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100 Days of AI

Learn, play, design & experiment with generative AI.

AI was already everywhere but with chat-gpt’s explosion, it captured everyone’s attention. Even though it might seem like there is an AI hype cycle, unlike other tech bubbles AI is here to stay. And whether you are developer, product manager, marketer or any other knowledge worker, you are better off, if you invest time in learning AI and think about how you can leverage it for you career. I have previously learnt machine learning, so my focus in this exercise would be to learn about LLMs (open source, closed source), what new products or features can be built, what it takes to build them, what new workloads would cloud technologies need to support as LLMs become mainstream. Below I will document all the ideas, learnings, experiments, how-to guides that I encounter during these 100 days.

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Day 3: How to Use Inferring to Create new AI Features?

I write a newsletter called Above Average where I talk about the second order insights behind everything that is happening the big tech. If you are into tech and don’t want to be average, subscribe to it. Inferring is essentially to extract insights, sentiments, trends using clever prompts while interacting with LLMs. Previously before LLMs… Read…
Substack Individual Post 1456 + 1048 (44)

Day 2: How to Write Better Prompts for ChatGPT?

I write a newsletter called Above Average where I talk about the second order insights behind everything that is happening the big tech. If you are into tech and want to be above average, subscribe to it. I don’t know if prompt engineer will actually become a role in companies in the future. But writing… Read…