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According to Golden Finance, REX Shares has announced the launch of the T-REX 2X Long SpaceX Daily Target ETF (SPAX), which will provide 2x daily leveraged long exposure to SpaceX stocks. However, REX Shares warns that this fund is a high-risk leveraged product suitable for investors with professional trading experience, and there is a significant risk of deviation from the performance of the underlying asset during holding periods beyond a single day.

[REX Shares Launches 2x Long SpaceX ETF SPAX]According to Golden Finance, REX Shares has announced the launch of the T-REX 2X Long SpaceX Daily Target ETF (SPAX), which will provide 2x daily leveraged long exposure to SpaceX stocks. However, REX Shares warns that this fund is a high-risk leveraged product suitable for investors with professional trading experience, and there is a significant risk of deviation from the performance of the underlying asset during holding periods beyond a single day.

REX Shares Launches 2x Long SpaceX ETF SPAX

On June 16, U.S. President Trump expressed his hope for a formal signing before the document is released. The negotiations with Iran may take longer or shorter than 60 days. The Strait of Hormuz will be free of tolls.

[Trump: Hopes for Formal Signing Before Document Release]On June 16, U.S. President Trump expressed his hope for a formal signing before the document is released. The negotiations with Iran may take longer or shorter than 60 days. The Strait of Hormuz will be free of tolls.

Trump: Hopes for Formal Signing Before Document Release

On June 16, U.S. Vice President Vance stated regarding the Iran agreement that no U.S. funds will be provided to them. (Jinshi)

[Vance: No U.S. Funds Will Be Provided to Iran]On June 16, U.S. Vice President Vance stated regarding the Iran agreement that no U.S. funds will be provided to them. (Jinshi)

Vance: No U.S. Funds Will Be Provided to Iran

On June 16, the ADP employment change in the U.S. for the week ending May 30 showed an increase of 25,500 jobs, compared to a previous value of 29,000 jobs. (Jin Shi)

[ADP Employment Change in the U.S. for the Week Ending May 30 Increases by 25,500]On June 16, the ADP employment change in the U.S. for the week ending May 30 showed an increase of 25,500 jobs, compared to a previous value of 29,000 jobs. (Jin Shi)

ADP Employment Change in the U.S. for the Week Ending May 30 Increases by 25,500

On June 16, Bloomberg reported that the UK's energy regulator Ofgem is assessing whether data centers should be required to reduce their power consumption during periods of stress on the electricity system. This initiative is part of the UK's response to the surge in electricity demand driven by the rapid development of artificial intelligence and cloud computing. In its latest policy update, Ofgem stated that it is exploring the potential introduction of mandatory load reductions as a backup mechanism within the regulatory framework. The regulator believes that more effective load management for large power users could provide greater flexibility to the electricity system, allowing it to accommodate more new electricity demand while ensuring reliability of supply. In other words, as AI data centers become the new 'super consumers' of electricity, UK regulators are considering granting grid operators the authority to temporarily require data centers to reduce computing power or lower electricity usage in extreme situations to alleviate grid pressure and avoid supply risks. This move reflects the growing contradiction between the global expansion of AI infrastructure and the capacity of electricity supply.

[UK Regulator Considers Limiting Data Center Power Usage During Peak Times]On June 16, Bloomberg reported that the UK's energy regulator Ofgem is assessing whether data centers should be required to reduce their power consumption during periods of stress on the electricity system. This initiative is part of the UK's response to the surge in electricity demand driven by the rapid development of artificial intelligence and cloud computing. In its latest policy update, Ofgem stated that it is exploring the potential introduction of mandatory load reductions as a backup mechanism within the regulatory framework. The regulator believes that more effective load management for large power users could provide greater flexibility to the electricity system, allowing it to accommodate more new electricity demand while ensuring reliability of supply. In other words, as AI data centers become the new 'super consumers' of electricity, UK regulators are considering granting grid operators the authority to temporarily require data centers to reduce computing power or lower electricity usage in extreme situations to alleviate grid pressure and avoid supply risks. This move reflects the growing contradiction between the global expansion of AI infrastructure and the capacity of electricity supply.

UK Regulator Considers Limiting Data Center Power Usage During Peak Times

According to monitoring by Dongcha Beating, 'on-track sampling' in post-training of large models (i.e., training the model based on its own real-time generated data) is crucial for preventing model degradation and enhancing problem-solving abilities. Online reinforcement learning (RL) and on-track distillation (OPD) outperform traditional supervised fine-tuning (SFT) because they allow the model to optimize based on the steps it generates itself, rather than memorizing external standard answers. SFT forcibly instills standard answers, applying modification uniformly across each word, which can easily disrupt the model's original knowledge structure and lead to forgetting. In contrast, RL and OPD enable the model to find and reinforce the best steps within its own drafts. This not only avoids the cumulative error of 'writing one wrong word at the beginning and going off track later,' but also ensures that updates occur only within the areas of knowledge the model already possesses, thereby maximizing the retention of its inherent capabilities. In the 'minimal code editing' experiment, whether using SFT or RL mentors for on-track distillation, the student model's success rate (Pass@1) for writing correct code in one attempt reached 80.0% and 78.7%, respectively, both surpassing that of the mentor model. Even when the SFT mentor became significantly 'dumbed down' due to excessive fine-tuning (dropping from 0.320 to 0.286 in the LiveCodeBench coding ability test), the student model it produced still achieved a high score of 0.297, showing almost no impact from the mentor's flaws, thus proving that on-track practice can effectively filter out the mentor's bad habits. Currently, DeepSeek-V4 and GLM-5 have incorporated on-track distillation to merge expert model capabilities. In expert training, areas with clear right and wrong answers, such as coding and mathematics, are more suited for RL, while creative and knowledge-based subjective tasks are better suited for on-track distillation. Future ultimate fine-tuning algorithms will need to seek new mechanisms under the on-track training framework that combine the high efficiency of distillation (high information density) with the objectivity of RL (unbiased updates).

[New Findings in Post-Training of Large Models: Self-Generated Data for 'On-Track Training' is Key for Students to Surpass Mentors Without Degradation]According to monitoring by Dongcha Beating, 'on-track sampling' in post-training of large models (i.e., training the model based on its own real-time generated data) is crucial for preventing model degradation and enhancing problem-solving abilities. Online reinforcement learning (RL) and on-track distillation (OPD) outperform traditional supervised fine-tuning (SFT) because they allow the model to optimize based on the steps it generates itself, rather than memorizing external standard answers. SFT forcibly instills standard answers, applying modification uniformly across each word, which can easily disrupt the model's original knowledge structure and lead to forgetting. In contrast, RL and OPD enable the model to find and reinforce the best steps within its own drafts. This not only avoids the cumulative error of 'writing one wrong word at the beginning and going off track later,' but also ensures that updates occur only within the areas of knowledge the model already possesses, thereby maximizing the retention of its inherent capabilities. In the 'minimal code editing' experiment, whether using SFT or RL mentors for on-track distillation, the student model's success rate (Pass@1) for writing correct code in one attempt reached 80.0% and 78.7%, respectively, both surpassing that of the mentor model. Even when the SFT mentor became significantly 'dumbed down' due to excessive fine-tuning (dropping from 0.320 to 0.286 in the LiveCodeBench coding ability test), the student model it produced still achieved a high score of 0.297, showing almost no impact from the mentor's flaws, thus proving that on-track practice can effectively filter out the mentor's bad habits. Currently, DeepSeek-V4 and GLM-5 have incorporated on-track distillation to merge expert model capabilities. In expert training, areas with clear right and wrong answers, such as coding and mathematics, are more suited for RL, while creative and knowledge-based subjective tasks are better suited for on-track distillation. Future ultimate fine-tuning algorithms will need to seek new mechanisms under the on-track training framework that combine the high efficiency of distillation (high information density) with the objectivity of RL (unbiased updates).

New Findings in Post-Training of Large Models: Self-Generated Data for 'On-Track Training' is Key for Students to Surpass Mentors Without Degradation

Trump: The Strait of Hormuz will fully resume navigation by Friday.

[Trump: Strait of Hormuz Will Fully Resume Navigation by Friday]Trump: The Strait of Hormuz will fully resume navigation by Friday.

Trump: Strait of Hormuz Will Fully Resume Navigation by Friday

On June 16, it was reported that the ADP employment change in the U.S. for the week ending May 30 was an increase of 25,500 jobs, down from the previous value of 29,000 jobs.

[ADP Employment Change in the U.S. for the Week Ending May 30: 25,500 Jobs]On June 16, it was reported that the ADP employment change in the U.S. for the week ending May 30 was an increase of 25,500 jobs, down from the previous value of 29,000 jobs.

ADP Employment Change in the U.S. for the Week Ending May 30: 25,500 Jobs

Brent crude oil has fallen below $80 per barrel, marking a new low since March 10, with a daily decline of 3.56%. WTI crude oil also experienced a significant drop of 4.00%, currently reported at $78.12 per barrel.

[Brent Crude Oil Falls Below $80 per Barrel, Lowest Since March 10]Brent crude oil has fallen below $80 per barrel, marking a new low since March 10, with a daily decline of 3.56%. WTI crude oil also experienced a significant drop of 4.00%, currently reported at $78.12 per barrel.

Brent Crude Oil Falls Below $80 per Barrel, Lowest Since March 10

火币HTX数据监测显示，ETH突破1800  USDT，现报1802.26  USDT，24H涨幅7.86%。

【ETH突破1800  USDT】火币HTX数据监测显示，ETH突破1800  USDT，现报1802.26  USDT，24H涨幅7.86%。

ETH突破1800  USDT

The Higher Bitcoin Goes, The Less Institutions Want It? Coinbase Executive Weighs In

Just Now, Claude Mythos 5 Released, Handles 50 Million Lines of Code in One Day

SemiAnalysis Report Claims Delay in Two Key Technologies, Triggers Sharp Decline in 'Optoelectronics', Sparking Online Debate Over CPO

$500 Billion, 20-Year Lease: OpenAI in Talks for 10GW Ohio Data Center, Nvidia Set to Act as Credit 'Backstop'

Internet-Famous Institution Battles White-Haired Stock God: What Does the Report That Crashed CPO Stocks Actually Recommend?

SpaceX's Core Window for Listed Trading: July 7th Nasdaq Inclusion Date and Post-Q2 Earnings Lockup Expiration

TON Revives the Gram Brand, a Name That Disappeared Six Years Ago Returns

Top Crypto Coins With Real Use Cases To Watch in June 2026: NEAR, HYPE, Humanity Protocol, and BlockDAG Compared

Sequoia Dialogue with Jensen Huang: Computing Model Undergoes a 60-Year Transformation; You Won't Be Replaced by AI, But You Will Be Dimensionality-Reduced by 'Those Who Master AI'

The Recursive AI Anthropic Warned About: Tian Yuandong's New Company Has Just Taken the "First Step"

Article

Energy Company TAR Completes $27 Million Seed Funding to Address Power Issues for Data Centers in the AI Era

BTC breaks through 67000 USDT

ETH突破1800 USDT

Disclaimer：The content above does not represent HTX's positions.，HTX does not provide any trading recommendations.。

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