Robots on the road

Just heard that California is about to start working on formal regulations for robot cars to travel their roads which is the second state to regulate these autonomous machines, the first was Nevada.  At the moment the legislation signed into law requires CA to draft regulations for these vehicles by January 1, 2015.

I suppose being in the IT industry this shouldn’t be a surprise to me or anyone else. Google has been running autonomously driven vehicles for over 300K miles now.

But it always seems a bit jarring when something like this goes from testing  to production, seems almost Jetson like.  I remember seeing a video of something like this from Bell Labs/GM Labs or somebody like that when they were talking about the future way back in the 60s of last century.  Gosh only 50 years later and its almost here.

DARPA Grand Challenges spurred it on

Of course it all started probably in the late 70s when AI was just firing up.  But robot cars seemed to really take off when DARPA, back in 2004 wanted to push the technology to develop a autonomous vehicle for the DOD. They funded a and created the DARPA Grand Challenge.

In 2004 the requirements were to drive over 150 miles (240 km) in and around the Mojave desert in southwestern USA. In that first year, none of the vehicles managed to finish the distance.  Over the next few years, the course got more difficult, the prize money increased, and the vehicles got a lot smarter.

In 2005 DARPA grand challenge once again a rural setting, 5 vehicles finished the course 1 from Stanford, 2 from Carnegie Mellon (CMU), 1 from Oshkosh Trucking, and the other 1 from Gray’s Insurance Company.  At first I thought an insurance company, then it hit me maybe there’s a connection to auto insurance.

DARPA’s next challenge for 2007 was for an urban driving environment but this time  DARPA providing research funding to a select group as well as larger prize to any winners.  Six teams were able to finish the urban challenge, 1 each from CMU, Stanford, Virginia Tech, MIT, University of Pennsylvania & Lehigh University and Cornell University.  That was the last DARPA challenge for autonomous vehicles, seems they had what they wanted.

Google’s streetview helped

Sometime around 2010, Google started working withg self-driving cars to provide some of the streetview shots they needed.  Shortly thereafter they had  logged ~140K miles with them.   Fast forward a couple of years and Google’s Sergey Brin was claiming that people will be driving in robotic cars in 5 years. To get their self-driving cars up and running they hired the leaders of both the CMU and Stanford teams as well as somebody who worked on the first autonomous motorcycle which ran in the Urban Challenge.

For all of the 300K miles they currently have logged, the cars were manned by a safety driver and a software engineer in the car, just for safety reasons.  Also, local police were notified that the car would be in their area.  Before the autonomous car took off another car, this one driven by a human, was sent out to map out the route in detail including all traffic signs, signals, lane markers, etc.  This was then up(?) loaded to the self-driving car which followed the same exact route.

I couldn’t find and detailed hardware list but Google’s blog post on the start of the project indicated computers (maybe 2 for HA), multiple cameras, infrared sensors, laser rangefinders, radar, and probably multiple servos (gear shift, steering, accelerator and brake pedals), all fitted to Toyota Prius cars.  Although the servos may no longer be as necessary as many new cars, use drive by wire for some of these function.


I could imagine quite a few ways to monetize self-driving, robotic cars:

  • License the service to the major auto and truck manufacturers around the world, with the additional hardware either supplied as a car/truck option (probably at first) or provided on all cars/trucks (probably a ways down the line).
  • Cars/trucks would need computer screens for the driving console as well as probably for entertainment.  Possibly advertisements on these screens could be used to offset some of the licensing/hardware costs.
  • Insurance companies may wish to subsidize the cost of the system.  Especially, if the cars could reduce accidents, it would then have a positive ROI, just for accident reduction alone, let alone saving lives.
  • In the car internet would need to be more available (see below). This would no doubt be based on 4G or whatever the next cellular technology comes along. Maybe the mobile phone companies would want to help subsidize this service, like they do for phones, if you had to sign a contract for a couple of years. I am thinking the detailed maps required for self-driving might require a more bandwidth than Google Maps does today, which could help chew up those bandwidth limits.
  • With all these sensors, it’s quite possible that self-driving cars, when being driven by humans, could be used to map new routes.  If you elected to provide these sorts of services then maybe one could also get something of a kickback.

I assume the robotic cars need Internet access but nothing I read says for sure. Maybe they could get by without Internet access if they just used manual driving mode for those sections of travel which lacked Internet  Perhaps, the cars could download the route before it went into self-driving mode and that way if you kept to the plan you would be ok.

Other uses of robotic cars

Of course with all these Internet enabled cars, tollways and city centers could readily establish new congestion based pricing.  Police could potentially override a car and cause it to pull over, automatically without the driver being able to stop it.  Traffic data would be much more available, more detailed, and more real time than it is already.  All these additional services could help to offset the cost of the HW and licensing of the self-driving service.

The original reason for the DARPA grand challenge was to provide a way to get troops and/or equipment from one place to another without soldiers having to drive the whole way there.  Today, this is still a dream but if self-driving cars become a reality in 5 years or so, I would think the DOD could have something deployed before then.


If the self-driving car maps require more detailed information than today’s GPS maps, there’s probably a storage angle here both in car and at some centralized data center(s) located around a country.  If the cars could be also used to map new routes,  perhaps even a skosh more storage would be required in car.

Just imagine driving cross country and being able to sleep most of the way, all by yourself with your self-driving car.  Now if they could only make a port-a-potty that would fit inside a sedan I would be all set to go…, literally 🙂


Image: Google streetview self-driving car by DoNotLick


VMworld first thoughts kickoff session

[Edited for readability. RLL] The drummer band was great at the start but we couldn’t tell if it was real or lipsynched. It turned out that each of the Big VMWORLD letters had a digital drum pad on them which meant it was live, in realtime.

Paul got a standing ovation as he left the stage introducing Pat the new CEO.  With Paul on the stage, there was much discussion of where VMware has come the last four years.  But IDC stats probably say it better than most in 2008 about 25% of Intel X86 apps were virtualized and in 2012 it’s about 60% and and Gartner says that VMware has about 80% of that activity.

Pat got up on stage and it was like nothing’s changed. VMware is still going down the path they believe is best for the world a virtual data center that spans private, on premises equipment and extrenal cloud service providers equipment.

There was much ink on software defined data center which is taking the vSphere world view and incorporating networking, more storage, more infrastructure to the already present virtualized management paradigm.

It’s a bit murky as to what’s changed, what’s acquired functionality and what’s new development but suffice it to say that VMware has been busy once again this year.

A single “monster vm” (has it’s own facebook page) now supports up to 64 vCPUs, 1TB of RAM, and can sustain more than a million IOPS. It seems that this should be enough for most mission critical apps out there today. No statement on latency the IOPS but with a million IOS a second and 64 vCPUs we are probably talking flash somewhere in the storage hierarchy.

Pat mentioned that the vRAM concept is now officially dead. And the pricing model is now based on physical CPUs and sockets. It no longer has a VM or vRAM component to it. Seemed like this got lots of applause.

There are now so many components to vCloud Suite that it’s almost hard to keep track of them all:  vCloud Director, vCloud Orchestrator, vFabric applications director, vCenter Operations Manager, of course vSphere and that’s not counting relatively recent acquisitions Dynamic Op’s a cloud dashboard and Nicira SDN services and I am probably missing some of them.

In addition to all that VMware has been working on Serengeti which is a layer added to vSphere to virtualize Hadoop clusters. In the demo they spun up and down a hadoop cluster with MapReduce operating to process log files.  (I want one of these for my home office environments).

Showed another demo of the vCloud suite in action spinning up a cloud data center and deploying applications to it in real time. Literally it took ~5minutes to start it up until they were deploying applications to it.  It was a bit hard to follow as it was going a lot into the WAN like networking environment configuration of load ballancing, firewalls and other edge security and workload characteristics but it all seemed pretty straightforward and took a short while but configured an actual cloud in minutes.

I missed the last part about social cast but apparently it builds a social network of around VMs?  [Need to listen better next time]

More to follow…


Roads to R&D success – part 2

This is the second part of a multi-part post.  In part one (found here) we spent some time going over some prime examples of corporations that generated outsize success from their R&D activities, highlighting AT&T with Bell Labs, IBM with IBM Research, and Apple.

I see two viable models for outsized organic R&D success:

  • One is based on a visionary organizational structure which creates an independent R&D lab.  IBM has IBM Research, AT&T had Bell Labs, other major companies have their research entities.  These typically have independent funding not tied to business projects, broadly defined research objectives, and little to no direct business accountability.  Such organizations can pursue basic research and/or advanced technology wherever it may lead.
  • The other is based on visionary leadership, where a corporation identifies a future need, turns completely to focus on the new market, devotes whatever resources it needs and does a complete forced march towards getting a product out the door.  While these projects sometimes have stage gates, more often than not, they just tell the project what needs to be done next, and where resources are coming from.

The funny thing is that both approaches have changed the world.  Visionary leadership typically generates more profit in a short time period. But visionary organizations often outlast any one person and in the long run may generate significant corporate profits.

The challenges of Visionary Leadership

Visionary leadership balances broad technological insight with design aesthetic that includes a deep understanding of what’s possible within a corporate environment. Combine all that with an understanding of what’s needed in some market and you have a combination reconstructs industries.

Visionary leadership is hard to find.  Leaders like Bill Hewlett, Akio Morita and Bill Gates seem to come out of nowhere, dramatically transform multiple industries and then fade away.  Their corporations don’t ever do as well after such leaders are gone.

Often visionary leaders come up out of the technical ranks.  This gives them the broad technical knowledge needed to identify product opportunities when they occur.   But, this technological ability also helps them to push development teams beyond what they thought feasible.  Also, the broad technical underpinnings gives them an understanding of how different pieces of technology can come together into a system needed by new markets.

Design aesthetic is harder to nail down.  In my view, it’s intrinsic to understanding what a market needs and where a market is going.   Perhaps this should be better understood as marketing foresight.  Maybe it’s just the ability to foresee how a potential product fits into a market.   At some deep level, this is essence of design excellence in my mind.

The other aspect of visionary leaders is that they can do it all, from development to marketing to sales to finance.  But what sets them apart is that they integrate all these disciplines into a single or perhaps pair of individuals.  Equally important, they can recognize excellence in others.  As such, when failures occur, visionary leader’s can decipher the difference between bad luck and poor performance and act accordingly.

Finally, most visionary leaders are deeply immersed in the markets they serve or are about to transform.  They understand what’s happening, what’s needed and where it could potentially go if it just apply the right technologies to it.

When you combine all these characteristics in one or a pair of individuals, with corporate resources behind them, they move markets.

The challenges of Visionary Organizations

On the other hand, visionary organizations that create independent research labs can live forever.  As long as they continue to produce viable IP.   Corporate research labs must balance an ongoing commitment to advance basic research against a need to move a corporation’s technology forward.

That’s not to say that the technology they work on doesn’t have business applications.  In some cases, they create entire new lines of businesses, such as Watson from IBM Research.   However, probably most research may never reach corporate products, Nonetheless research labs always generate copious IP which can often be licensed and may represent a significant revenue stream in its own right.

The trick for any independent research organization is to balance the pursuit of basic science within broad corporate interests, recognizing research with potential product applications, and guiding that research into technology development.  IBM seems to have turned their research arm around by rotating some of their young scientists out into the field to see what business is trying to accomplish.  When they return to their labs, often their research takes on some of the problems they noticed during their field experience.

How much to fund such endeavors is another critical factor.  There seems to be a size effect. I have noticed small research arms, less than 20 people that seem to flounder going after the trend of the moment which fail to generate any useful IP.

In comparison, IBM research is well funded (~6% of 2010 corporate revenue) with over 3000 researchers (out of total employee population of 400K) in 8 labs.  The one lab highlighted in the article above (Zurich) had 350 researchers, covering 5 focus areas, or ~70 researchers per area.

Most research labs augment their activities by performing joint research projects with university researchers and other collaborators. This can have the effect of multiplying research endeavors but often it will take some funding to accomplish and get off the ground.

Research labs often lose their way and seem to spend significant funds on less rewarding activities.  But by balancing basic science with corporate interests, they can become very valuable to corporations.


In part 3 of this series we discuss the advantages and disadvantages of startup acquisitions and how they can help and hinder a company’s R&D effectiveness.

Image: IBM System/360 by Marcin Wichary

Roads to R&D success – part 1

Large corporations have a serious problem.  We have talked about this before (see Is M&A the only way to grow, R&D Effectiveness, and Technology innovation).

It’s been brewing for years, some say decades. Successful company’s generate lot’s of cash but investing in current lines of business seldom propels corporations into new markets.

So what can they do?

  • Buy startups – yes, doing so can move corporations into new markets, obtain new technology and perhaps, even a functioning product.  However, they often invest in  unproven technology, asymmetrical organizations and mistaken ROIs.
  • Invest internally – yes, they can certainly start new projects, give it resources and let it run it’s course.  However, they burden most internal project teams with higher overhead, functioning perfection, and loftier justification.

Another approach trumpeted by Cisco and others in recent years is spin-out/spin-in which is probably a little of both.   Here a company can provide funding, developers, and even IP to an entity that is spun out of a company.  The spin-out is dedicated to producing some product in a designated new market and then if goals are met, can be spun back into the company at a high, but fair price.

The most recent example is Cisco’s spin-in Insieme that is going after SDN and Open Flow networking but their prior success with Andiamo and it’s FC SAN technology is another one.  GE, Intel and others have also tried this approach with somewhat less success.

Corporate R&D today

Most company’s have engineering departments with a tried and true project management/development team approach that has stage gates, generates  requirements, architects systems, designs components and finally, develops products.   A staid, steady project cycle which nevertheless is fraught with traps, risks and detours.  These sorts of projects seem only able to enhance current product lines and move products forward to compete in their current markets.

But these projects never seem transformative.  They don’t take a company from 25% to 75% market share or triple corporate revenues in a decade.  They typically fight a rear-guard action against a flotilla of competitors all going after the same market, at worst trying not to lose market share and at best gain modest market share, where possible.

How corporation’s succeed at internal R&D

But there are a few different models that have generated outsized internal R&D success in the past.  These generally fall into a few typical patterns.  We discuss two below.

One depends on visionary leadership and the other on visionary organizations.  For example, let’s look at IBM, AT&T’s Bell Labs and Apple.

IBM R&D in the past and today

First, examine IBM whose CEO, Thomas J. Watson Jr. bet the company on System 360 from 1959 to 1964.  That endeavor cost them ~$5B at the time but eventually catapulted them from one of many computer companies to almost a mainframe monopoly for two decades years.  They created an innovative microcoded, CISC architecture, that spanned a family of system models, and standardized I/O with common peripherals.  From that point on, IBM was able to dominate corporate data processing until the mid 1980’s.  IBM has arguably lost and found their way a couple of times since then.

However as another approach to innovation in 1945, IBM Research was founded.  Today IBM Research is a well funded, independent research lab that generates significant IP in super computing, artificial intelligence and semiconductor technology.

Nonetheless, during the decades since 1945, IBM Research struggled for corporate relevance.  Occasionally coming out with significant IT technology like relational databases, thin film recording heads, and RISC architectures. But arguably such advances were probably put to better use outside IBM.  Recently, this seems to have changed and we now see significant technology moving IBM into new markets from IBM Research.

AT&T and Bell Labs

Bell  Labs is probably the most prolific research organization the world has seen.  They invented statistical process control, the transistor, information theory and probably another dozen or so Nobel prize winning ideas. Early on most of their technology made it into the Bell system but later on they lost their way.

Their parent company AT&T, had a monopoly on long distance phone service, switching equipment and other key technologies in USA’s phone system for much of the twentieth century.  During most of that time Bell Labs was well funded and charged with advancing Bell system technology.

Nonetheless, despite Bell Labs obvious technological success, in the end they mostly served to preserve and enhance the phone system rather than disrupt it.  Some of this was due to justice department decrees limiting AT&T endeavors. But in any case, like IBM research much of Bell Labs technology was taken up by others and transformed many markets.

Apple yesterday and today

Then there’s Apple. They have almost single handedly created three separate market’s, the personal computer, the personal music player and the tablet computer markets while radically transforming the smart phone market as well.   In every case there were sometimes, significant precursors to the technology, but Apple was the one to catalyze, popularize and capitalize on each one.

Apple II was arguably the first personal computer but the Macintosh redefined the paradigm.  The Mac wasn’t the great success it could have been, mostly due to management changes that moved Jobs out of Apple.  But it’s potential forced major competitors to change their products substantially.

When Jobs returned, he re-invigorated the Mac.  After that, he went about re-inventing the music player, the smart phone and tablet computing.

Could Apple have done all these without Jobs, I doubt it.  Could a startup have taken any of these on, perhaps but I think it unlikely.

The iPod depended on music industry contracts, back office and desktop software and deep technological acumen.  None of these were exclusive to Apple nor big corporations.  Nevertheless, Jobs saw the way forward first, put the effort into making them happen and Apple reaped the substantial rewards that ensued.


In part 2 of the Road to R&D success we propose some options for how to turn corporate R&D into the serious profit generator it can become.  Stay tuned

To be continued …

Image: Replica of first transistor from Wikipedia