Artificial IntelligenceTrends

As the cloud is a basic component of the Internet of Things (IoT) and it will be increasingly developed by artificial intelligence, the IoT will become more and more intelligent, ultimately changing into the IoE or Internet of Everything, writes ADM Hosting Managing Partner Klemens Arro.

According to him, IoE can translate spoken speech in real time or instantly recognize faces without error. This, in turn, will mean new services and new products.

The following is a comment by Klemens Arro on the future of cloud technology:

90% of the data in the world was generated in the last two years. This unprecedented volume of data that we use and create daily is growing at unprecedented speeds. On one hand, 3.7 billion internet users generate new data daily, but, on the other, there are more and more devices connected to the internet that are also creating endless strings of data.

All of this existing and new data must be securely saved somewhere while retaining 24-7 access to it. The most effective solution is cloud technology, which is developing at a very fast pace – predictions say that by 2020, 60-70% of all hardware, services and technologies will be cloud-based. What are the worthwhile future developments in cloud technology?

The Hybrid Cloud is a Passing Trend

Right now, the hybrid cloud is gaining popularity. This means that part of your data and applications is on the cloud and the other part on in-house servers. But the hybrid is a passing trend and will become a niche solution in the future. In the near future, most solutions will have moved to cloud servers and new solutions will be designed for the cloud from the get-go, i.e. they will be cloud native.

Therefore, on-premises solutions will start to fade out, though they will never be completely obsolete. For example, organizations with geographic restrictions and top-secret data will continue to use them as will services that need a local ultra-low latency but move very large amounts of local data.

And yet, it’s probable that the larger cloud service providers will start offering these so-called on-premises devices as well. They’ll also offer hardware devices for other cases, such as cloud services that can be duplicated to run locally on the service provider’s hardware. In that case, when there is an external network, the whole solution works at cloud efficiency but when there is no network, it continues to run on the local device.

What’s clear is that the period of migrating data over to the cloud will be very long and that time will see a lot of options for different types of cloud services, which will help speed up the creation of a hybrid cloud and keep it in operation.

Will it All Eventually Start to Work Together?

There has been much talk of interoperability, or an ideal world where all devices and new versions of them will immediately understand what solutions already exist and what these need. Though I would say that I see a clear development in this direction, unfortunately I don’t believe that this interoperability will remain central to different ecosystems.

The reason is standards – often a general standard for communication between applications is created but companies and communities then find that their solutions based on the current standard are faster, more powerful and more eloquent and they still end up making their own version of the existing standard.

Great examples come from Microsoft, Google and Apple: all of their products exist in their own ecosystem where they work together very well. But if you try to make the products from these different providers communicate with each other, it’s either extremely complicated or impossible. At least for now, the same goes for smaller players.

Speeds Will Continue to Grow

The better the services get, the sharper the video image and deeper the sound quality, the more users they have, the more devices are connected to the network, the more data volume they need.

This, in turn, means larger network speeds to move this data to an increasing number of devices and data centres. Of course, the quality and optimality of the solutions will also grow, but not for everyone and not enough. The technological limitations of the current backbone and home networks have created a bottleneck that limits the further development of many services. This has forced large companies like Google to invest big sums in their network infrastructure and technology to achieve larger network speeds. This type of development will continue and will not stop in the near future.

More Artificial Intelligence

The role of artificial intelligence, or AI, has changed and will continue to play a more important role for cloud services. First, AI helps understand data and use it to predict future needs, opportunities and dangers.

The cybersecurity field already uses the cloud and artificial intelligence very aggressively to identify potential security risks and incidents and active attacks. A lot of this used to be done (and often still is) by following different logs and system behaviour patterns. But now, services that use AI are becoming increasingly popular.

This is because, unlike humans, AI can analyze a very large amount of data at once and derive patterns to detect even the most complex problems and attacks. But reaching a point where AI will develop new IT solutions instead of developers means a few more steps to be taken. First, a number of smaller applications are being created for AI that don’t work together very well. As time passes, these will start to cooperate more and more and support each other until one day we will be able to tell the computer what we want to see, and it will do it for you.

The first steps are already being taken – for example, AirBnB is creating an AI that changes hand-drawn schemes into code; Google and others have voice-activated interfaces that are evolving through AI and can understand the context of a conversation (Google even offers its context-tracking capability as a cloud service).

The next phase will be that AI writes its own code, which is not far-fetched. And then, even further in the future, AI will go so far that it will look for the best solutions itself, meaning that it will create code without a command.

For example, AI could analyze the stock of products in an e-store, see a larger surplus than preferable for a certain product, make its own decisions for how to get rid of this, and then automatically make those changes. This change could be a highly targeted landing page, recoding the functionality of the e-store or purchasing precisely targeted ads in external environments.