Current trends to watch in AI

Recent developments in artificial intelligence (AI) include explainable AI, generative A, sustainable AI, and democratization of AI. Other notable developments include the use of AI in cybersecurity and quantum computing, as well as the increasing importance of AI ethics.

A lot of development has taken place in the field of technology and AI recently. We've structured this for you and arranged the most captivating tendencies in the field. These are the latest, most interesting and game changing developments in AI:
1.     Explainable AI- the black box problem

With most AI tools such as deep learning neural networks, we don’t know why outputs are what they are. Algorithms don’t explain how they produce their outcome. As organizations have more and more access to sensitive data such as financial information, concern grows about the ethics of using AI to make certain decisions. For example, hospitals and banks are using artificial intelligence to process data and make certain decisions, such as which patient gets access to what types of treatment and when. Banks use algorithms to determine if clients can be granted a loan. This is why explainable and ethical AI is being perceived as a strategic differentiator for businesses, according to Forbes. A deepened understanding of why algorithms do what they do and why can offer a huge advantage. According to author Bernand Marr, in 2023 there will be more attempts to develop systems that offer explanations on the way output is produced by AI.

2.     Generative AI

AI is generally perceived as being used mostly for routine tasks. However, there is a whole branch in development focusing on trying to recreate human originality: generalized AI. Large image and language models can be used to generate text that can be of equal or even higher quality than those written by humans. Generative AI aims to take existing information such as images, videos, or even sounds to create unique content. A well-known application is a model called GPT-3, designed by OpenAI. This is a neural network model created to take text and transform it to sophisticated and relevant content in every writing style imaginable. This machine learning model can write blogs and social media posts, and even poetry in the style of Shakespeare.

3.     Augmented workforce

The term augmented workforce is used to describe humans working alongside AI, optimizing efficiency. Employees could be working side to side with digital workers and robots. Augmented workforce could be able to perform tasks that are high safety risk to humans and predict hazards. For example, models will be used to reduce and predict accidents on the workfloor. It also creates the opportunity for AI to take on repetitive work that humans aren’t willing to do any more. In the future, the workfloor will be more hybrid and alternate robot employees with humans.

4.     Sustainable AI

The worldwide known research institute Gartner revealed that sustainability in technology has risen to be one of the top priorities for a lot of executives. The need for IT services that are more efficient with energy and C02 is expanding, as studies revealed that training one deep learning model can exceed the emission of 284.000 kilograms of C02, and can cause lots of harm to the environment. If companies invest in more sustainable technology frameworks, they can reduce their environmental impact and increase their power efficiency. The Gartner research also stated that the use of more sustainable technology will also optimize costs. In addition, the research institute has predicted that by 2025, more than 50% of top executives will implement data to track development on sustainability of their organization.

5.     Democratization

Democratization of AI signifies a shift in users. Instead of being reserved for those with specialized knowledge, its technology becomes available for a bigger base of users. By the democratization of AI and use of machine learning models more companies can reap the benefits that it offers. Now, different apps and programs like Google Teachable machine offer a variety of tools for non-professionals to build their own AI systems. This way, machine learning will become a common business strategy, according to software company Sagacify.

Finally, the takeaway is that there is an ongoing interest for developing more explainable AI that also shows key insights on how certain certain outcomes are produced. Explainable and ethical AI will become a strategic differentiator for businesses. There is also a growing branch that specifies in generative technology that produces human-like creative content that is unique and is available in every production style. In the future augmented workforce will cause a blend between robotic employees and human workers, optimizing efficiency and reducing safety risks by taking on repetitive and potentially dangerous tasks. As the demand for sustainable AI grows, companies will start to invest in analytics to track their progress on power efficiency. And lastly, the democratization of AI will cause non-professionals to get access to build their own technology systems and make machine learning a more common business strategy.

Are you interested in what these trends can do for your business? Contact us via our Baise website and let us know what you're looking for. We offer our personal advice and expertise on AI for your company. Our aim is to connect brains with business by providing you with talented and ambitious students looking to gain real experience in the field.

All images created by DALL-E

Published on
June 14, 2023

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