What is Blockchain?
If you have been following banking, investing, or cryptocurrency over the last ten years, you may be familiar with “blockchain,” the record-keeping technology behind bitcoin. And there’s a good chance that it only makes so much sense. In trying to learn more about blockchain, you’ve probably encountered a definition like this: “blockchain is a distributed, decentralized, public ledger.”
If this technology is so complex, why call it “blockchain?” At its most basic level, blockchain is literally just a chain of blocks, but not in the traditional sense of those words. When we say the words “block” and “chain” in this context, we are actually talking about digital information (the “block”) stored in a public database (the “chain”).
A simple analogy for understanding blockchain technology is a Google Doc. When we create a document and share it with a group of people, the document is distributed instead of copied or transferred. This creates a decentralized distribution chain that gives everyone access to the document at the same time. No one is locked out awaiting changes from another party, while all modifications to the doc are being recorded in real-time, making changes completely transparent.
What is Artificial Intelligence?
Artificial intelligence is a technology that is already impacting how users interact with, and are affected by the Internet. In the near future, its impact is likely to only continue to grow. AI has the potential to vastly change the way that humans interact, not only with the digital world, but also with each other, through their work and through other socioeconomic institutions – for better or for worse.
If we are to ensure that the impact of artificial intelligence will be positive, it will be essential that all stakeholders participate in the debates surrounding AI.
In this paper, we seek to provide an introduction to AI to policymakers and other stakeholders in the wider Internet ecosystem.
What is Machine Learning?
Machine Learning is a sub-area of artificial intelligence, whereby the term refers to the ability of IT systems to independently find solutions to problems by recognizing patterns in databases. In other words: Machine Learning enables IT systems to recognize patterns on the basis of existing algorithms and data sets and to develop adequate solution concepts. Therefore, in Machine Learning, artificial knowledge is generated on the basis of experience.
In order to enable the software to independently generate solutions, the prior action of people is necessary. For example, the required algorithms and data must be fed into the systems in advance and the respective analysis rules for the recognition of patterns in the data stock must be defined.
Internet of things
What is IOT ?
Typically, Internet of Things devices have sensors and software that enable the collection and exchange of data via the internet. IoT objects can be controlled remotely to allow direct integration with computer systems, which, it’s argued, results in economic benefit and improved efficiency for users.
IoT shopping applications, for example, could track a phone’s location to learn a person’s shopping habits. Companies will use this data to target individuals with special offers for their favorite shops and products.
A shopping app could also link to a smart fridge, which would decide what food is needed (based on past consumption) and send the grocery list directly to a person’s phone. In fact, it’s entirely possible a smart fridge could order products automatically without any human interaction.