{"id":5595,"date":"2023-08-03T09:24:29","date_gmt":"2023-08-03T09:24:29","guid":{"rendered":"http:\/\/ai-hub-demo-5.local\/?p=5595"},"modified":"2024-08-20T07:52:40","modified_gmt":"2024-08-20T07:52:40","slug":"best-practices-and-common-pitfalls-of-ai","status":"publish","type":"post","link":"https:\/\/test.ajentic.com\/?p=5595","title":{"rendered":"The Rise of AI Agents"},"content":{"rendered":"
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We are all inundated by the the term Artificial Intelligence, to the point of saturation. Everyone wants something to do with AI, build around AI or position their company around AI. You’ve heard that term 5+ times in the first few lines in this post. It’s reached such a ridiculous point that i recently saw a mattress company say that their mattresses are AI enabled. I was baffled, so i went through their blog to see what “AI Powered Sleep Solutions”<\/em><\/strong> meant and this is the best i could find..<\/p>\n\n

Wakefit Zense is India’s pioneering AI-driven sleep ecosystem designed to revolutionise sleep quality. Powered by artificial intelligence, it offers innovative solutions to enhance sleep health, marking a significant advancement in the realm of sleep technology.<\/em><\/p><\/blockquote>\n\n

I’ll leave a link below, if anyone can tell me what “AI Powered Sleep Solution” is, i would be grateful. I spend most of my waking hours working on AI, why should’t i do the same when i sleep!<\/p>\n\n

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When i first tried ChatGPT and it responded to every question i threw at it, i was blown away. Now, it seems mundane, but “back in the day” Wolfram alpha<\/a><\/em><\/strong> was the closes thing to an intelligent solution i had interacted with, and ChatGPT was miles ahead!

Ever since that day, I\u2019ve been tinkering with LLMs, mostly just to see what I could do with them. After a couple of years of building and experimenting, I\u2019m sure of one thing\u2014AI Agents are the future.<\/strong><\/p>\n\n

There will be more AI Agents than there will be humans
– Mark Zuckerberg<\/p><\/blockquote>\n\n

What are AI Agents?<\/strong><\/h4>\n\n

It’s the technology that makes science fiction like star trek com-badges into reality<\/em><\/p>\n\n

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Think of AI Agents as your personal Star Trek com-badges, but instead of just connecting you to the ship’s computer or your fellow crew members, they connect you to a whole universe of digital tasks and processes. In the Star Trek world, you\u2019d just tap your com-badge and say something like, \u201cComputer, locate Captain Picard,\u201d and boom\u2014the ship\u2019s systems spring into action, finding exactly what you need.
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AI Agents work much the same way, but instead of being limited to a starship, they operate within your digital world. Whether it\u2019s managing your emails, analysing customer feedback, or automating a complex workflow, you simply “tap” your AI Agent by giving it a command, and it handles the rest. It\u2019s like having a team of digital crew members always ready to execute your orders.

But here\u2019s where it gets really cool: just like the combadge integrates seamlessly with the Enterprise’s systems, AI Agents blend into your daily operations. They don\u2019t just follow orders\u2014they anticipate your needs, learn from your preferences, and adapt to your way of working. It\u2019s like having a tiny piece of Star Trek tech right here, helping you run your business or life more smoothly, efficiently, and intelligently.

AI Agents are a necessary, but not sufficient condition to make a technology like ComBadges & Jarvis a reality.<\/p>\n\n

What makes AI Agents so powerful?<\/h4>\n\n

Agents operate autonomously, processing information, making decisions, and performing tasks\u2014much like a human would.<\/em><\/p>\n\n

The term AI Agents may be complex to really comprehend but the simplest way to understand AI Agents is that they try to emulate what humans would do while performing a task. Agents beyond just answer questions like the AI chatbots<\/strong> we see everywhere today, they not only have the ability to answer questions from a knowledge base but also take decisions and perform tasks for you, just like a human would. To understand the power of AI Agents lets take a look at a real world scenario where agents would thrive, but chatbots, even AI chatbots would fail.<\/p>\n\n

AI Chatbots vs AI Agents<\/h4>\n\n
The Scenario: Canceling a Subscription<\/strong><\/h5>\n\n

A customer decides they want to cancel their subscription. They start by interacting with an AI Chatbot. The chatbot, designed to pull information from a knowledge base, can guide the customer through the basic steps of cancellation. It might say something like, \u201cTo cancel your subscription, please visit this link or follow these steps\u2026<\/em>\u201d It\u2019s quick, straightforward, and provides the necessary information.<\/p>\n\n

However, the chatbot\u2019s interaction is purely transactional. It doesn\u2019t consider why the customer is canceling or whether there\u2019s an opportunity to retain them. It can\u2019t pull up the customer\u2019s history, identify their value to the company, or offer any retention strategies.<\/p>\n\n

Enter the AI Agent: A Smarter Approach<\/strong><\/h5>\n\n

Now, let\u2019s see how an AI Agent would handle this scenario. When the customer requests to cancel their subscription, the AI Agent first pulls up the customer\u2019s profile. It checks their subscription history, usage patterns, and any past interactions they\u2019ve had with support. The agent notices that this customer has been with the company for several years and frequently uses premium features.<\/p>\n\n

Armed with this information, the AI Agent can offer a personalized retention strategy. It might present the customer with a special discount, an upgraded plan at a reduced rate, or a temporary pause in billing to accommodate a specific concern the customer has raised in past interactions.<\/p>\n\n

If the customer still chooses to cancel, the AI Agent can handle the cancellation process seamlessly. But it doesn\u2019t stop there\u2014the agent intelligently raises a ticket for the customer\u2019s feedback, which gets routed to the retention team for further analysis. Additionally, it might automatically send a follow-up message or survey to understand the reason behind the cancellation, helping the company improve its services in the future.<\/p>\n\n

Why It Matters<\/strong><\/h5>\n\n

In this scenario, the AI Chatbot provided basic assistance but couldn\u2019t go beyond that. The AI Agent, on the other hand, used customer data to craft a personalised response, potentially saving the subscription or at least gathering valuable insights for the company. The agent\u2019s ability to apply discounts, intelligently manage customer interactions, and ensure a smooth experience makes it far more effective in handling complex customer requests.<\/p>\n\n

AI Chatbots are excellent for handling routine tasks, but when it comes to scenarios where customer retention and personalised service are key, AI Agents take the lead. By using both, businesses can offer a more dynamic and responsive support experience.<\/p>\n\n

Conclusion<\/strong><\/h4>\n\n

Eric Schmidt of google recently gave a talk at Stanford and emphasised on the importance and future of AI Agents. I don’t have to say much to conclude this post, just read what his observation around AI Agents is & gives us a clear idea on the future, and why it is AI Agents. 
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Say I want a recipe to make a drug. I ask, \u201cWhat\u2019s the first step?\u201d and it says, \u201cBuy these materials.\u201d So, then you say, \u201cOK, I bought these materials. Now, what\u2019s my next step?\u201d And then it says, \u201cBuy a mixing pan.\u201d And then the next step is \u201cHow long do I mix it for?\u201d<\/em>
That\u2019s called chain of thought reasoning. And it generalizes<\/a> really well. In five years, we should be able to produce 1,000-step recipes to solve really important problems in medicine and material science or climate change. <\/em><\/p>\n\n


The second thing going on presently is enhanced agency<\/a>. An agent can be understood as a large language model that can learn something new. An example would be that an agent can read all of chemistry, learn something about it, have a bunch of hypotheses about the chemistry, run some tests in a lab and then add that knowledge to what it knows. <\/em><\/p>\n\n


These agents are going to be really powerful, and it\u2019s reasonable to expect that there will be millions of them out there. So, there will be lots and lots of agents running around and available to you. <\/em><\/p>\n\n

–Eric Schmidt 
Former CEO of Google<\/em><\/p><\/blockquote><\/div><\/div>

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