DNA Layer's Impact for AI

No single researcher today can explain exactly how neural networks can work so well in practice. No one knows why, for example, significantly fewer neural layers are needed in an artificial network than in a biological one to still far outperform the brain in cognitive tasks. This underscores the immense lack of understanding that we have in this technology that we are building so quickly.

LLMs hallucinate regularly today despite deep investment into methodologies to prevent this. The top researchers in the world at OpenAI and Google have said that their models “breathe on their own” and cannot fully be understood.

And everywhere you look, there is bias and negativity in AI output. Indeed, this is why safety is such a huge concern among the top companies in the space. These are the earliest days of AI evangelization around the world and already, there are unknowns even from AI’s foremost creators.

The only way to truly harness AI, to reign it in and successfully focus its implementation while guarding against misdirection, is by putting the process for its querying on-chain. This was the challenge that we embarked on solving over a year ago. And this is how DNA Layer's unique technology was born.