Many of today’s medical processes — chemotherapy, vaccine production, blood donation — will look as backwards to future generations as leeches, bloodletting, lobotomy, and trephination do to us now.
This experiment revealed to me the true power of blockchain. Even though the mechanics of blockchain are simple, the big idea hiding in blockchain is that economics are now programmable. These “tokenomics” provide very pure monetary rewards to perform certain actions. The upside can be so big that tremendous resources are spent by the market to automate certain behaviors. In software, this is very different than the voluntary open source community contributions of the past. Tokenomics provide economic incentives on a micro-level and they inject a big dose of capitalism into self organizing networks.
A complex system that works is invariably found to have evolved from a simple system that worked. A complex system designed from scratch never works and cannot be patched up to make it work. You have to start over, beginning with a working simple system.
A specific challenge in the AI community is: where are the datasets? Traditionally, they have been scattered throughout the web, though there are some lists here and there pointing to main datasets. And of course many of the datasets are proprietary, precisely because they have value. The data moat, remember?
“Despite the proliferation of new media in recent years, words are still the medium of almost all serious business and scholarship,” said DBRS Innovation Labs Director Amelia-Winger Bearskin. “That is why it is so important to develop robust and dependable tools for natural language processing. If we want to use computers to augment our understanding in these areas, we need methods by which computers can interpret the subtleties, idioms, and contextual cues that crop up in even the most official of documents.”
As a pioneer in ushering in the reading and writing of the genetic code and the programmability of biology, it is clear to me that understanding the brain and neural code will come next. Twenty years ago most thought that reading the human genome would be a nearly impossible task without billions of dollars and a huge army of scientists and decades of time. The reality was nine months, $100 million and a small team. I expect the same will happen when we look back in twenty years’ time on Kernel’s efforts. Today’s announcement of a $100M commitment to Kernel by Bryan Johnson, in an effort to amplify human intelligence has the potential to be one of the greatest contributions to humanity. I couldn’t be more excited to be working with Bryan on his audacious endeavor.
Ultimately however, this is not about what Viv gets, or what Samsung gains. This is now about a paradigmatic leap beyond everything that is available today, for everyone. This is just the beginning. It is a new line of thought. The age of single, vertical, hard-coded intelligence is over, and an era of flexible, vastly more capable, welcoming AI is set to begin.