AI Agents

• Context (IE): The recently launched GPT-4o by OpenAI and Project Astra by Google have been powered by AI Agents.
• AI agents are sophisticated AI systems that can engage in real-time, multi-modal (text, image, or voice) interactions with humans.
• Unlike conventional language models, which solely work on text-based inputs & outputs, AI agents can process and respond to a wide variety of inputs, including voice, images & input from their surroundings.

How are they different from large language models (LLMs)?

• While LLMs like GPT-4 have the ability only to generate human-like text, AI agents make interactions more natural and immersive with the help of voice, vision, and environmental sensors.
• Unlike LLMs, AI agents are designed for instantaneous, real-time conversations with responses much similar to humans.
• LLMs lack contextual awareness, while AI agents can understand and learn from the context of interactions, allowing them to provide more relevant and personalised responses.
• Language models do not have any autonomy since they only generate text output. AI agents, however, can perform complex tasks autonomously such as coding, data analysis, etc. When integrated with robotic systems, AI agents can even perform physical actions.

What are the potential uses of AI agents?

• AI agents can be ideal for customer service as they can offer seamless, natural interactions and resolve queries instantly without actually the need for human interventions.
• In education and training, AI agents can act as personal tutors, customise themselves based on a student’s learning styles, and may even offer a tailored set of instructions.
• In healthcare, it could assist medical professionals by providing real-time analysis, diagnostic support, and even monitoring patients.
• AI agents can offer personalised recommendations and schedule appointments.

Are there any risks and challenges?

• AI agents gain access to personal data and environmental information, leading to concerns over privacy and security.
• AI agents can carry forward biases from their training data or algorithms, leading to harmful outcomes.