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cc Hits New High of 0.1601 USDT, Up 5.05% in 24H

【cc soared to 0.1601 USDT, a new high with a 24-hour increase of 5.05%. It currently trades at 0.1601 USDT on HTX.】cc Hits New High of 0.1601 USDT, Up 5.05% in 24H

cc soared to 0.1601 USDT, a new high with a 24-hour increase of 5.05%. It currently trades at 0.1601 USDT on HTX.

On May 14, Intel's stock fell over 4% in pre-market trading, currently priced at $115.4.

[Intel Stock Drops Over 4% in Pre-Market Trading]On May 14, Intel's stock fell over 4% in pre-market trading, currently priced at $115.4.

Intel Stock Drops Over 4% in Pre-Market Trading

On May 14, JPMorgan announced that it has raised the price target for Cisco (CSCO.O) from $96 to $120. (Jin Shi)

[JPMorgan Raises Cisco Price Target from $96 to $120]On May 14, JPMorgan announced that it has raised the price target for Cisco (CSCO.O) from $96 to $120. (Jin Shi)

JPMorgan Raises Cisco Price Target from $96 to $120

According to monitoring by Dongcha Beating, the hacker group TeamPCP, responsible for the npm supply chain poisoning incident, has open-sourced the complete source code of the involved worm Mini Shai-Hulud on GitHub under the MIT license. Security personnel discovered that this malware comes with a 'kill switch'; if affected developers revoke their stolen GitHub or cloud service credentials without thoroughly cleaning up residual files, the malicious program will immediately wipe the entire home directory of the computer. Researchers confirmed that the worm installs a daemon in the background on macOS or Linux, checking every minute whether the stolen credentials are still valid. Once it detects that the credentials have been rejected by the server (indicating that the victim has executed a credential rotation), the worm will immediately invoke the system's underlying shred command to irreversibly destroy and overwrite all writable files in the current user's home directory. This directly undermines conventional security response processes: the usual first reaction for companies facing credential leaks is to immediately revoke keys, but in this attack, it would directly trigger the destruction of local data. Currently, the worm has been confirmed to have infected nearly 400 versions of over 170 package libraries, including TanStack, UiPath, and Mistral AI. After the hacker publicly released the code under the account name PedroTortoriello and mocked 'open-sourcing this massacre', a third party even submitted a PR to add FreeBSD support. Microsoft has swiftly banned this account and removed all GitHub repositories and fork branches, but the leaked source code continues to circulate through other channels.

[Revocation of Credentials Triggers Physical Liquidation? TanStack's Stealth Worm Open-Sourced with Irreversible Kill Switch]According to monitoring by Dongcha Beating, the hacker group TeamPCP, responsible for the npm supply chain poisoning incident, has open-sourced the complete source code of the involved worm Mini Shai-Hulud on GitHub under the MIT license. Security personnel discovered that this malware comes with a 'kill switch'; if affected developers revoke their stolen GitHub or cloud service credentials without thoroughly cleaning up residual files, the malicious program will immediately wipe the entire home directory of the computer. Researchers confirmed that the worm installs a daemon in the background on macOS or Linux, checking every minute whether the stolen credentials are still valid. Once it detects that the credentials have been rejected by the server (indicating that the victim has executed a credential rotation), the worm will immediately invoke the system's underlying shred command to irreversibly destroy and overwrite all writable files in the current user's home directory. This directly undermines conventional security response processes: the usual first reaction for companies facing credential leaks is to immediately revoke keys, but in this attack, it would directly trigger the destruction of local data. Currently, the worm has been confirmed to have infected nearly 400 versions of over 170 package libraries, including TanStack, UiPath, and Mistral AI. After the hacker publicly released the code under the account name PedroTortoriello and mocked 'open-sourcing this massacre', a third party even submitted a PR to add FreeBSD support. Microsoft has swiftly banned this account and removed all GitHub repositories and fork branches, but the leaked source code continues to circulate through other channels.

Revocation of Credentials Triggers Physical Liquidation? TanStack's Stealth Worm Open-Sourced with Irreversible Kill Switch

On May 14, Tencent Cloud officially announced the open sourcing of TencentDB Agent Memory, which provides short-term memory compression and long-term personalized memory capabilities for Agent long-task scenarios. According to the introduction, TencentDB Agent Memory utilizes the technology of 'Context Offloading + Mermaid Task Canvas' to offload complete information to external storage while retaining key states and execution paths in a structured task graph. This allows the Agent to maintain a lightweight context during long tasks, while also supporting the layered tracing and recovery of original information. In experiments with continuous multi-task sessions, this solution achieved a maximum reduction of 61% in token consumption, while also improving the success rate of tasks in long-task scenarios.

[Tencent Open Sources Agent Memory, Reducing Token Consumption by Up to 61%]On May 14, Tencent Cloud officially announced the open sourcing of TencentDB Agent Memory, which provides short-term memory compression and long-term personalized memory capabilities for Agent long-task scenarios. According to the introduction, TencentDB Agent Memory utilizes the technology of 'Context Offloading + Mermaid Task Canvas' to offload complete information to external storage while retaining key states and execution paths in a structured task graph. This allows the Agent to maintain a lightweight context during long tasks, while also supporting the layered tracing and recovery of original information. In experiments with continuous multi-task sessions, this solution achieved a maximum reduction of 61% in token consumption, while also improving the success rate of tasks in long-task scenarios.

Tencent Open Sources Agent Memory, Reducing Token Consumption by Up to 61%

According to monitoring by Beating, three key technical personnel directly involved in the construction of the Grok model at xAI announced their departures over the past week. Unlike the previous exits of co-founders and executives, these three individuals were the actual heads of the core product lines of search post-training, pre-training, and voice. Their collective departure will directly impact the iterative capabilities of the next generation of Grok models. Tianyi Zhang confirmed his departure today on X. He was the head of the search and factual post-training team and had previously served as a machine learning engineering manager at Apple for five years. He led the team to reduce the factual error rate of Grok's real-time model by 70% to 80%, helping Grok 4.20 achieve the top position in the Search Arena blind test upon its launch. This search capability is currently integrated into Tesla's in-car system. Juntang Zhuang announced on May 9 that he had left earlier this year. He was deeply involved in pre-training since Grok 2 and later became the head of the pre-training team, overseeing the training infrastructure and core formulas for the entire Grok 4 series of models. Before joining xAI, he worked at OpenAI for two years and was a core contributor to GPT-4o and the inventor of the GPT-4 Turbo 128k long-context algorithm. David Haxton confirmed his departure on May 10; he had built Grok's voice agent, real-time thinking voice, and voice cloning features from scratch. Under his leadership, Grok Voice currently ranks first in the τ-Voice benchmark tests by Sierra AI, ahead of OpenAI and Google. The timing of these departures is particularly striking. The publicly available Grok 4.3 is still just an intermediate version with 0.5T parameters. Musk stated on April 18 that the true 1T flagship was 'about 5 days away from completing initial training,' and the next day clarified that Grok 4.4 would be 1T, expected to be released in early May, while Grok 4.5 would be 1.5T, aiming for delivery by the end of May, claiming that the model factory was operational, with a new foundational model expected to be released every two weeks thereafter. Now, in mid-May, Grok 4.4 has yet to appear, while the core personnel responsible for creating these models are rapidly leaving. xAI is experiencing a systemic talent collapse from co-founders to the core model team.

[Elon Musk Promises New Grok Release Every Two Weeks, But Key Model Developers Depart Within a Week]According to monitoring by Beating, three key technical personnel directly involved in the construction of the Grok model at xAI announced their departures over the past week. Unlike the previous exits of co-founders and executives, these three individuals were the actual heads of the core product lines of search post-training, pre-training, and voice. Their collective departure will directly impact the iterative capabilities of the next generation of Grok models. Tianyi Zhang confirmed his departure today on X. He was the head of the search and factual post-training team and had previously served as a machine learning engineering manager at Apple for five years. He led the team to reduce the factual error rate of Grok's real-time model by 70% to 80%, helping Grok 4.20 achieve the top position in the Search Arena blind test upon its launch. This search capability is currently integrated into Tesla's in-car system. Juntang Zhuang announced on May 9 that he had left earlier this year. He was deeply involved in pre-training since Grok 2 and later became the head of the pre-training team, overseeing the training infrastructure and core formulas for the entire Grok 4 series of models. Before joining xAI, he worked at OpenAI for two years and was a core contributor to GPT-4o and the inventor of the GPT-4 Turbo 128k long-context algorithm. David Haxton confirmed his departure on May 10; he had built Grok's voice agent, real-time thinking voice, and voice cloning features from scratch. Under his leadership, Grok Voice currently ranks first in the τ-Voice benchmark tests by Sierra AI, ahead of OpenAI and Google. The timing of these departures is particularly striking. The publicly available Grok 4.3 is still just an intermediate version with 0.5T parameters. Musk stated on April 18 that the true 1T flagship was 'about 5 days away from completing initial training,' and the next day clarified that Grok 4.4 would be 1T, expected to be released in early May, while Grok 4.5 would be 1.5T, aiming for delivery by the end of May, claiming that the model factory was operational, with a new foundational model expected to be released every two weeks thereafter. Now, in mid-May, Grok 4.4 has yet to appear, while the core personnel responsible for creating these models are rapidly leaving. xAI is experiencing a systemic talent collapse from co-founders to the core model team.

Elon Musk Promises New Grok Release Every Two Weeks, But Key Model Developers Depart Within a Week

UP fluctuated by 74.67% within 24 hours, current price $0.186989

【UP24-hour fluctuation exceeds 50%!】UP fluctuated by 74.67% within 24 hours, current price $0.186989

UP24-hour fluctuation exceeds 50%!

On May 14, Fractal Bitcoin announced the official launch of the first phase of public testing for its standardized data indexing service based on the FIP-101 proposal. Following the start of the public test, users can participate in index mining through non-custodial staking and receive corresponding rewards based on their staking shares. As of now, the total amount staked in the public test has exceeded 1.5 million FB. FIP-101 represents a significant upgrade for Fractal's data infrastructure layer. This proposal aims to introduce an open-source, permissionless, standardized data indexing service to the Fractal ecosystem and integrate the indexing service into the Fractal block reward system, transforming the indexing infrastructure from a purely external service into a component of the network incentive structure.

[Fractal Bitcoin Launches Public Test for FIP-101, Index Mining and Non-Custodial Staking Now Open]On May 14, Fractal Bitcoin announced the official launch of the first phase of public testing for its standardized data indexing service based on the FIP-101 proposal. Following the start of the public test, users can participate in index mining through non-custodial staking and receive corresponding rewards based on their staking shares. As of now, the total amount staked in the public test has exceeded 1.5 million FB. FIP-101 represents a significant upgrade for Fractal's data infrastructure layer. This proposal aims to introduce an open-source, permissionless, standardized data indexing service to the Fractal ecosystem and integrate the indexing service into the Fractal block reward system, transforming the indexing infrastructure from a purely external service into a component of the network incentive structure.

Fractal Bitcoin Launches Public Test for FIP-101, Index Mining and Non-Custodial Staking Now Open

On May 14, Ripple's Chief Legal Officer Stuart Alderoty stated before the Senate Banking Committee's review of the CLARITY Act that currently, 67 million Americans hold cryptocurrency, and each senator on the committee represents these holders. These holders are millions of ordinary Americans: construction workers, retirees, small business owners, and parents. They come from various income levels, industries, and states across the U.S. They deserve clear rules. They deserve strong consumer protections. They deserve a regulatory framework that allows responsible innovation to thrive in the United States.

[Ripple's Chief Legal Officer: 67 Million Americans Holding Cryptocurrency Deserve Clear Rules and Regulatory Framework]On May 14, Ripple's Chief Legal Officer Stuart Alderoty stated before the Senate Banking Committee's review of the CLARITY Act that currently, 67 million Americans hold cryptocurrency, and each senator on the committee represents these holders. These holders are millions of ordinary Americans: construction workers, retirees, small business owners, and parents. They come from various income levels, industries, and states across the U.S. They deserve clear rules. They deserve strong consumer protections. They deserve a regulatory framework that allows responsible innovation to thrive in the United States.

Ripple's Chief Legal Officer: 67 Million Americans Holding Cryptocurrency Deserve Clear Rules and Regulatory Framework

According to U.Today, the activity of the Ethereum network has reached the lowest level in the last 5 years as the number of contracts deployed on the chain decreased and dropped below 300,000 deployments while staying at around 2.7 million in July 2021. Such a rapid drop in the number of contracts released on the chain is tied to two factors: the overall crisis in the industry caused by the lack of inflows and the upcoming fundamental update that might have caused a calm before the storm. The spike in the number of deployed contracts back in summer 2021 was the catalyst of the rally that almost pushed Ethereum to the $5,000 threshold. One of the main reasons behind such a strong drop in the number of deployed solutions on the network is a period of extremely high fees that disincentivized developers and caused a stalemate with no new solutions appearing on the network. Most likely, it is going to see a spike in the number of new applications and network activity on Ethereum post-Merge as new development tools and a better network environment should attract more companies that will look for investments in the new version of the second largest network in the digital asset industry. According to the reaction of the cryptocurrency market, a lot of investors believe in the upcoming spike in the number of users on Ethereum after the update gets successfully implemented.

Detail

【Data: Ethereum on-chain activity reaches 5 year-low】According to U.Today, the activity of the Ethereum network has reached the lowest level in the last 5 years as the number of contracts deployed on the chain decreased and dropped below 300,000 deployments while staying at around 2.7 million in July 2021. Such a rapid drop in the number of contracts released on the chain is tied to two factors: the overall crisis in the industry caused by the lack of inflows and the upcoming fundamental update that might have caused a calm before the storm. The spike in the number of deployed contracts back in summer 2021 was the catalyst of the rally that almost pushed Ethereum to the $5,000 threshold. One of the main reasons behind such a strong drop in the number of deployed solutions on the network is a period of extremely high fees that disincentivized developers and caused a stalemate with no new solutions appearing on the network. Most likely, it is going to see a spike in the number of new applications and network activity on Ethereum post-Merge as new development tools and a better network environment should attract more companies that will look for investments in the new version of the second largest network in the digital asset industry. According to the reaction of the cryptocurrency market, a lot of investors believe in the upcoming spike in the number of users on Ethereum after the update gets successfully implemented.

Data: Ethereum on-chain activity reaches 5 year-low

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Data: Ethereum on-chain activity reaches 5 year-low

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