GPT-3 Personal assistant: Where are we at?


  • GPT-3 expands as a dynamic personal assistant.
  • Diverse roles: translation, drafting, coding, analysis, and more.
  • GPT-4 emergence questions output quality asymmetry.
  • Potential untapped in GPT-3 personal assistant realm.
  • Argil envisions user-friendly, skill-driven AI assistants.

While many people don’t conceptualize nor vizualize how much of a revolution the launch of GPT-3 was, if you’re reading this article it means that you understood that’s it’s more than just a chatbot.

You understood that GPT-3 can also play the role of a personal assistant, and that my friend is not a little achievement.

The essence of AI is to give through high amount of data procession, outputs that would normally require human reflection, research, and interpretation.

GPT-3 showed that you can now outsource a part of these to an AI and it’s stunning.

GPT-3 personal assistant is a real and pertinent evolution of the simple vision of chatGPT. The proof is the direct change in the UI for chatGPT as you can now have different discussion each on different topics and with different outputs.

Productivity is the bottleneck topic in most industries:

  • How can we automate these task?
  • How can we focus on high-return tasks?

On this article I’ll cover the potential features that may come related to a GPT-3 personal assistant version and the benefits coming with them.

Understanding GPT-3 as a Personal Assistant

What is a personal assistant? This question is primordial if we want to efficiently define the applicable use-cases of a GPT-3 personal assistant.

Here’s the common definition:

‘A secretary or administrative assistant working exclusively for one particular person.’

On the other hand the first usage people did with GPT-3 is to ask general question and considerer it as a search engine instead of a personal assistant.

Here’s how GPT-3 can be used as a personal assistant:

  • Translations.
  • Drafting emails.
  • Writing part of code.
  • Analysing part of documents you copy past to it.
  • Help you define your marketing campaigns and their steps.

GPT-3 as a personal assistant means outsourcing the performance of components of your task not the final output, and that’s because the quality given is still lacking.

That’s a shame when you see the infinite potential, solopreneurs might build empires alone only using AI tools to help them in their day-to-day work.

Availability and Accessibility of GPT-3

Is GPT-3 enough?

Now that GPT-4 is available (payed subscription of chatGPT), real questions are being held in regards to the asymmetry of output quality people using one or the other model will get.

On top of that OpenAI is not building tailored features to the personal assistant use-case on top of GPT which means that other players will leverage this.

For instance here are some features that are needed to achieve the GPT-3 personal assistant vision:

  • Upload document and interacting with it.
  • Personalize GPT to your datasets and projects.
  • Interact in a multimodal framework (generate text, images, documents, etc).

As long as this approach is not yet on market, I am afraid the added value as a personal assistant of GPT-3 stays very low.

An existing already existing vision of AI as a Personal Assistant

How do we use Siri?

How do we use google?

How do we use social networks?

AI algorithms have already been shaping the way we work, process, and interpret information for a while now.

The only difference is that we’re now getting more in-depth in the assistance and have a broader impact. The advancement in LLM training and distribution was the trigger point.

Remember when you first used Siri?

Remember when you first used Google?

Remember when you first used Instagram?

They were all lacking, but the promise was there. That’s exactly what’s happening with GPT-3 as a personal assistant.

The promise is here and companies needs to build on that.

Argil’s role in building GPT-3 Personal Assistant

At Argil, after building on AI for more than a year now, we came to the following conclusion:

  • People want tailored AI to their projects.
  • People don’t want to learn how to prompt.
  • People don’t know how to prompt (ask the AI).
  • People want one tool from which they can do all of that.

That’s why our vision of the GPT-3 personal assistant market tends towards the following:

  • One tool for all.
  • Skill-based approach.
  • Natural language based generation.

Imagine a tool in which you can use different ‘Experts’ that got tailored skills to your need and interact with your specific projects. That’s what we’re building at Argil and your feedback is more than welcome.

If you haven’t tried yet Argil, what are you waiting for? Try it here

Othmane Khadri