Artificial intelligence (AI) is constantly evolving and transforming the world around us. From generative AI that can create realistic text, voice, and images, to multimodal AI that can understand and interact with different types of data, AI is reshaping various industries and domains.
But what are the most important AI trends to watch in 2024? How will AI impact our lives and businesses in the coming year? Based on our research and experience, we have identified the top 5 AI trends that will shape the future of AI in 2024. Here they are:
1. Customized and Open Source AI Models
As AI becomes more accessible and affordable, more businesses and developers will adopt customized and open source AI models to meet their specific needs and challenges. Customized AI models are tailored to the data, domain, and goals of the users, while open source AI models are freely available and can be modified and improved by the community.
One example of customized AI is IBM’s geospatial AI foundation model, which was created in partnership with NASA. This model uses satellite data to provide insights and solutions for climate change and geospatial intelligence. Another example is Meta’s LlaMa family of large language models, which are open source and can be fine-tuned and adapted for various tasks and domains.
2. Responsible and Ethical AI
As AI becomes more powerful and pervasive, it also raises more ethical and social issues, such as bias, privacy, accountability, and transparency. Therefore, responsible and ethical AI will be a key trend in 2024, as more stakeholders will demand and implement AI solutions that are fair, explainable, secure, and trustworthy.
One way to achieve responsible and ethical AI is to follow the principles and best practices of the Global AI Ethics Consortium, which is a network of organizations and experts that collaborate to promote and advance AI ethics. Another way is to use tools and frameworks that help measure and mitigate the risks and impacts of AI, such as IBM’s AI Fairness 360, AI Explainability 360, and AI FactSheets 360.
3. Multimodal and Conversational AI
Multimodal and conversational AI are two related trends that will enhance the capabilities and user experience of AI in 2024. Multimodal AI refers to AI systems that can process and generate different types of data, such as text, speech, images, and video. Conversational AI refers to AI systems that can understand and communicate with humans in natural language, such as chatbots, voice assistants, and virtual agents.
Multimodal and conversational AI will enable more natural and intuitive interactions between humans and machines, as well as richer and more personalized content and services. For example, IBM’s Watson Assistant can leverage multimodal AI to provide context-aware and empathetic responses to customers across various channels and devices.
4. Edge and Federated AI
Edge and federated AI are two trends that will improve the performance and privacy of AI in 2024. Edge AI refers to AI systems that run on the edge devices, such as smartphones, tablets, and sensors, rather than on the cloud or centralized servers. Federated AI refers to AI systems that learn from distributed and decentralized data sources, without transferring or exposing the data.
Edge and federated AI will enable faster and more efficient AI applications, as well as more secure and compliant AI solutions. For example, IBM’s Edge Application Manager can help deploy and manage AI models on the edge devices, while IBM’s Federated Learning can help train AI models on the encrypted data from multiple parties.
5. Hybrid and Quantum AI
Hybrid and quantum AI are two trends that will expand the possibilities and potential of AI in 2024. Hybrid AI refers to AI systems that combine different types of AI, such as symbolic AI, neural AI, and evolutionary AI, to achieve higher levels of intelligence and reasoning. Quantum AI refers to AI systems that leverage quantum computing, which is a new paradigm of computing that uses quantum physics to perform complex calculations.
Hybrid and quantum AI will enable more advanced and novel AI applications, as well as more scalable and robust AI solutions. For example, IBM’s Neuro-Symbolic Concept Learner can help integrate symbolic and neural AI to learn from both data and knowledge, while IBM’s Quantum AI Hub can help explore and experiment with quantum AI algorithms and applications.
Conclusion
AI is a dynamic and exciting field that is constantly changing and improving. The trends we have discussed are some of the most important and influential ones that will shape the future of AI in 2024. By following and adopting these trends, you can stay ahead of the curve and leverage AI to achieve your goals and aspirations.
