As we bid farewell to 2024, the AI space reflects a year of transformative advancements reshaping industries, workflows, and human-technology interaction. Andrew Ng, one of the key figures of the AI community, encapsulates the essence of this year with key takeaways and reflections. Let’s have a look at the 2024 AI Roundup by Andrew Ng.
Agents Ascendant: The Growth of Agentic Workflows
One of the most significant trends of 2024 has been the rise of AI agents and agentic workflows. These autonomous systems, capable of performing complex tasks with minimal human intervention, have become integral to industries ranging from healthcare to finance. Frameworks like Qwen-Agent, AutoChain, and TaskGPT have demonstrated the potential of AI agents to streamline operations, enhance productivity, and enable more efficient decision-making.
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Prices Tumble: Rapidly Falling LLM Token Prices
The cost of using large language models (LLMs) has seen a dramatic decline in 2024, making AI more accessible than ever before. Falling LLM token prices have been driven by advancements in model efficiency, increased competition among AI providers, and economies of scale. For example, DeepSeek V3’s token pricing has been notaby lower than other models with similar capablities, enabling startups and researchers to experiment with advanced AI at a fraction of traditional costs.
Generative Video Takes Off
Generative AI has expanded beyond text and images to revolutionize the video production industry. In 2024, generative video models like OpenAI’s Sora, Google’s Veo 2, and AWS Nova Reel have taken center stage, enabling creators to produce high-quality video content with minimal effort. These models can generate realistic scenes, edit footage, and even create entirely synthetic videos based on textual prompts.
Smaller is Beautiful: Small Language Models
While large language models (LLMs) have dominated the AI landscape in recent years, 2024 has seen a growing emphasis on small language models (SLMs). Compact and efficient, these models cater to resource-constrained environments like edge computing and on-device applications. Launches such as Phi 4, Llama 3.2 3B, and Qwen 2.5 demonstrate advancements in performance and scalability, empowering specialized domains like healthcare and legal tech. SLMs highlight a shift toward pragmatic AI, blending practicality with innovation.
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Alternatives to Acquisitions
In 2024, the AI industry has witnessed a shift in how companies approach growth and innovation. Rather than relying solely on acquisitions, organizations are increasingly exploring alternative strategies, such as partnerships, open-source collaborations, and ecosystem development. This trend reflects a recognition of the value of community-driven innovation and the need to foster a more collaborative AI landscape.
For example, Meta’s Llama 3.2 was integrated into Snapdragon platforms through a partnership with Qualcomm, enabling advanced on-device AI experiences.
Microsoft deepened its ties with Hugging Face, focusing on integrating open-source models seamlessly into cloud platforms.
Google’s strategic partnership with Hugging Face enabled training and deploying models on platforms like Vertex AI and Google Kubernetes Engine.
End Note
As we look ahead to 2025, these trends are likely to continue shaping the AI landscape, driving new opportunities and challenges. The ongoing evolution of AI promises to transform industries, enhance human capabilities, and unlock unprecedented possibilities for innovation. By staying attuned to these developments, you can position yourself to thrive in the AI-driven future. What are your thoughts on these trends? Share your insights in the comments below!
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