Technology history as a prelude
For example, consider cotton gin. Invented in 1793, cotton gin used a combination of wire teeth on a rotating cylinder, and grates or screens to pull out the washed cotton fibers, greatly improving the speed and efficiency of cotton processing. This had a major impact on the cotton industry, particularly the southern states. Cotton in particular is a major labor-intensive crop, and commercial use has had a significant impact on the large part of the labor force. In the face of this fundamentally destructive technique, cotton gin inventor Eli Whitney wrote this to her father. “One man and a horse do more than 50 men with an old machine.”
And certainly, the potentially devastating meaning for society was much hidden by the entire industry, born of this simple invention that has fueled the growth of the southern region for over a century.
And that continues until this century. Andrew Ng, founder and lead of Google Brain and now a board member of Amazon, recently said the same thing. “I think AI could free humanity from many spiritual drastic humans just as the Industrial Revolution has freed its physical and laborious humanity.”
Mother of invention
From simple stone tools to complex genetic engineering and information technology, the history of technology is the history of human tools and inventions. The speed at which these tools and technologies are currently being delivered is exponential when machine learning applications and AI are all ubiquitous open source components layers, and is accelerated mutually by the arms race due to processing speed. Currently, it measures success with PetaFlops (quadrillion floating point operations per second) and trillions of parameters.Internal numeric values for LLMS to learn during training and process and generate text.
As knowledge-seeking animals, the potential value of these tools to enhance understanding of the world around us and solve some of our most pressing problems regarding the quality and quantity of life is just as appealing as Pandora's Box. As Mark Andressen said, “Technology is the glory of human ambitions and achievements, the front of progress, and the realization of our potential.”
For decades, this new computing power has led us to continue (seemingly) seeing breathtaking exponential breakthroughs, but less exciting than the field of synthetic biology where we can truly see the practical application of the positive outcomes of AI. One powerful example of how this is already being used is that it has been pioneered by Andrew Adams of Elily and Company. In pursuit of treatment for the debilitating disease of Alzheimer's, researchers discovered a Christchurch mutation. One copy of the Christchurch variant awarded protection against Alzheimer's disease, even individuals with genetic predisposition to the disease. The ability to apply synthetic biology to enhance and provide this modification will translate the field of Alzheimer's disease from treatment to prevention.
In this we have a free AI model that predicts the structure of all life molecules, Google's recent open source release of Alphafold, and we're beginning to see what is possible now. The fact that Google provided access to over 200 million proteins and provided free AI tools for scientists to experiment is exponential in itself.
Certainly, this seems interesting to the unscientific community, but it's puzzling until we start to see that real applications for new technology toolsets are being built. Enter Ben Lamm, founder of Colossal, a George Church protégé. The self-proclaimed “cereal entrepreneur” started Colossal in 2019 for $15 million. It currently costs $1.02 billion, and with the sole purpose of advancing the causes of detension, he reconstructed the DNA of lost megafaunas and other creatures using advanced gene editing techniques. Maintaining this integrity along with the Earth losing 30-50% of its biodiversity by 2050 is essential to life on Earth. His work is mission critical. His latest achievement, the birth of three miserable wolves (Romulus, Remus and Khaleesi), is considered “the world's first successful animal.” Wool mammoths and dodo birds are also featured on the roadmap, but work at Colossal is more than just creating 21 new creaturesst– Jurassic Parks of the Century; instead, it is to build technical capabilities to stop the current wave of extinction in their trucks. Colossal is also trying to use synthetic biology in other useful ways, editing the genes of Amazon microorganisms called “X-32” and editing from “X-32” from microorganisms that enjoy eating plastics to those that digest polymers in weeks rather than decades or century, leaving behind carbon dioxide, water, and living things. This new solution helps to address the plastic pollution issues on our planets, microplastic issues in our bodies, all enhanced use of data and computing power.
Synthetic Future
Naturally, synthetic data and synthetic biology have “all synthesis.” Synthetic people (robots), synthetic media (Google Veo, Midjourney), synthetic news, and even synthetic truths. It is clear to us that there are bad actors and bad intentions. And the dystopian industrious and eerie need for our own work is a reality, especially in this current era. The need for ethical human beings within the loop is no more miserable and we all have to remain enthusiastic about these poor consequences. We must be diligent as these are human decisions placed before us, and we have built this amazing new set of AI tools, and that promise is far beyond the risk.
At this year's World Economic Forum in Davos, technology optimist Andrew NG was asked directly about the dangers of AI and artificial general information (AGI) and said, “Do you think the world is better with more intelligence? We mainly use human intelligence. But on average, I think we all actually get much better.” But is this a false equivalence? More intelligence may be better intelligence, but is better AI better AI? The answer to this depends entirely on how you use it.
From our daily business to everyday feed, the exponential pace of practical use cases in machine learning, AI, and even agency application layers is indisputable. It is already known that AI is a ubiquitous open source business ingredient of speed, agility, efficiency and profitability. To paraphrase Eli Whitney, “From this technology you can create wealth.” However, only by fully understanding the meaning beyond opportunity and using the process of application innovation to see breakthroughs in technology outside of the industry can it be seen more clearly and drive the most desirable outcomes.
As leaders, we must always be cautious about what we move. In Pandora's f story, when we are open to all inevitability, unintended consequences can occur. But we also know that with the right insight, hope never leaves the box.
