Technologies constantly intersect. This impacts a technologyโs life cycle (TLC) that already has its own phases of development and market adoption.
Technology life cycles follow an S-Curve. The shape of each technologyโs S-Curve is unique, but generally, research and development requires an investment. With traction, the technology can ascend and become profitable. Over time, this ascension slows as a new normal is established. Market relevancy can be lasting, but eventually, new technologies push existing technology toward a final decline phase. The further a new technologyโs life cycle is from the current status quo, the faster one can push the other into history books. For example, when cell phones went mainstream, it did not take long for pagers to fall out of our pockets.
When different technologies ascend around the same time, they each have their own TLC, but the shared timeline only has room for what the market and adoption curves allow. This initiates a game of scarcity versus abundance. If two technologies remain isolated, scarcity wins and causes the ascension of one technology to force the other technology toward a decline. With a sense of abundance, different technologies find reasons to interact, interconnect, support, and perpetuate each other. Even if the relationship is not obvious at first, layered value broadens the impact and extends each technologyโs life cycle.
This can be seen in the rise of web3 and AI technologies.ย
At first, hype was focused on blockchains and everything under the web3 umbrella. As blockchain networks were ascending past early adoption, Narrow AI learned to speak our language and quickly stole the spotlight. This lowered the volume around web3 as everything became about AI. With volume lowered, it was easy to think web3 concepts were no longer relevant, but the interoperability of web3 technologies can support, guide, and tame AI.
When AI makes everything fake, blockchains make it real again. This symbiosis aligns two different technology life cycles. When balanced, AI is yin and web3 is yang. The yin of AI is exemplified by unpredictability and independence. The yang of web3 draws from decentralized dependancy.
AI is strongest when rooted in web3 concepts, which are strengthened by the capabilities and functionalities of AI. Together, these two seemingly unrelated technologies benefit in various ways. For example, ChatUX gave AI a voice, which can now imitate anyone, but blockchains and zero-knowledge proofs can confirm identity. The chaos continues as compute speeds of machine learning makes state management hard to uphold, but blockchains, smart contracts, and digital assets can track provenance and the present state of a digital system. If AI projects need financial capital, digital currencies and tokenomics can provide economies to scale. As the capabilities of Narrow AI move toward General AI and Super AI, generative data may struggle to preserve the source of truth, but web3 technologies add transparency to improve inputs and helps avoid unsteadiness. Even at the infrastructure level, AI can benefit from decentralized training algorithms and a growing thirst for electricity can be quenched by HPC data centers originally built for mining cryptocurrencies.
Extra Shot
Darkness will always lurks in the shadows, but the virtuous light of abundance bets on a shared, atomically exquisite existence.
This example highlight how mixing different concepts can greatly extend technology life cycles. Such abundance also paves the way to more exotic technologies.
