Will AI Agents Replace All Our Apps
The ability for AI agents to handle a range of complex tasks, might reduce our need for single applications focusing on just one job.
Reading through the plethora of posts and articles online, I still see a number of people confusing AI agents with chatbots. There are, of course, some similarities, but they are two very different sets of capabilities.
Let's take a look at the main differences:
Chatbots
Chatbots are far more simple. They perform a single task which is nearly always retrieving information for you. By nature they are reactive, waiting for a user to ask it a question, and are very limited in being able to interact with other tools and systems apart from a database that they reference for answers.
AI Agents
On the other hand, AI agents are far more complex. Opposed to dealing with a simple back-and-forth question and answer mode, they can go away and "think" about a request, and can make subsequent decisions to deliver it. They also might do this proactively as well, depending on a set of rules that developer writes. To enable them to deliver more complex scenarios, AI agents will have access to a greater range of tools and technologies, typically interacting with APIs to make calls to other systems.
A Useful Analogy
Chatbots are like waiters. They give you a list of options, you make your decision, and they come back with the result. An AI agent on the other hand is like a chef, where you might indicate what type of food you want, and they respond by creating a dish for you, sourcing the necessary ingredients and recipe etc all by themselves.
Bill Gates
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Curated News
Amazon's AGI Lab Unveils Advanced AI Agents
Amazon's AGI Lab in San Francisco has introduced their AI model, Amazon Nova Act, which surpasses benchmarks set by competitors like OpenAI and Anthropic in intelligence and aptitude, particularly excelling in tasks such as web interactions. Led by David Luan, the lab emphasizes creating reliable AI agents capable of independent actions. Amazon has also launched a software development kit (SDK) to facilitate the creation of advanced AI agents using Nova Act, highlighting their commitment to advancing AI capabilities for practical applications.
Challenges in Scaling AI 'Super Agents' Due to Computing Constraints
As the AI industry evolves from simple chatbots to autonomous "super agents" capable of performing complex tasks, concerns arise over the sufficiency of computing power to support this transformation. A recent Barclays report suggests that while the industry might support between 1.5 billion to 22 billion AI agents, these advanced agents generate significantly more tokens per user query—up to 25 times more than chatbots—requiring far greater computational resources. The transition to super agents poses logistical challenges but also promises vast potential if the necessary computing infrastructure can be scaled accordingly.
Scaling Agentic AI Requires Comprehensive Business Transformation
At the Agentforce World Tour event hosted by Salesforce in Sydney, significant interest in Agentic AI was evident, with over 8,000 attendees and various impressive demonstrations of AI capabilities in customer interactions. According to a Deloitte survey, around 25% of businesses trialed Agentic AI in the first three months, and 50% plan to launch AI pilots by 2027. The successful adoption of Agentic AI hinges on businesses' organizational flexibility and readiness for transformation, emphasizing the need for trust, informed technology choices, and organizational readiness.
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Thanks for reading, and see you next Friday.
Simon,
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