The Top 5 AI Trends In 2024

30th November 2022 changed the game in artificial intelligence forever. As soon as OpenAI launched ChatGPT on this date, the world went wild. And, by 2023 it became part of every conversation in the business world.

And now 2024 is pivotal for AI, as researchers and organizations seek ways to make it a part of our lives - we shift our focus from experimentation to real-world applications. As AI is developed, deployed, and regulated, there seems to be heightened caution and questions about ethics and safety.

For season 2024, here are the top 5 AI learning trends!

1. Open Source AI

GenAI and large language systems need a lot of data and computation to be powerful - it can be pretty crazy expensive.

Open-source AI comes in handy here. It allows developers to capitalize on each other's work at a fraction of the cost and broaden AI's reach. Open-source AI models are typically free and public for all.

Last year, GitHub data revealed a significant increase in developer engagement with artificial intelligence, especially generative algorithms. Thousands of first-time contributors contributed to projects such as Stable Diffusion in 2023 when generative AI projects made their debut in the top 10 most popular projects on the code hosting platform.

With access to sophisticated AI tools and models, smaller, less resourced entities could completely change the AI landscape in 2024. It may also cultivate an environment of transparency and ethical development, because of the opportunity for more people to scrutinize code, and the chance of spotting bias, error and security vulnerabilities increases.

However, some experts have also wondered how open-source AI could be misused to spread harmful information. Besides this, the development and management of open source is also considered to be a challenge even when dealing with plain software and not AI models which are complicated and computationally intensive.

2. Multi-modal AI

According to Mark Chen, the chief of frontiers research at OpenAi who presented at EmTech MIT in November 2023, "The interfaces of the world are multimodal." "We want our models to see what we see and hear what we hear, and we want them to also generate content that appeals to more than one of our senses."

Multimodal AI surpasses the single modality of conventional data processing including texts, pictures and sound which is a stepping stone to human supersensuality mode.

There are many applications of multimodal AI technology, all of which are evolving and growing. In the healthcare field, for example, multimodal models can blend medical images with the patient’s history and genetic information to refine diagnostic procedures. The multimodal models allow for the expansion of job functions at the worker level, where employees can now enhance design and programming tasks that otherwise require a formal background in those fields.

3. Shadow AI

People from all sectors have begun using AI for their professional tasks, often without the IT department's approval or permission. This is the issue of Shadow AI.

This trend is ever more visible as AI technology develops to the stage when even non-technical workers can use it independently. Shadow AI tacitly arises as employees try to find a quick fix to a critical issue, or simply want to respond quickly than the authorization process makes it possible. This is particularly true for AI chatbots that are easy to use and invoke without the need to go through the IT approval process.

At the same time, looking at how emerging technologies can be put to these uses means being constructive, proactive, smart and open-minded. However, just as it brings substantial opportunity, it also increases risk because ordinary users often lack technical knowledge regarding security, data privacy and compliance issues.

Shadow AI awareness and implementation is expected to be a critical task for organizations in 2024. The frameworks will include governance mechanisms to balance support and protection of innovation, individual rights and business security. This would encompass establishing specific AI use guidelines and approved platforms of choice in addition to the joint IT and business leaders’ information dissemination so that they know the various departments’ needs for AI use.

4. An increased focus on AI ethics and security

AI ethics and security concerns are a new discussion that has recently shifted the focus from theoretical to practical.

A growing number of deepfakes and advanced AI-produced content are causing worries that lie in imitation and deceptive messages or statements as well as identity theft, among others. Another significant way AI is changing security is that it makes ransomware and phishing attacks more effective, realistic, flexible and difficult to detect.

The fact that technological inventions are going towards identifying AI-created content indicates that it remains a big dilemma. Present is the fact that mainstream AI watermarking techniques are not resistant to technical manipulation, and these can cause false alarms in AI detection software.

AI systems becoming more popular also bring out this significance, i.e., they should be transparent and fair no matter what the case is like. The training data and the algorithms should be checked for biases.

Indeed, from that point of view and also considering ethics and security questions, the next year will be a milestone for AI regulation, which is intended to be developed with laws, policies and industry frameworks throughout the US and around the world. It is going to be crucial for companies to be well-informed and adaptable in the times to come given the fact that changing compliance rules might have a profound influence on operations on a global scale and strategies for AI development.

5. Increased demand for AI and machine learning talent

Developing, training and testing a machine learning model is a challenging job -- at least deploying it to production and maintaining it in an advanced information technology setting. This is, of course, the reason that the growth of demand for AI and machine learning experts is expected to continue into 2024 and beyond.

Artificial Intelligence (AI) and Machine Learning are increasingly integrated into organizational management processes, which means there is greater demand for individuals who can connect theory and practice. Therefore, the skill of implementing, monitoring and maintaining AI tools is also in demand - this is usually called MLOps or Machine Learning Operations.

A survey conducted by O’Reilly concluded that AI programming, data analysis and statistics, and AI/ML operation were the top three skills that companies needed for their generative AI projects. Compared to these abilities and the demand for them, there are few with them.

In 2024, expect to see many businesses, in particular, start-ups looking for potential employees with these types of skills. Thanks to the fact that IT and data are almost always present as business functions and with AI projects rising, digital transformation will move to in-house AI and machine learning capabilities.

Conclusion

These 5 will set the course for the future of AI and our lives as well. AI agentics, retrieval-augmented generation, and customized enterprise generative AI models are some of the other hottest trends for 2024. Which one are you most excited about? It's the 5th one for me!