Leaders: The New Dark Age of Advertising

🏝 TheTechOasis 🏝

Breaking down the most advanced AI systems in the world to prepare you for the future.

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🥇 Leaders 🥇

For almost 5 years, language models have been at the cusp of the AI industry. However, it’s becoming clear we are in an unavoidable transition from language to video.

In other words, instead of Large Language Models, or LLMs, we will soon have Large Video Models, or LVMs, as models like Genie or Sora prove.

But, for once, instead of celebrating the great things that AI gives us as we usually do, we are plunging into the scary side of AI.

No, I’m not going to tell you that AI video models are going to kill you, or that they are an existential threat to humanity. I’m not a doomsayer. However, we must not forget about the worst things about AI that will happen.

While LVMs have the potential to bring huge prosperity to our civilization, I fear they will also become the ultimate surveillance weapon, not only to target us through manipulative advertising, but also as a tool for massive censoring of unwelcomed opinions.

Simply put, while LVMs might be the door to AGI, or at least that’s what OpenAI seems to be betting on, they will also be the gate to our secrets and unconscious desires, a gate that will kickstart the golden age of advertising and manipulation of the masses, a world where you are, put bluntly, the ultimate product.

The Language Era

At some point in your life, you might have asked yourself, “If we have been hearing about AI for decades, why is there so much hype?”

Probably, ChatGPT comes up pretty quickly as a reasonable explanation. But ChatGPT is not the reason, but the moment a vision pushed almost a decade earlier finally took form.

In fact, the golden age of AI started back on September 7th, 2013.

From Word2Vec to ChatGPT

That day, word2vec was presented to the world.

Created by Google, it was the first time we created a semantic representation of text.

In other words, we had managed to turn a word into a vector of numbers, known today as embedding, that represented that word in a comprehensible way for machines while retaining the meaning of the original word.

This concept was very powerful to the point that you could perform arithmetics with words, which led to the famous “king - man + woman = queen”.

This was fascinating, as we could now teach machines, elements that can only see numbers, how our world worked.

Then, around a year later, the concept of attention was first introduced.

This mechanism, the quintessential component of most frontier models today, if not all, was the first time we have found a way to help machines learn about our data while allowing them to ‘choose’ where to pay attention to.

Leveraging that words now had meaning, thanks to innovations derived from word2vec, the attention mechanism allows the model to, over…

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