Nine Important AI Trends for 2024

🔍The trend is towards more realistic expectations of generative AI, with integrated elements complementing existing tools.

📊Multimodal AI, combining natural language processing and computer vision tasks, is expanding the capabilities of AI models.

💡Smaller models are gaining popularity due to their lower resource requirements and cost-effectiveness.

☁️The increasing demand for GPUs and cloud infrastructure is driving up costs for AI training and inference.

🔬Model optimization techniques, such as quantization and low-rank adaptation, are being used to reduce resource usage and improve efficiency.

What is multimodal AI?

—Multimodal AI refers to AI models that can process multiple layers of data, such as text, images, and videos, and perform tasks in multiple domains like natural language processing and computer vision.

Why are smaller models gaining popularity?

—Smaller models require fewer resources, are more cost-effective, and can be run locally on devices like personal laptops, reducing the dependence on cloud infrastructure.

How can model optimization techniques improve efficiency?

—Model optimization techniques like quantization and low-rank adaptation reduce memory usage, speed up inference, and make AI models more resource-efficient.

What are virtual agents?

—Virtual agents are AI-powered assistants that automate tasks and help users complete activities like making reservations, completing checklists, and connecting to other services.

What is shadow AI?

—Shadow AI refers to the unofficial use of AI by employees without proper oversight or approval from the organization, which can pose risks related to security, privacy, and compliance.

00:00The pace of AI in 2024 is expected to be fast and impactful.

00:31Generative AI tools are now being implemented as integrated elements rather than standalone chatbots, leading to more realistic expectations and understanding of AI's capabilities.

01:30Multimodal AI models that can process multiple layers of data are advancing, allowing for more diverse and holistic learning.

02:30Smaller models are gaining popularity due to their lower resource requirements and cost-effectiveness, making AI more accessible on personal devices.

04:20The increasing demand for GPUs and cloud infrastructure is driving up costs for AI training and inference.

05:03Model optimization techniques, such as quantization and low-rank adaptation, are being used to reduce resource usage and improve AI model efficiency.

06:52Virtual agents are automating tasks and providing assistance, improving productivity and efficiency.

07:19Regulation in the field of AI is gaining more attention, with the European Union reaching provisional agreement on the Artificial Intelligence Act.

07:49Shadow AI, the use of AI by employees without proper oversight, raises concerns about security, privacy, and compliance.