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Scene from “Squid Game” by Netflix
Source: Netflix

When Bernard heard about a token named after the popular South Korean Netflix series “Squid Game,” which chronicles the lives of cash-strapped adults who play in a deadly tournament for a big jackpot, he did a quick scan on Google to see if the coin was legit.

After catching headlines – but before reading the full articles, many of which warned of some red flags around the project – he decided to invest his entire life savings of $28,000 into SQUID, a coin that billed itself as a “play-to-earn” cryptocurrency. On Monday, the token hit a high of just over $2,860, before plummeting to nearly zero, according to CoinMarketCap.

“My rush to buy this token is for a single idea that went into my brain that ‘Squid Game’ is very, very popular now, and its token must be popular now,” said Bernard, who lives in Shanghai, and asked to be identified only by his English first name because trading in cryptocurrency is of questionable legality in China. “It’s a tragedy. I don’t know how to recover my loss.”

Bernard tells CNBC that he supports his family and is now worried about how to pay his bills.

Transaction records from BscScan appear to show the token’s anonymous creators collected least $3.4 million in investor funds. The crypto ecosystem is rife with so-called “rug pull” schemes wherein token founders abruptly abandon their project and take investor funds with them by swapping the project coin for cash.

“Squid Game Dev does not want to continue running the project as we are depressed from the scammers and is overwhelmed with stress,” Squid developers posted Monday in their Telegram channel, which now has more than 89,000 members.

The token’s white paper and website have since disappeared, though archived copies of its official landing page and white paper are still online. Twitter has temporarily restricted its account due to “suspicious activity.” The creators did not respond to multiple emails that CNBC sent to the addresses listed on the web site.

Bernard says he has reached out to the FBI and the SEC about his lost investment.

He has also reached out to the team behind the token, as well as Binance-owned CoinMarketCap, which listed the coin on its website, both of whom “did not take responsibility” for his loss.

Bernard, who says he has a lot of experience in crypto and computers, blames media outlets for his investment in SQUID as well.

He isn’t alone. Others have taken to Twitter to say that giving any oxygen to meme coins like this one functions as an implicit endorsement.

“In this trading space, everyone will rush,” said Bernard, “and sometimes you feel FOMO.” That sense of FOMO, or the fear of missing out, is a common sentiment among crypto traders who invest in early-stage altcoins, eager for a chance at big and quick returns on their investment.

‘Some have a shot at going nuts’

Saurabh Dubey has been interested in cryptocurrencies since 2016. He now works for an accounting firm in the U.S., and in his free time, he regularly day trades new altcoins.

Just past midnight each day, Dubey looks at new coins being listed on CoinMarketCap and CoinGecko, trying to identify trends based on the charts. He typically places bets of around $100 on coins that he thinks show promise in their initial price movements.

“Some have a shot at going nuts,” he said.

Dubey says that he used the proceeds from a recent successful bet on another meme coin to invest $250 into SQUID.

“I thought I’ll play with house money,” said Dubey.

This was when SQUID was trading at about 4 cents – well before all the media hype began.

Dubey says he invested in SQUID because it was the second-ranked token on CoinMarketCap’s list of the most recently listed coins.

“I picked it up because it already had some amount of volume and already had some amount of gain, and if you look at the chart, you will see that the chart mimics the start of how SafeMoon got started,” said Dubey, referring to an altcoin launched in March that appreciated quickly and is still being traded.

He noted that his investment was a gut move more than anything else. “It wasn’t scientific.”

But then Dubey started to notice all the red flags, many of which he hoped were not that big a deal.

“The biggest flag was that it never had a dip,” explained Dubey. “Every coin has to have a dip. There is no way a coin goes up constantly for five days…The only thing that looked like a dip was when it stayed at the same level.”

The level of price appreciation was another big concern. “When it hit $1, I was like, ‘Okay, 20x is reasonable. That can happen.’ When it got to $10, that’s when I started thinking there’s something off,” he said.

“Most coins that actually have a product behind them are barely able to reach that point,” continued Dubey.

Another red flag: None of the token’s founders could be found on LinkedIn, plus its website and white paper were filled with grammatical and spelling errors.

Ultimately, Dubey’s exposure was limited, but investors like Bernard who gambled all their savings on this coin want the creators behind the project to be held accountable.

Bernard, who has been proactive in reaching out to U.S. authorities, says that his hands are tied to take any further action, because he can’t file a report with local police.

“In China, it’s not so legal to trade cryptocurrencies,” Bernard shared with CNBC.

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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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