That’s especially true when it comes to J.A.R.V.I.S., that cocky know-it-all digital butler that runs Tony Stark’s house. Having a powerful assistant as that A.I. has been a dream of many superhero fans since that movie came out, mainly because it would be so awesome to have a digital system so capable and witty (and voiced by Paul Bettany, of course).
In fact, many people have been chasing that dream ever since. If you make a quick Google search, you’ll find that there are people discussing the J.A.R.V.I.S. program code and even building something like it. Of course, in those discussions, you’ll quickly find developers that point out the many problems that come with trying to take on such a project.
Fortunately, we have come a long way since 2008 in artificial intelligence development, so we have more expertise, experience, and tools to make it happen. Still, some questions remain: how many J.A.R.V.I.S. tasks could we actually code into a similar AI? How many we can’t? What are the challenges? What are some of the considerations from the technical perspective? And, the most important question of all – could we build it?
Let’s try to answer all of these questions.
How many J.A.R.V.I.S. tasks could we code now?
It would be easy to answer the question in c level contact list the title with the (many) challenges involved in building a J.A.R.V.I.S.-like system, say “not right now”, and move on. But focusing on the negative would prevent us from seeing the many things that we could actually do – which aren’t few! A quick recap of J.A.R.V.I.S. capabilities can help us with that.
In the beginning, J.A.R.V.I.S. (an acronym for Just A Rather Very Intelligent System) was a natural-language user interface. That means that Tony Stark could use his voice to issue commands that J.A.R.V.I.S. executed. That definitely should sound familiar to you, especially since Siri (considered the first digital virtual assistant) was released in 2011 along with the iPhone 4S.
What J.A.R.V.I.S. tasks we can’t code?
A super-advanced system like J.A.R.V.I.S. has how to use the google trends api to extract data many complex sides that we can’t still get. Let’s start with the most obvious one – we can’t code a personality as strong as J.A.R.V.I.S.’s. Sure, we can infuse some jokes and some witty responses and train a machine-learning algorithm to talk back sarcastically but the result is more like a compound of personality fragments rather than a full-on personality.
Without getting too much into psychology, let’s just say that human personality is extremely complex (and not completely understood, even now). Trying to artificially recreate it would be an impossible task mainly because we don’t truly know all of the components that make up a personality. We can mimic it but we still can’t create an algorithm that develops a personality of its own. If we don’t train an AI to have a personality (providing it with references and training datasets) we won’t get a witty (or a shy, lovable, whatever) personality.
What are the challenges of building a J.A.R.V.I.S.- like system?
Aside from those things that we can’t code, we could give it a shot to building a system like J.A.R.V.I.S. Doing so would imply a well-thought planning stage that boils down the technical capabilities of the AI to its core sale leads features, so we can later decide how we could create each and one of them.
I’ll discuss some technical considerations below, so I’ll stop here on the parts that feel the most difficult for me when building J.A.R.V.I.S. First, there’s the massive processing power it’ll take to run such a comprehensive system. It’s not something unthinkable or impossible to achieve, mind you, as we could rely on cloud computing to garner enough to run a system that powers multiple devices across different locations.