Top Artificial Intelligence (AI) Trends to Watch in 2023

As we all move farther into our digitally altered world, artificial intelligence (AI) continues to be a potent transformation catalyst for international sectors and enterprises. In 2023, it is anticipated that governments and corporations will spend more than $500 billion on AI globally. In many areas of our society and daily life, artificial intelligence (AI) has now become integrated. It’s hard to dispute its effect on everything from chatbots and virtual helpers like Siri and Alexa to automated industrial equipment and self-driving cars. The technology most often used to achieve AI today is machine learning, which consists of sophisticated software algorithms designed to perform a single specific task, such as answering questions, translating languages, or navigating a journey, and getting better at it as they are exposed to more and more data.

The list of the most intriguing AI developments to watch out for in 2023 is provided below.

1. Voice and language-driven intelligence

By 2029, the voice and speech recognition industry is projected to have increased from $11.2 billion to $49.7 billion. Smart speaker use in homes significantly increased due to the remote working revolution, and speech solutions focused on streamlining corporate procedures will take center stage in 2023. As internal systems like CRM and business processes become more connected with voice assistants, they will become increasingly adapted to address unique company needs.

2. Ethical and Explainable AI 

For these reasons, it is crucial to create AI models that are more moral and comprehensible. But the most important factor is trust. AI needs data to learn, which frequently consists of personal information. For many of the most valuable and potent AI use cases, this might be extremely private data, such as health or financial information. There will be initiatives to solve the “black box” issue with AI in 2023. Those in charge of installing AI systems will exert more effort to make sure they can communicate how judgments are reached and what data was utilized to reach them. As businesses learn how to remove prejudice and injustice from their automated decision-making systems, AI ethics’ role will also become more important.

3. AI-powered cybersecurity

AI will be applied to proactive cybersecurity projects by 2023. This is mostly caused by the rise in the usage of personal laptops and computers by employees to access company servers, which exposes businesses to online attacks.

This year, it’s expected that more businesses will invest more money using advanced cybersecurity tools to protect their data. Unfortunately, thieves are breaking through traditional IT security measures to access systems that store critical customer and personal data by exploiting AI technology. But AI also aids in the battle against cyber attacks.

4. Generative AI

Using existing data, such as video, photos, sounds, or even computer code, by generative AI algorithms creates new material that has never been in the non-digital world. GPT-3, designed by OpenAI, is one of the most well-known generative AI models. It is capable of producing text and prose that is almost identical to human-written text and writing. Images are created using a GPT-3 variation called DALL-E.

The technique has gained widespread attention thanks to experiments like the well-known deep-faked Tom Cruise films and the Metaphysic act, which dominated this year’s America’s Got Talent. But by 2023, it will be utilized more regularly to generate fake data that organizations may use for various things.

Generative AI is the application of AI to produce novel goods and new objects. While generative AI is mostly used to create media content like lifelike images of people and things, it may also generate code, produce synthetic tabular data, and building materials and medications with certain qualities.

5. Sustainable AI

 By 2023, there will be pressure on all businesses to lessen their environmental effect and carbon footprint. The rush to embrace and benefit from AI might be both a help and a handicap in this regard. The power and resources needed to run AI algorithms and the infrastructure necessary to support and distribute them, including cloud networks and edge devices, are growing.

6. MLOps

The gap between machine learning, data science, and data engineering is filled by MLOps. It has become the connection that more effortlessly connects various operations than ever before. Many human mistakes and quality difficulties can be resolved by the new powerful MLOps apps. Here are a few top MLOps trends and forecasts for 2023 that will undoubtedly become more well-known in the sector.

  • Data-based MLOps
  • Identify Drift
  • Enhancing the value of ML solutions
  • An increase in the amount of MLOps libraries and packages 
  • Transferring AutoML to AutoMLOps

7. Federated learning

 A new area of artificial intelligence called federated learning has ushered in a new era of machine learning. To offer a more specialized experience without sacrificing “user privacy,” it can make use of both the “decentralized data” (data not held in a single location, leaving it susceptible) and the “decentralized computational power” accessible in the current world. Through homomorphic encryption, information sharing between a client and server is feasible without sacrificing user privacy.

Federated learning can be used by self-driving connected automobiles to improve road safety. For federated learning, the following five years will be quite fascinating. The usage of federated learning will be evident in many new apps that improve user experience in ways that were not before feasible.

Tensorflow Federated, a framework for federated learning developed by Google, has already been made available. Although it is still in its infancy, it is a fantastic starting point for learning.

8. Large Language Models (LLMs)

DALL-E 2, an Open AI-developed generative AI, was released in July 2022, sending global waves through the AI community and the general public. Then ChatGPT appeared. Until that point, striking text-to-image models dominated the media.

With the introduction of ChatGPT, a new type of LLM that served as the basis for generative AI and transformative neural networks made a clear exit. They are being hailed as innovative AI disruptors, including for business applications.

Recent developments are already driving a tsunami of AI and machine learning innovation. PaLM 540B and Megatron 530B, two of the biggest models in the world right now, are LLMs. The foundation of ChatGPT is Open AI’s GPT 3.5, released in late November 2022. The much-anticipated release of GPT-4 will probably confirm the increasing consensus that “Transformer AI” is a significant development that will fundamentally alter how AI systems are developed and taught.

Apart from LLMs, we can also expect the trend of LLMOps in the upcoming years.

9. Augmented Working

By 2023, most humans will be working alongside robots and intelligent machines that were created to assist them in performing their tasks more effectively. This may come from smartphones that provide workers immediate access to data and analytics tools since these devices are increasingly utilized in industrial and retail industries. It could refer to headgear with augmented reality (AR) capabilities that project digital information over the environment. AI-powered virtual assistants, who can rapidly respond to inquiries and automatically offer different, more effective ways to achieve goals, will also become increasingly common in the workplace.

10. Increased Personalisation

As people anticipate customized interactions with companies of all stripes, from banking to e-tail, personalized digital experiences have swiftly become the norm. Because of this, machine learning (ML) and artificial intelligence (AI) prediction skills are advancing rapidly, assisting organizations in gaining additional user insights.

Businesses will get a fuller understanding of the personalities behind their users to anticipate better and offer items, and customers will value much enhanced more efficient shopping experiences. The capacity of organizations to implement this level of mass personalization will be the largest advancement in this technology for 2023.

In 2023, AI can be utilized to continue building websites, designing user interfaces, and creating effective marketing plans tailored to individual users’ needs.


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References:

  • https://jimcarroll.com/topics-trends/23-trends-for-2023/
  • https://jimcarroll.com/2022/12/23-trends-for-2023-10-the-massive-velocity-of-a-i/
  • https://wearebrain.com/blog/ai-data-science/ai-trends-for-2023/
  • https://www.linkedin.com/pulse/5-biggest-artificial-intelligence-ai-trends-2023-bernard-marr/
  • https://enterrasolutions.com/trends-2023-artificial-intelligence/
  • https://www.analyticsinsight.net/top-10-mlops-trends-and-predictions-to-lookout-for-in-2023/
  • https://towardsdatascience.com/how-federated-learning-is-going-to-revolutionize-ai-6e0ab580420f
  • https://venturebeat.com/ai/large-language-models-broaden-ais-reach-in-industry-and-enterprises/

Dhanshree Shenwai is a Computer Science Engineer and has a good experience in FinTech companies covering Financial, Cards & Payments and Banking domain with keen interest in applications of AI. She is enthusiastic about exploring new technologies and advancements in today’s evolving world making everyone's life easy.

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