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On April 7, according to official news from the Polygon Foundation, the Giugliano hard fork upgrade will take place on the Polygon mainnet around 22:00 Beijing time on April 8 at block height 85,268,500. This upgrade will bring the following improvements: allowing producers to announce blocks earlier for faster finality; directly adding fee parameters to the block header; and introducing new RPC interfaces to support fee data. The officials remind all node operators that they must upgrade Bor to version 2.7.0 or Erigon to version 3.5.0 to ensure normal operation.

[Polygon Mainnet to Undergo Giugliano Upgrade on April 8, Nodes Must Upgrade Promptly]On April 7, according to official news from the Polygon Foundation, the Giugliano hard fork upgrade will take place on the Polygon mainnet around 22:00 Beijing time on April 8 at block height 85,268,500. This upgrade will bring the following improvements: allowing producers to announce blocks earlier for faster finality; directly adding fee parameters to the block header; and introducing new RPC interfaces to support fee data. The officials remind all node operators that they must upgrade Bor to version 2.7.0 or Erigon to version 3.5.0 to ensure normal operation.

Polygon Mainnet to Undergo Giugliano Upgrade on April 8, Nodes Must Upgrade Promptly

According to monitoring by 1M AI News, OpenAI has released a 13-page policy white paper titled "Industrial Policy for the Intelligence Age," proposing a comprehensive reform plan for the economic and social order following the advent of superintelligence. Altman stated in an interview with Axios that superintelligence is imminent, and incremental policy adjustments are insufficient, necessitating a "new social contract at the level of progressive eras and new policies." The white paper focuses on three goals: broadly sharing prosperity, reducing risks, and universalizing AI usage rights. Core proposals include: 1. Tax reform: As AI replaces human labor, wage taxes (currently the main source of funding for social security, Medicare, and other programs) will gradually decline, necessitating a shift towards higher taxes on capital gains and corporate income, and exploring an "automation labor tax," commonly referred to as a robot tax. 2. Universal AI Wealth Fund: Establishing a national public wealth fund modeled after the Alaska Permanent Fund (which distributes oil revenue to residents), allowing every citizen to directly hold a share of AI-driven economic growth, with funding partly sourced from contributions by AI companies. 3. Four-day workweek: Transforming productivity gains from AI into "efficiency dividends," recommending that the government pilot a 32-hour workweek with unchanged salaries and maintained output levels. 4. Automatic safety net trigger mechanism: Automatically increasing unemployment benefits, wage insurance, and cash assistance when AI-related unemployment metrics hit preset thresholds, gradually phasing out once the job market recovers. 5. Positioning AI usage rights as a "fundamental right to participate in the modern economy." The white paper also acknowledges the dangers of AI systems that "cannot be easily recalled" due to their autonomy and self-replicating capabilities, and includes emergency plans for uncontrolled AI that require government collaboration. Altman warned that significant cyberattacks on recent AI models are "entirely possible," and creating new pathogens using AI is "no longer a theoretical hypothesis." Altman stated, "Some ideas will be good, some will be bad, but we do feel a sense of urgency." OpenAI is simultaneously launching a research funding program, offering scholarships of up to $100,000 and API credits of up to $1 million for related policy research, and will hold an OpenAI Workshop in Washington in May to discuss these issues. OpenAI is preparing for an IPO, while Congress is drafting AI legislation, making the timing of the white paper's release particularly significant. By proactively proposing taxes on AI companies and establishing redistribution mechanisms while its technology may disrupt the job market, OpenAI is not only making a preemptive gesture towards regulation but also adding a layer of "responsible AI" narrative to its IPO roadshow.

[OpenAI Releases 13-Page Policy White Paper Proposing Robot Tax, Universal AI Wealth Fund, and Four-Day Workweek]According to monitoring by 1M AI News, OpenAI has released a 13-page policy white paper titled "Industrial Policy for the Intelligence Age," proposing a comprehensive reform plan for the economic and social order following the advent of superintelligence. Altman stated in an interview with Axios that superintelligence is imminent, and incremental policy adjustments are insufficient, necessitating a "new social contract at the level of progressive eras and new policies." The white paper focuses on three goals: broadly sharing prosperity, reducing risks, and universalizing AI usage rights. Core proposals include: 1. Tax reform: As AI replaces human labor, wage taxes (currently the main source of funding for social security, Medicare, and other programs) will gradually decline, necessitating a shift towards higher taxes on capital gains and corporate income, and exploring an "automation labor tax," commonly referred to as a robot tax. 2. Universal AI Wealth Fund: Establishing a national public wealth fund modeled after the Alaska Permanent Fund (which distributes oil revenue to residents), allowing every citizen to directly hold a share of AI-driven economic growth, with funding partly sourced from contributions by AI companies. 3. Four-day workweek: Transforming productivity gains from AI into "efficiency dividends," recommending that the government pilot a 32-hour workweek with unchanged salaries and maintained output levels. 4. Automatic safety net trigger mechanism: Automatically increasing unemployment benefits, wage insurance, and cash assistance when AI-related unemployment metrics hit preset thresholds, gradually phasing out once the job market recovers. 5. Positioning AI usage rights as a "fundamental right to participate in the modern economy." The white paper also acknowledges the dangers of AI systems that "cannot be easily recalled" due to their autonomy and self-replicating capabilities, and includes emergency plans for uncontrolled AI that require government collaboration. Altman warned that significant cyberattacks on recent AI models are "entirely possible," and creating new pathogens using AI is "no longer a theoretical hypothesis." Altman stated, "Some ideas will be good, some will be bad, but we do feel a sense of urgency." OpenAI is simultaneously launching a research funding program, offering scholarships of up to $100,000 and API credits of up to $1 million for related policy research, and will hold an OpenAI Workshop in Washington in May to discuss these issues. OpenAI is preparing for an IPO, while Congress is drafting AI legislation, making the timing of the white paper's release particularly significant. By proactively proposing taxes on AI companies and establishing redistribution mechanisms while its technology may disrupt the job market, OpenAI is not only making a preemptive gesture towards regulation but also adding a layer of "responsible AI" narrative to its IPO roadshow.

OpenAI Releases 13-Page Policy White Paper Proposing Robot Tax, Universal AI Wealth Fund, and Four-Day Workweek

On April 7, the strategic advisor to Iranian Parliament Speaker Ghalibaf commented on President Trump's '48-hour ultimatum,' stating, 'Trump has about 20 hours left to either surrender to Iran or his allies will regress to the Stone Age. We will never back down.'

[Iranian Parliament Speaker's Strategic Advisor Issues Ultimatum to Trump: Surrender or Allies Will Regress to Stone Age]On April 7, the strategic advisor to Iranian Parliament Speaker Ghalibaf commented on President Trump's '48-hour ultimatum,' stating, 'Trump has about 20 hours left to either surrender to Iran or his allies will regress to the Stone Age. We will never back down.'

Iranian Parliament Speaker's Strategic Advisor Issues Ultimatum to Trump: Surrender or Allies Will Regress to Stone Age

On April 7, Piedao reported that 32.4 million wstUSR (40% of the illegally minted 80 million $USR) held by attackers have been destroyed. Through direct destruction and blacklisting, the total amount of illegally minted USR has been reduced by approximately 46 million.

[Piedao: 32.4 Million wstUSR Held by Attackers Have Been Destroyed]On April 7, Piedao reported that 32.4 million wstUSR (40% of the illegally minted 80 million $USR) held by attackers have been destroyed. Through direct destruction and blacklisting, the total amount of illegally minted USR has been reduced by approximately 46 million.

Piedao: 32.4 Million wstUSR Held by Attackers Have Been Destroyed

On April 7, PeckShield reported that 32.4 million wstUSR (40% of the illegally minted 80 million $USR) held by attackers have been destroyed. Through direct destruction and blacklisting, the total amount of illegally minted USR has been reduced by approximately 46 million.

[PeckShield: 32.4 Million wstUSR Held by USR Attackers Have Been Destroyed]On April 7, PeckShield reported that 32.4 million wstUSR (40% of the illegally minted 80 million $USR) held by attackers have been destroyed. Through direct destruction and blacklisting, the total amount of illegally minted USR has been reduced by approximately 46 million.

PeckShield: 32.4 Million wstUSR Held by USR Attackers Have Been Destroyed

According to monitoring by 1M AI News, three early employees of OpenAI have teamed up with two industry professionals to establish a venture capital fund named Zero Shot, targeting a size of $100 million. The first closing has already raised $20 million and several investments have been completed. The fund's name is derived from the AI term 'zero-shot learning.' The three co-founding partners from OpenAI are: Evan Morikawa, former head of application engineering at OpenAI, who experienced the release cycles of DALL·E, ChatGPT, and Codex, and is now with the robotics startup Generalist; Andrew Mayne, OpenAI's first prompt engineer and host of The OpenAI Podcast, who founded the AI deployment consulting firm Interdimensional; and Shawn Jain, a former researcher at OpenAI who transitioned to venture capital and founded the GenAI company Synthefy. The other two partners are Kelly Kovacs, founding partner of the growth fund 01A under former Twitter CEO Dick Costolo, and Brett Rounsaville, who has worked at Twitter and Disney. Invested projects include Worktrace AI, an enterprise automation platform founded by former OpenAI product manager Angela Jiang (seed round of about $10 million, with investors including Mira Murati and OpenAI's own fund), and Foundry Robotics, an AI factory robotics company (seed round of $13.5 million, led by Khosla Ventures), with a third project still in stealth mode. It may be more interesting to note what they choose not to invest in. Mayne has explicitly expressed skepticism towards most vibe coding platforms, arguing that advancements in programming capabilities by model vendors will soon render these platforms' paid subscriptions unnecessary. Morikawa is not optimistic about the current surge of 'robot video training data' companies, stating that the research community has yet to solve the transfer gap from video to physical entities, and that 'many companies are betting that the research community will solve this issue, but we are far from achieving that.' Mayne also holds a skeptical view towards 'digital twin' startups, having conducted due diligence and built a reasoning model to test, concluding that the performance of ordinary large language models is roughly the same. The fund's advisory board includes Diane Yoon, former head of HR at OpenAI; Steve Dowling, former head of communications (also a former communications head at Apple); and Luke Miller, former head of product.

[OpenAI Early Employees Establish $100 Million VC Fund Zero Shot, Bearish on Vibe Coding and Robot Video Data]According to monitoring by 1M AI News, three early employees of OpenAI have teamed up with two industry professionals to establish a venture capital fund named Zero Shot, targeting a size of $100 million. The first closing has already raised $20 million and several investments have been completed. The fund's name is derived from the AI term 'zero-shot learning.' The three co-founding partners from OpenAI are: Evan Morikawa, former head of application engineering at OpenAI, who experienced the release cycles of DALL·E, ChatGPT, and Codex, and is now with the robotics startup Generalist; Andrew Mayne, OpenAI's first prompt engineer and host of The OpenAI Podcast, who founded the AI deployment consulting firm Interdimensional; and Shawn Jain, a former researcher at OpenAI who transitioned to venture capital and founded the GenAI company Synthefy. The other two partners are Kelly Kovacs, founding partner of the growth fund 01A under former Twitter CEO Dick Costolo, and Brett Rounsaville, who has worked at Twitter and Disney. Invested projects include Worktrace AI, an enterprise automation platform founded by former OpenAI product manager Angela Jiang (seed round of about $10 million, with investors including Mira Murati and OpenAI's own fund), and Foundry Robotics, an AI factory robotics company (seed round of $13.5 million, led by Khosla Ventures), with a third project still in stealth mode. It may be more interesting to note what they choose not to invest in. Mayne has explicitly expressed skepticism towards most vibe coding platforms, arguing that advancements in programming capabilities by model vendors will soon render these platforms' paid subscriptions unnecessary. Morikawa is not optimistic about the current surge of 'robot video training data' companies, stating that the research community has yet to solve the transfer gap from video to physical entities, and that 'many companies are betting that the research community will solve this issue, but we are far from achieving that.' Mayne also holds a skeptical view towards 'digital twin' startups, having conducted due diligence and built a reasoning model to test, concluding that the performance of ordinary large language models is roughly the same. The fund's advisory board includes Diane Yoon, former head of HR at OpenAI; Steve Dowling, former head of communications (also a former communications head at Apple); and Luke Miller, former head of product.

OpenAI Early Employees Establish $100 Million VC Fund Zero Shot, Bearish on Vibe Coding and Robot Video Data

According to monitoring by 1M AI News, Meta is preparing to release a new generation of AI models developed under the leadership of Alexandr Wang, with plans to offer open-source versions of some of the models. Wang joined Meta last year through a $15 billion deal from AI data infrastructure company Scale AI, where he previously served as CEO. There had been speculation that Meta might completely abandon the open-source route, but according to Axios, citing informed sources, Wang believes that Meta can play a unique role in popularizing the latest AI technologies while ensuring developers have access to an American-made open-source option. However, Meta's largest new models will remain closed-source, marking a shift from the company's previous full open-source approach to a hybrid strategy that includes both open and closed-source elements. Wang's strategy focuses on differentiated competition: while Anthropic and OpenAI increasingly target government and enterprise clients, Meta aims for the consumer market, with the goal of distributing its models as widely as possible to global users. Meta's advantage lies in its global reach through its three free platforms: WhatsApp, Facebook, and Instagram, which provide a distribution channel that is difficult for competitors to match. Meta acknowledges that its new models may not fully compete with the next-generation models soon to be released by OpenAI and Anthropic across all dimensions, but it believes it will have its own competitive edge in consumer scenarios. Previously, the Llama 4 series significantly lagged behind competitors, and the primary goal of the new model series is to close that gap. The trend of reducing open-source initiatives is not limited to Meta alone; Alibaba has also recently transitioned its strongest new Qianwen model to closed-source, reversing its earlier strategy of full openness. The industry is forming a consensus: even the most open-minded companies are retaining control over their most powerful systems.

[Meta's New AI Model to Adopt Hybrid Strategy with Partial Open Source]According to monitoring by 1M AI News, Meta is preparing to release a new generation of AI models developed under the leadership of Alexandr Wang, with plans to offer open-source versions of some of the models. Wang joined Meta last year through a $15 billion deal from AI data infrastructure company Scale AI, where he previously served as CEO. There had been speculation that Meta might completely abandon the open-source route, but according to Axios, citing informed sources, Wang believes that Meta can play a unique role in popularizing the latest AI technologies while ensuring developers have access to an American-made open-source option. However, Meta's largest new models will remain closed-source, marking a shift from the company's previous full open-source approach to a hybrid strategy that includes both open and closed-source elements. Wang's strategy focuses on differentiated competition: while Anthropic and OpenAI increasingly target government and enterprise clients, Meta aims for the consumer market, with the goal of distributing its models as widely as possible to global users. Meta's advantage lies in its global reach through its three free platforms: WhatsApp, Facebook, and Instagram, which provide a distribution channel that is difficult for competitors to match. Meta acknowledges that its new models may not fully compete with the next-generation models soon to be released by OpenAI and Anthropic across all dimensions, but it believes it will have its own competitive edge in consumer scenarios. Previously, the Llama 4 series significantly lagged behind competitors, and the primary goal of the new model series is to close that gap. The trend of reducing open-source initiatives is not limited to Meta alone; Alibaba has also recently transitioned its strongest new Qianwen model to closed-source, reversing its earlier strategy of full openness. The industry is forming a consensus: even the most open-minded companies are retaining control over their most powerful systems.

Meta's New AI Model to Adopt Hybrid Strategy with Partial Open Source

According to monitoring by 1M AI News, an AI usage ranking named 'Claudeonomics', after Anthropic's flagship product Claude, has surfaced within Meta's internal network. This ranking was created by employees using company data, compiling token consumption from over 85,000 individuals and listing the top 250 users. A copy of the ranking seen by The Information shows that the total consumption in the past 30 days has surpassed 60 trillion tokens, which roughly translates to about $900 million based on the public average price of Claude Opus 4.6 (approximately $15 per million tokens), though the actual model combinations and pricing protocols at Meta remain unclear. The top individual user has an average consumption of 281 billion tokens, potentially costing millions of dollars. The ranking features gamified incentives, with tiers ranging from bronze to emerald, and the highest titles including 'Token Legend' and 'Session Immortal', along with 'Model Connoisseur' and 'Cache Wizard'. Some employees have been running AI agents for hours on end purely to inflate their usage for ranking purposes. Meta CEO Mark Zuckerberg and CTO Andrew Bosworth did not make it into the top 250. Recently, there has been a trend in Silicon Valley known as 'tokenmaxxing', where token consumption is becoming a new metric for measuring engineer productivity. Bosworth mentioned at a tech conference in February that the token expenditure of a top engineer is equivalent to their salary, with productivity improvements reaching up to 10 times, stating, 'This is a no-lose deal; keep burning, there’s no limit.' NVIDIA CEO Jensen Huang remarked last month that if an engineer with a $500,000 annual salary consumes less than $250,000 in tokens each year, he would be 'deeply concerned'. Meta engineers are currently using external models from Anthropic, OpenAI, and Google, as well as internal tools like MyClaw (Meta's version of OpenClaw) and the recently acquired Manus. In an internal memo this year, Zuckerberg made a 'bold request' to the engineering team to rewrite Meta's codebase to enable AI agents to directly understand and modify the code.

[Meta's Internal 'Claudeonomics' Ranking Revealed: 85,000 Employees Burn 60 Trillion Tokens in 30 Days]According to monitoring by 1M AI News, an AI usage ranking named 'Claudeonomics', after Anthropic's flagship product Claude, has surfaced within Meta's internal network. This ranking was created by employees using company data, compiling token consumption from over 85,000 individuals and listing the top 250 users. A copy of the ranking seen by The Information shows that the total consumption in the past 30 days has surpassed 60 trillion tokens, which roughly translates to about $900 million based on the public average price of Claude Opus 4.6 (approximately $15 per million tokens), though the actual model combinations and pricing protocols at Meta remain unclear. The top individual user has an average consumption of 281 billion tokens, potentially costing millions of dollars. The ranking features gamified incentives, with tiers ranging from bronze to emerald, and the highest titles including 'Token Legend' and 'Session Immortal', along with 'Model Connoisseur' and 'Cache Wizard'. Some employees have been running AI agents for hours on end purely to inflate their usage for ranking purposes. Meta CEO Mark Zuckerberg and CTO Andrew Bosworth did not make it into the top 250. Recently, there has been a trend in Silicon Valley known as 'tokenmaxxing', where token consumption is becoming a new metric for measuring engineer productivity. Bosworth mentioned at a tech conference in February that the token expenditure of a top engineer is equivalent to their salary, with productivity improvements reaching up to 10 times, stating, 'This is a no-lose deal; keep burning, there’s no limit.' NVIDIA CEO Jensen Huang remarked last month that if an engineer with a $500,000 annual salary consumes less than $250,000 in tokens each year, he would be 'deeply concerned'. Meta engineers are currently using external models from Anthropic, OpenAI, and Google, as well as internal tools like MyClaw (Meta's version of OpenClaw) and the recently acquired Manus. In an internal memo this year, Zuckerberg made a 'bold request' to the engineering team to rewrite Meta's codebase to enable AI agents to directly understand and modify the code.

Meta's Internal 'Claudeonomics' Ranking Revealed: 85,000 Employees Burn 60 Trillion Tokens in 30 Days

On April 7, several former OpenAI employees jointly established a venture capital fund named Zero Shot, with a target size of $100 million. The first round has raised approximately $20 million and completed several investments. The fund was initiated by Evan Morikawa, Andrew Mayne, Shawn Jain, along with participation from Kelly Kovacs and Brett Rounsaville. The invested projects include the enterprise automation platform Worktrace AI and the robotics company Foundry Robotics. The team stated that they will focus on AI sectors with long-term potential while adopting a cautious approach towards certain areas, including 'vibecoding' platforms and robotic video data training.

[Former OpenAI Employees Launch $100 Million VC Fund Zero Shot, Focusing on AI Investments]On April 7, several former OpenAI employees jointly established a venture capital fund named Zero Shot, with a target size of $100 million. The first round has raised approximately $20 million and completed several investments. The fund was initiated by Evan Morikawa, Andrew Mayne, Shawn Jain, along with participation from Kelly Kovacs and Brett Rounsaville. The invested projects include the enterprise automation platform Worktrace AI and the robotics company Foundry Robotics. The team stated that they will focus on AI sectors with long-term potential while adopting a cautious approach towards certain areas, including 'vibecoding' platforms and robotic video data training.

Former OpenAI Employees Launch $100 Million VC Fund Zero Shot, Focusing on AI Investments

火币HTX报道，2025 年第二季度，公共矿工的平均比特币生产成本达到 74.6 万美元现金，总成本达到 137.8 万美元。

【公共矿工的平均比特币生产成本达到 74.6 万美元现金】火币HTX报道，2025 年第二季度，公共矿工的平均比特币生产成本达到 74.6 万美元现金，总成本达到 137.8 万美元。

公共矿工的平均比特币生产成本达到 74.6 万美元现金

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公共矿工的平均比特币生产成本达到 74.6 万美元现金

Isenção de responsabilidade：O conteúdo acima não representa as posições da HTX.，A HTX não faz quaisquer recomendações de negociação.。

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