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The U.S. has placed major chip export restrictions on Huawei and Chinese firms over the past few years. This has cut off companies’ access to critical semiconductors.

Jaap Arriens | Nurphoto | Getty Images

Taiwan has added China’s Huawei and SMIC to its trade blacklist in a move that further aligns it with U.S. trade policy and comes amid growing tensions with Beijing. 

The two leading Chinese chip firms have been put on Taiwan’s “Strategic High-Tech Commodities Entity List,” along with many of their international subsidiaries.

Taiwan’s current regulations require licenses from regulators before domestic firms can ship products to parties named on the entity list. 

In a statement on its website, Taiwan’s International Trade Administration said that Huawei and SMIC were among the 601 new foreign entities, blacklisted due to their involvement in arms proliferation activities and other national security concerns.

Huawei and SMIC are also on a U.S. trade blacklist and have been impacted by Washington’s sweeping controls on advanced chips. Companies such as contract chipmaker Taiwan Semiconductor Manufacturing Co already follow U.S. export restrictions. 

However, the addition of Huawei and SMIC to the Taiwan blacklist is likely aimed at the reinforcement of this policy and a tightening of existing loopholes, Ray Wang, an independent semiconductor and tech analyst, told CNBC. 

He added that the new domestic export controls could also raise the punishment for any potential breaches in the future. 

UBS GWM: Taiwan's security means it needs to remain relevant to the world, including China

TSMC had been embroiled in controversy in October last year when semiconductor research firm TechInsights found a TSMC-made chip in a Huawei AI training card. 

Following the discovery, the U.S. Commerce Department ordered TSMC to halt Chinese clients’ access to chips used for AI services, according to a report from Reuters. TSMC could also reportedly face a $1 billion as penalty to settle a U.S. investigation into the matter.

Huawei has been working to create viable alternatives to Nvidia‘s general processing units used for AI. But, experts say the company’s advancement has been limited by export controls and a lack of scale and capabilities in the domestic chip ecosystem. 

Still, Huawei is believed to have acquired several million GPU dies from TSMC for its AI chips by using previous loopholes before they were discovered, according to Paul Triolo, partner and senior vice president for China at advisory firm DGA-Albright Stonebridge Group. 

A die refers to a small piece of silicon material that serves as the foundation for building processors and contains the intricate circuitry and components necessary to perform computations. 

The Taiwanese government’s crackdown on exports to SMIC and Huawei also comes amid tense geopolitical tensions with Mainland China, which regards the democratically governed island as its own territory to be reunited by force, if necessary.

In April, the U.S. reaffirmed its commitment to support the existing status quo as China conducted large-scale military exercises off the coast of the island.

In statements reported by state media on Sunday, China’s top political adviser Wang Huning echoed Beijing’s position, calling for the promotion of national reunification with Taiwan and for resolute opposition to Taiwan independence. 

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Week in review: The Nasdaq’s worst week since April, three trades, and earnings

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Week in review: The Nasdaq's worst week since April, three trades, and earnings

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Too early to bet against AI trade, State Street suggests 

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Too early to bet against AI trade, State Street suggests 

Momentum and private assets: The trends driving ETFs to record inflows

State Street is reiterating its bullish stance on the artificial intelligence trade despite the Nasdaq’s worst week since April.

Chief Business Officer Anna Paglia said momentum stocks still have legs because investors are reluctant to step away from the growth story that’s driven gains all year.

“How would you not want to participate in the growth of AI technology? Everybody has been waiting for the cycle to change from growth to value. I don’t think it’s happening just yet because of the momentum,” Paglia told CNBC’s “ETF Edge” earlier this week. “I don’t think the rebalancing trade is going to happen until we see a signal from the market indicating a slowdown in these big trends.”

Paglia, who has spent 25 years in the exchange-traded funds industry, sees a higher likelihood that the space will cool off early next year.

“There will be much more focus about the diversification,” she said.

Her firm manages several ETFs with exposure to the technology sector, including the SPDR NYSE Technology ETF, which has gained 38% so far this year as of Friday’s close.

The fund, however, pulled back more than 4% over the past week as investors took profits in AI-linked names. The fund’s second top holding as of Friday’s close is Palantir Technologies, according to State Street’s website. Its stock tumbled more than 11% this week after the company’s earnings report on Monday.

Despite the decline, Paglia reaffirmed her bullish tech view in a statement to CNBC later in the week.

Meanwhile, Todd Rosenbluth suggests a rotation is already starting to grip the market. He points to a renewed appetite for health-care stocks.

“The Health Care Select Sector SPDR Fund… which has been out of favor for much of the year, started a return to favor in October,” the firm’s head of research said in the same interview. “Health care tends to be a more defensive sector, so we’re watching to see if people continue to gravitate towards that as a way of diversifying away from some of those sectors like technology.”

The Health Care Select Sector SPDR Fund, which has been underperforming technology sector this year, is up 5% since Oct. 1. It was also the second-best performing S&P 500 group this week.

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People with ADHD, autism, dyslexia say AI agents are helping them succeed at work

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People with ADHD, autism, dyslexia say AI agents are helping them succeed at work

Neurodiverse professionals may see unique benefits from artificial intelligence tools and agents, research suggests. With AI agent creation booming in 2025, people with conditions like ADHD, autism, dyslexia and more report a more level playing field in the workplace thanks to generative AI.

A recent study from the UK’s Department for Business and Trade found that neurodiverse workers were 25% more satisfied with AI assistants and were more likely to recommend the tool than neurotypical respondents.

“Standing up and walking around during a meeting means that I’m not taking notes, but now AI can come in and synthesize the entire meeting into a transcript and pick out the top-level themes,” said Tara DeZao, senior director of product marketing at enterprise low-code platform provider Pega. DeZao, who was diagnosed with ADHD as an adult, has combination-type ADHD, which includes both inattentive symptoms (time management and executive function issues) and hyperactive symptoms (increased movement).

“I’ve white-knuckled my way through the business world,” DeZao said. “But these tools help so much.”

AI tools in the workplace run the gamut and can have hyper-specific use cases, but solutions like note takers, schedule assistants and in-house communication support are common. Generative AI happens to be particularly adept at skills like communication, time management and executive functioning, creating a built-in benefit for neurodiverse workers who’ve previously had to find ways to fit in among a work culture not built with them in mind.

Because of the skills that neurodiverse individuals can bring to the workplace — hyperfocus, creativity, empathy and niche expertise, just to name a few — some research suggests that organizations prioritizing inclusivity in this space generate nearly one-fifth higher revenue.

AI ethics and neurodiverse workers

“Investing in ethical guardrails, like those that protect and aid neurodivergent workers, is not just the right thing to do,” said Kristi Boyd, an AI specialist with the SAS data ethics practice. “It’s a smart way to make good on your organization’s AI investments.”

Boyd referred to an SAS study which found that companies investing the most in AI governance and guardrails were 1.6 times more likely to see at least double ROI on their AI investments. But Boyd highlighted three risks that companies should be aware of when implementing AI tools with neurodiverse and other individuals in mind: competing needs, unconscious bias and inappropriate disclosure.

“Different neurodiverse conditions may have conflicting needs,” Boyd said. For example, while people with dyslexia may benefit from document readers, people with bipolar disorder or other mental health neurodivergences may benefit from AI-supported scheduling to make the most of productive periods. “By acknowledging these tensions upfront, organizations can create layered accommodations or offer choice-based frameworks that balance competing needs while promoting equity and inclusion,” she explained.

Regarding AI’s unconscious biases, algorithms can (and have been) unintentionally taught to associate neurodivergence with danger, disease or negativity, as outlined in Duke University research. And even today, neurodiversity can still be met with workplace discrimination, making it important for companies to provide safe ways to use these tools without having to unwillingly publicize any individual worker diagnosis.

‘Like somebody turned on the light’

As businesses take accountability for the impact of AI tools in the workplace, Boyd says it’s important to remember to include diverse voices at all stages, implement regular audits and establish safe ways for employees to anonymously report issues.

The work to make AI deployment more equitable, including for neurodivergent people, is just getting started. The nonprofit Humane Intelligence, which focuses on deploying AI for social good, released in early October its Bias Bounty Challenge, where participants can identify biases with the goal of building “more inclusive communication platforms — especially for users with cognitive differences, sensory sensitivities or alternative communication styles.”

For example, emotion AI (when AI identifies human emotions) can help people with difficulty identifying emotions make sense of their meeting partners on video conferencing platforms like Zoom. Still, this technology requires careful attention to bias by ensuring AI agents recognize diverse communication patterns fairly and accurately, rather than embedding harmful assumptions.

DeZao said her ADHD diagnosis felt like “somebody turned on the light in a very, very dark room.”

“One of the most difficult pieces of our hyper-connected, fast world is that we’re all expected to multitask. With my form of ADHD, it’s almost impossible to multitask,” she said.

DeZao says one of AI’s most helpful features is its ability to receive instructions and do its work while the human employee can remain focused on the task at hand. “If I’m working on something and then a new request comes in over Slack or Teams, it just completely knocks me off my thought process,” she said. “Being able to take that request and then outsource it real quick and have it worked on while I continue to work [on my original task] has been a godsend.”

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