Top Artificial Intelligence Trends to watch out for in 2023

In today’s fast-paced world, artificial intelligence is the buzzword of choice in the tech industry. Numerous industries worldwide are benefiting from autonomous systems, cybersecurity, automation, RPA, and other advantages provided by AI models.

To boost productivity and efficiency smoothly, tech and data-driven businesses need to be aware of emerging artificial intelligence trends. We can expect to see the continued development of machine learning algorithms, increased use of AI in healthcare, including diagnosis and treatment recommendations, development of autonomous vehicles, growth of AI-powered IoT, and more.

Let’s look at some of the most impactful AI trends for 2023 in the fiercely competitive tech market.

AI in predictive analytics

Predictive analytics did not just suddenly appear; instead, as one follows its history, it emerged from the realm of mathematics and statistics and is now one of the top artificial intelligence trends. The development of predictive analytics is based on data, statistical algorithms, and machine learning (ML) methods to determine future outcomes using historical data. The aim will continue to be to make the most accurate prediction of what will happen in the future by drawing on past knowledge.

AI models across industries

AI models cover every field, from network and infrastructure security to data integrity. As AI models evolve, they will permeate every sphere using domain knowledge to extract features from raw data to improve the performance of machine learning models. AI models will be used to create more meaningful features for the problem at hand, i.e., models will learn from data effectively and make better predictions.

AI in everyday tasks

We can classify how AI is helpful in improving the functionalities of everyday life into two broad streams: hardware and software. The hardware side of AI includes its use in self-driven vehicles, drones, the Internet of Things (IoT), assembly-line robots, and more. As for AI-enabled software, you have voice assistants, image recognition for face unlock in mobile phones, and ML-based financial fraud detection.

Some everyday indoor tasks that could be completed with AI models include

  • Turning lights on or off
  • Setting the temperature
  • Opening or closing blinds
  • Speech recognition in voice assistants like Siri or Alexa
  • Automatic text recognition on your smartphone
  • Fraud detection by your bank
  • Product recommendations on e-commerce websites
  • Speech recognition in voice assistants like Siri or Alexa

Some everyday outdoor tasks that AI models will take over include:

  • Automated agricultural tasks like soil moisture monitoring, planting, watering, and harvesting
  • Traffic control and monitoring
  • Predicting traffic patterns to optimize routing
  • Weather monitoring and prediction
  • Air quality monitoring

Autonomous systems

AI models will catalyze the development of drone technology and autonomous exploration for the future generation of autonomous systems. Technology like machine learning will enable greater adaptability, independent thinking, and appropriate response—for instance, self-driving ambulances. Self-driving cars are already a reality, and AI will likely play a role in developing other new automotive technologies. For example, AI could develop cars that can park themselves, create safer driving conditions, and reduce traffic congestion. Another example is in healthcare, as in prosthetic legs that automatically adapt to a wearer’s gait.

AI in art to empower artists

NFTs allow artists to create unique works of art that can be sold and traded on the blockchain, providing a new level of authenticity and provenance for artworks. Additionally, NFTs offer a new way for artists to generate revenue from their work, as they can sell their art directly to collectors and investors, having greater control over their success. Artificial Intelligence applications are expected to allow voice commands to create art, which can be personalized further.

Digital avatars to be more lifelike

Digital avatars are commonly used in video games, online chatrooms, and virtual worlds. There is increasing use of artificial intelligence (AI) to create realistic 3D models of people and to animate the avatars so that they move and behave like real people. It will help create believable and immersive experiences in games and virtual worlds. As the technology continues to develop, AI-powered avatars will likely become even more realistic and lifelike.

Conversational AI applications

According to a report by Gartner, by 2023, 85% of customer interactions will be without human interaction. This suggests that conversational AI applications will become increasingly important in managing customer interactions. There are many potential applications for conversational AI in customer service, sales, marketing, and human resources. For example, customer service chatbots can handle customer queries, complaints, and requests. Sales chatbots can provide product information and pricing, while marketing chatbots can provide personalized recommendations and deliver targeted content. And human resources chatbots can assist with recruitment, onboarding, and training.

AI in healthcare

Machine Learning (ML) and Deep Learning have been the most common forms of artificial intelligence in the healthcare industry. While Artificial Intelligence in healthcare is primarily pathology-assisted diagnosis, intelligent imaging, medical robots, and analyzing patient records will predict patient outcomes and recommend treatment options. Additionally, AI-embedded applications will include more image processing systems, as in medical imaging. AI will likely take over managing patient data and reduce the time needed to complete tasks.

Large language models with AI

The use of AI in Large Language Models (LLM) is to help the machine learning algorithm learn the relationships between words in a text corpus. The algorithm then creates a mathematical model of the relationships between the words in the text corpus. This model can predict the probability of a word appearing in a new text document. Future AI models are expected to do more than merely reflect the data but will show our chosen values.

AI to predict crypto markets

As AI applications can take into account a vast amount of data, it is particularly well-suited to predicting the volatile and ever-changing crypto markets. Global events and individual news stories drive these markets, and AI can still make accurate predictions. AI will expand its usefulness by making decisions on when to buy and sell cryptocurrencies, and it can even be used to trade on behalf of investors automatically.

Deep fakes in the media

We will see more democratization of AI through pre-trained models in the Open Source community, like an update from Open AI on GPT. It will significantly impact NLP, and expand into end-user applications such as Chatbots. As deep fakes continue to plague our media, filtering content will likely improve. With more regulation in AI ethics, we will also have stricter GMLP (Good ML Practices) that will adhere to FDA regulations.

To conclude

While AI-enabled services will become more specialized, we will also find more pre-trained AI models across all industries. As we move into 2023 and beyond, it’s clear that AI will play an increasingly significant role in our lives. Businesses are already beginning to adopt AI technologies to gain a competitive edge, and, likely, AI will soon become a staple in many homes. With the rapid advances in AI technology, it’s hard to predict exactly what the future holds for us. However, the emerging trends in AI mentioned in this blog will change the way we live and work.

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