Get me outta here!

Altered Carbon — Futuristic Detective “noir” , with Bladerunner Bleakness

As you know I have been on a reading binge (HereHere and Here), usually finishing 2–3 books a week ! Focussing mostly on Sci-Fi and mystery. Discovered Richard K.Morgan !

Very interesting, and as an amazon reviewer says “The whole system and the workings of society are very well thought out

Turns out it is also a Netflix series !

Lots of interesting ideas — I like the hotel Hendrix fully run by an AI. You have to read the book to appreciate the concepts !

And see here for his interesting Quell quotes from “Things I Should Have Learned by Now” by Quellcrist Falconer

Talking about BladeRunner, can you guess if all the pictures below are from the movie BladeRunner 2049 ?

Of course, if all pictures were from the movie, there is no mystery ! Actually only the right two are from the movie, the left three are from San Francisco area two days ago, on 9/9/20.

In San Jose, where I live, we had the Dystopian Orange sky — dimly glowed in a pumpkin orange color you’d expect to see on Mars. The whole day ! It was an eerie day … to say the least …

Finally, as the author says,

May the road always rise to meet you ! … May the wind be always at your back !

The Art of an Artificial Intelligence Pipeline & Jen-Hsun Huang’s nVidia GTC Keynote

The background of this blog is the GPU Technology Conference’16 Amsterdam keynote by nVIDIA CEO Jen-Hsun Huang. Extremely eloquent, very knowledgeable, articulate and passionate – all great ingredients for a memorable keynote and you won’t be disappointed. He keeps the energy up for 2 hours – no curtains, no diversions, a feat on it’s own ! (P.S: I have heard from other folks that JH’s whiteboard talks are exponentially more informative and eloquent).

Popping the stack back to the main feature, the goal of this blog is to address a very thin slice of the talk – the AI backbone for a scalable infrastructure beyond the lab experiments. I had talked with many folks and the topic of a scalable AI pipeline/infrastructure gets lost in the hyperbole discussions on Artificial Intelligence and the rest …

First let us take a quick detour and put down some thoughts on an AI Backbone in four visualizations, nothing less-nothing more ….


With this background, let us take a look at the relevant slides slides from Jen-Hsun Huang’s eloquent GTC’16 Keynote at Amsterdam.

I. Computing is evolving from a CPU model to a GPU Model

  • Since 2012, GPU based systems have surpassed human level cognition in fields like image recognition, translation and so forth

There is a new computing model – the GPU Computing pipeline with four components:

  1. Training,
  2. The network master models a.k.a the AI backbone,
  3. Inferencing in the data center (AI applications) and
  4. Inferencing in IoT/devices (eg. autonomous cars)

II. Training

  • This where new architectures are tested with large amounts of data, transfer learning with pre trained models and so forth.
  • I like nVidia’s DGX-1 or AWS GPU clouds. You can also build a local cluster with nVidia GPUs like the Titan-X (like mine, below).

III. The Master Models

  • Reference Models, curated data and other stuff live here. Engineers can interact with the models, morph it to newer domains (using Transfer Learning, for example) and so forth. They will train using the DGX-1s or GPU clouds

IV. Scoring the models at various contexts

  • Now we reap the benefits of our hard work, the applications ! They have two flavors – either run in the datacenter or run on devices – cars, drones, phones et al.
  • The Datacenter inferencing is relatively straightforward – host in a cluster or in the cloud. The hosting infrastructure can use GPUs.
  • The device inferencing is a little more trickier – in my world, it is the Drive PX-2 for autonomous cars (you can see it in my picture of the desk)

The new Xavier Architecture is interesting – tastes better, less calories (er … power).

P.S: BTW, I like the view from the camera on the top right corner of the podium ! The slides have an elegant 3-D look !

V. Epilogue

Interesting domain, with a future.

“… something really big is around the corner … a brand new revolution, what people call the AI revolution, the beginning of the fourth industrial revolution … “

As you can see I really liked the keynote. Digressing, another informative & energetic presenter is Mobileye’s CTO/Chairman Prof. Amnon Shashua. I usually take time to listen and take notes.

The Bridges of Pittsburgh County … That Autonomous Cars can’t SLAM through !

Same as my post in Linkedin

Autonomous cars do bring out interesting nuances to the normal things that we take for granted and don’t think twice about !

Business Insider’s article “Here’s why self-driving cars can’t handle bridges” fits this category.

“Bridges are really hard,… and there are like 500 bridges in Pittsburgh.”

Of course, it is the infinite (or near infinite) context that we, humans can process and machines aren’t even close … But, one would think bridges would be easier – no distractions, well designed straight roads; of course with the current GPS accuracy, the car might think that it is in the water and start rolling out it’s fins !!

“You have a lot of infrastructure on the bridge above the level of the car that we as humans take into account, … But when you sense those things with a sensor that doesn’t have the domain knowledge that we do … you could imagine that the girders coming up from the side of the bridge and that kind of thing would be disturbing or possibly confusing.”

Pittsburgh does have bridges, lots of them … There is even a BBC documentary! Even how the city deals with the bridges is interesting.

In fact Pittsburgh is called “The City of Bridges”, even though some have different interpretations (we will come to that discussion in a minute)

While we are on the subject, I do have a couple of books for the Uber Car to read ! It can even order them through it’s robotic friend Alexa ! or drive to wherever fine books are sold, on it’s own time – Uber might not pay for the impromptu solo drive.

  1. Bob Regan’s Book is the first one to read
  2. Next is Pittsburgh’s Bridges (Images of America)
  3. The book Bridges… Pittsburgh at the Point… a Journey Through History gives interesting perspectives the riders would enjoy (of course, the ones with enquiring minds…)
  4. Finally, the hardcore bridge fans would be thrilled to hear from Pittsburgh’s Bridges: Architecture and Engineering

Now, to SLAM, it is the set of algorithms collectively called Simultaneous Localization And Mapping – a very interesting topic by itself.

In short, a SLAM system needs known points in addition to unknown points, to reason about & figure out it’s trajectory – bridges have less of known points it can rely on …

We can definitely employ Deep Learning ConvNets as well as traditional computer vision with a dash of contextualization is a good start … that is a topic for another time (sooner than later…). Probably an interesting opportunity for or

For those snappy Machine Learning experts, there is even a Pittsburgh Bridges Data Set at UCI, to start with ! Probably nowhere near the data needed to train modern Convolutional Nets, but one can augment the images with algorithms like Flip, Jitter, Random Crop and Scale et al.

If we think Pittsburgh is difficult, wait until Uber starts autonomous driving in Amsterdam ! While Pittsburgh has 446 bridges, many sources put Amsterdam with over 1000 bridges that cars can travel. There are many bicycle and pedestrian bridges in Amsterdam that an Uber car wouldn’t be interested in – except, of course, to pick up the tired pedestrians ;o). The which-city-has-max-number-of-bridges discussions can be followed here:



  • The bridges in Pittsburgh are not painted Yellow (as one might tend to think) but Aztec Gold !
  • And yep, it is Allegheny County ! But Pittsburgh rhymes better ;o)



A Stylistic Chronicled Guide to Isaac Asimov

It is an experience to read and brood over the writings of Isaac Asimov.

If you are just starting, I envy you – you have a wonderful journey ahead of you !!


But don’t just start a series randomly, the journey has a very disciplined roadmap, so that the mysteries of the world of robots will be systematically revealed to you.

Asimov is a required reading for anyone working on Autonomous Cars, Artificial Intelligence and to a lesser extent, Machine Learning.

Detour : Other must read AI books include “The Master Algorithm“,  “Final Jeopardy”  – among a lot of good books …

The books are more relevant now than then – you see, then it was science fiction, now the concepts are turning into reality !!!

As the Reddit Series Guide mentions, you can follow the publishing order or the internal story chronological order. But both are non-optimal and I think the orders would interfere with the reader’s thinking.

Isaac Asimov, himself, has suggested an order, which is more closer to my thinking but still not quite …

[Note : I pieced together the list from various discussions in Reddit and will note original comments within quotes]

First things first – read the Robot Series, in chronological/publication order. You have to meet Elijah Baley and R. Daneel Olivaw !

A) The Caves of Steel 

B) The Naked Sun

C) The Robots of Dawn

D) Robots and Empire


Then comes the Foundation Series.

The two common recommendations are to read these either publication order or chronological order.

I have a third recommendation: start with the original trilogy, then read the prequels, and end with Edge and Earth. …

This gives a good arrangement stylistically, with the earlier novels followed by the later ones. Asimov’s writing style changes distinctly over time. It also gives a good arrangement chronologically, with the prequels foreshadowing the final two books, instead of explaining things you’ve already read about.

And best of all, you end with the cliffhanger, instead of reading it and then reading 2-5 more books that don’t resolve it.

The following order “preserves the mystery the first-time reader would have going into the first Foundation book. Part of the enjoyment of the Foundation novel is that you don’t know who Seldon is, in those opening scenes on Trantor, or what role he’s going to play in the story. If you read Prelude and Forward first, you’ll already have an earful about Trantor and Seldon before you get to Seldon’s introduction through Gaal Dornick’s eyes in Foundation


E) Foundation

F) Foundation and Empire

G) Second Foundation

H) Foundation’s Edge

I) Foundation and Earth

J) And finally read Stephen Collins’ Conclusion The Foundation’s Resolve. I found it a satisfying end to a great saga

(Optional – Rest of the Foundation Books)

i) Prelude to Foundation

ii) Foundation’s Fear (if you really must)

iii) Forward the Foundation

iv) Foundation and Chaos

v) Foundation’s Triumph

Now you are read for the rest.

K) “Complete Robots”

The books are packaged with overlapping content. Questions like “The Complete Robots” vs “”Robot Dreams” & “Robot Visions” vs “I, Robot” comes up all the time. This Reddit discussion addresses this dilemma.

Then you can diverge to other books like Nemesis and The End Of Eternity. The [Galactic] Empire Series are not essential, but do read them – “The Currents of Space”, “The Stars, Like Dust” and “Pebble in the Sky”. Publishing order is fine.

You should also explore Isaac Asimov’s Home Page.

Now you are part of the Asimov club – And have one interesting task to do – which is feedback ! Add comments to this blog with insights – you could even add a new roadmap guid of your own with a very different POV !!!

Autonomous Vehicles – On the road to a Standardization : 5 Questions

In view of the recent developments, the Automated Vehicle Symposium 2016 and the SAE On-Road Automated Vehicle standards work is more relevant. The Connected Car meetup is organizing a meeting with the standards committee; of course, I plan to attend the meetup.

As I was contemplating, extending my experience from OASIS, W3C, IETF and EU FP6 STFs, thought of a few questions that would be good to get clarified. I will try to get answers on Monday, and if you have any, pl add to the comments.

P.S: I will post notes from the meetup next week.

1. Software Telematics

  • One of the important aspects of standardization is the ability to look inside a system declaratively, i.e. one doesn’t have to know “how” a system implements “stuff” but the “what” should be inspected, understood, analyzed, verified and debated (if necessary); the software equivalent of the CAN bus

Question 1 : Will the SAE define the essential semantics of the software pins – a basic curated schema with capabilities for extensibility?

Thinking more, this probably is a bigger effort that what is evident at a first glance, as we have to define the software model before we can define the telematics.

2. Verification of behavior by Induction vs deduction

  • We can either say that a system works because it has worked for the last 130,000 miles (deduction) or strive to prove the correctness of a system by analysis(induction). The proverbial deduction vs induction.

Question 2 : Will the standards effort address the mechanics of behavior verification ?

3. Definitions

  • Of course, definitions are the essential and fundamental ingredients of standardization. And definitions what a system is NOT is equally or more important.
  • As we are seeing in the media, defining AI and autonomous behavior are way more difficult and subject to multiple interpretations. For example, in the autonomous world, we can define AI like so.

  • Probably we are not looking for a humanoid, but we still need intelligent interactivity with the environment which includes pedestrians, drivers, intelligent infrastructure and other vehicles. We also need the Robots Rules of Order.

Question 3 : How deep does the committee plan to define the concepts & components ?

4. Simulation

  • Simulation is another interesting topic that we need to address. Companies do claim 100s of thousands of miles of virtual driving, but in order to characterize, compare and contrast, the simulation frameworks need to be equalized.

Question 4 : Does the committee plan to specify the essentials of simulation ?

  • Probably, a broader framework, with some of the software pins, would be a good start

5. MHI – Machine to Human Interface

  • The machine to human interactions are also another essential aspect.
  • When we drive a different car, e.g. a rental car, we don’t need to study new interfaces or vocabulary. What we know about brakes, accelerator, R and D positions – all are valid.
  • A similar set of ontologies and taxonomies are required for autonomous driving. To make a point, compare the driving controls with the rest of the controls eg infotainment systems, climate controls;  sometimes it takes a lot of effort to understand the infotainment systems that we are not familiar with.  That is OK for connecting iTunes via USB to a car, but not OK for autonomous driving.

Question 5 : Does the committee plan to standardize the interfaces – not just the control but also the metadata ?

What are your thoughts ? Do you have more questions ?

P.S: We haven’t addressed a host of related domains like v2v protocols, v2I protocols(vehicle-to-intelligent infrastructure), security mechanisms, embedding behaviors and extending to the world of drones !

5 Lessons on AI from the Tesla Autopilot Fatality

Unfortunately it takes extreme repercussions for us to feel in our bones, the limitations of our technologies.

Three points :

  1. I have included relevant links about this incident at the end of the blog (incl the AutoPilot v8 with Radar). Informative read
  2. One of my parent died in an automobile accident; so I do know, first hand, the human toll – I do not take this lightly; in fact the reverse is true
  3. And the views expressed in my writing are my own and do not reflect any organization I am part of … now or in the future …


Lesson 1 : Our machines inherit our faults (so far …)

As I pointed out in one of my AI blogs:



Lesson 2 : Many domains are not forgiving to byzantine failures

We are learning that painful lesson whether they are rockets, airplanes or cars. Even though we freak out of snapchat is down for an hour, we can survive that, but not these. The drivers need to understand the downside of technologies and be alert.

Lesson 3 : Mission Critical Systems should have redundancy, over coverage & independency

For example multiple sensor sources & probably independent situational interpretation. I saw the following from somewhere where the Japanese Ministry talks about “correcting the wrong train of thoughts”:

Lesson 4 : Swarm Intelligence

Lesson 5 : This might lead to some level of Standardization & Legalization

  • Standardization of components & protocols
  • Legislation/Standardization of algorithms or semantic behaviors incl image recognition, policies and pragmas …
  • Even driver education and certification to dive autonomous vehicles !



  7. Tesla’s Response to fortune’s Article
  22. Finally AutoPilot v8 with Radar !


Robot’s Rules of Order

As a designer of AI & autonomous behaviors, this week was pretty interesting:

Both are must read & discuss for the AI community. The abstracted 8 rules are :

This could beg the question, what exactly is an AI ? Let me make an attempt from an autonomous vehicle (cars, drones et al) perspective, which might not be complete or sufficient for other situations ….

What says thee ?

Yann LeCun @deeplearningcdf Collège de France

I am spending this weekend with Yann LeCun (virtually, of course) studying the excellent video Lectures and slides at the College de France. A set of 8 lectures by Yann LeCun (BTW pronounced as LuCaan) and 6 guest lectures. The translator does an excellent job – especially as it involves technical terms and concepts !

(I will post a few essential slides for each video …)

Inaugural Reading – Deep Learning: a Revolution in Artificial Intelligence


My favorite slide – of course !!! And the DGX-1 !!

Missing Pieces of AI – interesting …

The reasoning, attention,episodic memory and  a rational behavior based on a value system are my focus for autonomous vehicles (cars & drones!)

Convnets are everywhere !

Probably the most important slides of the entire talk – the future of AI.

Parse it couple of times, it is loaded with things that we should pay attention to …

Can AI beat hardwired bad behaviors ?


I agree here, here, here and here – we don’t want AI to imitate us, but take us to higher levels !

Stay tuned for rest of the video summaries …..

@GoldenStateWarriors Basketball IQ & Robotic Sense – Lessons to be learned



In the eve of the probable final NBA game of the season, and with the Green suspension, it is interesting to note the skill that the team has. Interestingly the agility, domain IQ and the team spirit are equally applicable in business as well !

I came across 4 insightful blogs that tell the story of a talented, multi-faceted team that can snatch victory from seemingly impossible situations … I had written about the GoldenStateWarriors last year, it time now to write again !!!

[Update after Game 7 – at the end of the blog]

Zach Love has the right insights in “The Warriors are more than a bunch of jump shooters

  • There is a jagged, robotic quality to that brand of defense… there is a liquid quality to their defense.
  • They are like one of those college marching bands whose members combine to form massive images that move so convincingly, you almost forget for a second that the giant video game character on the football field is actually composed of hundreds of people

That is not some random accident of team construction. The Warriors sought smart players who felt the game instinctually, and had a history of playing hard for their teammates … they deserve credit for chasing high-IQ guys who play for the right reasons

  • I’m not sure I’ve ever seen a team communicate and shift around the floor so seamlessly. The Warriors swap assignments on the fly without even a millisecond of finger-pointing confusion that might open scoring windows – An agile team, at it’s best !
  • They quite literally move together, as one entity. On most teams, one guy rotates, everyone pauses to observe the new geometry of the floor, and then one guy realizes, holy crap, it’s my job to move now!

Ben Gollliver at Sports Illustrated “LeBron James, Cavs squander chance to even Finals in late-game collapse

  • In hindsight, Cleveland’s late-game struggles mimicked Oklahoma City’s in Game 6 of the West finals to the point of eeriness. … Both times, the Warriors dug out of fourth-quarter holes, on the road, by stopping superstar scorers in their tracks.

@MikePradaSBN writes “The Warriors are daring LeBron James to beat them, and he can’t

  • LeBron James is still one of the league’s very best players
  • Last year, the Warriors unveiled a unique strategy to defeat James. They correctly identified James’ court vision as his most dominant skill and elected to shut that off while living with the consequences.

@MattMooreCBS writes “NBA Finals: This one Warriors play likely ended the Cavaliers’ season

  • In an NBA game, there’s not always a defining moment. Sometimes it’s just all the possessions together making a mosaic for whatever team winds up with more points. Sometimes, though, there are plays, often subtle ones, that offer a window into so much more — microcosms, really, of a much bigger story, one that under the right circumstances can wind up shifting championship fortunes, and thus, legacies. …

One team was faster, smarter, hungrier, sharper, and in the end, they hit the shot. The other team was hesitant, out of position, and too late to do anything about it

What shall it be, we will see tomorrow ….!

I am a big fan of LeBron James, but I love them Warriors more … ;o) 

[Update 6/19/16 10:00 PM]

Two more good articles – both good read and insightful observations … :

  1. Dan Wetzel at Yahoo Sports writes “Mission accomplished: LeBron transforms Cleveland into a winner
  2. @rodger_sherman SB Nation “Never doubt LeBron James again

Room With A View to the Thames

Copy of my post in Linkedin


View From My Room

London has changed a lot since I visited last ! Interesting constructions – at least this part of the town.

Am at the Aloft London Excel, ready for our tutorial at the StrataHadoop London “Building machine-learning apps with Spark“. I will be talking aboutApache Spark/GraphX along with my esteemed colleagues Jayant & Vartika.

Got a good room with a view to the Thames !

Took the Norwegian flight OAK-GTW. This is a good alternative to London. Am also flying by Norwegian to Gothenberg.

The OAK-GTW fight was a 787-8 ! Good plane – I really like the window – a lot bigger … and it has the hi-tech ElectroChromatic Dimming System (or Sun Glasses as they are colloquially called ! ) that replaces the window shutter – you can always see the outside.

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