In the last few years, Artificial intelligence (AI) has taken its roots almost in every domain; from chatbots to virtual assistants like Siri and Alexa, to automated industrial machinery and self-driving cars. While this is often true, machine learning(ML) acts as a spinal cord for AI applications and advanced software algorithms which are designed to carry out one specific task, such as answering questions, translating languages, or navigating a journey and thereafter mastering the art by getting exposed to data. Global government spending on AI tech has touched $500 billion in 2023. This article shall be highlighting AI top trends for 2023.
The Ongoing Democratization Of AI
Fortunately, AI will be able to realise its full potential in 2023, and doing so will be simpler than ever. No matter one’s level of technical expertise, these constantly expanding apps have put AI at everyone’s fingertips. This can be understood more simply. Similar to how predictive text suggestions cut down on the amount of typing required to conduct searches or send emails, apps enable us to produce complex visualisations and reports with just a few mouse clicks. With the aid of no-code and low-code platforms, it’s rather easy to create your own app if you feel there isn’t one already available that meets your needs. At the end of the day, AI will enable democratisation and solve the problems brought about by the AI skills gap.
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Generative AI
Although much of science has been utilized for AI applications, one thing which scientists are trying to incorporate into machines is- creativity. Generative AI algorithms use previous actual data to create entirely new content that never existed in the non-digital world and take existing data. To name generative AI model could be GPT-3, which was developed by OpenAI capable to create text and prose close to humans. Another example could be DALL-E which creates images by achieving mainstream exposure. For 2023, the frequency of creating such synthetic data that can be used by businesses for all domains shall be increased.
Ethical And Explainable AI
In 2023 there will be efforts to overcome the “black box” problem of AI. To make machines work as close as humans, AI requires data which often means personal data like health or financial data. If we, as a layman, will not trust AI, we simply cannot feel safe giving our data, and the whole thing will fall apart. Those responsible to put AI functionalities fall in place shall be working harder so as to ensure that they are able to explain how decision-making is done and what data is used. The role of AI ethics shall help to eliminate bias and unfairness from automated decision-making systems.
Augmented Working
In 2023, robots and smart machines moving around shall not be a surprising thing. Rather these shall be specifically designed to help us do everything efficiently and shall become indispensable work skills. To name a few- smart handsets give us instant access to data, as we have seen increasingly used in retail as well as industrial workplaces, or it could also mean, augmented reality (AR) enabled headsets that overlay digital information on the world around us. The pros are that real-time information is provided which can help identify risks, and give an instant up-to-the-minute nutshell of the operational effectiveness. AI-powered virtual assistants will also become a commoner which shall be able to quickly answer questions as well as automatically suggest an alternative.
Sustainable AI
In 2023 all corporates shall be under immense pressure for reducing their carbon footprint and thereby minimize any negative impact on the environment. In this context, the race for the adoption of AI could be both a blessing and a disguise. AI algorithms and the infrastructure needed to embrace them, such as cloud networks or edge devices shall require greater resources. It’s an astonishing fact but a single DL model could result in the emission of 284,000 kilograms of CO2. As a part of developing a sustainable AI, more green and renewable energy-powered infrastructures are deployed which can make AI a driver of sustainability in other industries and areas of operation, too. We can quote the example of computer vision which is used in conjunction with satellite imagery to identify deforestation and illegal logging, and illegal fishing, which in turn impacts the biodiversity of oceans.
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