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- Mind Blowing Test of ChatGPT Vision
Mind Blowing Test of ChatGPT Vision
PLUS ➜ Insane Free PDF of 100 ChatGPT Vision Use Cases
Make Money with ChatGPT Vision AI apps to watch (image by author)
ChatGPT Vision is truly astonishing and a chilling warning at the same time.
A team of researchers in Microsoft just published this brand new paper that pushes this Vision module to its limits.
ChatGPT Vision Use Cases For Making Money
We review how ChatGPT Vision may be used to monitor our activity and also save human lives,
I’ll demonstrate a random example from my own life and then we get into the good stuff…
How do we make money with ChatGPT Vision?
1) Big Brother Really IS WATCHING You
With the introduction of the Vision module, the concept of ai training context has evolved to include images.
This means that GPT can now not just understand your textual context, but also any visual information you provide.
So, if you give it a photo of a broken machine, it won't just rely on a description; it can see the machine for itself, understand the broken parts, and provide a more informed solution or analysis.
The Microsoft research paper is a testament to this evolution. It's not just about GPT having vision; it's about how this vision has redefined the way GPT interacts and responds to queries.
The potential applications span numerous fields from healthcare, where it can analyze X-rays, to entertainment, where it can offer critiques or breakdowns of visual content like TikToks.
One can imagine a doctor in a remote area taking an X-ray, sending it to ChatGPT with Vision, and getting a preliminary diagnosis. Or a student wanting to understand a complex concept visually represented in a diagram and get an instant breakdown from ChatGPT.
This visual context provides a deeper level of interaction. It's akin to the difference between reading a book and watching a movie.
While both can tell you the same story, one gives you visual cues and context that the other doesn't.
ChatGPT with Vision can now 'watch the movie' (and the movie is you), giving it a richer understanding of the content.
Testing ChatGPT Vision on Philosophy
I had to test it for myself.
So I sent a picture of a drawing I created last week. It is a concept I am always learning about and also teaching to my daughter.
Thoughts. Become. Things.
A famous quote I learned from Mike Dooley when ‘The Secret’ was first released.
Mkey Dooley - Thoughts. Become. Things.
I had sketched out a circle and intended to explain the Psycho-Cybernetics concepts of how our self-image can influence our thoughts.
Later in the circle, we can become aware of how our emotions are like a magnet where our thoughts send out our intentions to the universe and our emotions draw matching things back to us.
There’s not much to go on in the image - let’s see what ChatGPT Vision says:
Thoughts Become Things - the Cycle of Creating (image by author)
Here is the prompt: “can you create a long form article explaining this image?”
and here is what ChatGPT Vision came up with:
This is So BIG I Can’t See It All
This is pretty astonishing - but we have not yet started to understand the consequences of innovative developers and AI having this power.
Let’s just narrow our focus on the subject of getting rich, ethically.
Let’s focus on getting wealthy in a way that provides service to others by reducing their suffering or by increasing their abundance in some area of their lives.
How can we use AI Tools for good - and make money at the same time?
Make Money With ChatGPT Vision
Prioritizing based on the potential for making money involves considering several factors:
Market Size and Demand: Which of these sections pertains to industries or sectors with large markets or a growing demand?
Degree of Innovation: Which of these sections presents concepts that are innovative and not readily available in the market?
Commercial Applications: Which of these sections has a direct, tangible application in industries or services that could charge money for the application or outcome?
Urgency: Which of these sections addresses problems that industries or individuals face right now and are willing to pay to solve?
Based on these factors, I can use Helium 10 to research opportunities in this priority list of sections that seem to have a significant potential for making money:
Industrial defect detection and safety inspection (Sections 70-73): Defect detection and safety inspections are crucial in manufacturing and industrial settings. Automation here can save millions by preventing accidents and product recalls.
Automation of quality control in manufacturing lines.
Predictive maintenance in factories and plants.
Safety compliance checks in industrial environments.
AI Tool: SparkCognition's Darwin is an AI platform used for manufacturing and industrial applications, including defect detection.
Customized captioner for photo organization (Sections 81-83): With the increasing volume of digital content, tools that can automatically organize and caption photos can be valuable for both consumers and businesses.
Integrate with cloud storage platforms for automatic photo tagging.
Provide solutions for digital marketers and social media managers.
Offer tools for personal photo management and memory recall.
AI Tool: Google Photos uses AI to automatically organize, tag, and generate albums based on image content.
Clarifai business page on LinkedIn (screenshot by author)
Logo recognition and description, especially in-the-wild (Sections 20-21): Useful for brand management, marketing analysis, and potential copyright infringement detection.
Brand monitoring and management on social platforms.
Anti-counterfeiting in e-commerce.
Copyright infringement detection.
AI Tool: Brandwatch offers image recognition for monitoring brand mentions across the web.
Document and long document understanding (Sections 39-40): Businesses are inundated with documents. Being able to quickly understand and summarize them has significant value.
Integrate with enterprise systems for document summarization.
Legal document analysis and insights.
Research paper summarization and academic work.
AI Tool: OpenAI's Codex (and by extension, tools built on GPT-3 or GPT-4) can understand and generate human-like text, making it suitable for document understanding.
Affectiva screenshot by author
Emotion reading from facial expressions:
Useful for marketing, user experience testing, and entertainment industries.
User experience testing for games or software.
Feedback systems for virtual meetings or webinars.
Marketing analysis for advertisements.
AI Tool: Affectiva specializes in emotion detection through facial expressions.
The other sections, while they have potential, might be more niche or may require more extensive development and validation before commercial applications can be realized.
That’s a Wrap
In our next issues, we’ll get into more detail on how we can use ChatGPT Vision to make money.
To Your Success,
Doug and the team at ai-businessplans.com
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