Japan's Leading Economic Index Final Value for July

Yesterday I went to my cousin's wedding and saw him and his wife finally reach the happy ending after eleven years of a long-distance relationship. When they stood on stage smiling, their eyes were shining with light, and at that moment, I really felt envious! The result is touching, and my mom suddenly leaned over and turned to ask me, "What about you? When are you going to start a relationship?" I was momentarily taken aback, originally full of emotions, but suddenly I was stuck and couldn't say anything on the spot, I could only silently lower my head and focus on eating. To be honest, right now I only want to make money, and I really have no thoughts about dating for the time being! Just happened to talk about "everyone has their own goals and takes different paths"; it reminds me that the AI community is also like this now. Every AI project has its own small goals, and there can be significant differences in the approaches taken regarding "open source and openness" and "practical usability:" • Pursuit of practicality above all: Like OpenAI and Anthropic, focusing on solving real problems with a clear profit model. They are decided by specialized company teams, who handle everything from research and development to management, ensuring that technology is implemented quickly and stably. • Main Open Source Sharing: For example, DeepSeek openly shares its technical code, allowing anyone to use it, which greatly lowers the barrier to entry. Although it is initiated by the enterprise, it will control the overall direction to ensure that everyone works towards a common goal. • Build an open community: Taking Bittensor as an example, it has built a decentralized collaboration platform that encourages everyone to participate in its construction. Attract more people to join through a reward mechanism, making this smart network grow bigger and bigger. ■The core disagreement among these different development paths ultimately comes down to how to balance "technological control" and "the actual application value of technology": • Some practices are directly managed by a central organization to unify technology and rules in order to see actual results quickly. • Some practices focus more on technology that allows everyone to use it, although management is still centralized to ensure that the entire ecosystem remains orderly. • There are also some practices that focus entirely on building decentralized networks, first establishing the ecosystem without rushing to let the technology generate benefits in reality. ■Breakthrough: Sentient's "Value Closed Loop" New Design @SentientAGI is pondering how to make "open" and "practical" complement each other based on existing explorations. It has designed a set of gameplay to turn these two into good partners. • Governance rights are linked to practical value The management of the community no longer only considers identity status or the discourse power of enterprises, but rather who can create useful things, and those who can do so have more discourse power. • Optimization of reusability for open-source modules To address the common issue of "low efficiency in teamwork" in open source technology, Sentient has come up with a building block approach: No matter which team develops the functional modules, they can be assembled like building blocks for reuse, eliminating the need for everyone to repeat the same work. This not only maintains open and shared technology but also saves a lot of effort, allowing technology to be implemented and utilized more quickly. ■Break the cognitive boundaries of "open-practical" Sentient's methods can enable everyone to collaborate effectively on research and development outcomes, and the money earned from these outcomes can further support more research collaboration. This way, it resolves the contradiction between "how to open cooperation" and "how to apply it in practice" for AI, finding a new approach. However, whether this method is effective or not will depend on the results of its actual implementation in the future. #SentientAGI

*takes Tylenol* > be an electric engineering student > start quant trading *cracked af* > founded a quant firm in his 30's > makes ¥100B trading with ai/ml *even more cracked with ai* > buys thousands of Nvdia GPUs CEO of DeepSeek everybody.

Recently, a project called $BLESS has attracted some follow. The core idea of this project is to utilize the Computing Power of idle personal computers for distributed computing, mainly applied in fields like artificial intelligence model training. However, upon closer analysis, it is found that this technological concept is not novel, as similar ideas have existed for many years. The main challenge currently faced by the $BLESS project is how to achieve effective commercialization and specific monetization channels. Although distributed computing itself has certain potential, more innovation and practical implementation are needed to truly achieve breakthrough applications. For example, if a successful case similar to deepseek can be created, it will truly demonstrate the actual value and impact of the project. Currently, the $BLESS project does not seem to have demonstrated a sufficiently deep value proposition or unique technical advantages. In the absence of a clear path for implementation and points of innovation, the market's enthusiasm for this project may stem more from FOMO (Fear of Missing Out) rather than recognition of its technology or business model. As a distributed computing project, $BLESS needs to articulate more clearly its differences from existing solutions and how it overcomes common challenges faced by distributed systems, such as data security, computing efficiency, and network stability. At the same time, the project team should also provide more specific application scenarios and potential business models to demonstrate the feasibility of its long-term development. Overall, although the $BLESS project touches on a potentially promising technological field, its true value and innovativeness still need further verification. Investors and followers should remain rational and closely monitor the project's subsequent developments and actual implementation, rather than blindly following market sentiment.

Deepseek just released a new model and is close to becoming the first org on a certain AI platform to cross 100,000 AI builder followers!

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