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On May 10, the Islamic Republic News Agency (IRNA) reported that Khalil Sherkhani, Iran's Ambassador to Armenia, emphasized that an agreement could be reached if countries that have illegally aggressed against Iran return to rational and logical policies and actions. In an interview with Armenian television on Saturday, Sherkhani stated that the aggression of the U.S. and Israeli regimes towards Iran clearly shows that military means, pressure, or threats cannot force Iran to surrender or accept extreme demands from either side. He expressed Iran's willingness to reach an agreement through negotiations, but this requires clear guarantees that the U.S. will adopt rational and logical practices to ensure that military aggression against Iran will not occur again. He also stressed that Iran opposes the selective interpretation of international law and will never allow the Iranian nation to be deprived of its right to peacefully utilize nuclear capabilities.

[Iranian Envoy: Agreement Possible if U.S. Acts Rationally]On May 10, the Islamic Republic News Agency (IRNA) reported that Khalil Sherkhani, Iran's Ambassador to Armenia, emphasized that an agreement could be reached if countries that have illegally aggressed against Iran return to rational and logical policies and actions. In an interview with Armenian television on Saturday, Sherkhani stated that the aggression of the U.S. and Israeli regimes towards Iran clearly shows that military means, pressure, or threats cannot force Iran to surrender or accept extreme demands from either side. He expressed Iran's willingness to reach an agreement through negotiations, but this requires clear guarantees that the U.S. will adopt rational and logical practices to ensure that military aggression against Iran will not occur again. He also stressed that Iran opposes the selective interpretation of international law and will never allow the Iranian nation to be deprived of its right to peacefully utilize nuclear capabilities.

Iranian Envoy: Agreement Possible if U.S. Acts Rationally

On May 10, Santiment reported on platform X that Tether (Ethereum-based) experienced its largest net outflow from exchanges in nearly three months, with a net outflow of $1.29 billion (USDT) on Friday. Such a large-scale outflow of USDT typically reflects institutional or whale-level participants moving funds to self-custody wallets, DeFi protocols, or over-the-counter trading platforms in preparation for larger operational plans. This is merely a reallocation of funds, not a complete exit from the ecosystem.

[Ethereum-based USDT Sees Largest Exchange Net Outflow in Nearly Three Months This Friday]On May 10, Santiment reported on platform X that Tether (Ethereum-based) experienced its largest net outflow from exchanges in nearly three months, with a net outflow of $1.29 billion (USDT) on Friday. Such a large-scale outflow of USDT typically reflects institutional or whale-level participants moving funds to self-custody wallets, DeFi protocols, or over-the-counter trading platforms in preparation for larger operational plans. This is merely a reallocation of funds, not a complete exit from the ecosystem.

Ethereum-based USDT Sees Largest Exchange Net Outflow in Nearly Three Months This Friday

LAYER fluctuated by 50.5% within 24 hours, current price $0.1325

【LAYER fluctuated over 50% in 24 hours!】LAYER fluctuated by 50.5% within 24 hours, current price $0.1325

LAYER fluctuated over 50% in 24 hours!

According to monitoring by Beating, Tilde Research has discovered a hidden flaw in the optimizer Muon, used by leading models such as DeepSeek V4, Kimi K2.5, and GLM-5: it causes over a quarter of the neurons in the MLP layer to permanently die early in training. Based on this finding, the team designed an alternative optimizer, Aurora, and made it open-source. A 1.1B model, trained with approximately 100B tokens, matched the performance of Qwen3-1.7B, which was trained with 36T tokens, on language understanding benchmarks like HellaSwag and Winogrande. The issue lies in a mathematical characteristic of how Muon handles MLP weight matrices. Early in training, some neurons happen to receive weaker gradient signals. Traditional optimizers like AdamW normalize per parameter, naturally leveling out these differences; however, Muon's orthogonalization step passes the weak signals unchanged. Weak neurons continue to receive weak updates, becoming increasingly silent, creating a 'rich get richer' death spiral. By the 500th training step, over a quarter of the neurons are effectively dead, wasting parameter capacity. The previous improved version, NorMuon, alleviated this by forcing uniformity in update magnitudes for each row, but at the cost of disrupting the orthogonality of the update matrix (orthogonalization makes each step as efficient as possible, which is a core advantage of Muon), resulting in a loss of optimization precision. Aurora sets 'uniform updates' and 'orthogonality' as joint constraints, alternating iterations to satisfy both: ensuring that each neuron gets a fair learning opportunity without sacrificing update precision. Un-tuned, Aurora incurs only 6% more computational overhead than Muon and can be directly replaced. In modded-nanoGPT optimization benchmarks, Aurora set a new record with 3175 steps. The advantages of Aurora will also amplify with increased MLP width; the higher the expansion factor, the more pronounced the improvements. The code and the 1.1B pre-trained model have been made open-source.

[Muon Silently 'Starves' 25% of Neurons: Aurora Increases Data Efficiency by Over 100 Times After Fix]According to monitoring by Beating, Tilde Research has discovered a hidden flaw in the optimizer Muon, used by leading models such as DeepSeek V4, Kimi K2.5, and GLM-5: it causes over a quarter of the neurons in the MLP layer to permanently die early in training. Based on this finding, the team designed an alternative optimizer, Aurora, and made it open-source. A 1.1B model, trained with approximately 100B tokens, matched the performance of Qwen3-1.7B, which was trained with 36T tokens, on language understanding benchmarks like HellaSwag and Winogrande. The issue lies in a mathematical characteristic of how Muon handles MLP weight matrices. Early in training, some neurons happen to receive weaker gradient signals. Traditional optimizers like AdamW normalize per parameter, naturally leveling out these differences; however, Muon's orthogonalization step passes the weak signals unchanged. Weak neurons continue to receive weak updates, becoming increasingly silent, creating a 'rich get richer' death spiral. By the 500th training step, over a quarter of the neurons are effectively dead, wasting parameter capacity. The previous improved version, NorMuon, alleviated this by forcing uniformity in update magnitudes for each row, but at the cost of disrupting the orthogonality of the update matrix (orthogonalization makes each step as efficient as possible, which is a core advantage of Muon), resulting in a loss of optimization precision. Aurora sets 'uniform updates' and 'orthogonality' as joint constraints, alternating iterations to satisfy both: ensuring that each neuron gets a fair learning opportunity without sacrificing update precision. Un-tuned, Aurora incurs only 6% more computational overhead than Muon and can be directly replaced. In modded-nanoGPT optimization benchmarks, Aurora set a new record with 3175 steps. The advantages of Aurora will also amplify with increased MLP width; the higher the expansion factor, the more pronounced the improvements. The code and the 1.1B pre-trained model have been made open-source.

Muon Silently 'Starves' 25% of Neurons: Aurora Increases Data Efficiency by Over 100 Times After Fix

As of May 10, according to Coinglass data, the cryptocurrency Fear and Greed Index is currently at 48, an increase of 11 points from yesterday. The average over the past 7 days is 43, while the average over the past 30 days is 32.

[Current Crypto Fear and Greed Index at 48, Neutral State]As of May 10, according to Coinglass data, the cryptocurrency Fear and Greed Index is currently at 48, an increase of 11 points from yesterday. The average over the past 7 days is 43, while the average over the past 30 days is 32.

Current Crypto Fear and Greed Index at 48, Neutral State

On May 10, according to Barchart data, the S&P 500 index has now risen for six consecutive weeks, marking the longest streak since 2024. On the other hand, the SOX semiconductor index weekly chart shows that the overbought index RSI(14) has reached 85.54, the highest level since the peak of the 2000 internet bubble, raising concerns about the semiconductor sector being overbought. However, some analysts point out that the current strong rise in semiconductor stocks is different from the internet bubble era, as this increase is supported by real demand from AI, data centers, and corporate cash flow, rather than mere speculation.

[S&P 500 Posts Six Consecutive Weekly Gains; Semiconductor Stocks Reach Overbought Levels Not Seen Since Internet Bubble Peak]On May 10, according to Barchart data, the S&P 500 index has now risen for six consecutive weeks, marking the longest streak since 2024. On the other hand, the SOX semiconductor index weekly chart shows that the overbought index RSI(14) has reached 85.54, the highest level since the peak of the 2000 internet bubble, raising concerns about the semiconductor sector being overbought. However, some analysts point out that the current strong rise in semiconductor stocks is different from the internet bubble era, as this increase is supported by real demand from AI, data centers, and corporate cash flow, rather than mere speculation.

S&P 500 Posts Six Consecutive Weekly Gains; Semiconductor Stocks Reach Overbought Levels Not Seen Since Internet Bubble Peak

On May 10, significant signs of peace emerged in both the US-Iran and Russia-Ukraine conflicts this week, leading to a substantial easing of geopolitical risks. Next week, it will be crucial to monitor whether these two geopolitical conflicts can further de-escalate. Additionally, macroeconomic events will focus on the US April CPI data, with the following specifics: On Tuesday at 15:15, FOMC permanent voting member and New York Fed President Williams will participate in a panel discussion on monetary policy; on Tuesday at 20:15, the ADP employment change for the week ending April 25 will be released; on Tuesday at 20:30, the US April CPI data will be announced; on Wednesday at 04:30, API crude oil inventories for the week ending May 8 will be reported; on Wednesday at 20:30, the US April PPI year-on-year and month-on-month data will be released; on Friday at 05:30, Fed Governor Barr will give a speech; and on Friday at 21:15, the US April industrial production month-on-month data will be published. Lastly, next week will see significant personnel changes at the Fed, with incoming Chair Kevin Walsh expected to be confirmed by the Senate on Monday and officially taking over from Powell on May 15. In the stock market, as of this Friday, a new surge has driven the S&P 500 index to an 8% cumulative increase in 2026, continuing to rise on the foundation of double-digit returns over the past three years. The tech-heavy Nasdaq Composite index has risen nearly 13% year-to-date, with both indices reaching historic highs. Although the first quarter earnings season is nearing its end, corporate reports will remain a key driver of stock prices in the coming days.

[Macroeconomic Outlook for Next Week: Potential Peace Talks in US-Iran and Russia-Ukraine Conflicts, Walsh Officially Takes Over as Fed Chair]On May 10, significant signs of peace emerged in both the US-Iran and Russia-Ukraine conflicts this week, leading to a substantial easing of geopolitical risks. Next week, it will be crucial to monitor whether these two geopolitical conflicts can further de-escalate. Additionally, macroeconomic events will focus on the US April CPI data, with the following specifics: On Tuesday at 15:15, FOMC permanent voting member and New York Fed President Williams will participate in a panel discussion on monetary policy; on Tuesday at 20:15, the ADP employment change for the week ending April 25 will be released; on Tuesday at 20:30, the US April CPI data will be announced; on Wednesday at 04:30, API crude oil inventories for the week ending May 8 will be reported; on Wednesday at 20:30, the US April PPI year-on-year and month-on-month data will be released; on Friday at 05:30, Fed Governor Barr will give a speech; and on Friday at 21:15, the US April industrial production month-on-month data will be published. Lastly, next week will see significant personnel changes at the Fed, with incoming Chair Kevin Walsh expected to be confirmed by the Senate on Monday and officially taking over from Powell on May 15. In the stock market, as of this Friday, a new surge has driven the S&P 500 index to an 8% cumulative increase in 2026, continuing to rise on the foundation of double-digit returns over the past three years. The tech-heavy Nasdaq Composite index has risen nearly 13% year-to-date, with both indices reaching historic highs. Although the first quarter earnings season is nearing its end, corporate reports will remain a key driver of stock prices in the coming days.

Macroeconomic Outlook for Next Week: Potential Peace Talks in US-Iran and Russia-Ukraine Conflicts, Walsh Officially Takes Over as Fed Chair

On May 10, insiders revealed that Alibaba is preparing to announce the integration plan of its artificial intelligence platform Qwen with the e-commerce platform Taobao, aiming to enhance shopping through conversation rather than keyword searches. The integration will enable consumers to interact with an AI assistant via the Qwen app, allowing them to browse, compare, and purchase products without manually sifting through product lists. The Qwen app is expected to access the complete catalog of over 4 billion items from Taobao and Tmall, supported by a 'skill library' capable of managing logistics and after-sales services. It will also provide shopping recommendations based on users' order history and shopping preferences. Additionally, within the Taobao platform, Alibaba will launch an AI shopping assistant powered by Qwen, featuring tools such as virtual try-ons and 30-day price tracking.

[Sources: Alibaba to Integrate Qwen AI with Taobao for Smart Shopping Service]On May 10, insiders revealed that Alibaba is preparing to announce the integration plan of its artificial intelligence platform Qwen with the e-commerce platform Taobao, aiming to enhance shopping through conversation rather than keyword searches. The integration will enable consumers to interact with an AI assistant via the Qwen app, allowing them to browse, compare, and purchase products without manually sifting through product lists. The Qwen app is expected to access the complete catalog of over 4 billion items from Taobao and Tmall, supported by a 'skill library' capable of managing logistics and after-sales services. It will also provide shopping recommendations based on users' order history and shopping preferences. Additionally, within the Taobao platform, Alibaba will launch an AI shopping assistant powered by Qwen, featuring tools such as virtual try-ons and 30-day price tracking.

Sources: Alibaba to Integrate Qwen AI with Taobao for Smart Shopping Service

"AI Geek Championship" has officially launched today. This event is produced by HTX DAO and jointly organized by Golden Finance, Twinkle, and Dushu Finance, bringing together top industry resources to explore the innovative power of the integration of AI and blockchain. The competition focuses on the cross-disciplinary collision of AI technology and Web3, symbolizing the underlying logic and innovative pulse of the digital intelligence era. This is not only a contest of technology but also a foresight into future trends. Scan the QR code now to follow the latest updates on the event and witness the birth of AI geeks.

[AI Geek Championship Officially Launched on May 10]"AI Geek Championship" has officially launched today. This event is produced by HTX DAO and jointly organized by Golden Finance, Twinkle, and Dushu Finance, bringing together top industry resources to explore the innovative power of the integration of AI and blockchain. The competition focuses on the cross-disciplinary collision of AI technology and Web3, symbolizing the underlying logic and innovative pulse of the digital intelligence era. This is not only a contest of technology but also a foresight into future trends. Scan the QR code now to follow the latest updates on the event and witness the birth of AI geeks.

AI Geek Championship Officially Launched on May 10

According to the content posted and retweeted by Ethereum core developer Tim Beiko，the tentative Ethereum Mainnet Bellatrix fork Epoch is 144896, time is 11:34:47 AM on September 6 (UTC). The tentative Mainnet TTD (Terminal Total Difficulty) is 58750000000000000000000. However, there may be changes until it's in client release.

Detail

【The tentative Ethereum Mainnet Merge TTD released】According to the content posted and retweeted by Ethereum core developer Tim Beiko，the tentative Ethereum Mainnet Bellatrix fork Epoch is 144896, time is 11:34:47 AM on September 6 (UTC). The tentative Mainnet TTD (Terminal Total Difficulty) is 58750000000000000000000. However, there may be changes until it's in client release.

The tentative Ethereum Mainnet Merge TTD released

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The tentative Ethereum Mainnet Merge TTD released

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

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