China hasn’t banned gold. It has restricted leveraged paper gold trading for retail investors through some of its biggest banks.

At the same time:

1. Physical gold buying remains open.

2. Some gold accumulation products have become cheaper.

3. China’s central bank continues to add to its gold reserves.

That’s why it’s important to look beyond the headlines.

The bigger story isn’t that China is moving away from gold.

It’s that China is discouraging short-term speculation while continuing to treat physical gold as a long-term strategic asset.

Taken from New York Post: https://nypost.com/2026/07/01/us-news/third-of-democrats-are-fond-of-socialists-as-party-drifts-further-to-the-left-poll/?utm_source=facebook&utm_medium=social&utm_campaign=nypost&sr_share=facebook&fbclid=IwY2xjawS0qkNleHRuA2FlbQIxMABicmlkETFUZUFjaFZqazhUaVdwMW5Pc3J0YwZhcHBfaWQQMjIyMDM5MTc4ODIwMDg5MgABHtxlRhq8Q7rJEYaIw_QsvceI7oEbon0VtZ3HX4wo5N5nmqDtNXAcUx8OMbwZ_aem_q6zASq91ZcivbLP3zhI6qA

Nearly one-third of Democrats say they want to see democratic socialists in office, according to a new poll released as far-left candidates rack up victories in New York City and Colorado.

A firm 32% of Democrats indicated they like democratic socialist pols, compared to just 11% who don’t and 56% who have no strong opinions on them, according to a survey from Pew Research.

Predictably, among self-described liberal Democrats, 52% like politicians who identify as democratic socialists, while 4% dislike them and 43% don’t have an opinion.

Moderate and conservative Democrats were more split, with 17% inclined to dislike socialists, compared to 15% who liked them, and 66% with no opinion.

Democratic socialists had the highest support from white, younger, upper-income, and college-educated party members — despite their claim of standing against the elites of society and for the working class.

White Democratic support for the socialist wing (40%) is nearly double that of black (21%) and Hispanic Democrats (20%).

Four in 10 upper-income Democrats also say they like democratic socialists, compared to 34% of middle-income Dems and 24% of low-income Dems.

The left flank of the party has racked up a series of victories in Democratic primaries over recent weeks, largely in safe blue districts.

More than three dozen Democratic Socialists of America (DSA)-backed candidates have won their primaries so far this year, including a trio of New Yorkers endorsed by Mayor Zohran Mamdani and Melat Kiros — who defeated 15-term incumbent Rep. Diana DeGette in Colorado Tuesday.

Still, data from Pew Research indicates that the broader American public is skeptical of the DSA.

Overall, 38% of Americans dislike self-described democratic socialist politicians, compared to 15% who like them, while 43% are indifferent, per the poll.

The highest disapproval rate came from Republicans (69%), though 3% of GOPers claimed to like democratic socialists and 27% were indifferent.

Three years ago, Washington bet that restricting China’s access to advanced semiconductors would preserve American technological dominance. That bet is not paying off the way its architects imagined. A February 2026 analysis in American Affairs Journal found that China’s semiconductor manufacturing equipment sector has reached a level of maturity that would have seemed implausible just a few years ago.

Huawei is building advanced fabrication facilities in Shenzhen targeting 7-nanometer commercial-scale production as early as this year. SMIC, the state-backed foundry, has repeatedly pushed foreign equipment past its rated specifications to achieve manufacturing nodes that the export controls were specifically designed to prevent. This is the uncomfortable logic of economic coercion: the more you restrict, the more you incentivize the other side to build what you’re withholding.

To be clear, the export controls imposed since 2022, and progressively tightened through 2025, have had real effects. They disrupted China’s semiconductor supply chains, caused price spikes, and delayed access to the most advanced fabrication nodes by multiple years. Independent analysts broadly agree that the United States retains a meaningful lead in frontier chip design and production.

But a May 2026 CSIS assessment found a consistent pattern: every tightening of restrictions has prompted China to double down on state-backed domestic investment. China’s target is roughly 50 percent self-sufficiency in semiconductor equipment by 2025, up from 13.6 percent in 2024. Export controls have not halted that trajectory. By some measures, they’ve accelerated it.

Semiconductors generated $627.6 billion in global sales in 2024. China is one of the largest single markets. American chipmakers barred from selling there lose revenue that would otherwise fund the research and development cycles that keep them ahead. The Information Technology and Innovation Foundation’s economic modeling found that sustained revenue losses reduce R&D investment, slow innovation cycles, and weaken the long-term competitive position of US firms. The controls are designed to protect American technological leadership. But by cutting into the revenues that fund American chip research, overly broad restrictions may erode the very lead they claim to be defending.

China’s state-backed firms do not face the same constraint. Beijing can backstop losses that market forces would punish. This is not a neutral observation. It points to a structural asymmetry in how the two sides are playing the game, where blanket commercial restrictions impose real costs on private firms while doing relatively little to slow a state-directed industrial policy with a decades-long time horizon.

Washington has begun to recognize this. A December 2025 policy reversal included a significant concession: allowing NVIDIA to resume shipping H200-class chips to China under a case-by-case licensing review, reversing the blanket denial posture that had been in place. National security hardliners objected. But the move reflects a pragmatic acknowledgment that restricting commercially available chips with broad civilian applications carries limited security benefit while imposing real costs on American industry.

What the walk-back reveals is that the original policy was not as carefully calibrated as its architects suggested. Controls that made sense for cutting-edge military-relevant systems were bundled with restrictions on hardware with legitimate commercial uses. The result was a blunt instrument presented as precision policy.

The semiconductor question does not exist in isolation. In healthcare, Chinese manufacturing is deeply embedded in supply chains for medical devices, pharmaceutical ingredients, and diagnostic equipment. A 2025 disruption in active pharmaceutical ingredient supply underscored just how much of American drug manufacturing depends on Chinese chemical production. No export control regime has addressed this dependency.

In AI and digital infrastructure, Chinese firms are deploying sector-specific models in logistics, healthcare diagnostics, and manufacturing across Southeast Asia and other fast-growing markets. They are competing not on headline model performance, but on embedded, industry-specific integration. The technology competition is not only about who has the largest model. It is about whose systems are most deeply woven into the infrastructure of the world’s fastest-growing economies. No chip export control addresses that either.

If the goal is genuinely to protect American technological capacity—rather than to perform strategic anxiety through trade restrictions—three things need to change. First, export controls should be calibrated by actual security risk, not by the nationality of the buyer. A Chinese civil engineering firm purchasing legacy semiconductors for infrastructure control is not the same security concern as the People’s Liberation Army acquiring GPU clusters for weapons simulation. Policy that treats them identically is not rigorous but reflexive.

Second, domestic investment in research capacity needs to be sustained—and scaled. CHIPS Act funding was a meaningful start. But it cannot substitute for the revenue base being eroded by overbroad restrictions on the very firms it is meant to support. One cannot simultaneously cut the funding streams and promise to out-innovate.

Third, the framework needs to distinguish between managed engagement and capitulation. In legacy semiconductors, industrial AI, and healthcare technology, U.S. and Chinese capabilities are often genuinely complementary. Treating all technology trade as an extension of military competition forecloses arrangements that could serve both economic and stability interests.

The semiconductor rivalry between the United States and China is real, consequential, and will shape the technological landscape for the next decade at minimum. CSIS analysts argue that the United States holds genuine leads in frontier chip design, advanced manufacturing equipment, and the research ecosystem that generates next-generation capabilities. The question worth asking is whether current policy is protecting that lead—or gradually undermining it by cutting revenues, accelerating Chinese domestic investment, and conflating commercial competition with existential threat.

A November 2026 policy deadline offers an opening to move from reactive restriction to something more strategic: a framework that distinguishes between the technologies and transactions that genuinely threaten security and those that simply compete. The difference matters. So far, U.S. policy has not consistently made such a distinction.

Chinese artificial intelligence models have reportedly caught up to top US systems in cybersecurity – a shift that could add pressure on the White House as it works to nail down its domestic AI policy.

Security researchers said a new model released this month by China’s Zhipu AI, also known as Z.ai, is on par with Anthropic’s flagship Mythos model in some bug-finding scenarios. While the Chinese model – known as GLM-5.2 – still trails U.S. giants Anthropic and OpenAI in other areas, researchers said the overall performance gap has greatly narrowed, according to the Wall Street Journal.

Meanwhile, a flood of high-powered, cheap-to-use Chinese AI models are quickly drawing customers across the US. Even companies including Microsoft are considering integrating the systems on their platforms, which could shift the competitive balance across the tech industry.

According to OpenRouter, which provides access to more than 400 AI models, GLM-5.2 ranks among the 10 most-used AI systems. Cybersecurity company Semgrep said the model outperformed Anthropic’s Claude Opus 4.8 in some benchmark tests. Researchers also found that, with additional prompting, both Opus 4.8 and GLM-5.2 can match Mythos in finding software bugs.

On Wednesday, Chinese cybersecurity firm 360 Security Technology unveiled a new bug-finding tool called Tulongfeng, saying it performs on par with Mythos. The advances have raised concerns among national security officials and corporate executives.

“China is making sure that the gap becomes smaller and smaller over time,” Lior Div, chief executive of cybersecurity company 7AI, told the WSJ.

“Genuinely impressed, almost shocked, at how good GLM 5.2 by @zai_org is at coding,” Guillermo Rauch, the CEO of US-based AI firm Vercel, wrote on X earlier this month. “This changes things.”

AI’s growing capacity to identify software vulnerabilities has increased pressure to use the technology to patch security flaws before hackers can exploit them. Researchers have warned that failing to do so could lead to what some have dubbed “bugmageddon.”

Zhipu’s GLM-5.2 is an open-weight model, meaning anyone can download, run and modify it on their own hardware without oversight. That’s in contrast to models built by Dario Amodei’s Anthropic or Sam Altman’s OpenAI.

While open-weight models give organizations greater control, it also gives hackers access to powerful tools.

“This kind of powerful weapon that can alter the landscape of cyberwarfare can’t remain solely in American hands,” 360 Security Chief Executive Zhou Hongyi said at a cybersecurity conference in Beijing, according to the Journal.

Zhou said China would face unacceptable risks if US organizations could use advanced AI models to scan critical Chinese networks while Chinese companies lacked comparable capabilities.

China’s progress comes as the US government has imposed restrictions on releasing advanced AI models.

On Friday, OpenAI said it was limiting access to its newest model, GPT-5.6, citing security concerns raised by administration officials. The company said its current case-by-case review process is a temporary measure while a recent executive order on AI security and model oversight is implemented.

One of Anthropic’s latest general-purpose models has also remained offline for more than two weeks after the Trump administration ruled that no foreign entity or individual could use it because of security risks. Anthropic shut down access to comply with the order. On Friday, the administration restored limited access to a related Anthropic model, Mythos 5, for some users.

Critics have argued that the administration’s actions toward a leading U.S. AI company are counterproductive, particularly as it has allowed exports of AI chips to China despite the country’s rapid AI advances.

“Banning Fable while selling chips China needs to develop its own version is a gift to China,” said Saif Khan, a distinguished technology fellow at the Institute for Progress who worked on export restrictions during the Biden administration.

Khan added that the US should maximize use of Mythos and similar models to strengthen its cyber defenses while it has the advantage.

Critics of the White House’s approach have also argued that it has not done enough to limit the use of Chinese open-weight models from companies such as DeepSeek and Zhipu, which have become popular with US businesses.

In another sign the administration is looking to support domestic open-weight AI developers, the Pentagon recently announced a deal with Reflection AI for classified applications, along with several similar agreements.

At the same time, AI users said US efforts to restrict access to increasingly capable cybersecurity models have fueled concerns that important AI tools could become unavailable.

“It is incentivizing companies across the globe to use cheaper but very capable Chinese open-weight models, while at the same time undermining the U.S. AI industry,” said Niels Provos, a researcher who previously led security teams at Google and Stripe. “I don’t understand it.”