haystax – bg

Haystax Technology Names Advisory Board Members

Six Advisors with Defense, Intelligence and Commercial Experience to Deliver Strategic Guidance to Haystax

McLean, VA – January 14, 2014 – Haystax Technology, Inc. today announced its strategic advisory board members. The members include top executives from AEG Worldwide and Lockheed Martin Corp., and high-ranking former officials from government organizations, including the Central Intelligence Agency (CIA), Defense Intelligence Agency (DIA), Department of Defense (DoD), Department of Homeland Security (DHS), National Geospatial-Intelligence Agency (NGA) and National Security Agency (NSA).

“Our goal is to create a world-class advisory board that provides unparalleled strategic guidance for Haystax,” said Haystax Technology CEO William Van Vleet III. “The panel delivers expertise and leadership in the defense, intelligence, military and commercial arenas that will enable Haystax to gain insights into its customer base and fine-tune product and service offerings. Haystax is honored and pleased to have our advisors join our integrated team, and we are looking forward to their counsel and contributions.”

The new advisory board members include:

• Matt Bettenhausen, Vice President and Chief Security Officer (CSO) for AEG Worldwide. Bettenhausen has overall responsibility for security, public safety and preparedness for the domestic and global operations and facilities of AEG, a leading sports and entertainment presenter. AEG that is affiliated with more than 100 of the world’s preeminent facilities, including the STAPLES Center (Los Angeles), Sprint Center (Kansas City, Mo.), Best Buy Theater (New York City), and the Target Center (Minneapolis). Previously, Bettenhausen served as director of the California Office of Homeland Security and Homeland Security Advisor to Gov. Arnold Schwarzenegger, where he was responsible for developing and implementing a statewide strategy to prevent terrorism and prepare for all potential hazards facing California. He has held a number of senior leadership positions with national and state organizations, such as the chair of both the National Homeland Security Consortium and National Governors Association’s Homeland Security Advisors Council, as well as vice president of the National Emergency Managers Association.

• Bob Flores, Founder and President, Applicology Incorporated. Prior to starting Applicology, an independent consulting firm specializing in informatics and cyber security issues, Flores spent 31 years at the CIA where he held various positions in the Directorate of Intelligence, Directorate of Support, the National Clandestine Service and the Office of the CIO. He also was a representative on several government-wide information sharing committees and councils; and was assigned line and staff management roles in applications programming, training and education, contract and program management. He completed his career as the CIA’s CTO, where he was responsible for ensuring that the agency’s technology investments matched the needs of its mission.

•Crucial Point CTO Bob Gourley  Founder and CTO, Crucial Point LLC. Gourley founded Crucial Point, a technology research and advisory firm providing fact-based technology reviews in support of governments, venture capital, private equity and emerging technology firms. He also serves as editor of CTOvision.com, an award-winning technology blog. As a former CTO for the Department of Defense Intelligence Information System (DoDIIS), Gourley was responsible for establishing and overseeing enterprise wide technology decision-making processes. He provided technical and operational advice and senior technical review regarding DIA and DoDIIS information architectures, data processing, IT systems, applications, networks and communications. He served as the CTO for the DIA, leading its strategic engagements with industry, venture capital and academia. He is a board member for a number of industry and government organizations and is a participant in the National Security Agency Advisory Board (NSAAB) Emerging Technologies Panel.

• Peter Marino, former President and COO, Lockheed Electronics Co. Inc. and Fairchild Industries Inc. Marino has extensive experience in both government and private industry. In the government he held a number of senior positions over nearly 20 years with the CIA. Upon leaving the government he served as president and COO of both Lockheed and Fairchild; senior vice president of E-Systems, Inc.; CEO and president of Fire Arms Training Systems; and senior advisor at Morgan Stanley. Marino serves on 7 corporate boards and chairs 3 of them, including as an advisor for the Office of the Director of National Intelligence, DHS, Department of Defense (DoD), CIA, National Geospatial-Intelligence Agency (NGA), National Reconnaissance Office and the CIA’s Senior Advisory Group. He is on the Defense Science Board on ISR, is a principal of The Center for Excellence in Government, chaired The Congressional Commission on the National Imagery and Mapping Agency, and is a senior executive Fellow at Harvard University.

• Lieutenant General (RET) Richard Zahner, former Deputy Chief of Staff for Intelligence, Department of the Army. LTG(R) Zahner is a retired military intelligence professional with service in a number of senior Defense, Joint and Army leadership positions over a thirty-six year career. His last assignments included Director, Signals Intelligence for the National Security Agency; Deputy Undersecretary of Defense (Joint and Coalition Warfighting Support) and Director, ISR Task Force for the Office of the Secretary of Defense; and the Army’s Deputy Chief of Staff for Intelligence. LTG Zahner is a member of a number of boards, including the Technology Directorate Panel of a major element of the intelligence community Advisory Board.

About Haystax
Haystax Technology, Inc. provides next-generation products, systems and service solutions to sift, refine and analyze large, disparate and unstructured volumes of data to reveal undiscovered connections and enable precise, actionable intelligence for government and commercial market clients. In essence, these technologies allow users to find “the needle in the haystack” quickly and reliably. For further information about Haystax Technology, visit www.haystax.com

Media Contact:
Laura Taylor
202-271-8216
laura@gaiapr.com

###

Google Glass and National Security Missions

At this link and at the clip embedded below I capture some thoughts regarding Google Glass and national security missions.

http://www.youtube.com/watch?v=pZeqhhKAP9E

Do you have ideas/thoughts/suggestions relevant to this discussion? I would love your feedback via any channel convenient to you, including of course your social media account (we are at Google+/Facebook/LinkedIn/Twitter).  I would especially appreciate your views on how privacy can be enhanced in an age of ubiquitous wearable high res photo and video and audio devices. As for me I have not seen satisfactory solutions or event thoughts for how we citizens can optimize any remaining privacy we have in public places in this new technological world. What about you? any thoughts?

Other Reading of interest:

Apple’s AR Glasses Could Transform Multiple Industries

After another massive Google+ data breach, you should probably delete your profile right now

 

More Content

Cyber War

SciFi

Super Bowl Ads Indicate Big Businesses Think You Are Afraid of AI

Tom Loftus provided an insightful review of some of Super Bowl ads in the 4 Feb 2019 Wall Street Journal. Like AI parody in SNL, these ads really poked fun at computers: Seriously, did anyone catch the commercials? If the Super Bowl is the zeitgeist, then it is safe to say that America is not […]

HBO’s Westworld: The Man In Black is a special kind of Twitter user

HBO’s Westworld is a modern take on the Michael Crichton SciFi tale of a robotic amusement park. The HBO version has a new twist. The creators/writers were all exposed to years of Twitter, which has influenced every episode and the entire arch of two seasons of the show. Now that season two is wrapping up, […]