TheWhiteBox · Independent AI analysis
Neuralink Deep Dive, How Does it Work?
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Breaking down the most advanced AI systems in the world to prepare you for the future.
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TLDR:
AI Research of the Week: Answering the Real Question, How Does Neuralink work?
Leaders: EVO, the First Biological Foundation Model that Could Change the World
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🤩 AI Research of the week 🤩
The moment we all saw Trevor playing chess with the mind, we knew something had changed.
A few days ago, Neuralink presented its first real patient testing its brain chip. The user played chess, or even Mario Kart.
Overall, an impressive and life-like demonstration of the hugely optimistic future that awaits people with severe disabilities like Trevor, who is a quadriplegic.
And while the exact intricacies of the system aren’t fully disclosed, what we know, combined with cutting-edge AI research in Brain-Computer Interfaces (BCIs) is more than enough to give us great insight and understanding of how Neuralink works.
Welcome to Pattern World
Whenever you see an AI product, no matter how complex or secretive it is, it all boils down to the same principle: finding patterns in data.
There are two ways of doing so: generative or discriminative.
Generative AI models
Although the definition is in the name, it’s not quite as obvious. Yes, generative models generate data, but I’m not here to state the evident but to help you understand how they truly work.
Simply put, generative models learn the distribution of the training data and sample from it. In other words, they figure out the statistical correlations in the data to maximize the likelihood of being capable of replicating it.
In essence, this is what ChatGPT is, a set of parameters that maximize the likelihood of generating data that is similar to the training data.
In practice, for a given sequence, they give you a statistically reasonable continuation of that sequence. In other words, “based on my training data, what is the set of next words more likely to be ‘similar’ to what I saw during training?”
At this point, you would be…
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