Digital data is the lifeblood of companies like Google, Facebook, and Amazon that deal with customers almost completely online. They live and die on this data, using it to improve the way they interact with customers every day. Such companies can afford to run big, expensive and complex data processing operations that crunch billions of pieces of data on what their online viewers are clicking on, viewing, writing about, and purchasing.
Because they deal with much larger volumes of data than the average company (which does not do the vast majority of its customers interactions online), Google, Facebook and Amazon can do lots of experimentation with much smaller volumes of data. They can work on insufficient data sets and pre-production/test versions of systems. Then they can modify them, introduce new ones, and unleash new online innovations that keep their customers in tow.
That is how these firms have been able to monopolize their markets. Google sites had 63% share of the U.S search engine market in early 2017, according to market researcher Statista. Facebook was on track to gain 78% of the U.S. social media advertising market in 2017, according to Statista. And Amazon’s share of U.S. e-commerce sales (43.5%) is six times the next biggest player’s (eBay, at 6.8%), says eMarketer.
That brings us to the topic of artificial intelligence. To be able to use AI well, a company must have a huge amount of digital data. Small companies, including startups, can have great ideas for new businesses that run on AI. But they have a huge data disadvantage when they compete against the big digital players.
Which makes me wonder: Will AI be a big competitive advantage for the big digital companies only?
– Artificial intelligence is a new electricity
– Machine, when you will become closer to me?
– Will a basic income guarantee be necessary when machines take our jobs?
– Can machines tell right from wrong?
– Medicine of the future – computerized health enhancement
– Machine Learning. Computers coming of age
– The brain – the device that becomes obsolete
The real question is about our role, multi dimensional question…
brace yourselves- they are coming 🙂
The most essential thing that our society must do as these technologies advance is to have an open conversation about where we want humanity to go as a species. These technologies are being rapidly developed with no signs of slowing down, so it is up to us to decide how far down this road we want transhumanism to go. Unless we do, the transhuman future we will get may not necessarily be the one that we want.
Not only technology. Leaders/people as well
Neural networks as creative agents have some advantages. They excel at being trained on large datasets, identifying the patterns in those datasets, and producing output that follows those same rules. Music inspired by or written by AI has become a growing subgenre—there’s even a pop album by human-machine collaborators called the Songularity.
Just another of many articles that continues to drip feed the incorrect, false information regarding AI and ML.
For Eg.” by the way, all this raises doubts about the claim that machines will never be able to experience human emotions and feelings. But that deserves a separate article.”
Well, here’s a few of those articles.
Adam Spark Two
All AI is is an abstraction or map of another system. If navigating said map is less expensive than navigating the system it maps, it is said to be intelligent.
A triangle responds (selectively causes) local futures that are different from those caused by squares. A triangle (or a square or any other shape) is therefore an example of intelligence every bit as valid as is a brain or a electronic computer.
In my view, the same issue that permeates the AI can be said about any technology being hyped right now, such as Block Chain or ML. The issue becomes that the technology itself becomes bigger than the problem or benefit it’s supposedly offering.
The same issue keeps popping up, what is it that we’re trying to accomplish, in an effective manner. If the proposed solution isn’t efficient, productive or effective vs the CURRENT environment, there is never going to be a tipping point toward mass adoption.
Only recently have I become interested in the AI field. I am a retired business consultant with a very strong passion for studying the lotteries in general. That has been a long time hobby and I have constructed some systems in Delphi to analyse lotto characteristics and behaviours.
For many on-demand platforms, algorithmic management has completely replaced the decision-making roles previously occupied by shift supervisors, foremen and middle- to upper- level management. Uber actually refers to its algorithms as “decision engines”. These “decision engines” track, log and crunch millions of metrics every day, from ride frequency to the harshness with which individual drivers brake. It then uses these analytics to deliver gamified prompts perfectly matched to drivers’ data profiles.
I really enjoyed reading your article. Truly inspiring, as I am currently diving into the world of AI.
Fantastic read! Thank you for sharing.
Automation and Artificial Intelligence will accelerate technical, social and emotional skills in the workforce.
Robotic process automation covering more and more rules based tasks is inevitable and you are right that it may bring unexpected side effects like creating more jobs or increasing creativity of those released from boring tasks ..:)
In 69% of the opportunities to use AI are in improving the performance of existing analytics use cases. Deep neural networks can be used to improve performance beyond that provided by other analytic techniques.
Adversarial. Probability will suffice for this problem, machine learning will be used only if you have an unlimited amount of tries or have a large amount of historical data
Neural networks are a subset of machine learning techniques. Essentially, they are AI systems based on simulating connected “neural units,” loosely modeling the way that neurons interact in the brain. As computer processing power has increased we see that large training data sets have been used to successfully analyze input data such as images, video, and speech. AI practitioners refer to these techniques as “deep learning,” since neural networks have many (“deep”) layers of simulated interconnected neurons.
it is only matter of time and broader cloud adoption when any size company will be able to benefit and effectively compete in that space
cloud as a enabler for AI propagation?
At them moment I think so. In the future… think of who knew Google 20 y ago and FB 15? And what about China speed and expansion? Disruption may happen in just 5 y from now.
Who is going to lead the race? And should we be afraid of super intelligence?
Adam Spark Two
At the moment – yes. But I belive that in next few years AI will be available as lot of SaaS platforms for specific purposes also for medium/small companies.
AI as a platform?
New economy industry rulez
nice and short. all the best
From one who has only a layman’s level of computer knowledge, over thirty years of self-taught kludging, I have seen the collapse of the first Tech bubble, the market crash of ten years ago, and am now trying to weigh the best options to balance our retirement funds so as to protect best leading in to what I expect to be the next economic decline. I don’t worry as much about outright crashes immediately, but do foresee how too much blind infatuation with cryptocurrencies, as well as the consequences for global governments and institutions, could create massive problems, should wide adoption compromise established systems for taxation and security.
2018-2020 gonna be about AI !
Adam Spark Two
The goverment in a developed country will know much more than GAF, esspecially about your finance and health. In general big player can more but… it must have a will to act. Big and fat cats will always give place to those who are hungry. In my humble opinion AI will give us new big players coming from merge of government data and private innovation.
why private only, not public as well?
Humans are nothing but a bunch of atoms.