Tuesday, December 27, 2016

The disappearance of Big Data

Quoting from my blog April 2016

No one will be talking Big Data in 24 month (November 2017)

It  is going to get so good, so fast, so in 24 month, I mean literally in less than 24 months, that no one will be talking about Big Data. We will just spit in data like using a fire hose, and then spit out patterns predictions, correlations, causation, that we could never  understood. These technologies are compressing things so hard and our brains are built linearly. That why we can not see it.

We will not bother with Hadoop 3.0. We will use "this thing"

I do believe that the notion of Hadoop 3.0 would  simply be, "we will not even bother with it."  

Yes, indeed. It did already happen, December 2016


Sunday, December 18, 2016

The myth of Google Translate

The article The Great A.I. Awakening is typical of the flamboyant style journalists from New York Times use to create an artificial suspense ex-nihilo
Late one Friday night in early November, Jun Rekimoto, a distinguished professor of human-computer interaction at the University of Tokyo, was online preparing for a lecture when he began to notice some peculiar posts rolling in on social media. Apparently Google Translate, the company’s popular machine-translation service, had suddenly and almost immeasurably improved. Rekimoto visited Translate himself and began to experiment with it. He was astonished. He had to go to sleep, but Translate refused to relax its grip on his imagination.
The highlighted text  is added to manipulates the reader. Profesor Rekimoto, went on and tested a Japanese version of Hemingway's The Snows of Kilimanjaro translated  back into English using Google Translate. The result is decent.

This made me experiment too. As I was born in Romania, I selected the classic writer -  considered impossible to translate,  Ion Luca Caragiale.

Here is the Romanian version of a fragment extracted from the short sory The Visit
După un moment, se-ntoarce cu cheseaua goală; o pune pe o masă, se apropie de mine, îmi ia de pe mescioară tabacherea cu țigarete regale, scoate una, o pune în gură și mă salută militărește, ca orice soldat care cere unui țivil să-i împrumute foc. Eu nu știu ce trebuie să fac. Mama, râzând, îmi face cu ochiul și mă-ndeamnă să servesc pe domnul maior. Întind țigareta mea, militarul o aprinde pe a lui și, fumând, ca orice militar, se plimbă foarte grav de colo până colo. Eu nu-l pot admira îndestul, pe când mama îl scuipă, să nu-l deoache, și îmi zice:
— Scuipă-l, să nu mi-l deochi!
Here is the version from Google Translation
After a time, coming back with empty cheseaua; puts it on a table, get close to me, I take the small table royal Cigarette cigarette, take one, put it in his mouth and a military salute me, like any soldier who asked to borrow a ţivil fire. I do not know what to do. Mother, laughing, winking at me, and I-ndeamnă to serve Mr. Major. I extend my cigarette, lights it on his military and smoking, as any military walking from place to place very seriously. I do not admire îndestul, while mother spat, not to deoache, and I say:
- Spit it, not me him the evil eye!
Although Google did a decent translation, with only four words kept in  original Romanian, there is no sense of style. Some of the words are archaic and suggest a comic perfume the Romanian reader captures and laughs, while the English reader still struggles to make sense of the text and can't understand the reason why the Romanians are laughing.

So no mater how advanced the AI translation engine is and no matter if the Natural Language Understanding has a high rating, they can't translate from culture to culture the  sentiments which make literature a pleasure to read.

In my humble opinion, we can improve language , but we can not replace the people completely. We still need very skilled human translators to take over from AI/ML. The leading companies in applied AI  understand this very well.

The suspense from the New York Times article has been created by a  human,  GIDEON LEWIS-KRAUS,  and not by a machine

Love me some Google translate (Go here for the magic http://translate.google.com/  ):

Monday, December 05, 2016

What makes Cooldimi bot different?

Written by Kuldip S. Pabla, co-founder and CTO of Cooldimi 


What is Cooldimi?

"Cooldimi is a stealth mode startup in based out of Silicon Valley. Cooldimi's bot platform is focused on enabling conversational commerce by using Chatbots. Cooldimi thinks that AI machine learning Chatbots will not replace human beings in the near future.

The  Yale University Professor David Gelenter's  view  is  The Danger is not Machines Becoming Humans, but Humans Becoming Machines

As a result, Cooldimi's unique approach involves creating super intelligent bots by blending artificial intelligence alongside human intelligence, which is irreplaceable in bots technology for the time being.

What is "bite-sized content"?


A bite-sized content is what a bite-sized snack is as compared to a normal sized meal. By analogy, the bite sized content came up with the advent of the millennials generation. They do not like long articles, long videos; they like shorter articles, shorter videos (5 minutes max versus 30 minutes).

One of the customers - a popular science center- shared that they have a website that they continuously update. However, the customer has experienced lower web traffic that has been  going down, though their site is continuously updated and has excellent contents. In my discussion, I suggested a messenger based interface, where the users can ask for smaller, shorter questions, and the responses are smaller, shorter and relevant answers.  The customer would love to use that service. More important for desktops, laptops, tablets you need to open the website. In Cooldimi solution,  all you need is to send a message, ask a question and then you get back the relevant responses. The customer marketing  representative also would like to know whether their marketing campaign are successful or not. In addition they liked this  idea, as is so focused to the point, because youngsters with a limited attention span would like to use messengers rather that browse entire websites looking  for a specific answer.

They want to understand what is the real meaning  of the  questions people have (Gap Analysis) - What people really mean? What questions they should really ask, and they don’t?

Why a Cooldimi bot is different?


Most of the bots - according to some sources they estimate close a million bots floating the Internet - are rule based. I would say between 80% to 90%  bots are rule based. They behave exactly how they are programmed to. They cannot learn and cannot respond to anything they do not know.

The next generation of bots is when a user can communicate in natural language, the way speak. This is also referred to as Natural User Interface (NUI), like GUI. So if I say for example: What is the price of apples? or How much the apples cost? , while the intention is the same, different users may ask it in many different ways. Using Natural Language Understanding (NLU), the second generation bots can understand intentions and can answer the queries even if they are not programmed to answer so. These bots can also be continuously trained to augment their smartness.

That said, these bots cannot do what a human can do - understand emotions and sentiments. Humans in a face to face interaction, can see the gestures, voice inflections, the body language. One can see whether the person I am talking to is happy or not, maybe she or he is frustrated or enthusiastic . These are important cues in sales interaction.

But when  talking to a broad audience of humans, how would an inanimate bot fine tune these conversations? It has to be done through sentiment analysis, and this is how a bot from cooldimi stands out. Not just we analyze sentiments, we use the cues to improve bot behavior to make it smarter.

Sunday, November 13, 2016

Apcera re-purposed itself.

Apcera

Apcera started as a PaaS platform called Continuum; then HCOS (Hybrid Cloud Operating System); then simply Apcera  platform.

The latest Apcera incarnation from Network World Nov 8  is
 Apcera’s container management platform for cloud-native and legacy applications. At the same time, the company also announced it has expanded integration features to further support Amazon EC2 Container Service (Amazon ECS), Google Compute Engine and Microsoft Azure—strong integrations that should further the company's claim to providing near-seamless movement of workloads across heterogeneous environments.
According Mark Thiele, chief strategy officer for Apcera.
“Apcera has an enterprise-first approach to container management, and customers regularly turn to us to help modernize legacy applications, as well as to run Docker securely and at scale,”

Joyent

There is a January 2015 - famous now - blog from Bryan Cantrill, Joyent CTO . The title is Predicteria 2015 . If you wonder what Predicteria means, Bryan told me and I wrote it down in this The new Joyent blog.

According to Bryan
  1. 2015 is the year of the container. ... Thanks to Docker, the world is finally figuring out that OS-based virtualization is actually highly disruptive (better performance and lower cost!), and I think that this realization will become mainstream in 2015. I don’t think that Docker will necessarily be the only substrate,
  2.  The impedance mismatch between containers in development and containers in production will be a wellspring of innovation. Currently, containers have a ton of developer enthusiasm — but limited production deployments, in part because of production concerns around security, persistence and network virtualization. But it’s a sure bet that there will be (many) players tackling the problems in interesting ways.
 I asked, how did  he notice the impedance mismatch?
When I speak to a developer event, I ask people the audience: "How many of you have used Docker containers?"  About one third to half of the audience raises the hand. Then I ask:  "How many of you have used Docker containers in production?" and I see just a few hands  still up
I am convinced it was the vision of Bryan that lead Joyent to re-invent itself

Why Docker is a winner versus VMs

This is the title of my LinkedIn blog . I am humbled by the traffic generated from Docker, Quora and LinkedIn

I ended the article like this
If Docker is a contract between devs and devops, then Apcera's HCOS seals it in form of ITOps policies that make it  respected and implemented in an automated fashion
I still believe this today.

Friday, November 04, 2016

How to stop AI bots from creating a Mad Max world

What Cooldimi offers?

We enable intelligent Chat-Robots, in short Bots. We make a bot smarter. To use an analogy, a hunter needs a dog. But this is not any dog, but a special breed and trained as a hunting dog.



Similar to a hunting dog, a cooldimi bot learns faster to make successful it's owner, knows it's  limitation and lets the human take initiative when it has no answer, It will quickly learn new skills to improve his owner satisfaction.

We have demo available  on how we actually do this with a bot, any bot from Facebook, Microsoft, Pandorabot and so on.

What can I do with a bot?

Before answering this question, Facebook’s introduction of a bot-building platform at its F8 developer conference event April 2016, triggered indirectly some colossal profit increase for the company. Facebook had a wildly successful Q3, earning $7.01 billion in revenue. Facebook destroyed analyst estimates, which were $6.92 billion in revenue 
The first thing you can do with a bot you can make money for your company.
This is Cooldimi's bot platform ultimate goal.

Do all bots have intelligence?

Cubbot

Do you mean machine learning intelligence?  No. Most of them are rules based. Like this Rubik's Cube Kuldip Pabla (Cooldimi CTO) built in one day for his son who trains for Rubik speed solving competitions.


So what is Cooldimi?

Cooldimi is bot platform.   It enables Conversational Economy, meaning one can order services and manage infrastructure with leaving the messenger chat.

It focuses on industry specific (narrow) domains, For example a bot calling an Uber car can not be used for email promotions

Cooldimi measures happiness factor using human sentiments It  blends Artificial Intelligence with Human Intelligence.

Cooldimi makes bots that meet business specific goals  and the users are happy. People never buy something they are not happy with.

Cooldimi adds a meaningful conversation in a suitable narrow domain. with clear business goals, directly or  indirectly, and we intelligently monitor the bot to make sure it delivers. Do you want to make money?

That will be nice.

Cooldimi makes the difference between (money-in to  garbage-out) versus (money-in to a-lot-more-money-out)

Can Artificial Intelligence appear as human intelligence?

Not  in the foreseeable feature

According to WILDML blog 
Many companies are hoping to develop bots to have natural conversations indistinguishable from human ones, and many are claiming to be using NLP (Natural Language Processing)  and Deep Learning techniques to make this possible. But with all the hype around AI it’s sometimes difficult to tell fact from fiction.
 Most of the value of deep learning today is in narrow domains where you can get a lot of data. Here’s one example of something it cannot do: have a meaningful conversation. There are demos, and if you cherry-pick the conversation, it looks like it’s having a meaningful conversation, but if you actually try it yourself, it quickly goes off the rails.

What do you mean "it quickly goes of the rails?"

If you’ve actually used any of the personal assistants (PSa) you may be skeptical. Siri still barely understands what you want, and Facebook has put hordes of human workers behind Facebook M to get it to do anything useful. How will these things ever replace all the complex tasks we’re doing apps and browsers? 
So you need human intervention. Machine learning can not sort it out by themselves, Have you heard Microsoft TAY?

I did. It made an uproar. How it happened?

It is a failure that was a success, as we learned so much from it. See Microsoft’s disastrous Tay experiment shows the hidden dangers of AI  
Microsoft’s disastrous chatbot Tay was meant to be a clever experiment in artificial intelligence and machine learning. The bot would speak like millennials, learning from the people it interacted with on Twitter and the messaging apps Kik and GroupMe. But it took less than 24 hours for Tay’s cheery greeting of “Humans are super cool!” to morph into the decidedly less bubbly “Hitler was right.”

How Coodimi avoids a Mad Max invasion?

The domain millennials mean all people aged 18 to 36 . This a huge land, impossible manage to via artificial intelligence, where one starts training a bot with an initial conversation, and improves this conversation as the bot gets used more and more. A bot has no notion of ethics. The users take control of the space creating out of Chaos an unpredictable world. Just like the movie Mad Max, a 1979 Australian post-apocalyptic dystopian action film.

24m of Twitter‘s 284m active users are bots with “no discernible user action involved”,  This was back in January 2015. Today the number can be much larger.

A clear domain narrowing is key for enabling  business bots that deliver results

Monday, October 10, 2016

Cooldimi Bots

Americans do not like long words. A Bot is a  shortening of  ChatRobot. A poet, Eli Siegel wrote
Substance
is what remains
when everything you think of
has gone

 2016 will be the year of conversational commerce

This is the Medium blog by Chris Messina
... utilizing chat, messaging, or other natural language interfaces (i.e. voice) to interact with people, brands, or services and bots that heretofore have had no real place in the bidirectional, asynchronous messaging context
The Aha! came from this observation

 

What does it mean? 

No longer do you need to convince users to “download and install” an app — they can just invite a bot to a conversation and interact with it [eventually] like they would a person. Zero barriers to adoption, with minimal risk to the user (i.e. malware, etc).
While you may have bristled when that news app alerted you to “new stories”, you might appreciate a particularly friendly newsbot delivering a personalized recommendation with context that you uniquely care about.

Bots have no menus and are no human either

You just text, or talk. "Conversational apps are therefore organized around the way I organize my life, rather than the way the app maker might dictate."

Bots are not humans. Bots will not become indistinguishable from humans in the foreseeable future. Bots have no sentiments

95% of the bots lack intelligence and are not learning from human interaction

Artificial Intelligence is hot


From 14 deals to 143 deals in five years

Bots themselves have not feelings. But the people using them have emotions.

The bot substance is..

To make happy the humans using them ." this is what remains when everything you think of has gone"

Cooldimi Bot

Diagram of Cooldimi Bot

Cooldimi rules

  1. Goal-driven dialogue bots that learn to engage in natural conversations with humans. It will recognize "Hi, how are you today?" or "It's a nice day in Arizona" as greetings. It will take more time to learn how to place the greetings at the right place
  2. We optimize users’ satisfaction and agent’s knowledge 
  3. We know that Bots are AI machines talking to real humans.A caller to some of the  government voice mail system is furious after waiting for hours. This can no happen with Cooldimi bot. 
  4. Cooldimi is enabler for a company to have happy users. Most other 3rd party are disablers.
  5. Bots are specific for each vertical. No mix and match, please, as a recent 3rd party discovered the hard way. A 40 verticals "ready to use bots" went out of business in 3 months
Cooldimi Bot: Demo will be available on web site during Nov 2016

3rd party disablers

A new start up in New York area uses peer too peer bots to sell insurance from a smart phone. Their business model requires the society to change. They even hired a Chief Behavioral Officer.

In my humble opinion any company that needs to change the people behavior, as a precondition for success has to fight two wars with very meager startup resources

From Talmud

Seek not things that are too hard for you. Search no things that are hidden from you. Think only at the things that are permitted to you. You have no business with the things that are secret.

Chatbots And The Future Of Facebook Messenger
Note: The ideas expressed in this article are  from Cooldimi  co-founders: Kuldip Pabla and Miha Ahronovitz

Tuesday, September 06, 2016

Insurance Industry and the next Industrial revolution

At World Economic Forum in Davos 2016, this picture feels grandiose

3 key questions for the digital revolution, by Jim Snabe, WEF USA
According to Harvard Business Review , the article Is Your Organization Ready for Total Digitization? explains:
What do the following items have in common: credit cards and streaming or recorded music, robots for production, CAD systems, telephone networks, digital games, computers in products like cars and vacuum cleaners, sensors, and video consoles used in remote mining? Answer: They are all digital and connectable.
This is the world of total digitization: a multitude of digital devices and sensors creating streams of data, as well as any number of digital services and products for both internal and external use, distributed throughout the enterprise, and sometimes, but not always, connected.
However the road to the 4th industrial has the devils in the details.

The amazing challenges of digitization the life insurance industry

This is an industry that bills total premiums of 2.3 trillions dollars per year worldwide As part of the work we did in Cooldimi we discovered  some interesting facts

Insurance documents are verbose and complex

On average insurance products come with "more than 25,669 words of explanation written in PhD level language." This is more than Shakespeare's Romeo and Juliet . See Customers ‘only read 15%' of insurance documents they receive' . One of the big enemies for getting the right cover is complexity.
There two startups trying to bring life insurance on line.   Quilt coming soon
"Quilt is for people who live online, value what they have, and expect more from their insurance. We promise: we'll never make you read pages of legalese or hound you with calls from salesy agents".
Another is PolicyGenius that compares life, renters, pet and health insurance on line. Their mere existence is a proof of Insurtech 3rd party disruption, I see why their methods can not be adapted gradually in all incsurance industry

No national databases of all life insurance policies

This is unthinkable
The following article has a self-explanatory title: 12 Easy Steps To Locating Lost Life Insurance Policy Documents. Quote:
Locating life insurance documents for a deceased relative can be a daunting task—for one thing, as of this moment there are no national databases of all life insurance policies.
There are reports of over 1 billion dollars in  unclaimed life insurance - accumulated over the years in US alone.

The role of human happiness in selling insurance products

 Why are people reluctant to buy life insurance?

From a millennial (someone in her mid 30's) Quora contributor
People are often reluctant to join a plan that provides no immediate benefit. Not only does life insurance not provide an immediate benefit, but it doesn’t provide any at all as long as you are alive. It’s likely that many people are turned off by the idea that they will not personally benefit from having a life insurance policy.
There are people who have an intense fear of their own death. It’s not that any of us are somehow okay with that prospect, but some people fear it to the degree that they don’t want to talk about it, and don’t want to plan for it either. Some might even believe that planning for their own death, such as buying life insurance, is like willing it to happen
Jewish orthodox people (and many other religions) believe our life is sustained by Gd and we could  trust  a life insurance policy the way we trust Gd.  According to Rabbi Alan Yuter
The head of the household viewed children as old age insurance; children were expected to care for the mother in old age. Life insurance fills this social need. The marriage document is at its core a life insurance policy which the wife collects at her husband’s demise or at her divorce, i.e., the demise of the marriage. 
For Hebrew culture, love requires tangible expression. This expression includes giving financial and emotional security for those who depend upon us.
These sentiments are attached to the product called life insurance.  Simply lowering the price of the product will not make it more desirable

Happiness  Index 

The 4th Industrial revolution will not happen, unless we digitize  the human sentiments in addition to credit cards, life insurance, and other soulless infrastructure objects.  Using machine learning and sentiment analysis, we should always have a clearer picture of the buyers and sellers happiness. See the blog  Happiness in Business

Measuring happiness is not an interview process. People are not entirely honest in interviews, and the samples are too small.

Cooldimi translates and monitors continuously the Sentiment Analysis from   business data into a  Happiness Index , per product, line of business, geography or society impact. We detect the polarity (negative, neutral, or positive sentiments) in real time using Natural Language Processing (NLP).

Otherwise the barriers between man and machine won't dissolve.


Post Script

Amazon started using machine learning in consumer products reviews evaluation. Just click the stars in any review like this, and this text pops up.
Amazon calculates a product’s star ratings using a machine learned model instead of a raw data average. The machine learned model takes into account factors including: the age of a review, helpfulness votes by customers and whether the reviews are from verified purchases
If Amazon stopped calculating simply raw averages in rating, everyone will follow soon. Behind each human rating, there is a sentiment: joy, envy, maliciousness, sincerity, fanaticism and so on

Thursday, August 18, 2016

Artificial Intelligence or Artificial Narrowness ?

Artificial Intelligence (AI) is “intelligence” that is not the result of human cogitation.

I followed the question on Quora What is the difference between artificial intelligence and human intelligence?  and here are some answers from clever contributors
"Artificial means man-made. The only way we can be considered artificially intelligent is if we considered biological reproduction resulting in intelligent humans as a man-made process."
"We know that we are not artificial intelligence because we know that we are not artificial."
"In my opinion it is misleading to talk about "artificial intelligence". The alternative term, "machine intelligence", is far better."
Machine Learning (ML) is the subset of the Artificial Intelligence (AI)  focused on algorithmic approaches, while traditional methods mostly use a parametric approach.  Yet ML and AI are used almost interchangeably

Botchats

Botchats (simply called Bots) are illustrated like this in slackAPI manual

Fig.1 This is hilarious!
Using Artificial Intelligence, I have a bot mimicking me in a supermarket receiving instructions from my wife on what to buy. This is best done with a pencil and any piece of paper. But in this case, my Bot named Officebot talks to my wife Bot called Celeste.
Bot users have many of the same qualities as their human counterparts: they have profile photos, names, and bios, they exist in the team directory, they can be direct messaged or mentioned, they can post messages and upload files, and they can be invited to and kicked out of channels and private groups.
The biggest difference between bot users and regular users is that instead of interacting with a team via one of Slack's mobile or desktop apps, bot users are controlled programmatically via a bot user token
On a web site  a Bot greeted me:
The bot: May I help you?
Me: Are you human?
The Bot: Yes I am
Me: Prove it me you are human
The Bot: I can answer your questions
This was a clever little bot.

From AI (Artificial Intelligence) to AN (Artificial Narrowness) 

An article on Tech Target: If Chatbots are trend #1, this is trend #2
The second macro push came from Facebook's Mark Zuckerberg. In April Zuckerberg announced that Messenger was going to be extended from its origin of friend-to-friend communication to consumer-to-business applications. Even beyond allowing you to chat with businesses, he was specifically referring to the ability to embed that artificial intelligence into Messenger. 
The author sees the future of bots in human resources
 The values of self-service transactions in HR are
  • Candidate self-service
  • Manager self-service
  • Employee self-service
Not only your resume lands in an enormous database untouched by human hands, the follow-up is using bots. As a defense in the future, it would be better to apply to a job using ten or more bots, with ten or more different descriptions of yourself.

We just had a peek to an Orwellian future. The my-bot-speaks-with-your-bot is not going to work as it goes against spirituality

Happiness  

Artificial intelligence usefulness is not apparent to every one

Lets assume an author who is adapting complex ideas for public consumption must be a.) capable of understanding the ideas thoroughly in their original form; and b.) familiar with the limits of understanding of the general public and the way these materials must be presented to them.

This author is a "man of God" . It comes from a commentary to Psalm 90 by a great scholar. Moses was the only individual capable of transmitting the Torah from its heavenly sources to earth
Over 50% from all life experiences are emotions and these emotions drive primarily our behavior. In business as in our personal life, if we deal with customer experiences without considering emotions, we are not doing our job. 
2008 Global Customer Experience Management Survey from “The DNA of Customer Experience: How Emotions Drive Value”   by Colin Shaw.
We do not make money as a business organization by cutting customer service jobs and replacing people with bots. We make money through people
Machine learning is here to give the management a view of profits, along side the human assets sentiments who are the true generators of wealth in well managed companies.

Machine Learning should justify how employees, working closely with prospects and customers, can generate 100x, even 1,000x more business than the meager , short term savings when replacing people with bots.

One can not have ultimately a company made out of token activated bots.

Imaginative uses of ML

The article why Good Companies Go Bad from Harvard Business Review 1999, describes the term Active Inertia. This is an organization’s tendency to follow established patterns of behavior—even in response to dramatic environmental shifts. Many large companies fall victims. Machine Learning may have access to documents where it can extract proof of the Active Inertia. Than the management makes changes and see if the symptoms of Active Inertia are less than before.

The happiness literature has identified one of the most deeply satisfying human psychological states to be one called “flow.” It occurs when you are so immersed in an activity that you lose track of the passage of time. Can we identify roughly what is the the percentage of total employees who experienced it?

Finally, we want in our country to give people the ability to work productively in steady jobs, without the stressful fear of being riffed. Most humans are not entrepreneurs and are risk averse.

Look at Intel, Cisco, and the like laying off people in massive numbers. They could have had avoided it is they have had identified the Active Inertia in their companies and the lack of flow in their employees.

Machine Learning can transform our world, as long as we know how to use it.

I saw a new start up who wants to teach very wealthy people how to invest on Silicon Valley firms, without any previous high tech experience. I shook my head: AI alone, can not answer their questions, unless they want to loose their shirts off

Thursday, July 28, 2016

Happiness in Business

I will start by making the following statement:
Happiness is the biggest unused revenue making asset in a business organization today
In real life, when we meet socially a person, we have a conversation. After a few meetings and conversations, we unconsciously evaluate each other. We start having fuzzy opinions about what the other person needs, what she likes and what she dislikes.

A character in a hit Israeli TV series, is a young  medical doctor listed number four on a local list of most desirable bachelors. He is attracted by a young woman, Tehila, but he learns she only goes out with poets. This is an essential piece of information, specific, individualized  and can not be extracted easily through classic predictive analysis.

The happiness question in business

How can we create a tool to deliver this more precise information from interactions with millions of people? Could it make us trust each other more and replace the fear of rejection?  This applies equally to the employees of a company and it's prospects and customers.

The banner "we are nice people to do business with" if it gets across, can make tens, hundreds an even thousand more revenues as unprecedented growth

The advent of artificial intelligence (AI)

Ray Kurzweil,  futurist and inventor, now the director of engineering at Google believes human level Artificial Intelligence (AI) will be achieved by 2029

David Gerlerner  disagrees. The encyclopedic computer scientist whom Bill Joy, the co-founder of Sun Microsystems called "one of the most brilliant and visionary computer scientist of our time"  said you can not separate the mind from a body
The human mind is not just a creation of thoughts and data; it is also a product of feelings. The mind emerges from a particular person's experience of sensations, images and ideas. The mind is in a particular body. Engineers can build sophisticated robots, but they can not build human bodies

The Master Algorithm. Machine Learning

 This a revolutionary book by Pedro Domingos,   Tech Insider  makes the introduction
We're in the middle of a historic moment. It used to be the case that you had to program a computer so that it knew how to do things. Now computers can learn from experience.
The breakthrough is called "machine learning." It's unimaginably important for understanding where technology is going, and where society is going with it. 
Pedro Domingos says more:
A self-driving car is not programmed to drive itself. Nobody actually knows how to program a car to drive. We know how to drive, but we can’t even explain it to ourselves. The Google car learned by driving millions of miles, and observing people driving.
This is what happens with every single human driving a car. But we can not experience what millions other people do when driving their cars.
That's the key: machine learning allows algorithms to learn through experience, and do things we don't know how to make programs for. 
 There were two stages to the information age, One stage is where we had to program computers, and the second stage, which is now beginning, is where computers can program themselves by looking at data.
Google's Eric Schmidt says that every big startup over the next five years will have one thing in common: machine learning.

All models are wrong, but some are useful

On page 290, at the end of his book, Pedro Domingos writes
So now you know the secrets of machine learning. The engine that turns data into knowledge is no longer a black box: you know how the magic happens and what it can and can’t do.
 Here is another attempt of finding a spouse using Machine Learning
One hardy geek extracted twenty thousand profiles from OkCupid (dating online) , did his own data mining, found the woman of his dreams on the eighty-eighth date, and told his odyssey to Wired magazine. To succeed with fewer dates and less work, your two main tools are your profile and your responses to suggested matches
We need to produce  a learning algorithm that works. Using the wrong algorithm, it does not work. We have to know what we are doing,  and watch out  that we do not get garbage-in, garbage-out. I dug out the article from Wired on the web How a Math Genius Hacked OkCupid to Find True Love. You can read the details, the math. In my view, it is a classical example of garbage-in, garbage out for most people, except mathematician Chris McKinlay.

The goal of ML is never to make “perfect” guesses… The goal is to make guesses that are good enough to be useful. Because, as the British mathematician George E. P. Box  says: "All models are wrong, but some are useful."

Happiness makes the most successful businesses thrive even more

Happiness in Business

In his 2008 book The Geography of Bliss , Eric Weiner says
Happiness is a Number
He visits Rotterdam, Holland, where the World Happiness Database is maintained. Students at Claremont University in California can earn a Ph.D. in positive psychology- in happiness.

Since 2012, we have an annual  World Happiness Report Update  Denmark is the number one happiest country in the world for 2016.

Other countries close to the top are  Switzerland, closely followed by Iceland, Norway and Finland, What strikes me is these are relatively small counties in terms of population where people communicate and know each other best.

The report says:
Happiness is a better measure of human welfare than measuring education, health, poverty, income and good government separately, the report's editors argue.
There are at least seven key ingredients of happiness: People who live in the happiest countries have longer life expectancies, have more social support, have more freedom to make life choices, have lower perceptions of corruption, experience more generosity, experience less inequality of happiness and have a higher gross domestic product per capita, the report shows.
It is now the time to publish The World Happiness Report for business. Multinational companies like Ericsson, Zurich Insurance, Facebook, Microsoft, Shell have customers and do business all over the world. All we have now in use are Fortune lists (500, 2000 global, and the wealthiest people in the world)

The only way to write such reports is to implement using finesse the AI technologies,

Example from Insurance Industries

I will cover this in depth in a future blog. Based on my research, traditional insurance companies, billing worldwide 4.1 trillion dollar a year in premiums, are under attack by third party startups using artificial intelligence. Executive earning as much as 350,000 a year are fearing for their future jobs. Some stats predict 25% of the jobs in financial and insurance will be replaced by machine learning tasks. The insurance customers are millennials gen x people , under 50 year old. Insurance companies sell insurance essentially  the same way as 80 years ago, with few changes.

According to I2C: Insurance2Customer USA to be held September 19-20 in Chicago these are the new goals.
  • The Undisputed Rise of the Insurance Customer  – Manage the shift from product-centric to a customer-centric culture to meet sky-high customer demands
  • Understanding Your Customer to Build Relationships – Actionable insights to engage customers through targeted segmentation and personalized messaging
  • Creating a Memorable Insurance Customer Experience – Create and deliver a streamlined and simple customer experience across all channels
  • The Next Wave of Marketing Strategies – From social media, content marketing, branding and digital advertising, learn new tools to win and retain more customers

Cooldimi

I hope this article touches a sensitive chord in the readers. Cooldimi is a stealth company. It's mission is to help companies, particularly insurance companies to set up meaningful machine learning projects


Reaching the customer insurance goals in 2016 requires machine learning implemented and interpreted with elegance and intelligence. Simply hiring a famous mathematician does not make companies reach the goals.

Because the goal is still to keep the executives employed and create bridges to happier and happier customers. Those companies will have happier employees, who can be promoted, not laid off. Will make easier for them to feel the flow. Robert Frank says in New York Times what the flow is:
The happiness literature has identified one of the most deeply satisfying human psychological states to be one called “flow.” It occurs when you are so immersed in an activity that you lose track of the passage of time. If you can land a job that enables you to experience substantial periods of flow, you will be among the most fortunate people on the planet. What’s more, as the years pass, you will almost surely develop deep expertise at whatever it is you’ve been doing.
A business that goes ten times in revenues has no need of laying off people,. Quite the contrary, it creates more jobs and can be mutually beneficial co-opetition. It will attract young customers and make the existing customers buy more.

Post Script: The test of happiness

The  Hungarian psychologist (with a hard to pronounce name)  Mihaly Csikszentmihalyi, also one of the founders of positive psychology. He introduced the concept of "flow" in 1975 He started studying creative people. This Pursuit of Happiness  web page has the mission of bringing the science of happiness to life. It took 40 years to bring the relatively dry, academic research in mainstream media. 

You can try to take a very simple happiness test on line.

The next step could be a  breakthrough article in Harvard Business Review (and other business prestigious publications) to make happiness widely adopted as business goal  Now we have the tools and the wisdom to make it practical

Saturday, June 25, 2016

Brexit disrupts the European Union.

Fintech disrupts banks

Fintech disrupts the banking and insurance industry, (see the previous blog ) The World Economic Forum's insights on the future of banking  uses a document from Citi  DIGITAL DISRUPTION How FinTech is Forcing Banking to a Tipping Point to project gloom (loss of jobs, etc), because the paper is produced by one of the largest US banks and a leading target of fintech.

Brexit disrupts European Union (EU)

So I ask myself: isn't Brexit disrupting EU, in the same way fintech disrupts banking and insurance?


I wonder how many people know what European Union  is and how it works I thought I knew, but I didn't. After some googling and I realized it is a giant labyrinthine bureaucracy.  It has reminiscences of Kafka (who in real life was clerk at an insurance company in Prague). Kafka accumulated the famous frustration, we named Kafkaesque ;  "something having a nightmarishly complex, bizarre, or illogical quality".

The best way to understand EU is to quote in the end of this blog the entire article by Gareth Harding Explaining the EU: United in Complexity

UK exit from EU is not irrational. Brexit is the messenger who tells us that EU must by broken and rebuilt for the 21st century.

After reading, we should spare UK of any accusations, and take our hats off

Addendum

With over 20 years experience describing how the European Union works, what it does and what challenges it faces in speeches, articles, lectures and trainings, I thought I could explain what the EU is all about in terms that anybody could understand. How wrong I was.
In the last month I have given half a dozen ‘EU in an hour’ talks to visiting groups of American politics, journalism and international relations students - who are all extremely keen, bright and willing to ask questions. But almost invariably, the students leave the classroom flabbergasted at how needlessly complicated the EU is and suspecting that I have made up some of the Byzantine decision-making procedures just to mess with them.
This is how the average talk goes:
Me: So basically, you have three main institutions: The European Commission, Parliament and Council.
Q: I thought there were four?
A: Well, yes, if you include the European Council.
Q: Wasn’t that one of the three you just mentioned?
A: No, that’s the Council of the European Union. Which is different from the Council of Europe, which is a non-EU body that meets in Strasbourg.
Q: Doesn’t the European Parliament meet in Strasbourg?
A: It does. But so does the Council of Europe. And to be precise, the Parliament also meets in Brussels.
Q: So, just to be clear, the Parliament has offices in both Brussels and Strasbourg?
A: Yes, and Luxembourg, where a lot of the support staff are based. But anyway, let’s go back to the institutions I mentioned before. Firstly, the European Commission. This is often called the EU executive body.
Q: So like the U.S. President?
A: Not really. The Commission can’t declare war or veto laws. But it can do trade deals. So it has some executive functions, but also some legislative.
Q: But my textbook says the parliament and EU Council are the two law-making bodies?
A: Correct, but the Commission proposes all draft laws.
Q: Wait. What? How can an unelected body propose laws? Shouldn’t that be the Parliament?
A: No, the Commission has what they call the ‘sole right of initiative’ because it is supposed to represent the European interest and be free from national prejudices.
Q: But don’t EU member states propose Commissioners?
A: Yes they do. But when they arrive in Brussels they have their national hard drives erased. In theory. Unlike the Council of the EU, which represents the naked national interests of the 28 states.
Q: So the Council is a bit like our Senate? One member per state, regardless of size?
A: Yes, except big states like Germany have many more votes than small states like Malta.
Q: So it’s not really like our Senate?
A: Er…no. Anyway, the Council makes laws, along with the Parliament. It also adopts the EU budget, which is about €140 billion a year.
Q: That’s not much. I thought the EU was the world’s biggest economy?
A: Ah, yes, the total GDP of the 28 member states is the biggest in the world but Brussels is only responsible for about 1% of that.
Q: The Council meets in Brussels right?
A: Yes, except in April, June and October, when it meets in Luxembourg.
Q: You’re kidding?
A: I wish I was.
Q: So who’s in charge of the EU?
A: Ah, the Kissinger question. In one word – nobody. In reality, there are three presidents - of the European Council, Commission and Parliament. The first two are basically chosen by EU leaders and the third by MEPs. None are directly elected to the post by voters. Oh, and there’s also a presidency of the Council of Ministers.
Q: Wait, what?
A: Well, every six months a different EU state is in charge of chairing ministerial meetings. At present, that is Latvia but on July 1 that changes to Luxembourg. However, meetings of foreign ministers are presided over by EU foreign policy chief Federica Mogherini, who is also vice-president of the European Commission. And Eurogroup meetings are chaired by Dutch Finance Minister Jeroen Dijsselboem.
Q: Hang on, what’s the Eurogroup?
A: Well, that’s the meeting of EU finance ministers from the 19 EU states that use the euro?
Q: What? I thought the EU had a single currency?
A: It does, but not for all its states. Britain, Denmark and Sweden decided to keep their own currencies and some central European countries are not ready to join the Eurozone yet.
Q: You’re making this up aren’t you? The EU can’t possibly be that complicated.

Tuesday, June 21, 2016

Disrupting the mortgage industry

Note: a day after publishing this post, New York Times published How Housing’s New Players Spiraled Into Banks’ Old Mistakes . It documents the thoughts from this blog
I did recently some research about financial services. Here is a refreshing example of the good way to disrupt a bank business. As always, it is the way we treat the customers. And customers are people. Better said, it is the way we treat people

What is Fintech

It's a segment of the technology startup scene that is disrupting sectors such as mobile payments, money transfers, loans, fundraising and even asset management.

Fintech was added to Oxford Dictionary on line only in 2016  Many – including tech savvy and clued up entrepreneurs – don’t quite have a handle on.

The modern name was coined after 2010. Previously, it applied to the back office of banks or trading firms  These technologies emphasize machine learning, predictive behavioral analytics, data-driven marketing. It appears  by far the machine learning (ML) has the biggest impact

Fintech is a modern business disruptor, impossible to ignore. Mortgages will change because the people changes and have different expectations

Affirm startup

Quoting Max Levchin the founder of the startup Affirm and a leading member of the PayPal Mafia
The millennial demographic that we are trying to serve is growing. We are on the track to become really, really big. It isn’t hard to convince people in this country that financial institutions are really, really broken and there is an opportunity to build something that could revolutionize the entire system.

MSN Money reports the net worth of millennial ranging from $20K at the age of 35, zero at the age 30, to negative (34K ) at the age of 22. This why the latest generation avoids banking and prefers to use whatever application from fintech disruption

When asked why he had to start with consumer lending, Max replied
I see building any bank as an exercise in building trust. To get there, you have to go through a lot of trust building. This is not easy at all. In the universe, there are some things people are willing to trust. 
Today, people don’t like their bank — they make money when you screw up or make a mistake. 

How Affirm structures a loan 



The millennial customer (or any customer)  selects a budget and the payments are spread accordingly to  his needs. There are no hidden charges, no arrears and interests for past due, no penalties. You may be a month or two out of a job, you may have a child, you may move apartments. Life is not steady, is event driven. Missing a payment does not mean people are dishonest

Disrupting the financial companies business

It is virtually impossible today  to start a new bank or insurance company. How To Start Your Own Bank claims you can start a community bank, which to me is an exception. Or you must be another Max Levchin.

People must feel pleasure, not fear when dealing with banks.

Using legacy tools like FICO, with no "Machine Learning",  the traditional (not community) banks place us in inflexible silos.

FICO is 60 years old. They started in 1956, when 80% of the US population was not born yet, never mind millennials. Actually millennials are uncomfortable with institutions like FICO, which rate people and decide their fate based on the past, using actuarial static calculations.  Machine Learning has yet to be adopted


Bloomberg says
Of the 7 million Americans who experienced foreclosure from 2004 to 2015, only 7.3 percent obtained a mortgage again.
That means, under the current system of big banks running the mortgage business for the nation, FICO-like thinking made an invisible tattoo on the foreheads of seven million American families, saying "Thou shall never own a home again"

The Mortgage Industry: Ripe For Disruption

The existing mortgage industry in US is "too challenged, too inefficient, too costly and too unresponsive to the needs of business and consumer alike". See  Collingwood Group White Paper: The Mortgage Industry is Ripe for Disruption, which can be downloaded from http://info.collingwoodllc.com/mortgage-industry-ripe-for-disruption 

The disruptive business models exploit advanced technology. It  takes the guess out via machine learning. predictive behavioral analytics and data-driven marketing.
2015  National Association of Realtors Home Buyer and Seller Generational Trends reported for the second consecutive year that millennials represented the largest share or 32 percent of recent home buyers.
Dealing with millennials, we know it means change.

The Big Short

 But before change is possible, we must clear the mess from the past.

Dr. Michael Burry, {Played by Christian Bale)  a California physician suffering from Asperger’s Syndrome and Bipolar Disorder who became fascinated with the bond market coupled to mortgage-making with falling lending standards in 2004. He made the move from medicine to mortgage funds with the help of a sizeable inheritance.

There is a book (2010) and a movie: The Big Short  is "a dramatic retelling of the 2007-8 financial crisis It  focuses on the lives of several American financial experts who predicted and profited from the build-up and subsequent collapse of the housing market and credit bubble in 2007 and 2008.

 Financial terminology and the chronology of the financial crisis is highly complex and difficult for a traditional audience to comprehend in a two-hour movie. From collateralized debt obligations (CDOs) and tranches to credit-default swaps and mortgage-backed securities, the production team employs a simple, yet stylistic approach to defining the tools that helped sink the global economy (for more, read The 2007-2008 Financial Crisis in Review.)
Words like  MBS (mortgage backed securities), CDO (collateralized debt obligations}, and many more.  mean nothing, except when, experiencing the results. The original mortgage from the builder is sold to Countrywide (for example), then to one of the big five banks and then is securitized by some Wall Street trust and sold to investors world wide. When the housing market collapses, and the homeowner discovers the value of her home is as low as one half the price she paid for it. In other words she is in default, by doing nothing and in spite for paying on time for five years.

Homeowners in distress do not deal with neighborhood bank, but with some remote shareholders spread around the world who want the highest profits generated

Are foreclosures necessary?

With top 5 Banks running the show their foreclosure activity is high.  and more painful in US  than other parts of the world


According to an expert familiar with the situation:
I think [foreclosure] a symptom of the current system and will continue to create problems in our banks'  way of  handling residential homes. We have now loans not directly related to the home owner, held in institutions that have no  direct relationships with the home owner. These are trusts that are acting on behalf of shareholders to make money from the homeowners. So the trust, uses a servicer to handle the customer service part of the mortgage. In the old day was a relationship based on solving problems and make home ownership sustainable, but now the servicer motivation is just to charge fees. The more fees they charge you, the better off they are. The generate fees by creating situations, such as default, that arises from the bank, when they mistakenly put an amount due there, which should not had have been there. The homeowners is faced to either have to pay that, or potentially face a foreclosure process. The homeowner can not start making payments because they did not pay the additional bill. Many feel as if they are victims of an extortion
Is the mortgage industry today supposed to be about foreclosures? Taking away homes from millions of Americans is ethical? Do we want our system to perpetuate for ever this model? Can't we find a system creating real wealth?

Defending against abusive foreclosures?

 They are  very few law firms specialized in foreclosure fraud, and very few options, for a a variety of reasons:
  1. The banks' tacit policy is "if you sue us, we are going to make it hard and tough for you". 
  2. You are dealing with a part of law that is constantly changing; it makes more difficult to keep up with the law, not only to be aware of it, but also to advance it. That takes a lot of extra work. 
  3. You are dealing with clients that are very stressed out because their home is part of their life. Many clients don't have any money to pay for the legal service.
We need a new type of startups, a consumer legal firm startup, to be a match for the banks' powerful legal machine and stop them.

Experts say they need to have at least 10 cases that went to trial that have hit big. This will change the industry, because the trusts' shareholders will be so upset, and there will be so much bad press that will give power to the individuals. That's why these cases are so much better than class actions.

Perhaps an individual homeowner may get ten million awarded if she has the right case, the right attorneys to convince the judiciary. Then this is significant. And if it can happen multiple times, 5 or 10 times,  we will have an industry that will stop operating for profits only.

Funding Law Firms as startups

What people want from a lawyer?  Millennials,  are seeking an attorney who is a specialist. The second thing, they want empathy, someone who cares, and who will do everything that can be done to fight for them. Third, they want communication on their case, and their calls returned. Venture Capital and large investors funding of law firms is new.

In my opinion,  a funded law firm will redefine what it means to be an attorney and clean the way for a renewed mortgage industry model.

Bottom line  

Should the mortgage industry be always in the shade of foreclosures? 

No.

But how to change? Buckminster Fuller was an extraordinary American;
In 1927 Fuller, then aged 32, lost his job as president of Stockade. The Fuller family had no savings to fall back upon, and the birth of their daughter Allegra in 1927 added to the financial challenges. Fuller was drinking heavily and reflecting upon the solution to his family's struggles on long walks around Chicago. During the autumn of 1927, Fuller contemplated suicide, so that his family could benefit from a life insurance payment.
Then, a voice spoke directly to Fuller, and declared:
From now on you need never await temporal attestation to your thought. You think the truth. You do not have the right to eliminate yourself. You do not belong to you. You belong to Universe. Your significance will remain forever obscure to you, but you may assume that you are fulfilling your role if you apply yourself to converting your experiences to the highest advantage of others.

The motto from the Collingwood Group White Paper:
The Mortgage Industry is Ripe for Disruption
http://info.collingwoodllc.com/mortgage-industry-ripe-for-disruption 






Friday, June 10, 2016

Google's new Cloud Data Center Strategy

I am a long time grid and cloud computer observer, blogger and dreamer.

Three years ago, everyone thought Amazon, Google are the very personification of cloud computing.

I read What Cloud and AI Do and Don’t Mean for Google’s Data Center Strategy. About a year ago, Google brought in new people to revitalize their cloud computing.
 The Alphabet subsidiary has been taking big steps to show that it is “dead serious” about its cloud business, to quote Diane Greene, the founder of VMware whom Google hired last year to lead this charge.
In March 2016, only tree month ago, we read  Google to Build and Lease Data Centers in Big Cloud Expansion

The man in charge is Joseph Kava, a Google VP who leads the company’s data center engineering, design, and operations. This is what he says that I thought is worth commenting

Hybrid Strategy 

We all know that as people move to the public cloud, they are developing a hybrid strategy. They are still keeping some of their apps and some of their systems either on-premise or in their colo, and they’re offloading a tremendous amount of workloads to the public cloud providers
Of course we knew, but this is the first time Google admits it! The Diane Green team made a difference Ericsson right from the beginning adopted the hybrid model and said that we are not too late in cloud computing. From hyperscale Ericsson website
The problem: the infrastructure is dictating the business, instead of the other way around. It’s time to say goodbye to traditional IT infrastructure. Say hello to the new era of digital industrialization. 
One can not create the IoT as part of the networked society, or the Planet as a Service by hosting everything on Google or Amazon classic public on demand clouds.

Google proved Ericsson right, and not the other way around

 The Internet of Things

 The question asked is: What implications do you think IoT has for Google’s data center strategy? Joseph Kava replies
We’ve already had the Internet of Things. They’re called smartphones. Android has over a billion registered things that are chatting with our data centers all the time. 
Well, this is not so. Google Android and Apple IoS  are platforms for smart phones using a specific OS When a platform enters the market of a pure pipeline business, the platform virtually always wins as business model.

Phones are not made to chat to data centers (yet). They are designed to send voice and text to other human beings Android can not offer a service secure and reliable to make one phone, the same phone, accessible in 187 countries seamlessly. Ericsson has both the experience and technology to do that with any IoT device, not only phones
Having the next billion interconnected things doesn’t really worry me, because those devices, whether they’re your refrigerator at home, or whatever those internet-connected things are going to be, they’re generally not going to be as chatty with data centers as your smartphone is. We’ve already dealt with it.
Published studies of small scale IoT pilot trials contradict what Mr. Kava says. Just read IoT technologies hit their awkward tween years
Even with pilot projects, the data volume generated by IoT technologies is massive.

Machine Learning Tensor Processing Unit boards 

 Goggle's TPU

This shows Google's leadership
There are customized hardware platforms that machine learning runs better on. It doesn’t affect the way we design our data centers, 
The Tensor Processing Unit board. The TPU is a chip, or ASIC, Google designed in-house specifically to power Artificial Intelligence systems in its data centers
 Based on this, a year ago, a computer system beat a professional human player at the ancient Chinese board game Go. The AI system, AlphaGo, was built by Google and trained using machine learning techniques.

This how it works:
The chip is tailored for machine learning. It is better at tolerating “reduced computational precision,” which enables it to use fewer processors per operation. “Because of this, we can squeeze more operations per second into the silicon, use more sophisticated and powerful machine learning models and apply these models more quickly, so users get more intelligent results more rapidly,” 
The machine learning in Data Center is key in processing big volume of Data. Derek Collison from Apcera predicts all data will be ingested in Machine Learning engines and he says
I do believe that the notion of Hadoop 3.0 would  simply be, "we will not even bother with it."  We are going to plug our data in the Google Brain project 
Ericsson is a majority shareholder in Apcera.

If things are too beautiful to be true, you are right. There is new skill to learn on how to program many core processor. Please see An Interview with David Ungar, IBM Research

Nvidia Tesla P 1000

In April 2016, Nvidia announced a new chip called the Tesla P100 that’s designed to put more power behind a technique called deep learning. This technique has produced recent major advances such as the Google software AlphaGo that defeated the world’s top Go player.

Intel's  Xeon E7 v3 and Lustre* file-system, which is part of the Intel Scalable System Framework (Intel SSF}

From Intel's 18-core Xeon chips tuned for machine learning, analytics
With its new top-line Xeon E7 v3 server chips based on the Haswell microarchitecture, Intel hopes to capitalize on the demand for this type of server. With up to 18 CPU cores, the chips are Intel’s fastest, and designed for databases, ERP (enterprise resource planning) systems and analytics related to machine learning....
Complex machine learning models can’t be distributed over the cloud or a set of smaller hyperscale servers in a data center. Instead, a more powerful cluster of servers is needed to run deep-learning systems, where the larger number of cores could power more precise analysis of oceans of data.

“To create an algorithm to look across thousands of genomes, and to look for correlations, is not the sort of workload that existed a few years ago,”


People still believe this


There are too many new developments that are not reflected in this graph. It shows the past, not the future. The future is in having a cloud as reliable and easy to use as a cell phone worldwide.

Note; The opinions on this blog are mine and not of my clients and or employers

Sunday, May 01, 2016

Taking the 'No"

Advise from Om Malik. He is the founder of GigaOm and one of the best (if not the best) tech writer  I  ever read. On March 9, 2015, Malik announced on his blog that GigaOm, the company he left in January 2014, ceased operations and "and its assets are now controlled by the company’s lenders".
I think every time somebody said no to me, I tried to figure out why did they say no. No is fine, rejections are fine, but you use the no to calibrate why. That means having to take no graciously. I think it’s pretty painful to say no to somebody, as much as it is to take a no.
The advice i have for anyone, whoever they are. If you believe in something, you’ve got to go for it. Don’t worry about the consequences. Don’t worry about the financial outcome, or how famous you’re gonna get, or how poor you will be. If you believe and you can’t seem to do anything other than think about something, you’ve just got to keep doing it. I think the universe has to follow. What’s the point of living if you don’t chase what’s important to you? That’s how I see it.
JK Rowling samples of rejection letters for Harry Potter

The quote is from The Techies project.

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