Leveraging AI to increase personal and professional productivity

Imagine a world where technology and human imagination intertwine seamlessly, making our lives more efficient, more creative, and more impactful. This is not a distant reality, but a world that we are shaping today – a world propelled by Artificial Intelligence.

As we embark on this intellectual expedition together today, we will take a deep dive into the transformative power of AI and its profound impact on our productivity across personal, public, and professional spheres. But to truly appreciate the transformative potential of AI, it’s crucial that we first understand the journey of technology and its role in enhancing productivity.

Think back to the 18th century, the era of the Industrial Revolution, where steam-powered machines kicked off a new age of mechanization, skyrocketing our productive capabilities. Now, fast-forward to the 20th century, we are in the midst of the electric revolution, a period marked by assembly lines, telecommunication, and electrification – this era redefined the speed and efficiency of production.

In the blink of an eye, we’re swept into the Information Age, the late 20th and early 21st century, where the advent of personal computers and the internet interconnected the world. This was a time when information was just a click away, and productivity gained a whole new meaning.

And now, we find ourselves on the brink of a new era, an era of AI. As we delve deeper into this discourse, we will unravel how AI, with its ability to learn, reason, and self-correct, is pushing the boundaries of productivity. Moreover, we will explore how pretrained models, by reducing the entry barriers for AI applications, are fostering the democratization of AI. From personal tasks such as managing our calendars and curating our news, to public services like traffic management and healthcare, to professional scenarios involving data analysis and decision making – AI, coupled with the power of pretrained models, is reshaping our operational paradigm.

A Close Look at Pretrained Models

If you’ve ever used an online translator or asked a voice assistant for the weather, then congratulations! You’ve used a kind of artificial intelligence (AI) called a pretrained model.

• What are pretrained models?
  In the world of AI, a pretrained model is like a super-smart helper that has already done a lot of learning before it gets to you. It’s a machine learning model that has been trained on a huge amount of data beforehand. This data can be pictures (for image recognition) or sentences (for understanding and generating language), among other things.
  For example, a large language model like ChatGPT (the ‘P’ stands for ‘Pretrained’) has been trained on a huge number of texts so it can generate human-like text based on the input you give it.  Such models can be likened to a ballet dancer transitioning into football. Just as the dancer’s refined footwork and balance from ballet training offer an advantage on the football field, the broad training of these models on diverse text equips them with versatile language skills. These skills can be transferred to various language-related tasks, much like the ballet-to-football advantage, enhancing performance across multiple areas. This is what we call transfer learning in AI– where knowledge gained while solving one problem is applied to a different but related problem.
• Why are pretrained models important?
  Think about the considerable resources that tech giants like Google, Microsoft, Facebook, and OpenAI have at their disposal. They’ve trained complex AI models using extensive data science and computational power, resources that most individuals don’t have. It’s akin to learning how to ride a bike for the first time – it requires significant time and effort. But once it’s learned, it doesn’t need to be learned again. Similarly, these companies have done the heavy-lifting of training AI models, and we can utilize these pretrained models. We benefit from their expertise and resources, without the need to be data scientists ourselves or possess supercomputing capabilities.
  By using a pretrained model, you’re using a model that already knows a lot. You can use its existing knowledge and tweak it to suit your specific needs. Plus, many pretrained models are available for free online. This means anyone with a computer can use AI, just like how anyone with a bike can go cycling.
• How can we use pretrained models?
  There are two main ways to use pretrained models: use them “as-is” or fine-tune them.
  When you use a pretrained model “as is”, you’re using it just like it came out of the box. This is great for non-technical people, as they can use AI without needing to understand all the math and computer science behind it. For example, if you’re a teacher, you could use a language model to check for spelling or grammar errors in student essays.
  Fine-tuning a pretrained model is like customizing your bike. Maybe you need a basket for your grocery shopping or a bell to let people know you’re coming. In the same way, you can train your pretrained model on a smaller, specific dataset to better suit your needs. This might mean training ChatGPT on legal documents if you’re a lawyer so it can help draft contracts or court documents.