ChatGPT has caused me to question everything. I have been having this lingering thought that we give our minds too much credit. So I decided to write about it and would love to hear your own opinions.
Let me explain
Often when you hear about generative ai people mention that it’s just predicting the next word. Which is true, but there’s more. Fundamentally machine learning was used before 2015 to make predictions, summarize text and make translations of text.
So how is this different?
From what I am learning the difference is in the transformer’s decoder. This allows generative ai to create something new from the data that it’s already been trained on. Similar to how humans are.
So if I ask ChatGPT “Give me a creative way to make a peanut butter and jelly sandwich.” It can do this without me providing any context, details or examples of how to make that sandwich.
Super cool. But before you think I think ChatGPT is alive, I don’t. But after raising 4 kids and spending the last few months prompting engineering and now fine tuning models it’s scary how they both require guidance and attention. Some of you will see what I did there.
So why is the title of this post we give our minds too much credit?
The first reason is that when generative Ai gets something wrong we blame the machine. Often forgetting that humans make mistakes and blantenly gets things wrong all the time. Especially if they don’t have full context, examples to go off of or any prior information on a topic. And sometimes we just hullucinate and blurt things out because they sound right. And we will do it with zero authority and still sounds convincingly right!
Sound familiar?
Secondly, the rate at which GPT produces content, ideas, images and code is mind blowing. I’ve been in tech along time and I have never been more excited about being in tech. There’s no way mentally I could produce at this scale or speed. To assume it’s not smarter than me would be foolish.
So, is this the end? Will the world be taken over by chatbots? Are all of our jobs in danger. No, well to the later maybe. Jobs have always been in danger. Our minds trick us into thinking that when work for someone else we have security. The truth is we all can experience force reductions, layoffs or just be flat out let go.
So what can we do?
This is where human ingenuity comes in. Learn the tools. Figure out how to leverage generative ai in your job role with out plagiarizing, giving away intellectual property, or any information that should not be shared on the internet. Basically what I am saying is learn new skills. Continue to evolve with the times. And if you can, maybe be ahead of the times. Either way you have to keep learning, growing, and evolving as a human!
Here are a list of free courses to help you get started and learn generative ai:
Peace,
___Often, discussions about generative AI boil down to the idea that it’s simply predicting the next word. True, but there’s more to it. Before 2015, machine learning primarily focused on prediction, text summarization, and translation. But what’s changed now?
The game changer seems to be the transformer’s decoder in generative AI. It enables these models to create novel outputs from existing data, somewhat mirroring human creativity. For instance, if I ask ChatGPT for a creative way to make a peanut butter and jelly sandwich, it can generate ideas without any specific context or examples. It’s fascinating, yet simultaneously a bit unsettling.
However, don’t mistake my awe for thinking ChatGPT is sentient. Through my experiences in engineering, model fine-tuning, and even parenting four children, I’ve noticed similarities in the need for guidance and attention required by both AI and kids. Spot the parallel?
The title of this post, “We Give Our Minds Too Much Credit,” stems from two observations:
Firstly, when generative AI errs, we’re quick to fault the machine. Yet, we often overlook human fallibility—our propensity to make mistakes, especially without full context or background knowledge. Sometimes, we even confidently assert incorrect information.
Secondly, the sheer scale and speed at which models like GPT produce content are staggering. Claiming that these models aren’t in some ways smarter would be underestimating their capabilities. However, this doesn’t spell doom or suggest a future dominated by AI. Job displacement has always been a reality, and the notion of security in employment is often a fallacy of the human mind.
So, what’s our path forward?
Embracing human ingenuity is key. Learning to utilize generative AI tools in your job, responsibly and ethically, is crucial. This means continuous learning and adapting, possibly even staying ahead of the curve.
Below are some free courses to kickstart your journey into understanding generative AI:
[Insert List of Courses Here]
Peace,
Opinion Poll on AI Capabilities: Title: “How Do You Perceive the Capabilities of Generative AI?” Options: “A revolutionary tool transforming how we work.” “An interesting technology, but it’s not without its flaws.” “It’s overhyped and not as effective as people think.” “I’m not sure; I need to learn more about it.” Quiz on AI Knowledge: Title: “Test Your Knowledge: Facts about Generative AI” Questions like: “In what year was the original GPT model by OpenAI released?” “Which of the following is a primary use of generative AI? (Content creation, Data analysis, Battery optimization, Weather prediction)” “True or False: Generative AI can create original content based on input data.” Future of Work Poll: Title: “The Future of Work with AI: What’s Your Take?” Options: “AI will create more jobs than it replaces.” “AI will result in significant job losses.” “The impact of AI on jobs will be minimal.” “I believe it’s too early to predict the outcome.” Interactive Scenario Builder: Title: “Create Your AI Scenario” Provide a text box where readers can write a short scenario or task for an AI. Optionally, you could use an AI model to generate responses to these scenarios, demonstrating AI in action. Feedback Survey on AI Use: Title: “Share Your Experience with AI” Questions like: “Have you used generative AI tools in your work or personal projects?” “What do you find most challenging about using AI technology?” “What potential do you see for AI in your field of work or interest?”