10/30/2015

The Information Race - Data is the Virtual Asset with Unlimited Supply

At one time, you could get really rich by purchasing assets that were scarce.  Land for instance.  However, just about every piece of land on the planet has been surveyed, assessed for possible extraction of resources, plotted and purchased.  There's very little untouched land on the planet.  The resource has been used up.

So without any land to purchase, what other resources are available to exploit, plunder and profit?

Information.

What is information?  It's an accumulation of data.  And where's the data?  Everywhere.  Every company is collection information minute by minute.  And those with the financial backing, leverage and people to transform data into information, will rise to the top.  Because information is the biggest asset going right now.  The quantities are unlimited potentially, unlike land, that plateau's at a certain point.

And the information is an asset.  And processing that information is power.  So those who have the financial backing to process data into information will be the next overlords of the planet.  Not land owners.

You can already start to see some of the big players purchasing huge volumes of data.  The "Information Race" has begun.  The "Arms Race" was yesterday's news.

Data is the Virtual Asset with Unlimited Supply.

10/23/2015

Technology Inflation

Many years ago, things were quite simple.  Simple in the fact that there wasn't much complexity.

For example, the average weekend warrior could put his car up on a block in his driveway, do his or her own oil change, swap out the brake pads, even put in a new transmissions.

Now, even the most skilled car fanatics can't work on their own cars.  Because the complexity that's been added.  Everything is based on sensors and electronic gizmos.  If you want to diagnose an issue, you have to take it to the dealer, hook up a device, and it spits out the specific error.  No way to duplicate this at home.

Apply the same process to computers.  Back in the 1960's punch cards to us seem primitive, but the coders back then knew exactly what they were doing.  Because back then, they were in the details, as in writing to memory and low level functions, complete control of everything.

Now we have 4th generation languages that do us the favor of generating source code and sort of dumbing down the process.  We as programmers are a few layers away from the memory and raw source code because it runs in a black box.

And that black box is great for knocking out tons of code relatively fast, but on the other hand, we don't know what exactly it's doing under the hood.  In addition, the number of dependent items have dramatically increase, exponentially.

We have to deal with networks, security, connections to web services and databases and external calls across the web and other apps that depend on our process'.

Technology has gone through the process of complexity inflation.  It was supposed to simplify things.  Make our lives easier.  In hindsight, it's done the opposite.

That's just my two cents.  With inflation, that equals about a buck seventy five.

Again, thanks for reading~!

10/22/2015

Latest Thoughts on Artificial Intelligence

Artificial Intelligence is making headway in the world today.  The group called Deep Mind at Google has built a system that can become master game players through the use of learning algorithms.

They simply start the AI system, supply it a stream of incoming data, in the form of pixels, like an old Atari game.  The AI system, is first confronted with a series of events.  It soon learns the rules of the game.  And then becomes a master at the game.  Learning strategy, optimal methods to achieve goals faster and can outperform most humans.

It uses a simple set of rules.  Observe a set of environmental behaviors, learn, determine optimal outcomes based on specific possible outcomes, and continue the cycle.

Observe + Learn + Decide + Action then repeat.

Some of the advancements recently have been to add read/write memory to Recurrent Neural Networks.  What that means is the traditional Neural Networks could learn over time through algorithms, they now have the ability to remember prior knowledge over time, retained in memory, for future use.

This is known as the "Neural Turing Machine" in which an Artificial Neural Network can learn new algorithms by example.  For instance, you show the system a routine to sort numbers, and than ask it to perform the function and it knows how simply by watching it previously, actually bypassing the need and time to train the model.

Here's a tweet I posted earlier today: "#AI is a self learning technique by observing, determining possible outcomes, selecting best alternative, then observing... #AGI holy grail."

And another: ""process that converts unstructured data or information into useful actionable knowledge"=AGI, tech is neutral, requires ethical constraints"

Most of this information was lifted from a YouTube video from the Deep Mind founder Demis Hassabis, you can watch the video here



I think the best part of the video is where he differentiates between true Artificial General Intelligence and Narrow Artificial Intelligence.  Siri, Cortana and Big Blue are considered Narrow.  What Deep Mind is focused on is AGI.  A subject that's been around a very long time.  With lots of smart people working towards the goal.  Although it seems to be a hard nut to crack.

I recommend watching the full video to get insight into the happenings at Google Artificial Intelligence team.  I followed Deep Mind before they were acquired by Google and they have a tremendous pool of talent in the space of AI.

The interesting thing about this field, is although it's deeply rooted in technology, they depend on outside science for assistance, like psychologist, neural research for brain activity to behavioral of humans and a bunch more.

This field is pretty exciting.  Although most of my knowledge is self taught, I'm not an expert on the underlying technology that makes it work.  I do understand the base concepts of what a Neural Network is, a Recurrent Neural Network (has memory) to Models and some of the different methods for training them.

It seems some of the latest challenges are applying domain knowledge across multiple domains without the need to train the models for long periods of time.  And perhaps adding memory to the model is one way to accomplish this.

Another factor is the majority of the work thus far has been in a virtual environment.  They have not adapted the AI technology to robots or external environments, where the number of potential conflicting input streams is potentially unknown.  

How would a robot handle a barking dog, or a plane flying overhead or the mailman driving by, all unknown events that don't happen consistently over time.  So the AGI system wouldn't have prior knowledge so it would take to to learn and adapt.  Unless you could simply plug in an algorithm to the system so it understands and adapts immediately.

When we think of ethical concerns, Mr. Hassabis indicates that the technology is neutral or independent.  It depends on how the software is used.

An analogy I think about it the speedometer in a car.  Sure they could set a control to cap the maximum speed of a car.  Because technically, the speed limit is typically 70 MPH in the United States, so why would a car have a need to exceed that limit?  If the driver exceeds the limit, he or she is breaking the  law technically.  Why don't the car manufacturer's place a restriction on the vehicle to prevent us from speeding?  Perhaps that's an ethical question. 

Could the car send a signal to the patrol station, which electronically generates a citation sent in an email, where an ACH withdraws occurs the following business day, removing a $100 fine from your checking account?  I'm sure that could be done.  But it's not.  Why is that.  

How would you create the algorithm to select which drivers to give a citation, or would you apply a blanket rule that everyone exceeding 80 MPH would get a citation, if that were the case, why not place a cap on the accelerator of the car not to exceed 80 MPH.  They could do that today without an AGI system.

I suppose there's some flexibility baked into the system.  Perhaps you need to accelerate to 75 to overtake a car in the slow lane, multiple possible reasons.  But the level of enforcement is by human interpretation and perhaps not applied evenly.  In fact, I'm not sure how they know to pull over certain speeders and not others.  A mystery.  But it could be automated.  But would we want it to be?

What level of automation do we want for our future AGI systems?  Who gets to decide what is deemed ethical and what isn't.  How do you handle the exceptions and the gray areas?

Stay tuned to find out.

10/21/2015

Intro to Quantum Computers

Computers run on 0s and 1s.  Bits and Bytes.  On or Off.  Binary logic.

If you can understand an IF STATEMENT:

IF this logic is true THEN do this
Else IF this logic is true THEN do that
ELSE do something else

That right there is the gist of programming.  Sure there's a few other details to learn but that's the bread and butter.

What if you modified the logic a bit.

IF this logic is TRUE and the same logic is FALSE then do something

Huh?  You can't do that.  Something can only be this or that.  Can't be both.

Well, using this new concept where something can be 0, 1 or both, is called Qubits.

Well.  That's the new logic underlying the new type of computer called the Quantum Computer.   Which borrowed the concept from Physics Quantum Mechanics.
Quote from Wikipedia: "Large-scale quantum computers will be able to solve certain problems much more quickly than any classical computers that use even the best currently known algorithms"
It's the next step in the revolutionary evolutionary framework of computer hardware.  Using Atoms.

And who's the leader in this technology: D-Wave.

And here's the timeline of the events leading up: Timeline of Quantum Computers.

And an article on How do Quantum Computers Work?

I see this technology assisting to advance the progress of Artificial Intelligence and Neural Networks.

Here's a YouTube video:







 We are living in interesting times....

Have You Seen My Double