Understanding AI Basics
Artificial General Intelligence (AGI) refers to AI that can perform tasks as well as or better than humans. However, AGI is still a nebulous concept, and experts disagree on its definition. A related term, AI Agent, describes an autonomous system that can perform multiple tasks, such as filing expenses or writing code.
Key Concepts in AI Development
Large Language Models (LLMs) are deep neural networks that learn relationships between words and phrases to generate human-like responses. Training is the process of feeding data into a model to help it learn patterns and generate useful outputs. Tokens represent basic building blocks of human-AI communication, created through tokenization, which breaks down raw data into distinct units for an LLM.
AI Techniques and Challenges
Transfer learning involves using a previously trained model as a starting point for developing a new model on a related task. Weights are numerical parameters that determine the importance of features in the data used to train a system. Hallucination is when AI models generate incorrect information, which can be misleading or even lead to real-life risks. To mitigate these risks, AI companies are developing specialized and vertical AI models that require narrower expertise.
Industry Trends and Challenges
The AI industry faces challenges such as RAMageddon, an ever-increasing shortage of random access memory (RAM) chips, which is driving up costs for industries like gaming and consumer electronics. Compute refers to the vital computational power needed to train and deploy AI models. Infrastructure development is still underway to deliver on AGI's envisaged capabilities.
