The tech industry is always changing and it is always adapting as well. If you run a business then you need to make sure that you do everything you can to look out for these top growth sectors. With the UK leading the march when it comes to digital growth, output and innovation, it’s safe to say that it is now the digital capital of Europe and that it has also pushed boundaries more than ever before. The UK digital tech investment has now reached £6.8 billion and it’s estimated that there are over 1.64 million tech jobs available. Even though there is a looming uncertainty about the future, it’s safe to say that technology is probably one of the few industries that is going to thrive for years to come. There are so many industries which are being bolstered as a result as well, and this includes AI, Fintech and Big Data.
How Fast Is The Tech Industry Growing?
So how fast is the tech sector growing right now? It’s said that by the year 2020, there are going to be over 50 billion smart devices across the world. The smart devices are going to be analysing, collecting and sharing data. The web-hosting market is going to be reaching around $77.8 billion by the year 2025, and 70% of tech spending is going to be for cloud solutions. On top of that, there are around 1.35 million start-ups in the world of tech too. The global AI market is going to reach $89.8 billion too. Other statistics include the fact that there are around 4,383 million internet users and that solar adoption is growing. Right now it looks to have grown by over 50% and this alone shows how far things have come. If you found some of these statistics absolutely mind-blowing then here are some more facts about the tech sector and the total growth that it is experiencing. Gaming is a key part of this growth area. Companies such as AspireGlobal with its B2c Brand Karamba
bringing together the latest gaming technologies to users across the globe. From cutting edge graphics and new-age physics engines, the future of gaming is here.
Growth in Circuit Chips and Moore’s Law
It is said that every 18 months or so, computer processing speeds are able to double. This is otherwise known as Moore’s Law. It’s also important to know that the number of transistors that can fit into a microprocessor now stands at over 10 billion. This was in the year 2017. When you look at the year 1971 on the other hand, you will see that it was actually under 10,000. The latter proves Moore’s Law. In the last few years, it looks like things have slowed down a bit. Tech reached nano-size capabilities and now researchers are finding it hard to try and find new and creative ways to try and advance it. On top of this, the equipment for nanotech is not cheap to say the least. When you look at Moore’s Law you will soon see that it has become outdated and that the current methods for developing new tech are not showing as many positive results as before.
Technology is becoming more and more progressive and this is evident when you look at how transistors have been developing. Things are getting smaller and smaller. Right now, there are transistors that are over 14 nano-meters across that are being made. This is only 14 times bigger when compared to the standard DNA molecule. Transistors are now at the size of 17 silicon atoms. The smallest, yet functional transistor is 1-nanometer big. This is just another reason why tech is able to grow so quickly.
Technology statistics have shown time and time again that the market revenue from the tech market is going to carry on growing. It is expected to reach an astonishing amount in the next few years and big data is going to reach $103 billion in total revenue. The amount of websites that are live is also going to reach over $1.6 billion too. The website hosting market, by the year 2025, is going to reach $77.8 billion and of course, you have to take into account cloud platforms too.
The Big Three
The big three tech industries that are going to grow include:
So now we know how fast tech is growing and how it is able to advance so much, it’s now time to look at tech that is going to really rocket. One of them is Fintech. It is estimated that around 10% of the UK’s GDP is made up of financial services. There are always opportunities to grow when you look at financial tech and there are also so many job sectors that are growing as well. Millions of investors are drawn to the industry every single year and it is one of the fastest-growing sectors too.
Smart technology, self-driving cars and more are really becoming a reality in this day and age. By the looks of things, technological advances are going to carry on as well. If you want to find out more about that then simply take a look below.
What are the Four Types of AI?
There are four different types of AI. They can be found below:
The most basic of AI systems are actually reactive. They don’t have the ability to form memories and they are not able to use past experiences to inform current decisions either. When you look at the Deep Blue, which is a chess-playing super system, you will soon see that it was able to beat Garry Kasparov in the 1990s. This is an ideal example of this type of machine. Deep Blue is able to identify the pieces on a chessboard and it can also work out how things move. It even has the ability to make predictions as to what might be next, and it can also choose the optimal move in any given situation. It doesn’t however have the ability to remember anything from the past or anything that has happened before. When you look at the rule of not repeating a move three times, you will soon see that the computer excels at things like this. The computer is able to perceive the world directly and it can also act on what it sees. The main reason why they are called reactive systems is because the machines will react in the same way every single time they encounter a situation. This can be good at making sure that the AI is trustworthy and that it is also able to be counted on time and time again. These AI systems won’t ever become bored, disinterested or sad, and this alone makes them the ideal and most reliable choice for self-driving cars.
The Type II class contains various machines that are able to look into the past. Self-driving cars are able to do some aspects of this already. For example, they are able to observe the speed and even the direction of another car. This cannot be done in a single moment but it can be done if you identify the objects and then monitor the total speed. This needs to be done over a set period of time and it requires extensive monitoring as well. The observations that are added to a programmed response and they are also based on representations of the real world as well. Of course, this does include lane markings, traffic lights and more. It even includes curves in the road. These simple pieces of information are about the past but they are transient. They are not saved in the car’s library of experience but they can learn from and compile experience over the years when you look at the way someone behaves from behind the wheel.
Theory of Mind
Another thing that you need to think about is theory of mind. This is an important divide between the machines that we have now and the possible machines that we might have in the future. It is far better to be more specific about the representations that the machines need to form and what they might need to be about in the future. Machines in the past are far more advanced and they are able to form representations about the world as well. If AI systems were able to walk amongst us, then they would have to understand that every single one of us has a thought and that this comes with expectations on how people should be treated.
The final step of what AI development is all about is self-awareness. People have not yet been able to get to this stage because AI researchers need to understand consciousness and they also need to be able to build machines that have it. This is, in a sense, theory of mind. It is possessed by Type III artificial intelligence. We are probably quite some time away from being able to create machines that are this self-aware but it’s important that we focus our minds and our understanding on memory and the ability to base all decisions on past experiences. This is a very important step when it comes to creating human intelligence and it is crucial if we want to design or even evolve machines that have a level of intelligence as well.
What’s the Difference between AR and VR?
AR essentially adds different elements to a live view. This is often done by using the camera on a smartphone. Examples of this include Snapchat lenses or even Pokemon Go. VR on the other hand implies complete immersion as it shuts out the physical world. Using VR devices that include Google Cardboard or even Oculus Rift gives you the chance to transition yourself to the real world of VR as well as helping you to become part of something that you would otherwise not have been able to be part of. When you look at MR on the other hand, you will soon see that this combines both elements of AR and VR. Microsoft Hololens is a prime example of this.
- Big Data
It’s safe to say that big data, means big news. It is going to get even bigger in the next few years and as society moves on, vast amounts of data are then going to be collected. This is going to provide businesses with actionable insights that will help them to process way more data and in a very short space of time. Some say that big data could even be used to try and improve data production as well, which is very interesting to say the least.
Why We Need To Improve Food Production?
When you look at the last century, you will soon see that the population across the globe has quadrupled. There were around 1.8 billion people in the world and today, there are 7.3 billion. It’s possible that we are going to reach 9.7 billion by the year 2050. Of course, this growth, when combined with the rising income developments are ultimately going to mean a much bigger demand for food. The problem is that the ecological and social consequences that come with clearing more land are often high and this is especially when you look at the tropics. Crop yields are growing far too slowly in order for anyone to meet the forecasted food demand. Other factors, such as climate change or even urbanisation are going to make it very challenging for people to try and meet the right demands. Some are hopeful that big data is going to help us to know what we need to do in order to try and meet this demand, but right now, only time will tell.