Artificial Intelligence

End of life notice

February 2, 2018 By K. D. McAdams

The tiny mechanical creature lay motionless on the gravel path. It didn’t return to the base station last night but the empty battery had to be a symptom of a larger ill.

This particular bot wasn’t mission critical for human life, but without it the flora and fauna in Capability Park on the moon were going to be stressed. Last time this guy had an outage they lost over fifteen percent of the plants growing here. The losses were only recovered a few months ago.

Sean Reynolds was frustrated that they weren’t preparing for the loss of this device. He knew the bots and systems that worked to sustain life in the park and the machines knew the plants.

Scooping the aluminum body off the ground he was amazed at how light the package was. This bot was built over forty years ago and designed to crawl along the hull of a ship and look for defects and make minor repairs. Ines Nazca modified to be one of the first agro-bots.

It was due for replacement about twenty years ago, but the problem with a lot of the older artificial intelligence was that no one knew how they learned. This bot, George, learned more about the variety of trees and plants in the park than any human even considered.

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Space fighter pilots and artificial intelligence

January 22, 2018 By K. D. McAdams

I’m having my wisdom teeth out tomorrow. This is a bit of a short update, but I’m trying to get a little ahead on the word count for the week in case I don’t feel much like writing tomorrow. I also wanted to mention that last Friday I released Book 5 in my Seamus Chronicles sci-fi series. It’s called Exploration and is on sale for $0.99 for a few more days.

My Off Earth series is coming along nicely, I’m past the half-way point! One of the things I’ve been thinking about recently is how fighter ships will work in space.

From an action and excitement perspective I love space fighters and the cool pilots that fly them. As a kid I had X-wing and Y-wing fighters to play with. The BattleStar Galactica vipers were on almost every drawing I made from third through fifth grade. Afterburners, thrusters, and the control stick hard right or left inducing a roll is an adrenaline pumping scene.

Unfortunately, from a reality perspective I doubt that humans will be sitting at the controls of s a space ship with windows and guns. It makes sense to me that artificial intelligence will handle the bulk of flight control in space (and soon on Earth as well). And a big part of me thinks that artificial intelligence won’t want to conduct combat missions that have a real possibility of failure.

So where does the space battle action come from? For me it comes from an alien encounter (new data set) and AI instances struggling to learn. The humans are urging them to make exceptions to both comfort and safety protocols but the ships are reluctant to listen.

In the Off Earth Series I’ve decided my ships have commanders, not pilots. The commander directs the AI flight control and at times is required to persuade the AI to go against it’s programming. For example, if the odds of success are below twenty percent an AI flight controller might refuse to do a maneuver that could stop or destroy and alien star ship. It’s up to the human commander to override that decision, because the fate of the human race rests in their hands. This is a gray area that comes into play in other places.

As for the windows I don’t feel like those are going to be common in space. More likely are monitors that show a visualization of what the ship perceives to be outside the hull. They are already talking about doing this in airplanes and I think it makes even more sense in space. For my characters in They Awake, their salvage ships, the Cthulhu ships, have a small circle of port holes around the body. These are because the ships were designed and built by an Earthling who had grown up driving cars. He didn’t trust AI or computer representations to be one hundred percent reliable so there were small windows built into the ship, though rarely needed. Except of course in an emergency.

For those following along for the numbers update on the Off Earth Series progress –

Book 1 – They Awake
Target release date – 4/13/2018 On schedule
Last weeks word count/target – 25,723/22,000
This weeks word count target – 22,000 words
Total words/projected – 59,708/95,000

A companion for sorting

January 12, 2018 By K. D. McAdams

Humans are messy and tricky. While I was thinking about artificial intelligence working aboard a space salvage station I realized that there would be some unlabeled parts. This was even before the story about John Young smuggling a corned beef sandwich on board a Gemini-3 launch. When systems can’t identify things, people are going to get the job. Below is a story about a junk sorter from the Off Earth Series world.

Before the first orbital war there were tens of thousands of pieces of space debris orbiting the Earth. Expended satellites were parked in a geo-stationary orbit where they wouldn’t affect modern, functional satellites. Smaller decommissioned satellites were de-orbited to mostly burn up in the atmosphere though in some cases their mass survived and plummeted into one of the oceans. It wasn’t a great system and many people believe it was the true cause of the first orbital war. A piece of Chinese space debris collided with a United States based space tourist station. One hundred and four customers died and an equal number of staff perished when exposed to the void of space.

When the orbital war was finished the every day amenities people on Earth were accustomed to were gone. No satellite communications, no global positioning and limited weather forecasting. There was so much debris orbiting the planet and so little information available that any space launch was considered a suicide mission.

Then Kai Nazca returned.

Flying the rock now known as Lagrange-4 back from deep space was remarkable enough. But when he saw the mess preventing him from returning to his planet his next idea was pure brilliance. Using old radio wave technology he was able to communicate with the early ruling body that was to become the Planetary Operating Alliance (POA). In exchange for cleaning up the debris circling the Earth he was granted exclusive rights to the stationary orbit of Lagrange-4 in perpetuity and passable to his heirs, as well as complete ownership of anything he was able to recover for a ten year period.

The ten year period for ownership ended long ago. Now they were required to purchase any debris from the owners before it could be salvaged. While every component of a ship launched into space was logged and labeled, humans were less precise. Tourists, laborers and stowaway’s all brought personal affects with them. When a vessel failed and the escape pods were used, plenty of unlabeled items were left behind, eventually needing salvage.

Artificial Intelligence and bots were great at processing individual labeled items. They were terrible at processing unlabeled items or products that were assembled from multiple-labled items. A.I. Would routinely label complex systems as something simple based on the component on it’s surface.

When A.I. And bots fail, humans get involved. That’s how Kurt Plaque ended up in the massive salvage bay of Lagrange-4 parsing through a motley collection of jewelry. The value of gold, platinum and silver dropped dramatically after it was discovered in abundance in several asteroid mines. Here in space there was a market for handmade Earth goods. A gold necklace with a locket made on Earth was worth more than it’s weight in gold.

Snobots, shoveling and changing the way we think about things

February 9, 2017 By K. D. McAdams

Today is our second snow day this week, and yesterday the schools had a delayed opening due to weather. I grew up in this area so I’m used to the snow, but lately I’ve been thinking about it differently.

If you live in an area where it snows regularly you’ve probably developed your own approach to snow removal. You can ignore the next part and skip down to where I ask you to think. Our driveway is one that the plow truck operators refer to as a blower only drive. So before you tell me to “get a plow” it’s not an option.

If you’ve never dealt with snow, let me explain a few things. Snow is like a living organism, it’s constantly changing. Temperature, sunlight, wind, kids, pets, you name it and it has an effect on the snow. This means clearing the snow, so that you can get on with life, has an intuition aspect to it that’s hard to quantify (sounds like something A.I. would struggle with).

On Tuesday, when we last had school canceled, it didn’t start snowing until mid-morning, around 9:00. But then it snowed all day, dropping 4-6 inches. It was cold, so the snow was light and fluffy making it relatively easy to clear. BUT! Wednesday was forecast to warm up and possibly rain. So I had to clear it. Otherwise it would have packed in and frozen into a sheet of permafrost, not to be removed until May.

I timed my shoveling to about an hour before the snow stopped falling; roughly 4:30. This allowed me to get it done in the last drops of daylight and while it was still light and fluffy. On Wednesday morning there was a dusting coating the driveway and walk but I knew it would melt with the sun and rising temps.

Today we’re scheduled to get 10-16 inches with temperatures in the mid to upper 20’s. I just got home from running some errands and the snow is wet and heavy.

There is a huge difference between shoveling or snow blowing 5 inches of wet snow and 10 inches of wet snow. The effort curve is non-linear. Dealing with double the snow requires more than twice the effort. Instead of planning to go out close to the end, I have to figure out when we’re about half-way and get out there.

In fact, I like to wait until we’re a little past half way. That makes the second pass a little easier than the first. This is a good thing because by the time I’m doing the second pass I tend to be tired and grouchy.

Here’s where I start the thinking part.

I can clear up to 6 inches of snow from our walks and driveway in about an hour. If it’s really wet and heavy it might take 90 minutes. The issue us more about how much ground there is to cover than the snow itself. Walking the snow blower up and down the driveway simply takes time.

So even if I went out to clear snow every time it accumulated to 3 inches it would take me an hour. On a day like today thats 4 or 5 hours outside in the cold and snow. It wouldn’t bother a Snobot, but for me it would bring new meaning to the words grumpy.

That means that all the snobot has to be able to do is clear the maximum amount of snow in an hour – 6 inches if you don’t want to check.

But the other challenge of clearing a foot or more of snow is where to put it. In years when we’ve had multiple storms the driveway and walkway get more narrow with each snow. Three and four foot high snow banks are not unheard of. Lifting or throwing snow up and over a four foot high bank requires some muscle.

And this is where I remember we have to think differently. The problem statement is simple – how do I keep the walk and driveway free from snow?

The challenge isn’t about automating the snow blower or creating a robot to use one of the snow shovels. The snobot could be a tracked electric vehicle with a heating element underneath. It could be a flying drone that relies on the wash from it’s rotors to blow the snow away. Or it could be some crazy combination of heating, pushing, blowing and throwing that I can’t name.

A snobot would be connected, getting real time updates on both hyper-local and regional weather conditions, as well as smart. It would understand the ground temperature and topology and it would be tireless.

Artificial intelligence and automation doesn’t simply mean having computers take over existing machines. It’s about re-thinking how we solve problems.

Artificial Intelligence, Automation and jobs

February 7, 2017 By K. D. McAdams

As you dive into artificial intelligence it’s hard not to come across news and opinions about how it will be taking over jobs. While there are concrete examples like automated beer delivery if you compile a report, follow a route or repeat a task A.I. will impact your life.

I can remember once when I was like 8 years my mom yelled at us about offering to help. She said that if we walked into the kitchen and she was working on making dinner of cleaning we should ask if there was anything we could do to help. It was the least we could do to contribute she said.

Later, when we were older she yelled at us about asking if we could help. “You’re old enough now to know what needs to get done. The best way to help is to just do it. You don’t have to ask me!” she told us.

Simply following instructions didn’t add a lot of value, we had to think and act. That’s what artificial intelligence is starting to do and what we as humans have to get back to.

Image courtesy of Ilya Pavlov via Unsplash

There was a recent NY Times article about Siemens not having any jobs for high school graduates. They need people who can creatively solve problems and work with technology. It made me think about the kids who are in high school now with plans to go into a field that will be automated out of existence in the next 5 – 10 years.

For example, right now there is tremendous value in the ability and willingness to drive a tractor trailer truck from Sacramento to Chicago. Motor freight is a cost effective way to get a product from point A to point B. But the human is the most expensive part of the equation. Automation isn’t interested in getting rid of the person driving, it wants to get rid of the expense associated with the person. So humans need to look for other ways they can add value.

For those of us who sit in front of a computer all day it’s easy to see this with detachment. But regardless of whether your job is compiling reports, writing copy or assembling components artificial intelligence is looking for ways to perform that function better and cheaper.

The good news is that it won’t happen overnight. There will be places where automation makes too much sense to ignore and it will be implemented quickly. A straight clearly marked super highway is easier for A.I. to navigate than narrow, twisty and unmarked back roads. Analysis based on intuition and off-line data sets will be far more difficult for A.I. than a forecast for standard, everyday necessities.

We have to stop thinking about getting paid to follow a process. What we all have to start thinking about is where we can add value. Asking what you can do that wouldn’t be the same if a computer did it will lead you to opportunities that may not have existed before. Future opportunities won’t come from doing things that a computer can’t do, they’ll come from doing things that humans would rather have done by another human.

Conversational tid-bits on artificial intelligence

January 31, 2017 By K. D. McAdams

With 62% of enterprises planning to deploy some type of Artificial intelligence by 2018, AI is a hot topic these days. It’s concepts and capabilities are invading our cars, kitchens, and jobs. But what is it? And what does it mean?

Image courtesy of Kevin Curtis via Unsplash

The other issue is how do you get involved. If you go out for drinks after work and people are talking about artificial intelligence how do you identify the pretenders? Or better still, how can you ask a decent question to show that you are interested?

This is not intended to be an engineering paper or give you the tools needed to present an AI recommendation to the executive staff at work. It’s not even AI 101 level stuff. I want to offer a few tid-bits so that when someone starts talking artificial intelligence you can exhibit a little human intelligence.

Right now it looks like the Finance and Healthcare industries are deploying the most advanced AI instances. But if you’re in a manufacturing, transportation or marketing related field use of artificial intelligence is picking up speed.

When it comes to discussing Artificial Intelligence, it is obviously a broad topic. Don’t get drawn into an argument or conversation with anyone who paints with the “AI is about to take all of our jobs” brush. Those people are out there and they’ll cite examples from random websites but not have a lot of details to support the theory. Most likely they are afraid of change and don’t have the time to learn more.

Many of us, myself included, immediately think of what the experts call Artificial General intelligence (AGI) when we hear AI. AGI is the walking talking robot with a little bit of attitude and a whole lot of data. Or Jarvis from Iron Man. AGI is cool and flashy, but it’s not coming for your job in the next 5 years.

If you want to jump in on the conversation it’s good to ask what role the AI will be used for. There are all kinds if different AI’s coming to market. The AI used in Tesla’s autopilot is not going to also suggest a gluten free recipe you might enjoy based on the ingredients in your fridge. And the AI used to recommend a parts forecast for the manufacturing team isn’t going to start generating content headlines for marketing programs. Much like new head count, AI will have a specific job description.

Other terms you’ll hear related to artificial intelligence are machine learning and deep learning (Wikipedia links so you can read more). If you hear these mentioned it’s likely someone who is working with or growing familiar with actually using AI.

Machine Learning is a subset of artificial intelligence where an application can change based on receiving new data. It lets the computer learn without being programmed. Machine learning is the power behind many of the recommendation engines you see on your favorite content sites. It’s what allows the computer to suggest content based on what you have previously looked at.

Deep learning is closely related to machine learning. The biggest difference is that deep learning will take huge chunks of data and project a model of a predicted outcome. Deep learning is what would forecast your purchase of a new TV based on your last two months of researching them online. You probably wouldn’t know when your surfing is being fed into a deep learning algorithm, but it is.

Artificial intelligence is capable of many things. In most cases it will help people do their jobs better, not replace them. Getting involved in the conversation sooner will help you operate more comfortably as AI comes into your business.