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| By Jurica Dujmovic |
Out of all the techy buzzwords out there, “artificial intelligence” currently reigns supreme.
It has dethroned the metaverse, and even Meta (META) CEO Mark Zuckerberg understands that the future lies not in virtual worlds, but in the automation and pattern recognition only AI can provide.
As we continue to build a world for AI, will there be any room for us in it? How will AI affect our everyday lives … and perhaps even our jobs?
Well, let’s imagine the average day in an average company.
After a C-level executive has outlined an overall strategy, a manager ensures that lower-tier employees are able to implement it.
For instance, if it’s a marketing task, then it passes through a series of copywriters, artists and compliance specialists to ensure that the final marketing asset looks good, reads well and does not cause any legal trouble.
Now, you can imagine that this process takes a great deal of time, coordination and communication between various departments.
We all know time is money, so these costs are far from negligible.
But what if this average company had an AI system capable of doing all this work for it?
Here’s how that would look:
1. The high-level executive would introduce a strategy to the manager.
2. The manager would introduce the strategy to the AI system.
3. Based on the manager’s inputs, the system would engage several highly specialized AI models with tasks necessary to accomplish the goal.
To visualize how this works, let’s go back to the marketing example.
If we replace human workers with AI, then a natural language processing model like ChatGPT could be trained on the company’s marketing lingo to produce an outline and all the marketing copy needed for a project.
This copy would then be summarized and parsed into a prompt that an AI program like Stable Diffusion or Midjourney could use to generate the artwork.
Then, the resulting assets would be combined into a deliverable, such as a landing page for a website.
From there, the manager could review the final product and provide critiques where necessary.
Based on this information, the AI system could modify the prompts provided to its models to improve the output. Additionally, the AI would learn from these critiques, so it can do an even better job in the future.
In this workflow model, we have removed everyone except for the C-level and managerial employees. And I firmly believe this is something we can possibly expect in several years’ time.
With inflation running rampant and the economy on the brink of a recession, these changes could be expedited. This is because businesses will need to consolidate to keep their gains at previous levels, or to simply keep the company afloat.
Now, I believe C-level workers will remain for the large part unchanged. Instead, it’s the managers I want to talk to you about.
These individuals will not only need a senior level of expertise in their own field, but also a solid grasp on the sacred art of prompt engineering.
Essentially, prompt engineers are the horse whisperers of tech: They understand the best way to communicate with AI in order to get the job done while also improving its output and correcting its mistakes.
Also, these managers will need to know how to build datasets for the AI. After all, the AI system is only as good as its models, and the models are only as good as the datasets they are trained on.
For bigger companies — as well as those with a ton of data — specialized businesses will need to train custom-made models.
So, how close are we to this future? I would say pretty close.
Today, the best AI models out there can pass the bar exam, write content and create amazing works of art.
Although they still require some hand-holding, this is nowhere near the amount of oversight these models required mere months ago.
Fast forward six months into the future, and you can expect them to be even more autonomous.
So, AI will be even more valuable to trigger-happy companies all around the world.
And I’m not just talking about the tech giants that recently shed over 15% of their workforce on average. This includes smaller companies that are struggling in what is soon to become a global recession.
Is there a silver lining? For investors, absolutely!
For one, companies developing these types of AI systems are the ones to keep on your radar.
Microsoft (MSFT) seems like an obvious choice, but as far as I’m concerned, the jury is still out there.
Microsoft bought its way into AI with its OpenAI investment, but it’s obvious the Redmond giant is still struggling to figure out how to best merge it with its software suite.
Then we have NVIDIA (NVDA), with its innovative forays into generative art models and techniques.
Every month, NVIDIA releases new papers showcasing interesting and fascinating ways of utilizing AI to speed up rendering in games and applications and so much more.
Unlike Microsoft, NVIDIA is firmly entrenched in AI. And its contribution to the current and future development of AI is undeniable.
Next, we have Meta. Mark Zuckerberg’s fascination with all things new and shiny has led him to change his focus from the metaverse to AI.
Although he poured millions into something he couldn’t quite deliver with the metaverse, his venture into the AI space seems to be a bit more promising.
From its leaked natural language model LLaMA to its interesting text-to-video model, Meta is demonstrating it understands the AI game much better than virtual worlds and their audiences.
And it’s not just TradFi companies getting into this hot sector.
Swept along by the gathering excitement, the crypto community has lately been paying huge attention to AI-related coins. My colleague Marija Matić told her Undiscovered Crypto Members back in February to keep an eye on AI-leveraged crypto projects, chiefly, Render Network (RNDR, Not Yet Rated).
That is because it sits at the crossroads of three of the most powerful forces in crypto, AI included.
RNDR offers distributed computation for cloud rendering of images and videos. In English, it uses the unused processing power from a decentralized network of computers like yours and mine to render graphics for videos and images for everything online games, to blockbuster special effects for live action films and animated features, to avatars for the metaverse and more.
Its method of crowdsourcing hardware for rendering — meaning anyone in the world can connect to the network and lend otherwise idle computing power to those who need it — makes it infinitely scalable and much cheaper than its TradFi competitors, like AWS.
Most recently, Render has integrated Stable Diffusion. This will allow Render users to generate creative AI-enabled images through Stable Diffusion by using previously rendered images from their account. Users will also be able to edit and remix them using an in-app photoshop app.
Even better, Stable Diffusion is only the first AI app to be integrated with Render Network. Next up are plans to incorporate more AI programs, like ChatGPT. Among other things, this will allow users to help train large AI models … and get paid for their efforts via the interface's microtransaction royalty flows.
The vast unmet demand for GPU by AI platforms virtually guarantees a bright future for Render Network in this domain.
This just shows what a wild wave of popularity AI is presently riding.
The speed at which this sector is innovating may be shocking. And new technology — especially when it can do what a human can for faster and cheaper — can be intimidating.
But if you’re savvy, AI can be seen as a window of opportunity.
Whether it’s investing in the right companies or crypto networks or doing as I have done and building an AI-powered venture like my NFT Business Builder — an AI-powered business-to-business web3 service — innovative minds should be able to see AI’s potential.
What about you? What will you do to stand out in the world of AI? Let me know by tweeting @WeissCrypto!
Best,
Jurica
