The society today is roughly divided into 3 camps, those who are terrified that AI will replace them in the workforce, those who find AI useful but think that it will never be “smart enough” to actually replace most people in the workforce and lastly, those who don’t know much about Ai and doesn’t care either way.
This is my prediction on how AI will be integrated in our lives, and how it could replace a lot of us in the workforce even without “knowing” everything within every specific area.
The current state of AI
At this time a large part of the population has access to at least two types of AI.
- Large Language Models (LLM)
- Diffusion Models
When you run a LLM such as ChatGPT, Gemini or Copilot, you can ask a variety of questions about pretty much anything. These LLM models have enough information to give at least general (more or less accurate) information to almost anything you ask them.
The Diffusion models are the ones we typically use to create visual images or videos, and includes models such as Stable Diffusion, Flux and Red Panda. Here you provide commands in text, images or both to make the model understand how you want the image or video to look like.
To make things easier for the user, and make it more clear to the diffusion model what we actually mean, we can easily incorporate an LLM to translate our instructions to a more “diffusion friendly” command.
Let me show you two examples:
In my first example I am giving the basic text instructions to the diffusion model, and it will in return present me with an image that reflects my instructions.
In my second example I will give the same text command to an LLM model. The LLM model will interpret my command and rewrite it in a more optimized way to make it easier for the diffusion model to understand what I want.
To incorporate the LLM model into my work with the diffusion model is easily done with the help of API. While I could learn how to best write instructions for the diffusion model myself, it would require both a lot of knowledge and time. And since the diffusion models constantly are being upgraded and the optimized way to interact with them changes as well, it would be stupid of me to not utilize the tools at hand instead.
My prediction
This is how I imagine that AI will be integrated in our everyday lives in the near future. We will not have one single AI that will have all the answers and that may or may not have the knowledge to replace me or you in the workforce. Instead we will all have access to a free chat AI that knows how to communicate with a plethora of other, more specialized AI’s, that are trained specifically for one purpose. That purpose might be anything you can think of, from legal business to farming to computer science and programming.
The illustration above shows a rough sketch of how I imagine it will work. The user tells the interactive AI (a regular LLM model) that they wish to create an advertisement for a product. The interactive AI will then send requests to one or several other AI’s that are specialized in different things, such as “advertising”, “graphic design”, “demographic research” and “financial analysis”. If needed, these specialized AI’s will request information from even more narrowly specialized AI’s, and communicate the results back to the first interactive AI.
The interactive AI will then take the information it got from the specialized AI’s and make it into something more comprehensive for the user that made the initial request. Although it might seem like the whole process is a bit complicated, and that it might take a lot of time from the initial request until the user has a complete and final answer, I predict that the whole process will take somewhere between 30-120 seconds in the current state. 30 seconds if the answer only requires text, and up to 120 seconds if it also requires graphics in the answer.
I believe that it will not be long until AI developers start training these types of specialized models, and start selling API subscriptions to users that want access to them. Likely you will have an interface program, which connects to the interactive AI, installed on your computer. The interactive AI will be free to use, but be limited in what it can do. Upgrades to more specialized AI will be available through API, and will probably be aimed mostly towards small and medium businesses at the initial phase.
What do AI think of my predictions?
Because I’m curious, I asked AI to analyze my predictions and evaluate it. This is what I asked the AI to consider:
I’m explaining how I think AI will evolve and how it will be used in the near future. I would like to have your thoughts on the content of the article, such as if you believe my thoughts are likely or unlikely. I also would like to know what your own thoughts about how AI might be incorporated in our everyday lives the next 1-3 years.
I’m using Gemini 2.0 Flash Thinking Experimental, which is free to use (to an extent).
Here is the answer I got from Gemini:
The article presents a very plausible vision of AI integration in the near future, and I can offer some thoughts on it and share my own predictions:
Strengths of Your Article’s Predictions
- Realistic Division of Public Opinion: You correctly identify the three primary perspectives on AI among the public: fear of job displacement, cautious optimism, and indifference. This accurately reflects the current societal landscape.
- Leveraging LLMs and Diffusion Models: The core concept of combining LLMs for instruction translation with diffusion models for visual content is a sound and practical approach. It aligns with current AI development trends and offers a tangible solution for user-friendly AI interactions.
- Specialized AI Ecosystem: The idea of a network of specialized AIs communicating through a central interactive AI is particularly compelling. It addresses the limitations of monolithic “general AI” by distributing tasks to expert systems, which is more feasible and efficient.
- API-Driven Access: The prediction of AI developers offering API subscriptions for specialized models is a likely business model. It allows for both free basic access and premium, tailored services, catering to a wide range of users.
Areas for Consideration
- Complexity vs. Speed: While your timeline of 30-120 seconds for task completion is reasonable, consider the potential for optimization. As AI models and infrastructure improve, processing times could significantly decrease.
- Data Privacy and Security: The article doesn’t explicitly address data privacy and security concerns within the specialized AI ecosystem. As AI systems handle sensitive information, robust security measures and data governance policies will be crucial.
- Ethical Implications: Ethical considerations, such as bias in AI models and the potential for misuse of AI-generated content, should be acknowledged. Responsible AI development and deployment are essential for public trust.
My Thoughts on the Near-Term Future of AI (1-3 Years)
In the next 1-3 years, I expect to see the following trends in AI:
- Enhanced Personalization: AI will become more adept at tailoring experiences to individual users. This includes personalized content recommendations, adaptive learning platforms, and customized healthcare plans.
- AI-Augmented Workflows: AI will increasingly be integrated into professional workflows, automating routine tasks, providing real-time insights, and enhancing decision-making. Industries like finance, healthcare, and marketing will see significant AI-driven transformations.
- AI-Powered Creativity: AI will empower creators by providing tools for content generation, design, and editing. Expect to see AI-assisted writing, music composition, and visual art creation become more commonplace.
- AI in Everyday Devices: AI will be embedded into more everyday devices, such as smart appliances, wearable technology, and vehicles. These devices will learn user preferences and offer proactive assistance.
- Edge AI: As AI models become more compact and efficient, edge computing will gain traction. AI processing will occur directly on devices, reducing latency and improving privacy.
Overall, your article provides a well-reasoned and insightful perspective on the near-term future of AI. By considering potential challenges and ethical implications, you can further strengthen your analysis and provide a more comprehensive outlook on this rapidly evolving field.
What do you think the future of AI will look like, and are you worried it will replace you?