2025 AI Trends: Genetic AI, Understanding AI Agents, and Smarter Models
Key insights
- 💡 A genetic AI will be a significant AI trend in 2025, attracting interest and demand for understanding
- 🧠 AI agents struggle with consistent logical reasoning, prompting the need for better models by 2025
- ⏱️ Inference time compute is being extended for more effective reasoning in AI agents
- 🤖 Inference reasoning in large language models (LLMs) can be improved at training and inference time, leading to smarter AI agents
- 🔍 Small AI models with a few billion parameters can perform specific tasks without requiring large compute power, with common enterprise use cases including improving customer experience, IT operations, virtual assistants, and cybersecurity
- 🔄 AI systems are advancing to solve complex problems, with models having larger context windows and the potential for near infinite memory. Human-in-the-loop augmentation is a significant trend
- 👩⚕️ The combination of chat bot and doctors scored lower than the chat bot working alone, revealing the need for better AI systems to augment human professionals' workflow
- 🗣️ The audience was asked to share their thoughts on important AI trends for 2025
Q&A
What was the audience asked to do?
The audience was asked to share their thoughts on important AI trends for 2025, indicating the interactive and engaging nature of the discussion about future AI trends.
How did the chat bot perform compared to doctors?
The chat bot scored higher than doctors in some cases, but when doctors used the chat bot, their combined performance was lower than the chat bot working alone. This highlights the need for better AI systems to augment human professionals' workflow.
What advancements are expected in AI systems for complex problem-solving?
AI systems are advancing to solve complex problems, with models having larger context windows and the potential for near infinite memory. Human-in-the-loop augmentation is also a significant trend, indicating advancements in the interaction between AI and human professionals.
What are the common use cases for small AI models in 2024?
Small AI models with a few billion parameters can run on laptops or phones without requiring large data centers. Common enterprise use cases for AI in 2024 include improving customer experience, IT operations and automation, virtual assistants, and cybersecurity. More advanced use cases for AI are expected in 2025.
How large are the next-generation language models expected to be?
The next-generation language models in 2025 are expected to have upwards of 50 trillion parameters, making them significantly larger in size as compared to previous models.
What challenges do AI agents face by 2025?
By 2025, AI agents struggle with consistent logical reasoning and the need for better models. Inference time compute is being extended for more effective reasoning, and improvements in inference reasoning can occur at training and inference time to lead to smarter AI agents.
What are the important AI trends in 2025?
In 2025, the most important AI trends will include genetic AI and the growing demand for understanding AI agents. AI agents, which are intelligent systems capable of reasoning, planning, and taking action, will continue to attract interest and demand for understanding. Large language models with trillions of parameters are also expected to be a significant trend.
- 00:00 In 2025, the most important AI trends will include genetic AI and the growing demand for understanding AI agents.
- 01:06 AI agents struggle with consistent logical reasoning and need better models by 2025. Inference time compute is being extended for more effective reasoning.
- 02:16 Inference reasoning in LLMs can be improved at training and inference time, leading to smarter AI agents. Large language models are growing in size, with next-generation models expected to have upwards of 50 trillion parameters.
- 03:26 Small AI models with a few billion parameters can perform specific tasks without needing large compute power, and enterprises commonly use AI for improving customer experience, IT operations, virtual assistants, and cybersecurity.
- 04:33 AI systems are advancing to solve complex problems, with models having larger context windows and the potential for near infinite memory. Human-in-the-loop augmentation is also a significant trend.
- 05:49 The chat bot scored higher than doctors in some cases, but when doctors used the chat bot, their combined performance was lower than the chat bot working alone. There is a need for better AI systems to augment human professionals' workflow. The audience was asked to share their thoughts on important AI trends for 2025.