Context: GPT-4o by OpenAI and Project Astra by Google are the recently launched AI Agents. They have been touted as far superior to conventional voice assistants such as Alexa, Siri, and Google Assistant. The launch of these models marks a new phase in AI — the transition from chatbots to multimodal interactive AI agents.
AI agents
- AI agents are sophisticated AI systems that can engage in real-time, multimodal (text, image, or voice) interactions with humans. Unlike conventional language models, which solely work on text-based inputs and outputs, AI agents can process and respond to a wide variety of inputs including voice, images, and even input from their surroundings.
- AI agents perceive their environment via sensors, then process the information using algorithms or AI models, and subsequently, provide intelligent responses and assistance. The new AI models can have instant real-time conversations with a user.
- AI agents are quick to adapt to new situations. This facet makes them incredibly versatile and capable of handling a wide range of situations.
- Currently, they are used in fields such as gaming, robotics, virtual assistants, autonomous vehicles, etc.
How are they different from large language models?
- While large language models (LLMs) like GPT-3 and GPT-4 have the ability to only 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 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.
Potential uses of AI agents:
- Customer Service Assistants: AI agents can serve as intelligent and highly capable assistants. They are capable of handling an array of tasks, from offering personalised recommendations to scheduling appointments and resolving queries instantly without actually the need for human interventions.
- Personalised Tutors: In the field of 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.
- Healthcare assistants: In healthcare, they could assist medical professionals by providing real-time analysis, diagnostic support, and even monitoring patients.
Are there any risks and challenges?
- Privacy and security are a key area of concern as AI agents gain access to more personal data and environmental information.
- Just like any AI model, AI agents can carry forward biases from their training data or algorithms, leading to harmful outcomes.
Hence, as these systems become more common, appropriate regulations and governance frameworks should be laid out to ensure their responsible deployment.








