The price action of $BTC has been the hot topic in the market these past few days. When it pumps a bit, the chat's buzzing with bullish vibes; when it dips, the timeline floods with bearish sentiments. After riding the waves of several bull and bear markets, I've noticed an interesting phenomenon: most folks are fixated on the price daily, while a select few delve into what’s actually happening behind the scenes. A single candlestick can tell different stories; some see gains and losses, others track the flow of capital, some gauge market sentiment, and others spot industry trends. Often, the biggest gap between people isn't about who hustles harder, but who has a deeper understanding of the issues at hand.
Remember a few years back when AI first started to explode? The main discussions were around model parameters, computing power, and generative capabilities. Back then, I thought the future winners would definitely be the companies with the strongest models. But as more models emerged, I slowly realized that while being technically advanced is important, it might not be the most crucial aspect. Technology will ultimately spread; open-source models are becoming stronger, training costs are continuously decreasing, and the seemingly unreachable barriers are being quickly leveled. As more people acquire similar capabilities, the questions worth pondering start to shift.
It was during this process that I revisited @OpenLedger . I used to think the competition in the AI industry was all about technology, but then I realized that technology is often just the surface. The deeper issue is when AI starts generating more and more value, where will that value ultimately flow? Looking back at the development of the internet, users contribute content, developers build ecosystems, and communities create activity, but in the end, a large portion of the profits often remains with the platforms. The AI era is likely to amplify this phenomenon further, as models can continually learn, grow, and create value, but the knowledge, experience, and content that fuel model growth fundamentally come from countless ordinary participants.
This is also #OpenLedger what piques my interest. Instead of constantly chasing after model capabilities, it's more about contemplating the value distribution in the future intelligent economy. As more wealth is generated by AI, will ordinary participants be able to carve out their own space? Can a healthy ecosystem allow contributors to share in the growth dividends? Historically, every technological revolution creates wealth, but what truly determines the flow of that wealth isn't just the technology itself, but the design of the underlying rules. So now looking at $OPEN, my focus is no longer just on the AI concept, but on whether the industry can establish more reasonable collaborative relationships and value attribution mechanisms as AI gradually becomes a fundamental productivity force. The market always likes to chase the hottest narratives, but in the end, it's often those who redefine the rules that alter the industry landscape.