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Bitpush Column · 4 articles

Traffic in Hormuz has plummeted, yet the price of oil has not reached the $100 mark

Author: Huohuo Original title: Hormuz traffic has plummeted once again. Why haven't oil prices stabilized above $100? TL; DR · Some daily traffic levels in Hormuz fell to a very low level, but Brent did not continue to stand at $100. · The market is temporarily betting that inventory, transit, alternative exports, and buyer detours can absorb some of the impact. · Related subjects: BRENT/WTI crude oil, energy ETFs, oil tankers, independent Chinese refineries, diesel chains, gold. Since August, shipping tracking and media reports have shown that daily traffic volume in parts of the Strait of Hormuz has dropped to a very low level, and there are even statistics that almost no tankers pass through. But Brent crude did not stand at $100 continuously. After a brief surge in late July, it has recently been back around $90 for more time. This is where the current energy market needs the most explanation. Around 2024, about 20 million barrels/day of oil products passed through Hormuz, accounting for about 27% of global shipping oil, and LNG (liquefied natural gas) also accounts for about one-fifth of global trade. According to the traditional pricing framework, this area has been threatened for a long time, and oil prices should quickly be included in the supply cutoff premium. The answer given by Hormuz, which affects the oil and gas trade market, is now more restrained. The risk has not disappeared, but investors are temporarily convinced that inventory releases, trans-shipment outside the bay, and alternative export and shipping arrangements can share the impact. The oil price transaction is not “strait safety,” but “strait traffic becomes more expensive.” The US-Iran impasse provides the political context for this round of reevaluation. According to reports, the two sides are in dispute over the implementation conditions of the June Interim Memorandum. The US maintains blockade and sanctions pressure, while Iran requires that normal traffic be resumed only after the conditions are implemented. When the dispute hits the market, it's actually a matter of cost allocation: who bears the higher risk of insurance, financing, voyage, and sanctions. The worst case scenario for oil prices has yet to be traded. Currently, the market is not pricing Hormuz as a long-term complete supply cut. If investors believe that 20 million barrels/day of marine oil will disappear for a long time, it is difficult for Brent to repeat it around $90. The price did not continue to stand at $100, which means traders are more likely to understand it as blocked access, rising costs, and delayed delivery rather than a broken supply chain. There is still statistical noise here after Brent rushing higher and falling back. The sharp drop in some daily traffic volume may be due to ships shutting down AIS positioning, short-term waiting for shipowners, differences in data source screening, and may also indicate that commercial shipowners are unwilling to enter high-risk waters. The former is closer to data distortion, and only then will the latter cause a continuous supply shock. Therefore, oil prices have not stabilized above $100. It's not that Hormuz is unimportant, but that the market is still waiting for tougher verification. Whether Iran can continue to expand its attacks, whether the US escalates the blockade to more direct action, and whether Asian buyers can bypass shipping and sanctions restrictions will all change this pricing. The buffer mechanism split the shock into multiple segments where oil prices did not immediately get out of control. One of the core reasons was that the shock did not hit the terminal supply all at once, but was broken down into inventory, shipping, trade, and finance. The most immediate buffer comes from inventory and alternative supply expectations. Strategic oil reserves, coordinated international releases, idle OPEC+ production capacity, and Saudi Arabia and the UAE's export capacity outside the strait may weaken the impact of single channel disruptions on spot prices. They can't be used indefinitely, but they are enough to keep the market from pricing in disaster scenarios for a while. The detour capacity only covers part of the second layer of buffering from ship-to-ship transfers. Some cargo can be moved around Fujairah or the Gulf of Oman and then re-routed. This increases insurance, waiting times, and operating costs, but allows the logistics of goods to remain flexible. The third layer of buffering comes from the choice of buyers and shipowners. Some Asian buyers and shipowners may switch to off-bay loading, transshipment, or delayed port of call arrangements, and LNG transportation may also take similar safe-haven actions. As a result, a decrease in traffic volume in Hormuz does not necessarily equal a simultaneous decline in the amount of oil and gas available globally. That's the heart of current pricing. The physical risk remains, but it is being shared by financial inventories, shipping engineering, and trade arrangements. Oil prices haven't exploded because the system is still running. The reason why oil prices are not falling is because the system is more expensive to operate. Impacts are absorbed in segments, and long-term costs are buffered into the supply chain in the short term, and the more effective it is to invest in long-term restructuring. Saudi Arabia and the UAE are promoting off-strait reserves, Fujairah transit, and alternative export capacity, and discussions on pipeline and port investment in the region that bypass Hormuz are heating up, all pointing in the same direction: the energy chain is reducing its dependence on single-point traffic. This type of restructuring will not immediately change the global supply and demand schedule. The new pipeline requires financing, construction, and safety conditions, and the expansion of strategic reserves will take time...

2d ago律动BlockBeatsETFgold

Traffic in Hormuz has plummeted, yet the price of oil has not reached the $100 mark

“Graduation rules” under SEC's new rules: token financing is legal, but too many promises make it impossible to get away

Author: 0xFACAI Original title: The SEC threw a bombshell, is the spring of compliant token financing finally here? Public coin sales and financing have once again gained a legal path in the US. On August 18, the US Securities and Exchange Commission released a draft “Regulation Crypto Assets”. According to this draft, startups can raise $5 million in up to four years, and larger projects can raise $20 million or $75 million in 12 months. Without completing a complete set of securities registration, the project can also sell tokens to investors to raise money for network development. Sounds like IC0 is back. But the SEC gave far more than three funding lines. It wants to establish a set of rules for tokens from birth to “graduation”: projects can be sold to finance first, but it is necessary to clearly explain what to do with this money; if the key work promised by the team is not completed, the token continues to carry the regulatory responsibility for investment terms; only after fulfilling the promise, the token has a chance to exit this level of relationship. “Promises” are the core of the entire draft, and devs must “work” until the token “graduates” before they can “sell”. The draft rules gave the project parties two options. The first type is suitable for startup teams. Assuming a project required $3 million to develop, common choices in the past were to seek venture capital, limit buyers and issue coins outside of the US, or incur the high cost of registering securities. The new draft allows it to use the “startup exemption,” raise no more than $5 million over a maximum period of four years, and file with the SEC when the funding starts and ends. The second type is suitable for projects with greater funding requirements. The first tier raised up to $20 million every 12 months, and the second tier raised up to $75 million. Compared to the $5 million startup exemption, this path can be used over and over again, but the rules are more stringent. Projects can't just hand in a white paper and start selling coins. Both exemptions require the team to disclose how the network is being managed, how the product is being prepared and developed, what security risks the code has, what the company's financial situation is, and who is managing the project. The two larger funding levels also require financial statements to be provided and continuously updated, and the $75 million tranche requires an audit. The SEC didn't remove the original fence either. Issuers and insiders with a record of serious violations cannot use these exemptions, and anti-fraud and anti-manipulation responsibilities remain in effect. If the project uses other securities exemptions at the same time, it must also comply with existing consolidated financial calculation rules. The most important aspect of how to define “graduation” in the entire draft is to treat tokens separately from the investment relationships formed around tokens. A project sells coins to raise money to build a network. Buyers often buy more than just a digital asset that can already be used. They are also expecting the team to create products, attract users, increase token demand, and profit from these efforts. This relationship, which depends on the team's future work, is what the SEC calls an “investment clause.” The token itself can be just a digital asset, but how the project sells it and what it promises to the buyer makes it covered by a layer of investment terms. What the SEC really regulates is this level of relationship between issuers and buyers. The draft designs an exit path for the token. The token can only enter a “safe harbor” after the issuer has completed or permanently ceased all key management tasks of its promises, no new related commitments, and then submitted public certification and analytical instructions to the SEC. As a result, tokens have the concept of “graduation.” When the project is sold and financed, construction is promised to the market. After the project is completed and key tasks are completed, the buyer can no longer rely on the team to fulfill the old promises before the token can “graduate” and the project party can withdraw. The new regulations don't focus on whether tokens are considered securities. In the past, the market judged when a token was no longer subject to securities laws, and often questioned whether the network was “decentralized enough.” As long as the foundation, development company, or founding team continues to work, many people will understand this as the token still relies on a central entity. The SEC draft changed the question: what promises did the project rely on to sell the tokens, and are those promises fulfilled now? Take an example. When Project A sells coins, it tells investors that the team will develop the main network, launch transfer and pledge functions, and then leave the network to a decentralized validator to operate. The main network was later launched, and the features were also available, but the validators were still controlled by the team. Since “decentralizing the network” was also a promise at the time of financing, the token is still unable to “graduate” at this point. When Project B sells coins, it only promises to make a network that works properly; it does not include “the team must disappear” or “the network must reach a certain degree of decentralization” in the financing promise. Wait until the Internet is online and produced...

3d ago律动BlockBeatsSECfinancing

“Graduation rules” under SEC's new rules: token financing is legal, but too many promises make it impossible to get away

Fireworks that came out of Meta to talk about open source and closed source. Who will win?

Author: Silicon Valley Vector Silicon Valley Coordinates Editor: Peggy, BlockBeats Original title: Silicon Valley Coordinates x Fireworks Co-Founder Benny Chen: Open Source Models, Token Growth, Inference Optimization, and Model Customization Editor's Note: In the context of open source models speeding up and approaching cutting-edge closed-source models, industry discussions are shifting from “who has the most capable model” to “who can put models into production at a lower cost”. However, when model capabilities converged and token consumption increased, a lower-level question began to emerge: are companies really willing to pay a cheaper model call, or exclusive intelligence that can perform specific tasks in a stable manner? Recently, Cao Qingyun, host of “Silicon Valley Coordinates”, had a conversation with Chen Yufei, co-founder of Fireworks AI. Located between models and enterprise applications, Fireworks mainly provides customers with open source model inference, performance optimization, and customization services. Rather than simply discussing whether open source can catch up with closed sources, Chen Yufei's observations are closer to actual workloads: where tokens flow, why companies pay, and what is still missing from the model from proof of concept to production. In this conversation, Chen Yufei disassembled “who wins between open source and closed source” into a set of lower level structural questions: can token growth be converted into revenue, can generic capabilities replace vertical accumulation, can the low price model pass corporate evaluation, and how the inference platform can gain value between cloud vendors and application companies. First, the scale of use and commercial value of the open source model are diverging. In the past, the ability to catch up and call price were the main indicators for judging the competitiveness of open source; today, the Fireworks platform processes about 40 trillion to 50 trillion tokens every day, and the actual usage of the open source model has rapidly expanded. However, free traffic, promotional subsidies, and model price differences will cause Token statistics to overestimate some demand. Customers may heavily use lower-cost models and still hand over the highest budget to the best-performing closed source model. This means that the next phase of open source is not just expanding traffic, but proving that it can meet or even surpass cutting-edge models for high-value tasks, and turn cost advantages into willingness to pay. Second, the general model and the vertical model are beginning to evolve in different directions. In the past, every time a cutting-edge model was upgraded, it was possible to directly eliminate a number of fine-tuned models; now, vertical applications such as law, medical care, and programming are accumulating more detailed evaluations, data, and workflows, and their optimization goals are gradually separated from cutting-edge laboratories. Generic models need to increase the upper limit of capabilities, while vertical models require stable delivery of results in limited scenarios. The former can solve a wider range of problems, while the latter has a better understanding of how users define “right.” This means that the barrier for vertical companies is not just having a customized model, but being able to continuously transform industry needs into an evaluation system and migrate over and over again as the basic model is updated. Third, the bottleneck in enterprise AI implementation is shifting from model supply to evaluation capabilities. In the past, enterprise proof of concept often relied on trial experience and subjective judgment; now, when AI enters production processes such as call centers, legal searches, and medical assistance, it is no longer possible to support procurement decisions simply by “looking good.” Businesses must know what tasks the model works for, when it fails, and how much the cost and quality of switching from closed source to open source changes. Assessment is therefore no longer an ancillary tool, but an infrastructure connecting procurement, training, and production deployment. Who can define tasks, establish test distributions, and continuously update standards can truly control model choices. Fourth, the value of inference platforms is shifting from “selling cheap computing power” to organizational models, hardware, and workflows. In the past, inference optimization was mainly understood to reduce the cost of a single token; now, caching, task splitting, model routing, and context management can all directly change the task completion rate. Different models don't have to compete for the same position; they can act as performers and advisors separately. Fireworks' business logic is also based on this: instead of building asset-heavy hardware, revenue is tied to actual use of customer models through training, customization, and continuous reasoning. But the main rival in this path is not a single new cloud company, but a large cloud vendor that can simultaneously control computing power, software, and customer portals. Fifth, the rise of the open source model may not reduce infrastructure requirements; on the contrary, it may reduce model layer premiums and further push value towards reasoning and computing power. Tech giants continue to increase capital spending, not just calculating short-term returns, but measuring missed AI cycles...

4d ago律动BlockBeatsAI

Fireworks that came out of Meta to talk about open source and closed source. Who will win?

Remember NFTs? The price of the new project exceeds that of Bored Ape

Author: CookieRobinhood's NFTs are getting more and more attention, and the most immediate catalyst was an interaction between Robinhood CEO Vlad Tenev and Beeple's tweet. NFTs have been around for a long time, and Beeple is one of the few people who can also have a boosting effect on NFT assets. It's a bit like “whatever Beeple draws, whatever it goes up”. In the tweet above, Vlad appears as an NFT savior, holding Cash Cat with the caption “Robinhood is saving NFTs.” Vlad replied, “Someone always has to do this.” As the “second protagonist” in the picture, the Cash Cat NFT series's floor price rose to a maximum of around $660, a fivefold increase in 2 days. Before Vlad launched this direct catalyst, the floor price of StonkBroker, the leading NFT on the Robinhood chain, once surpassed 13 ETH (about $25,000), but now it remains at 11.75 ETH. Judging from the price of a single NFT, this series has surpassed BAYC, and its total market value once surpassed 100 million US dollars, surpassing many old blue-chip NFTs such as Pudgy Penguins and Milady. Are NFTs really revived on the Robinhood chain? How can I quickly get started on this track that has been forgotten by everyone for a long time? Meme Coin/NFTMeme Coin comes with an NFT series. This is the first Robinhood NFT project category worth mentioning in this article. In addition to CashCat, $HOODRAT has also launched a supporting NFT series, and this one is directly carried out by the meme coin project, so there is no need to worry about whether the community will recognize it or not. However, $HOODRAT's current market value is only about 3 million US dollars, making it difficult for NFTs to rise anywhere. We mentioned Cash Cat NFTs at the beginning of the article. Although this NFT series doesn't come from the official Cash Cat meme coin, after Vlad tweeted, it had 3 imaginable logics: - Currently, the market value of $CASHCAT is around US$1.5-160 million. Based on the highest floor price of 660 US dollars over the past few days, the corresponding market value of the entire NFT series is only 6.6 million US dollars. If the price of $CASHCAT continues to stabilize, break through new highs, and continue to rise, then the price of the NFT will seem more cost-effective - what if Vlad swaps his X avatar for a Cash Cat NFT? - Although it is not a part of the $CASHCAT project, there aren't any examples of a successful meme that came from the original project party. The most typical example is $SPX6900/AEON. The highest AEON has reached a market value of about 25 million US dollars, corresponding to a single floor price of about 7,500 US dollars. After a short period of FOMO, the floor price of Cash Cat NFTs has fallen back to about 375 US dollars. This is a normal correction, and it will still be An NFT collection that occupies a key position on the Robinhood chain depends on the height of $CASHCAT and whether it can be widely recognized by the $CASHCAT community. Therefore, this type of project should be tracked from two aspects: - A coin with a meme image that has risen well. Recently, $hmm on Pons has suddenly skyrocketed quite a bit. If the latter can withstand the current sharp correction, NFTs will also be picked up. It's just not easy to say which series - it's already led by the meme coin project or related meme coin NFTs that have already run out of price. Follow the price trend of the meme coin itself and observe whether the odds for the corresponding NFTs are appropriate StonkBroker is currently the top 3 most expensive NFT series, all of which are “StonkBroker series”. StonkBroke...

8d ago律动BlockBeatsNFTs

Remember NFTs? The price of the new project exceeds that of Bored Ape

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