Every year, new technologies emerge that provide innovative approaches to business challenges and life’s problems. Some of these stand the test of time and others fall by the wayside, leaving room for new technological developments and https://ryuukoi.id/ startups to join the race. It can be difficult to know which emerging tech is worth the investment and which you should pass over. This list will give you a better understanding of technology trends that will last into the next generation and real-world use cases you can expect to see in 2023 and beyond.
1. Artificial Intelligence (AI)
Artificial Intelligence continues to rank at the top of emerging tech. Chatbots and Apple’s Siri are common examples of AI in action, but we will see more complex versions being used in the near future.
Generative AI is taking us one step closer to what we’ve always seen from cinematic tech of the future. ChatGPT, a generative AI technology that utilizes natural language processing and can generate text based on a prompt, caused quite a stir upon its release in November 2022 as leaders evaluated the impact of the technology on business applications, but also tried to anticipate the ethical implications of a technology that can mimic human output. Largely, how can we determine if copy came from people or technology?
2. Internet of Things (IoT)
Internet of Things (IoT) uses connected devices, such as wearables and sensors, to provide more optimal results for businesses.
Trend: Expansion of IoT devices in various industries and increased focus on cybersecurity
IoT devices are becoming increasingly used across various industries. A large part of this expansion derives from the increasing bandwidths we are seeing with 5G. Running parallel to that expansion is the need for increased cybersecurity, particularly with respect to IoT. The open interconnectivity capabilities of IoT have made it a prime candidate for cyberattacks in the past. Providers will refocus their efforts to help ensure IoT is becoming more secure.
3. Machine Learning (ML)
Machine learning has helped technology advance significantly in recent years, giving us the ability to draw insights from massive amounts of data.
While machine learning has offered us many applications in the near past, the major breakthrough in machine learning will involve automated machine learning. Machine learning, while valuable, is highly resource intensive and consumes a ton of time to develop the learning models. With AutoML, many of the iterative and mundane tasks, such as data cleansing and parameter selection, are automated to reduce the burden on technical resources. Using algorithms rather than humans to build learning models, AutoML also allows non-technical people to make better use of the technology.
4. 5G Networks
5G networks have been key for increasing speeds, increasing capacity and reducing latency. The next wave of networks will involve 5G networks that stand alone.
When 5G networks originally rolled out, they were dependent on the 4G core network to provide data transfer and coverage. This allowed for the initial functionality without implementing a whole new infrastructure. Now, with the development of 5G standalone (5G SA) networks, users will have access to greater coverage and will experience lower latency. Utilizing a cloud-based architecture, 5G SA will provide a better user experience and pave the way for technologies such as autonomous vehicle automation and precision robotics.
5. Edge Computing
According to Deloitte, U.S. households have an average of 22 connected devices. Edge computing may well be the answer to managing big data.
The sheer number of devices being used on a regular basis is staggering and the amount of data that is created is astronomical in size. If all that data had to cross a network and be processed in a data center, users would see very low latency and long wait times for data analysis and insights. Edge computing allows this data to be processed closer to the point of creation to minimize the latency and increase speeds. The introduction of more devices in the healthcare and manufacturing fields is causing the adoption of edge computing to help improve patient outcomes and reduce delays in supply chain processes.