This week, Harris county, TX, saw an unprecedented amount of rainfall during the hurricane/tropical storm Harvey. The city of Houston and surrounding areas have been frequently affected by flooding in the past two decade or so, which led ProPublica to describe Houston: Boom Town to Flood Town. A major portion of the article is devoted… Continue reading Innovation – What is the secret sauce?
Learning from mistakes – Fixing pygpu attribute error.
I am part of a great AI community in New York. Today was the fourth week of an ongoing effort to share the practical tricks to developing a natural language processing pipe line using deep learning. This effort was borne out of my efforts to engage the community to develop a greater understanding of how… Continue reading Learning from mistakes – Fixing pygpu attribute error.
Marissa Mayer for Uber CEO – It will work.
I recently came across two news items, one from Vanity Fair and the other from Inc, on possible future role for Marissa Mayer as the CEO of Uber. Uber has a very interesting year, including a high profile intellectual property dispute with Google’s autonomous driving car division: Waymo, a series of horrible sexual harassment cases,… Continue reading Marissa Mayer for Uber CEO – It will work.
Hardware for artificial intelligence – My wishlist.
We recently developed an incredible machine learning workstation. It was born out of necessity, when we were developing image recognition algorithms for cancer detection. The idea was so incredibly powerful, that we decided to market it as a product to help developers in implementing artificial intelligence tools. During this launch process, I came across an interesting article… Continue reading Hardware for artificial intelligence – My wishlist.
Automation – A completely different thinking.
I have been spending some time on thinking about leadership. Recently, I had the opportunity to sit down and listen to an Angel investor, who specializes in life science companies particularly in New York. I was excited because I have heard incredibly fluffy pieces about this individual. But, the moment this individual started to speak, I… Continue reading Automation – A completely different thinking.
Forced errors – Lessons from an accounting scandal.
In 2015 Toshiba corporation based in Minato, Tokyo, Japan, disclosed to its investors of a major corporate accounting malpractice. The accounting scandal dated back to the 2008 financial collapse. When the market forces became unfavorable, Toshiba resorted to the terrible art of creative accounting practices a.k.a cooking the books. Toshiba created a very interesting mechanism… Continue reading Forced errors – Lessons from an accounting scandal.
Failure Mode Effects – What I learned from a failed car engine:
The 2010 Dodge Charger HEMI is the epitome of a modern muscle car. It is powered by an absolute monster of an engine. The V8 engine displacement is at 6.1L, produces 317kW of power and 569Nm torque. The engine is manufactured at Saltillo engine plant and has a great track record for being low maintenance high… Continue reading Failure Mode Effects – What I learned from a failed car engine:
Fine tuning the cloud – Making machines learn faster.
In a previous post I discussed how easy it was to setup machine learning libraries in python using virtual machines (vm) hosted in the cloud. Today, I am going to add more details to it. This post covers how to make machine learning code run faster. This post will help any user compile a tensorflow… Continue reading Fine tuning the cloud – Making machines learn faster.
In the cloud – Geography agnostic enterprise using Google Cloud Platform.
The concept of geography/location agnostic enterprise is very simple. Whether I am in Beijing or Boston, Kent or Kentucky, New Delhi or New York, Silicon Valley or Silicon Wadi, Qatar or Quebec; I should have access to a standard set of tools to run the company. Moving around geographic locations are hard challenge for any enterprise.… Continue reading In the cloud – Geography agnostic enterprise using Google Cloud Platform.
Pi day – Calculate 2017 digits of pi using Python3
Here is a short and elegant code to calculate 2017 digits of pi. The code is implemented in python3. In three lines of very simple python code; we are going to calculate the 2017 digits of pi. from mpmath import mp mp.dps = 2017 print(mp.pi) The output is: 3.141592653589793238462643383279502884197169399375105820974944592307816406286208998628034825342117067982148086513282306647093844609550582231725359408128481117450284102701938521105559644622948954930381964428810975665933446128475648233786783165271201909145648566923460348610454326648213393607260249141273724587006606315588174881520920962829254091715364367892590360011330530548820466521384146951941511609433057270365759591953092186117381932611793105118548074462379962749567351885752724891227938183011949129833673362440656643086021394946395224737190702179860943702770539217176293176752384674818467669405132000568127145263560827785771342757789609173637178721468440901224953430146549585371050792279689258923542019956112129021960864034418159813629774771309960518707211349999998372978049951059731732816096318595024459455346908302642522308253344685035261931188171010003137838752886587533208381420617177669147303598253490428755468731159562863882353787593751957781857780532171226806613001927876611195909216420198938095257201065485863278865936153381827968230301952035301852968995773622599413891249721775283479131515574857242454150695950829533116861727855889075098381754637464939319255060400927701671139009848824012858361603563707660104710181942955596198946767837449448255379774726847104047534646208046684259069491293313677028989152104752162056966024058038150193511253382430035587640247496473263914199272604269922796782354781636009341721641219924586315030286182974555706749838505494588586926995690927210797509302955321165344987202755960236480665499119881834797753566369807426542527862551818417574672890977772793800081647060016145249192173217214772350141441973568548161361157352552133475741849468438523323907394143334547762416862518983569485562099219222184272550254256887671790494601653466804988627232791786085784383827967976681454100953883786360950680064225125205117392984896084128488626945604241965285022210661186306744278622039194945047123713786960956364371917287467764657573962413890865832645995813390478027590099465764078951269 Happy 2017 pi day. The code… Continue reading Pi day – Calculate 2017 digits of pi using Python3