Wading Out of the AI Deep End
Grab your floaties.
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Cool ChatGPT prompt for PMs
Last week, I left you to drown in the deep end of AI.
I have a tendency to get ahead of myself.
I’ll jump five chapters ahead in a story I’m telling since I think the person I’m speaking to knows what I’m talking about.
Then, I need to rewind, return to the beginning, and bring the listener up to speed.
It's worse when I get excited about something - I need to remind myself to slow down and make sure the person I’m speaking with understands my ravings.
The same happens when I speak about AI, but I think I got a little ahead of myself in the last newsletter.
Talk dumb to me
I’m not the sharpest tool in the shed.
Despite my love of technology, I’m not a lab rat or a programmer, so I’m usually lost after the smartest people in the room start describing their work. If there’s a problem with what they’re working on - I’m not the one they want to ask for advice on how to fix it.
However, I need to understand what the team needs, so I ask them to explain what they are talking about to a five-year-old.
Strangely, it works - they dumb the incredibly technical thinking down me, and I gain a new piece of knowledge that I would have had to watch dozens of YouTube videos to comprehend. Plus, the team members usually respect me since I showed them a little bit of my vulnerability.
Let’s regress a few years to gain an understanding of AI.
Back to kindergarten
There’s run-of-the-mill AI known as just “AI”.
We’ve known about it since the 50s, but today’s AI is now known as GenAI or generative artificial intelligence.
Now that we know what GenAI is - how would you paint that picture if you were to describe it to a kindergarten class?
Here goes…
Imagine you have a nice shiny, metal magic box that can create music, stories, and pictures. It can even solve sophisticated problems in a near-human voice. All you needed to do was ask it to make whatever you wanted.
This magic box is a robot we call "GenAI."
GenAI can draw a cool picture of a dinosaur playing badminton if you ask it to - even if it has never seen a dinosaur playing badminton (has anyone seen this besides if they are on a bad acid trip?).
How does the magic box do this? People have created a ton of music, pictures, and stories. It looks at all these things and remembers everything it hears or sees.
When you ask it to create something new for you, it scrambles them all up and puts them back together in a new piece of art, story, or music that is made just for you.
There’s not just one magic box out there - some are good at writing stories, others at drawing, and others can make better music. The main point is that they get better as they learn more. Your magic boxes can even help mommy and daddy do their job better!
Remember to grab your juice and a cookie as we leave the world of kindergarten.
Re-entering the world of grown-ups
The explanation of AI through the eyes of a small child may be a little overkill, but that exercise explains what AI is in an easy-to-digest format.
Since we’re adults, you can’t go around talking to your boss about “magic boxes” unless you want to be locked up in a padded room. We need to have a definition we can grasp, understand, and be able to explain.
I wanted an all-encompassing definition, so I looked up three household names in the AI arena and examined what they were defining as Generative AI. The big three are:
You can review the pages and check out what they say about Generative AI, but this is the “adult” definition that I came up with:
Generative AI (GenAI) is a type of artificial intelligence focused on generating new content, such as text, images, music, and code, from existing data using deep learning models. The concept is underpinned by a variety of models and techniques that help the AI learn and create novel outputs.
Now that we have a definition, I’ll break it down.
Yo, hit the backbeat and break it down
The definition we have is somewhat vague in a few areas, so let’s see if we can dissect it and get a better understanding. We’ll break down the definition in the sections below.
Generative AI (GenAI) is a type of artificial intelligence…
We used to think there was only one type of AI, but now there is GenAI, which is a specific type of AI that continues below.
…focused on generating new content, such as text, images, music, and code…
Remember that generative AI generates “something,” which can be anything above.
…from existing data…
Existing data is pretty simple - it’s the internet. GenAI pulls its data from bits and pieces of everything that’s been posted over the last twenty years.
…using deep learning models.
If I explain deep learning models, I’m sure you’ll fall asleep. The key is that deep learning models think like the human brain. They also can learn from their mistakes. If we don’t like a song that GenAI makes for us, we can ask it to create another one and remember what to avoid.
The concept is underpinned by a variety of models and techniques…
Foundation models form the backbone of GenAI, and they range from text, image, and music generation. Techniques are how the AI learns, predicts the future, and makes computations.
…that help the AI learn and create novel outputs.
Again, the AI is always learning and creating something new.
Final Thoughts
Hopefully, this clarifies AI a bit since I got a little ahead of myself on the first day, but it’s pretty darn exciting!
There’s a lot to unpack when learning about AI, and I want to help. So, I’m taking the extra time to ensure you feel comfortable. I don’t want you to get frustrated and not see the advantages of learning about AI in your project management world. There will be other times when you are confused, and the internet can provide some definitions, and you can rely on ChatGPT to fill you in.
AI is a huge topic, and we’ll learn weekly to make a dent in all the knowledge.
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Fireflies.ai - Fireflies.ai helps your team transcribe, summarize, search, and analyze voice conversations.
Decktopus AI - An AI presentation maker, that will create amazing presentations in seconds. You only need to type the presentation title.
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Cool ChatGPT Prompt for PMs
Initiating the project
As a project manager, I'm looking to address an underlying need or problem within [specific domain/area, e.g., 'our software development lifecycle']. Based on recent data, stakeholder feedback, market trends, and any other relevant information available in this domain, can you help identify the primary challenges or gaps that our project should target? The ultimate goal is to [desired outcome, e.g., 'improve efficiency and reduce bug counts']. Please provide a comprehensive analysis of potential problems and their implications.