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25 May 2026, 19:35

Huawei just rewrote the rules of chipmaking. Can U.S really stop China’s AI takeover?

Huawei has achieved a breakthrough in building advanced chips in half a decade. The company announced a new technology called LogicFolding, which will allow them to stack computer circuits on top of each other. This technology will save them from the need to buy machines to make the chips smaller. He Tingbo, who leads Huawei’s chip division, said at a tech conference in Shanghai on Monday that the new 3D design will make their chip reach the performance levels of the best chips in the world. Washington and Beijing are fighting for control over artificial intelligence. American sanctions have stopped Huawei from getting the tiny chips that power phones, cars, and computers. The U.S. has also blocked China from buying the software and equipment needed to make these chips. Beijing has spent billions building its own supply chain. Huawei says its chips will match 1.4-nanometer technology by 2031. Right now, China can only make 7-nanometer chips. TSMC in Taiwan makes chips for Nvidia. It already uses 2-nanometer technology and expects to start making 1.4-nanometer chips in 2028. China breaks from Moore’s Law with new chip design The company is also replacing Moore’s Law with Tau Scaling Law. Moore’s law has been employed in the industry by making the transistors smaller. The Tau Scaling Law focuses on the speed of data transfer of the stacked chips. “The industry will face these problems sooner or later,” He told reporters after her speech. “We have confidence in this path because we have practice as proof.” People in the Chinese tech industry call her the “chip queen.” However, the company still has some hurdles. The big challenge is to keep stacked chips from overheating, which current tools can’t protect against. Costs, power use, heat, and putting everything together are already major hurdles for Chinese technology, according to Brady Wang from Counterpoint Research. Still on Weibo, Huawei’s breakthrough is being hyped as what DeepSeek offered. Lower costs for the American standard technology. Some are even saying that U.S sanctions have pushed China into “survival mode,” which needed faster innovation. Huawei also bounced back in 2023 with new phones that had surprisingly good Chinese-made 5G chips. American restrictions are an actual hurdle. Nvidia CEO Jensen Huang went to China this month with President Donald Trump for talks with Chinese leader Xi Jinping. He told CNBC his company has “largely conceded” the Chinese chip market to Huawei. But he also said China is part of a $200 billion market for Nvidia’s new processors, as reported by Cryptopolitan previously. American chipmakers bet big on new markets AMD is putting $10 billion into building infrastructure. Nvidia is changing its business strategy to focus on enterprise customers instead of just big cloud companies. Both moves show American chipmakers are shifting away from China. A new analysis from Anthropic warns that the next two years will decide whether democratic countries or authoritarian governments control the future of artificial intelligence. Anthropic is an AI company. The report says democracies now lead in “compute,” which means the advanced chips needed to build the best AI systems. This lead exists because of American innovation and export controls. But Chinese labs are staying close by, exploiting gaps in U.S. rules. They smuggle chips into China. They use American chips in data centers outside China. They run what Anthropic calls “distillation attacks.” These attacks involve creating fake accounts to copy American AI models. This steals decades of research and billions in investment. Anthropic describes two possible futures for 2028. In the first, democracies close these loopholes and build a lead of 12 to 24 months in AI capabilities. In the second, China keeps finding ways around the rules and catches up. It then uses AI to expand surveillance and control. The report says Firefox fixed more security problems last month using Anthropic’s new AI model than it did in all of 2025. A Chinese cybersecurity expert wrote that while China is “still sharpening our swords,” America has “suddenly mounted a fully automatic Gatling gun.” Chinese state media said after Huawei’s announcement that competition should be “moderate and healthy.” It should help both sides advance. A Foreign Ministry spokesman said Trump and Xi agreed to start government talks on AI during their recent meeting in Beijing. Anthropic says the decisions policymakers make this year will determine who controls transformative AI technology. It will also determine whether it serves democratic values or enables authoritarianism worldwide. If you're reading this, you’re already ahead. Stay there with our newsletter .

25 May 2026, 17:50

ClickUp’s mass layoff and the rise of AI agents: A blueprint for the future of work?

BitcoinWorld ClickUp’s mass layoff and the rise of AI agents: A blueprint for the future of work? When ClickUp CEO Zeb Evans announced on X last Thursday that the company had laid off 22% of its workforce, he framed the decision not as a cost-cutting measure, but as a strategic embrace of artificial intelligence. The collaboration software startup, last valued at $4 billion in 2021, is now positioning itself as a test case for a future where AI agents handle complex tasks while human employees shift to directing and reviewing their output. The move has sparked a broader debate about whether such efficiency gains are real, and at what human cost they come. The logic behind the layoff Evans stated that the savings from the reduction will be reinvested into remaining employees, including introducing “million-dollar salary bands” for those who create outsized impact using AI. ClickUp has deployed roughly 3,000 internal AI agents to automate a wide range of tasks, according to a recent Fortune article. Employees are now expected to manage these agents and ensure quality control, rather than performing the work themselves. Evans’s stated goal is to transform ClickUp into a “100x org” through this automation. Industry context and conflicting data ClickUp is not alone in betting on AI agents for productivity gains. A recent Gartner survey found that about 80% of companies using autonomous technology have cut jobs. However, the same study indicated that workforce reductions are not consistently translating into meaningful financial returns. This suggests that some companies may be using AI as a justification for downsizing, even when the technology has not yet proven its value. Evans, however, told Bitcoin World that ClickUp is already measuring internal productivity gains from its AI agents and plans to incorporate those metrics into a forthcoming product for customers. The rise of ‘tokenmaxxing’ and new performance metrics As companies adopt AI tools, new metrics are emerging to track adoption. Some firms now monitor employee token consumption to see who is using AI. Critics argue that “tokenmaxxing”—racking up AI usage—is a flawed metric because it simply increases AI expenses without guaranteeing value. Evans counters that ClickUp is “gamifying value created and time saved,” not token cost. This reflects a broader shift in how companies evaluate employee productivity in an AI-augmented workplace. An extreme example: The one-person startup The extreme potential of AI-driven automation is already visible at Polsia, a one-year-old startup that claims to handle all software operations for solopreneurs. The company is run by a single person, founder and CEO Ben Broca, and recently raised $30 million at a $250 million valuation. Polsia’s model represents a future where a handful of humans—or even one—can run a high-value company with the help of AI agents. This raises uncomfortable questions about the long-term trajectory of employment in tech. What this means for workers and the broader economy The ClickUp case is a microcosm of a larger shift. If AI agents can reliably automate complex tasks, companies will eventually need fewer people. Evans’s claim that “the people that automate their jobs with AI will always have a job” may be true for a select few, but it also implies that those who fail to adapt will be displaced. The challenge for the industry is not just technical—it is about how to manage a transition that could leave many workers behind, even as it creates new opportunities for a smaller, highly skilled workforce. Conclusion ClickUp’s layoff is a significant signal in the ongoing debate about AI and employment. While the company argues that its strategy is about efficiency and reinvestment, the broader data suggests that AI-driven job cuts are not yet delivering consistent financial benefits. As more companies follow ClickUp’s lead, the need for transparent metrics, worker retraining, and a realistic assessment of AI’s capabilities becomes increasingly urgent. The future of work may be more automated, but whether it will be more productive—or more equitable—remains an open question. FAQs Q1: Why did ClickUp lay off 22% of its workforce? The company says the layoffs are not a cost-cutting measure but a strategic move to embrace AI agents. CEO Zeb Evans stated that savings will be reinvested into remaining employees, with high performers eligible for million-dollar salary bands. Q2: What is an AI agent, and how is ClickUp using them? AI agents are autonomous software systems that can perform complex tasks without human intervention. ClickUp deployed roughly 3,000 internal AI agents to handle a wide range of work, with human employees now responsible for directing and reviewing the agents’ output. Q3: Are AI-driven layoffs actually improving company performance? Data is mixed. A Gartner survey found that about 80% of companies using autonomous tech have cut jobs, but those reductions are not consistently leading to meaningful financial returns. Some experts suggest that AI is sometimes used as an excuse for downsizing rather than a proven driver of efficiency. This post ClickUp’s mass layoff and the rise of AI agents: A blueprint for the future of work? first appeared on BitcoinWorld .

25 May 2026, 17:05

Singapore: AI Tailwinds Help Offset Conflict Drag, Says UOB

BitcoinWorld Singapore: AI Tailwinds Help Offset Conflict Drag, Says UOB Singapore’s economy is navigating a complex global environment, with strong growth in the artificial intelligence sector providing a counterbalance to headwinds stemming from ongoing geopolitical conflicts, according to a recent analysis from United Overseas Bank (UOB). The report highlights how the city-state’s strategic positioning and robust tech ecosystem are helping to mitigate external pressures. UOB’s Assessment of Singapore’s Economic Landscape UOB’s analysis points to a bifurcated economic picture for Singapore. On one hand, the global tech downturn and persistent conflicts, particularly in Eastern Europe and the Middle East, have disrupted supply chains and dampened trade sentiment. These factors have traditionally weighed on Singapore’s open, trade-dependent economy. However, the surge in demand for AI-related infrastructure, including advanced semiconductors, data centers, and cloud services, is providing a powerful new growth engine. The bank notes that Singapore’s established position as a regional hub for technology and finance makes it a primary beneficiary of the AI boom. Investments from major global tech firms in local data centers and research facilities are translating into tangible economic activity, from construction to high-value services. How AI is Driving Growth Amid Global Uncertainty The AI tailwind is not merely a theoretical concept; it is reflected in Singapore’s trade and manufacturing data. Exports of integrated circuits and other electronic components, which are critical for AI computing, have shown resilience. Furthermore, the services sector, particularly in areas like research and development, software engineering, and intellectual property management, is expanding to support AI adoption. This sectoral shift is helping to offset weakness in other areas, such as traditional manufacturing and retail trade, which are more sensitive to global consumer demand and geopolitical disruptions. UOB’s report suggests that this structural change could provide a more durable foundation for Singapore’s long-term growth, reducing its historical vulnerability to global economic cycles. Implications for Investors and Businesses For market participants, the UOB analysis underscores the importance of looking beyond headline GDP figures. While the overall growth rate may be tempered by external drags, the composition of growth is shifting towards higher-value, technology-driven sectors. This has implications for investment strategies, with sectors tied to AI, digital infrastructure, and advanced manufacturing likely to outperform. Businesses operating in Singapore are also advised to consider how they can leverage the AI ecosystem, whether through direct investment in technology, partnerships with research institutions, or by upskilling their workforce to meet new demands. Conclusion UOB’s balanced outlook for Singapore reflects a nuanced understanding of the current global economy. The bank acknowledges the very real challenges posed by geopolitical tensions but emphasizes that the AI revolution is creating a powerful countervailing force. For Singapore, the key to sustained growth will lie in its ability to continue attracting high-value tech investments and to navigate the ongoing uncertainties with its characteristic agility. The report provides a useful framework for understanding the competing forces shaping one of Asia’s most dynamic economies. FAQs Q1: What does UOB mean by ‘AI tailwinds’ for Singapore? UOB refers to the strong economic benefits Singapore is receiving from the global growth of the artificial intelligence industry. This includes increased investment in data centers, semiconductor demand, and high-value tech services, which are creating jobs and boosting exports. Q2: How are global conflicts dragging Singapore’s economy? Geopolitical conflicts, such as the war in Ukraine and tensions in the Middle East, disrupt global supply chains, increase energy costs, and dampen trade sentiment. As a major trading hub, Singapore is sensitive to these disruptions, which can slow down non-tech sectors. Q3: Is this analysis relevant for long-term investors? Yes. The analysis highlights a structural shift in Singapore’s economy towards technology and AI. Long-term investors may find opportunities in sectors like tech infrastructure, semiconductors, and digital services, which are expected to be key growth drivers despite short-term global uncertainties. This post Singapore: AI Tailwinds Help Offset Conflict Drag, Says UOB first appeared on BitcoinWorld .

25 May 2026, 12:56

Cryptopolitan Report: 37% Of Our Readers Say “Nope” To Consulting AI On Life Decisions. So Who Actually Is?

A little over a year ago, Sam Altman highlighted that Gen Z do not tend to make major life calls without consulting them over ChatGPT. He went onto say that while the older generation treat the tool as a “google replacement”, the younger populace in their 20’s and 30’s use it like a “life advisor”. That comment has aged almost like a cultural diagnosis rather than a prediction. Our newsletter poll, conducted last week as the conversation picked up again, suggests our audience is far less convinced with what was said. The Comment That Set This Off OpenAI CEO Sam Altman made a comment at Sequoia Capital’s AI Ascent event last year that made the rounds across newsrooms and social media. His assertion was that different age groups and generations used ChatGPT for various purposes. This did not come as a warning but rather as what he saw in the data. Older people, he said, use ChatGPT like a smarter version of Google. Meanwhile, people in their 20s and 30s used it more as a tool akin to a life advisor. College students, in his words, use it like an operating system, embedded into how they study, plan, write and make calls about their day. The initial reaction to these comments were not even to say the least. Some people saw it as evidence that this tool is finding its native users. Others on the other hand read it as a subtle warning or danger that an entire cohort or generation was using a machine for judgement even though it runs the risk of sounding confident even when it’s wrong. The truth is probably somewhere in the middle, and our poll suggests that even among readers who follow this space closely, the jury is still out. How Big Has This Behaviour Actually Become? A report published by OpenAI in September 2025 showed that nearly half of ChatGPT messages now come from users below the age of 26, making younger adults the dominant demographic. Younger users are pulling in even quicker. A Pew Research Center survey of 1,391 U.S. teens, conducted between September and October 2024, found that 26% of teens aged 13 to 17 had used ChatGPT for schoolwork, double the 13% recorded the year before. The pattern is even more pronounced among older students: 31% of 11th and 12th graders reported using it. Pew’s more recent 2026 follow-up survey shows the shift has moved beyond homework. According to that survey, 57% of teens now use chatbots for information searches, 54% for schoolwork, and 16% for casual conversation. Around 12% say they use these tools for emotional support or advice. That last number is the one worth sitting with. It is small, but it suggests that the line between “tool” and “confidant” is already being crossed in measurable ways. What The Poll Actually Tells Us As mentioned in our previous poll , these are readers who track AI developments closely and many of them follow OpenAI and Anthropic releases the day they drop. The average age of our newsletter audience sits at around 30, which places this cohort squarely within the “life advisor” group Altman described in his Sequoia talk. If anyone in a general audience would be expected to lean on AI for personal decisions, it would be this group. The fact that the leading response is “Nope” is therefore the most interesting part of the result. Note: The 30-year-old average is based on internal Cryptopolitan estimates and is provided as directional context. It has not been formally surveyed and individual respondents will fall on either side of that figure. Nope (36.76%): Around a third of responses in the poll do not ask AI for any sort of life decisions. It provides a clear view on how this cohort views the utility of AI, perhaps for more technical and productive tasks for work, code research or even thinking out loud. That said, certainly not for the kind of decision that has personal weight behind it. The line being drawn is not anti-AI. It is anti-outsourcing. Yes (~36%): Almost identical in size to the “Nope” cohort. Just over one in three respondents say they do consult AI before life decisions. This is the group most aligned with the behaviour Altman described back in 2025, and it is sizeable. The split between this group and the “Nope” cohort is essentially even, which is itself the story. Even in a tech-forward audience that demographically maps onto the cohort he was talking about, there is no consensus on whether AI belongs in the room when something important is being decided. Occasionally (~27.2%): Roughly one in four respondents sit in the middle. They will use it when it helps, but they are not running every choice through the chatbot. This is probably the most honest answer for most people, and it is a group worth watching. As AI tools improve, this cohort is the one most likely to drift toward the “Yes” column. Combine the “Yes” and “Occasionally” responses and you get just under 63% of readers using AI for personal decisions at least some of the time. That number lines up reasonably well with the broader behavioural trend Altman pointed to. What the poll adds is the texture underneath it, a clear segment of people who have looked at this technology, understood what it can do and then decided that some calls don’t require AI intervention and it’s theirs to make. The Quieter Trend Under The Headline The discussion about AI and decision-making usually splits into two camps. One worries about cognitive atrophy and the slow erosion of judgement. The other points to all the small, useful ways AI already helps people think more clearly. Both are right, depending on the type of decision. What our poll suggests is that the question may already be sorting itself out at the user level. Roughly equal portions of the audience are landing in three different places, and the largest of the three is the one drawing a line. That is not what you would expect to see if AI advice was simply replacing human judgement across the board. It looks more like people are learning where it helps and where it does not, and that calibration is happening in real time. The cohort to watch is still the one Altman described, the students who arrived on campus in 2022 with ChatGPT already in their pocket and never knew an academic environment without it. They are graduating now. The data on what happens when an entire working generation makes decisions with an AI assistant in the loop does not exist yet, because they are the first ones generating it. The next few years will tell us whether this is the smartphone moment for cognition, or something more complicated. Our poll suggests that even among people who follow this space for a living, the answer is still being worked out. 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25 May 2026, 12:20

Robinhood's acquisition of WonderFi secures Canadian regulator's approval

More on Robinhood Markets, WonderFi Technologies Inc. Robinhood: Not The Tokenized Stock Bet You're Looking For Robinhood Markets, Inc. (HOOD) Presents at J.P. Morgan 54th Annual Global Technology, Media and Communications Conference Transcript Robinhood's Customers Are Staying Away, You Should Too Inflation panic, rising yields, rate hike pressure returns: Crypto stocks drown in red

25 May 2026, 09:40

Bitwise Executive Compares Crypto’s Current Phase to AI’s Pivotal Moment in 2015

BitcoinWorld Bitwise Executive Compares Crypto’s Current Phase to AI’s Pivotal Moment in 2015 Jeff Park, Head of Alpha Strategies at asset manager Bitwise, has drawn a striking parallel between the cryptocurrency industry today and the state of artificial intelligence roughly a decade ago. In a recent commentary, Park described the current period as a “narrow window” of transition, suggesting that while the foundational direction of crypto has been proven, the industry is navigating its most challenging phase yet. A Historical Parallel: Crypto and AI in 2015 Park noted that in 2015, only a handful of individuals fully grasped the transformative potential of AI. It took approximately ten years for that technology to enter the mainstream. He argues that the cryptocurrency industry is now at a similar inflection point. The core concepts—permissionless money and on-chain capital markets—have been validated, but the path to widespread adoption is constrained by existing regulatory frameworks and legacy financial systems. “The direction has been proven,” Park stated, “but we are now in the most difficult phase.” He specifically pointed to Anti-Money Laundering (AML) and Know Your Customer (KYC) regulations, along with outdated financial infrastructure, as primary factors slowing the pace of expansion. Defining the Core of Crypto: Technological Financialization Park offered a nuanced perspective on the nature of different crypto assets. He described Bitcoin as a “monetary experiment created by technological evolution,” emphasizing its origins in computer science and cryptography. In contrast, he characterized most other cryptocurrency projects as “technological experiments created by monetary evolution,” suggesting they are driven by financial incentives and economic design. This distinction leads to Park’s central thesis: the core of the crypto industry is not simply decentralization, but rather “technological financialization.” This concept frames the industry as the intersection of software engineering and financial markets, where code and economic incentives are merged to create new forms of value transfer and capital formation. Why This Matters for Investors and the Broader Market Park’s analysis provides a framework for understanding the current market dynamics. The comparison to AI in 2015 suggests that while the technology may still be in a nascent stage for mainstream users, the underlying infrastructure is maturing. For investors, this implies that the current period of regulatory uncertainty and market volatility may be a necessary precursor to broader institutional and retail adoption. The emphasis on “technological financialization” also has practical implications. It highlights the need for regulatory clarity that distinguishes between different types of crypto assets, rather than applying a one-size-fits-all approach. It also underscores the importance of infrastructure improvements, particularly in areas like custody, compliance, and interoperability with traditional financial systems. Conclusion Jeff Park’s comparison of the crypto industry to AI in 2015 offers a valuable historical lens for understanding the current market. While the direction is clear, the industry faces significant hurdles related to regulation and legacy infrastructure. The concept of “technological financialization” reframes the debate, positioning crypto not merely as a movement for decentralization, but as a fundamental evolution in how financial systems are built and operated. The next few years will likely determine whether this narrow window of transition leads to the mainstream breakthrough that many in the industry anticipate. FAQs Q1: What did Jeff Park specifically compare the crypto industry to? Park compared the current state of the cryptocurrency industry to the state of the artificial intelligence industry around 2015, a time when its transformative potential was recognized by only a few before it became mainstream roughly a decade later. Q2: What does Park identify as the main barriers to crypto’s expansion? He identified AML/KYC regulations and legacy financial infrastructure as the primary factors limiting the speed of the crypto industry’s expansion during its current transitional phase. Q3: What does Park mean by “technological financialization”? Park argues that the core of the crypto industry is not simply decentralization, but the merging of software engineering with financial markets to create new forms of value transfer, capital formation, and economic incentives. This post Bitwise Executive Compares Crypto’s Current Phase to AI’s Pivotal Moment in 2015 first appeared on BitcoinWorld .