1/31/2018

Where & How Will Society Be Disrupted

Where will Technology Disrupt Society?

Sectors:

Education - think Students prepared for work life at fraction of Time and Cost.  Electronic Portable Records.

Healthcare - think Medical Records.  Faster Claims processing.  Holistic view of patients.  Doctor Collaboration.

Finance - think new Digital Currency to replace Paper Money across Globe, instant Stock Transactions.

Transportation - think Driver-less Autonomous Vehicles carrying Human passengers as well as Cargo.

Communication - think Instant access to Anybody Anywhere Anytime on Any Device.

Retail - think Instant access to Any Product Delivered promptly.

Insurance - think Faster Claims, Insightful Dynamic Precise Models on Specific Products.

Specific Technologies:

Artificial Intelligence - think Smart Everything connecting the Physical World with Digital World.

Drones - think National Security, Delivery Mechanisms, Photography, Weather, Provide Internet Access Faraway places.

Augmented Reality - think Removal of Boundaries between Internal Mind and External World, where Physical Properties dissolve and Reality Expands beyond Comprehension.

Blockchain - think distributed Ledger, Faster Cheaper Transparent Digital Transactions with Audit Trail.

Quantum Computing - think Simple Solutions to Infinitely Complex Problems, technology trickle into mainstream Development.

Microscopic Technology - think Embedded Chips and Sensors in Things, Cargo, People, Animals to Monitor in Real Time.  Also think Data Storage at the Atomic Levels.

1/23/2018

No Rules, Laws or Ethics for AI, Still?

What is interesting is the same rhetoric time after time.

Data is the new oil.  8 years ago.
Data is the new oil.  7 years ago.
Data is the new oil.  6 years ago.
Data is the new oil.  5 years ago.
Data is the new oil.  4 years ago.
Data is the new oil.  3 years ago.
Data is the new oil.  2 years ago.
Data is the new oil.  1 years ago.

Okay, we know that.  Except its not new news.  It was new news a while back.  Typing an article about it is rehashing old news.  Which other people reported about years ago.

On another note, we read time and again, ¨we really need to architect some type of rules and ethics for Artificial Intelligence¨.

Well, that´s true.  Except it hasn´t been done.  And it should have been done.  And it still isn´t done.

That leaves the door open for nobody writing the rules of law and ethics.

Or, it allows those in the know to write the rules.  Not a great idea to allow the gatekeepers of the technology to write the rule books.  Leave that to letting the credit card companies writing the new bankruptcy laws.


AI will be here before we know it in one form or another.  Without proper rules, laws, etc. we are asking for trouble.  And the fact that people keep saying rules need to be created, amplifies the fact that it hasn´t been done yet.

http://www.bloomconsultingbi.com/2016/11/intelligent-machines-require-lot-of.html

http://www.bloomconsultingbi.com/2017/09/can-mankind-create-artificial-general.html

http://www.bloomconsultingbi.com/2016/11/robot-are-people-too.html

http://www.bloomconsultingbi.com/2015/10/latest-thoughts-on-artificial.html

http://www.bloomconsultingbi.com/2016/04/smart-machines-and-robots-may-be.html

Early Computers

I have never walked on the moon.  Yet.  Anything is possible.  They say some people landed on the moon back in 1969, just in a nick of time.  To comply with JFK ambitious initiative to start space flight.  That is one small leap.  Quite an accomplishment.

The computers used to in the mission were antiquated as you can imagine, probably not as powerful as a smart phone.

Computers were once limited to NASA, Government Agencies, Universities, Research facilities.  Personal Computers took center stage in the early 1980s.  We had an IBM PC top of the line 1200 buad modem.  Used to dial up BBS download files, find lists, etc.  Early day hackers.



Anyone remember ¨global thermonuclear¨ in the war games movie.  A lone wolf smart kid outwits and outsmarts the greatest minds of the day.  Seems possible, or not.



Hackers have been around since the beginning of computers.  How to outsmart people, processes and systems.

Sort of a mentality of underdog, wits, whatever it takes mentality.  Only downside, in today´s world a hacker will spend time for their crimes.  I was never a hacker.  But one can easily understand the mentality behind them.  Do what can not be done, for fun, on a computer.

Another movie from a while back was ¨Real Genius¨" some smart students discover new ¨ray¨ device in college setting, only to be under minded and sold out by their professor.  I believe the smart kids win in the end.



Then of course there is Robert Redford ¨Sneakers¨ movie about paid hackers that discover great device to crack any code, ¨No more secrets¨:



Computers was once the domain of nerds.  Now, its become big business.  Social skills now required.  Some of us nerds are still working in IT, nerds as in early day computer users and programmers at young age.  It is amazing how embedded computers are in society.  Way back when, if you knew your way around a computer, you were among a unique tribe.  Now, everyone has jumped on board the bandwagon, for good reason.  Computers are the future, and present.  Only question, will humans survive or be cast aside for smart intelligent machines.

We will soon find out...

1/19/2018

Crypto Currency Bubble

BitCoin.  I heard about BitCoin a while back.  Was going to purchase a server to Mine BitCoin.

Free Money!


Who doesn´t want that.


Well, if we take a step back for a second.  There are no free meals.  There are suckers born every minute.  History dictates the appearance of manufactured bubbles every so often, to fuel the economy and displace money from the bottom upwards.


Based on this limited subset of information, I chose not to invest in BitCoin.  And now we hear that some big Tech Companies refuse to support BitCoin.  And leading investment advisers, billionaires in fact, shrug off as well.


I hate to be the messenger, but if you want to become wealthy, why not try working hard for it.  Yes, it sure would be a lot easier to lie, steal, cheat or ride the next bubble, but working hard builds character.


Try it, you may like it.


On another note, I would venture to guess that an alternative Crypto currencies appears in the not so distant future, built on similar foundation of BlockChain.  Except it will be regulated and controlled similar to current currency, yet it will cross country boundaries and be accepted worldwide currency.  Or segmented digital currency in North & South America, Europe, Africa, etc..


And who is this guy that created BlockChain.  A mystery man indeed.  Don´t you just love when new technology is created out of thin air by some phantom of the night, doesn´t stick around for accolades and wealth.  Seem funny to you?


Wasn´t there a super hero from another planet that had superior strength and his only downfall was ¨Crypto¨ Night.  Ah who knows.


And so it goes~!

We Replaced You with a Bot

We wrote a ¨bot¨ to replicate your personality.  Took about an hour.  You´re services are no longer needed.

Funny, but possible.


You as an entity, besides all the drama, are designed to work and spend money.  If your job description could be automated, you could be replaced by technology, in one form or another, and you would not have the capital to spend.  No work, no spend.  Then what?


What makes you ¨you¨.  Probably your accumulated experiences and thoughts and patterns and relationships over time.


One thing that´s baked into everyone, are their personal bias.  Your favorite color, your favorite meal, your view of the world is slanted towards your experiences plus your preferences.


If we remove your preferences, and distill your experiences down to simple truths, then combine them with others, a mash of consolidated truths across cultures and ages, we could create a generic intelligence, minus the personal preferences.  The Borg.


Who cares what your favorite color is.  Or your SAT scores.  Or your net worth.  What unique knowledge do you possess that could benefit the group?


Your believe that your are separate being entity, that´s is the mass hallucination we are taught from early age.  Kids are labeled from early age, how well does this child look out for themselves, how good are they are getting what they want, are they ruthless.  That´s considered a good trait, at least when I was growing up.


If you were deep thinker, lost in thought, shy, and didn´t care much for competition, they labeled and tossed you aside, make room for others.


When did we decide that aggressive winner takes all behavior was favorable?  What about those with deficits that can´t compete or choose not to compete?


Society is about to awaken to a new reality.  Job security.  Pensions.  Low cost education.  Expensive healthcare.  Inflation.  Elderly population without savings.


As we approach the perfect storm, we have automation waiting on the wings, ready for their entrance, to take center stage.  People have so much baggage, intelligence systems do not.


Does anyone maintain the belief that their role in society is going to remain in tact?  Just look around, the tides are beginning to shift.  With everyone looking out for themselves, instead of group effort, let´s see how this turns out.


Best of luck!

1/16/2018

Cavemen, Dirt, Wheelbarrows, Blockchain, CryptoCurrency and AI

Data is the new oil. Sort of a good analogy.

Except new oil is constantly required.  And there is only so many oil wells on the planet.  At some point, they will dry up.


Data is more like the new sunshine.  Chances are the Sun will be around for a very long time.  Giving off light and heat energy for many generations.


You could say we have been collecting data, or let us say dirt, for a long time.  We collect our dirt, store in Buckets.  At some point, someone discovered very large Buckets, or big Buckets (big data).  You can store a whole bunch of dirt in big Buckets.


We still need a way to transport that dirt from one location to another, we use wheel barrows, or ETL for Extract Transform and Load.  We move a pile of dirt from here to over here, we do this every night during ETL process, make copies of dirt over and over.


Next we reinvented a system to store that dirt across vast spaces, totally transparent, with rules to identify if the dirt is allowed to be approved for delivery and transaction, the block-chain.  We will split up the pile of dirt, keep some in varied locations to ensure accuracy and accountability.


Block-chain appears to be a good technology, can be leveraged across many sectors for near real time instant transaction recording, think Insurance, Healthcare, Stock Transfers, Voting Polls.  Block-chain raised its head in the form of Crypto currencies.  Thing to remember, if you control the creation of money, you are well positioned, let us not discount the fact that money printers are not going to relinquish their position any time soon.  So Crypto Currencies many come to fruition, putting dents into the banking system structure, but it will be a controlled currency, across the globe, with fees and specific groups that allow new currency units to be created into economy, all tracked electronically for audit trails and fraud prevention (or fraud creation).


Artificial Intelligence, great concept, to mirror the human brain.  Except as researchers explore the human brain, they realize teaching data models to become guests on Jerry Springer show is not all that great an accomplishment, as humans pretend they are logical, yet lack evidence for such.  Emotional creatures that know best practices, and go to great heights to completely ignore, think diets, savings, exercise, faithful, etc.


Augmented Reality is an up and comer.  As if Real Reality was not strange enough, we created artificial reality, with no holds bar, anything is possible.


Perhaps cavemen and cave women had it best.  Hunt.  Gather.  Mate.  Sit around the campfire.  That does not sound all that bad if you think about it.  Technology has propelled mankind forward, and added new dimension of Temple of Babble by confusing, over complexing, splintering, re-inventing new ways to solve same business problems, for a fee.  Yet that fee drives the economy.  And who could not use a few extra artificial units of currency to display their artificial status in artificial society.


I would say cavemen were just as smart, if not smarter, than today.

1/14/2018

How do we Scale & Speedup Artificial Intelligence

People have filters.  If you ask someone that drinks at bars a question about a bar, chances are, they will have more information that you care to know, as in what bars are in the vicinity, the culture of clients, the menu, etc.

Same with a person that enjoys coffee.  They have an internal map of all the coffee joints in town, hours, locations, people, baristas.

Reason being, they are domain experts in their specialized interest.

They say the average mind listens to thousands of signals a second.  Because the fact is we are bombarded by too much stimuli, so we filter out the stuff not important to survival or interest.  Perhaps running anomaly detection routines in the background for protection, subconsciously in the back of the brain.

The mind is always awake, processing stimuli into information for processing.  We filter on the basics, push aside the not important stuff, and go about our lives.  Perhaps we have special areas of interest that we are knowledgeable.  Perhaps we learn up to a point, then shut down anything new, at a certain age.

Artificial Intelligence is intelligence produced artificially.  Intelligence is derived as any other computer.  It takes Input.  Processes the input.  Returns Output.

We have developed multiple ways to teach computers patterns over time by feeding input data, process through multiple layers to produce output results based on percentages of predictability.

We have specific sets of data to train specific data models.  We tune these models for better accuracy, over time so the training can learn based on new data.

We have data models that watch other data models, receive input via feedback loops, for instant feedback, so the models can learn faster with better accuracy.

Yet, they are limited in their domain.  They may be experts in a specific area, but chances are, not multiple domains, in real time.

Input.  Process.  Output.

That is how computers work, and to some degree, that is how brains work.  Brains could be considered very advanced data models, how the data gets stored & archived, accessed on demand, memory, are sort of becoming more known, yet still a black box indeed.  Brains are extraordinary equipment and are a mystery.

Artificial Intelligence has progressed recently, as in the past 10 to 15 years.  Because data sets are more available, processing power has increased, software is freely available and expert thinkers and designers are hard at work at well funded organizations working night and day tirelessly to solve this unique riddle.

Some of the issues confronted are domain specific models do not scale easily, they take time to train, perhaps not real time models.  The process of obtaining data, cleansing to some degree, processing models through multiple layers is tedious, not fast and performed by trained professionals in unique office conditions.

With all the advancements so far, as in winning at Jeopardy, becoming master level at video games such as Othello, Atari, Go, Chess, Poker, how do we integrate multiple layers of AI across multiple domains in real time as well as scale globally with increased accuracy, better performance and lower costs.

Input.  Process.  Output.

With AI, we have facial recognition, classification of objects, speech, vision, natural language processing, predictions based on statistical probability, anomaly detection based on data points that do not comply with expectations.  Most of this is performed via computer software.  Robotics are entering the space as well as in manufacturing jobs and machinery to increase efficiency across physically demanding and repetitious patterns.

So if a software program can be trained by processing large sets of data, what if we could teach machines to learn faster.  As in learn by example.  A picture says a thousand words.

What if a computer could simply watch an action over time, and learn the techniques to duplicate the behavior, with efficiency and accuracy.  How would that be done.

Well, if you had a camera, that translated the external world into a digital world, for processing, that would handle the data input.

The processing could be short wired to watch the patterns, learn the best practices as well as exceptions.  The core learning wouldn´t take that long, its learning the exceptions that may take longer, and those can be archived and appended over time.  This is a challenge for humans as well, as long as things go as expected, people can process and move forward.  Its when exceptions occur, how do you handle, forward to manager as they have more experience or authorization, same with computers, flag occurrence for future follow up.  Otherwise continue as usual.

Teach computers to teach themselves by showing them actions to perform, may speed up the training of models.  And those models can be integrated with other models.  Each component becomes expert in their niche, other models can access each other model, such as a bee hive.  A series of combs together form a structure, the bee hive.  Each comb could display its meta data, what the model does, what its domain expertise is, how to interact with it, who created it, when, how often updated, etc. etc.

A combination of multiple domains spiced together across giant networks, to form a unified collection of knowledge across multiple domains in real time, scaled across the planet, continuously being updated with newer information.  New data models could leverage the already learned knowledge from other Data Models across similar domains.

When we think of Artificial Intelligence, we think technology, as in data or programming or algorithms, or what have you.  What you also need to consider are the liberal arts, the actual arts, the sciences, different cultures as in Anthropology, history, medical, banking, traffic patterns, engineering, politics, governments.  There is no set of knowledge outside the realm of AI, it encompasses everything, including languages, religions, tactical warfare, currencies, economies, etc..

It may be possible to speed up the development of Artificial Intelligence by leveraging the ability of software applications to learn by watching, osmosis.  We can not depend on huge volumes of new data sets, to take hours to program and train specific models in specific domains, which do not scale and perhaps not real time.

We need AI systems that can scale, faster, more accurate, by learning the basics of new systems by watching repetitious patterns and learning, as well as pickup up information from other trained models in other or similar domains.  We can expose these trained models using meta-data, telling users information about specific models, so they can be leveraged, why reinvent the wheel when that info has already been learned.

We have made great strides in the field of Artificial Intelligence.  I wonder if we could speed things up a bit, by introducing new ways to train models, and bypass the process of training models based on large data sets.  Let the models train themselves by watching and learning, over time, in real time, as well as leverage a network of trained models across the globe.

Any opinions on this line of thought.

1/01/2018

Are You A Data Scientist

Data Scientist cropped up a while back, became all the rage.  Here are a few requirements:


  1. Enjoys working with data
  2. Intellectual curiosity
  3. Programming skills
  4. Domain knowledge
  5. Cleanses data
  6. Big data
  7. PhD
  8. Statistical Algorithms
  9. Visualizations
  10. Problem Solver

I would say 20+ years working with data, programming and creating reports is a good skills set and foundation for career in IT.  I do not possess a 7.) PhD nor Masters Degree.  And I have not had much experience with 8.) Statistical Algorithms.

I have no intention of going back to school to earn PhD, that boat sailed years ago.  Adding Statistical Algorithms is just a matter of getting a juicy project in which to work with Statistics and training models in Machine Learning, to officially say I have real world experience as Data Scientist.

We see the rhetoric surrounding FAKE DATA SCIENTIST.  Perhaps they do exist.  Looking at the skills I've acquired over time, it sure looks like they overlap to a high degree.  The probability that I am a Data Scientist is fairly high percentage, plus or minus 3% (snark).  Until I get real world experience, will remain a data jockey.