The emergence of Artificial Intelligence (AI), Machine Learning (ML), Robotics and 5G networks have reshaped industries, opened up new applications, and altered our way of life. For instance, precision medicine is enabling patient-specific therapies, and driverless vehicles promise to decrease traffic accidents and increase mobility.
However, technology also poses new problems such as employment displacement and cybersecurity concerns. With good planning and management, technology can continue to advance and help create a better future for everyone.
Here are ten emerging technologies in computer science that will influence the future:
1. Artificial Intelligence and Machine Learning: AI and ML are changing the way people interact with technology. They are driving automation, creating intelligent systems, and enabling new applications in fields such as healthcare, finance, and transportation.
Moreover, AI and ML can be used on blockchains for various purposes, such as fraud detection, risk assessment, and predictive analytics. These algorithms can analyse large amounts of blockchain data to detect suspicious activity and anomalies and make predictions about future trends. They can also be used to automate certain processes, such as smart contract execution and asset management.
2. Quantum Computing: The promise of quantum computing is that it will be able to tackle issues that traditional computers cannot. They use quantum bits (qubits) to carry out calculations concurrently and exponentially more quickly than conventional computers.
One potential use case of quantum computers is in the field of cryptography, where they could be used to break certain types of encryptions that are currently considered secure on classical computers.
3. Blockchain Technology: Blockchain technology's primary use case is the creation of decentralised and secure digital records that can be used for various purposes. One of the most well-known applications of blockchain technology is in the creation of cryptocurrencies like Bitcoin, which are digital assets that can be used as a medium of exchange.
As blockchains provide trust-less and decentralised systems, they enable secure and more effective transactions, particularly in banking, healthcare, and supply chain management.
4. Internet of Things (IoT): IoT refers to the process of connecting physical objects to the internet so they can communicate and collect data. It has applications in fields such as manufacturing and healthcare and can be found in smart homes and wearable technology.
5. Biometrics: Biometrics involves the use of physical or behavioural characteristics, such as fingerprints or facial recognition, for identification and authentication. It has potential applications in areas like banking, healthcare, metaverse, and law enforcement.
6. 5G Networks: The next generation of wireless networks, or 5G networks, offers higher speed and reduced latency than 4G networks. They have the potential to enable new applications like remote surgery and smart transportation systems.
7. Augmented Reality (AR) and Virtual Reality (VR): AR and VR have the potential to enhance the user experience in various fields, including gaming, education, training, and entertainment. Users can interact with digital things in the actual world using AR technology, for instance, and can completely immerse themselves in a virtual environment using VR technology.
8. Autonomous Robots: Autonomous robots can perform tasks without human intervention, and they have the potential to revolutionise industries such as manufacturing, healthcare, and logistics.
9. Edge Computing: Edge computing involves processing data at the edge of the network, closer to where the data is generated. It has the potential to reduce latency and improve response times for applications such as autonomous vehicles and smart homes.
10. Natural Language Processing (NLP): NLP involves the use of machine learning algorithms to process and understand natural language. One example of how NPL is transforming the agricultural industry is through the use of autonomous drones for crop monitoring and management. These drones can be equipped with cameras and sensors that collect data on various aspects of crops, including growth rates, soil moisture content, and plant health.