AI, Blockchain, Machine Learning and Deep Learning are just some of the latest buzzwords and tech terms being used on a daily basis. But how many of us actually know what these terms mean and what the impact of each of these technologies has on the way we do business?
Here we explain what six of the hottest tech buzzwords actually are. So if you’re not a tech whizkid with a very deep knowledge of these topics, you can learn a little more on what each one means and make an impressive and relevant reference when you drop one of these terms in your next conversation.
Artificial Intelligence (AI)
This is probably the one buzzword that we’re actually all relatively sure of, with almost all of us having used this technology before. From our smartphone assistants (Siri, Cortana and Alexa) to self-driving vehicles (probably fewer of us have experienced these before); AI technology is making its way into our everyday lives in almost every way, and particularly within the business context.
So how does AI work? It’s all to do with data. AI capitalizes on data, something that is ever-growing and constantly generated. The conclusion on a fair amount of research is that machines are far-better suited than humans to consume data, and so the technology focus has gone into making machines ‘smart enough’ to do this. By ‘smart enough’ it means that machines are being built with human capabilities, making them capable of interpreting and acting on real life physical surroundings. AI teaches machines to do this; to be creative and interpretive through the use of computer logic.
Not to be confused with AI, although the two are often thought as being interchangeable. Machine Learning is considered an application of AI, and is more focused on making systems learn for themselves. Google’s AutoML project has taken this a step further with researchers having managed to teach machine learning software to build machine learning software (yep!).
The basic premise of machine learning is that machines and programmes don’t need to be taught everything explicitly. Systems can be programmed to be like humans, where we observe, classify and learn from our mistakes, and learn to use this data independently.
Deep learning takes machine learning to a whole new level with the introduction of neural networks. What this means is that systems and programs are modelled on the human brain’s structure and function. Deep learning imitates the way the human brain works; how it handles stimuli and the way we create patterns that influence our decision-making.
Still a little confused on this one? What this means is that deep learning tries to create relationships between stimuli and the responses each one generates from the human brain.
Deep learning uses artificial neural networks, which are structured like the human brain and connected like a web. These networks are hierarchical and this layering means that data is processed in a non-linear approach. Again, what does this mean? Simply put, deep learning builds on machine learning, using the data from a previous layer with the added data of the added neural network layer to create patterns, extract features and produce results.
If, like many others, you’ve always assumed that Blockchain and Bitcoin are the same thing, then keep reading.
Blockchain is a public database that acts as a digital ledger to keep track of cryptocurrency transactions. Blockchains were first introduced to support cryptocurrencies (which is what Bitcoin is), but the benefits of Blockchain can be used across many industries.
In a blockchain, all the storage devices that make up the database are decentralized. Within the blockchain, there are ‘blocks’ which is a growing list of ordered records or transactions. The information inside blocks is unchangeable once entered in. Blocks are time stamped and linked to other blocks to create a record, available to all members within a particular blockchain network. The full visibility into the entire history of a blockchain means that hacking is almost impossible to achieve, so blockchain technology is an absolute work of wonder for security across countless industries.
Data-as-a-Service is an instance of moving storage facilities into the cloud to make the end-user experience significantly better. Data-as-a-Service stores data (mostly business data) in the cloud, in a protected yet accessible space, and makes the useful data available to users on-demand, ignoring their location. For businesses, Data-as-a-Service makes a huge amount of sense, as businesses are becoming more remote, the physical storage of data makes less and less sense. Cloud technology means that data is accessible to the right users, on-demand, in any location. A great example of how data-as-a-service works is within news and media, with Reuters, Bloomberg and Thompson Reuters all existing as businesses that supply data to countless broadcasting companies as a part of their service.
Business Intelligence (BI)
This is the umbrella term covering all the technologies, data systems, applications and collection practices related to business information. These systems extract key pieces of data and information to ultimately enhance the strategic planning and decision-making processes within businesses.
BI systems can provide a huge amount of data to businesses, including historical, current and predictive data on business performance and industry trends. The BI information extracted can realise a company’s growth, help it perform better and improve its competitive advantage.
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