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Bitcoin miner Zack Pettit skating on his work break at the SCATE Ventures mining facility in Dallesport, Washington.
SCATE Ventures Inc.

Nick Sears was 17 years old when he helped build a bitcoin mining farm in Dallesport, Washington. He was 18 when he was legally allowed to buy bitcoin for the first time. And now, at 19, Sears has doubled down on his life as a bitcoin miner, saying “no” to college and “yes” to living in a room inside a data center that houses 4,500 whirling ASICs. 

“My room is sound-locked,” said Sears of the acoustic retrofitting of his living quarters. “So I can’t hear the machines when I close my door, but they are definitely noisy if I have my door open.”

The machines generate about 80 decibels of noise apiece — but Sears says he likes being as close to the action as possible. It also beats making the half hour commute each way from his parents’ house in White Salmon. 

The 19 year-old has spent pretty much every single day for the last two years teaching himself the nuances of how mining machines work – and crucially, how to fix them. He believes his education in soldering and electronics is worth a whole lot more to him than a university degree. 

“I don’t think about going to college at all, just pursuing further knowledge in the repairs of the miners,” continued Sears.

CNBC spoke with multiple miners for this story. Many explained that the allure of mining comes from being able to tangibly grasp the power of bitcoin. 

“If you’ve been to any of these data centers, the first thing you’ll notice is just how vast and how impressive they are. They’re huge,” said explained Thomas Heller, chief business officer for Compass Mining, which works with Sears’ employer, SCATE Ventures. 

“There’s so much noise, and there’s so much heat. There’s just so much action going on. It is quite cool to walk into a data center for  the first time that’s mining bitcoin, because you can really connect the intangible aspects of bitcoin as a currency, with the physical nature of these machines consuming power and doing these calculations.” 

Bitcoin miner Nick Sears lives on-site at the SCATE Ventures mining farm in Dallesport, Washington.
SCATE Ventures Inc.

A day in the life of a miner

Mining for bitcoin isn’t a glamorous job.

“When we first got here, we were setting up racks, creating the network infrastructure for the internet, and we essentially had to wire everything,” he said. 

Once the physical infrastructure was up and running, Sears got into more of a rhythm. He’s now up at 7 A.M. everyday and works from eight to four. He remains on site afterwards, just in case of an emergency, and there is a technician who works night shifts so that Sears can get some sleep.

But beyond the hours, there is no typical work day for Sears. 

“That’s the cool thing about this job – I don’t have a set routine that I do everyday,” he said. “Every morning, I find what needs to be fixed.” 

Some days, that means Sears repairs walls and other physical infrastructure. “If we have to repair a camera, maybe I’m fixing a cable.”

But the biggest part of the job is monitoring and managing every one of those 4,500 Bitmain and Whatsminer ASICs to ensure they are running 24 hours a day, seven days a week. If even one of those machines goes offline, or is only running at partial capacity, the SCATE Ventures mine loses money.

That’s because when someone is mining for bitcoin, what they are actually doing is lending their computing power to the bitcoin network. The more machines you have online, the better your chances at winning bitcoin.

Rig under inspection at the SCATE Ventures mining farm in Dallesport, Washington.
SCATE Ventures Inc.

Roughly every ten minutes, 6.25 bitcoins are created. In order to mint these new tokens, a global pool of miners are all contributing their computing power to running a hashing algorithm. But these miners aren’t working in a vacuum. They’re competing against each other to see who can unlock each batch of new bitcoin first. 

So the stakes are high for Sears. Being diligent and knowing how to triage issues across the entire facility is critical to success.

Some mining sites use more sophisticated software to monitor the machines, which includes checking the temperature of each hashboard within the individual miners. 

But most important for Sears is just figuring out which of his machines aren’t functioning at full capacity. 

“Every day, you find the machines that have stopped hashing, then you remove them from the rack, and you troubleshoot,” he explained. “You’ve got to find the problem with the machines. You’ve got to find out why it went offline.”

It could be a power outage, which would affect all the machines, or it could be a network outage which could impact all of the machines or just some. 

“Sometimes they just need a power cycle or a reboot,” he said.

But the hardware fix isn’t always as simple as that. 

“It could be that the fan on the individual machine that is used for cooling is broken, or maybe it’s the power supply that needs to be repaired or replaced,” explained Heller.

“It could be the hashboards themselves,” continued Heller. “Each hashboard has lots of individual chips, and those are the chips doing the calculations. I think with a Bitmain machine, if more than four chips on a single hashboard are broken, the whole hashboard will switch off. So instead of hashing at about 100%, you’re only hashing at two-thirds or one-third.” 

Seasonal changes in the weather add a whole other layer of complexity. 

Lead technician Nick Sears repairs hardware at the SCATE Ventures Inc. mining farm in Dallesport, Washington.
SCATE Ventures Inc.

Storms can lead to power outages or other disruptions. Heller says that in the summer, the machines can also overheat, especially at the farms which have upgraded to using more powerful units over the course of the last two years. 

SCATE’s mine in Washington seems to have found a way around this problem by using its own immersion cooling technology, which involves submerging bitcoin miners in a non-conductive fluid to dissipate heat, rather than relying on fans. 

Training up and getting paid

Sears may not need a diploma to mine, but taking online training courses run by Chinese engineers who work for Bitmain has gone a long way toward helping him repair specialized mining equipment.

Last month, Sears and another employee completed a virtual class through Bitmain to learn how to work on the ASIC chips on hashboards, as well as the power supplies of the S17s, one of the most popular machines now used to mint bitcoin. 

“I have a certification of maintenance repair, so lately, I’ve just been perfecting my skills in that category,” explained Sears. “It certifies my knowledge and gives me access to buy supplies and material directly through Bitmain.”

Lead technician Nick Sears at the SCATE Ventures Inc. mining farm in Dallesport, Washington.
SCATE Ventures Inc.

Next, he hopes to attend an in-person class in Atlanta, Georgia, to learn more about soldering. “The hard part is learning how to solder and disassemble a circuit board,” said Sears.

Sears’ boss, Scott Bennett, is big on giving his team access to the resources they need to get better at their jobs. 

Bennett, CEO of SCATE Ventures, is a self-taught miner who started his business in his parents’ garage back in 2017, just before the last crypto “winter,” when prices of bitcoin and other cryptocurrencies plunged. Similar to Sears, Bennett once lived at one of his data centers – only he opted for an on-site camper, rather than a room inside the facility itself. 

It helped that he lives within minutes of some of the cheapest power in the world. 

“All of our facilities are 100% hydro powered,” said Bennett. 

The mining facility where Sears works is next to the Columbia River and directly adjacent the Dalles Dam. “We love that source of power. It’s cheap, renewable, and very abundant,” he said.

As for employee pay, Sears says that he makes $54,000 a year, plus full health insurance, which is paid for by the company. 

Bennett also runs some mining machines exclusively for his employees. That amounts to about .02 BTC quarterly, which by today’s price equates to a $788 bonus every three months to Sears. 

“With all the miners in China going offline, the difficulty rate has been changing, so the rewards are higher,” said Sears. “The last time we got a little bit more than we did the previous time, which is cool by me.”

The SCATE Ventures mining farm runs on hydropower generated by the Dalles Dam.
SCATE Ventures Inc.

Mining remotely

It is also possible to become a crypto miner without physically handling any mining equipment at all.

Adam Gitzes decided in early 2021 that he really wanted to mine for bitcoin. After his wife vetoed the idea of installing equipment in their home, he began to look for alternatives.

Gitzes discovered Compass Mining, which allows customers to buy mining machines for between $5,800 and $11,700, then locates them in partner data centers and takes care of the physical logistics.

“I bought the machines on the website, Compass managed the logistics, delivering the machines to three different data centers in North America,” said Gitzes, who explained he spent 1.1 bitcoin — about $60,000 at the time of purchase — on them.

“Compass also configured them the way that I asked.”

So a typical day in the life of a miner like Gitzes consists of waking up and checking online to see how much bitcoin his machines mined overnight and to ensure that none of his units are down.

Inside the SCATE Ventures mining farm in Dallesport, Washington.
SCATE Ventures Inc.

Gitzes owns six machines that he says are on the “higher end.” When China expelled all its miners, Gitzes says it doubled the amount of money that his machines generate daily. 

After paying the mining pool fee of 1.25%, Gitzes’ miners generate about .0055 bitcoin a day, or $216 at today’s prices. Daily electricity costs are about $30, so he’s pulling in roughly $186 a day, or just shy of $5,700 every month. At that rate, he’ll recoup his investment in about 11 months, assuming no major fluctuations in energy or bitcoin prices.

Gitzes was so impressed by the Compass business model that he quit his job at Amazon to join the team in March. “The mission to decentralize mining and make it so that everyone can participate is something that I find really important,” said Gitzes.

The SCATE Ventures mining farm is in Dallesport, Washington.
SCATE Ventures Inc.

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Companies are blaming AI for job cuts. Critics say it’s a ‘good excuse’

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Companies are blaming AI for job cuts. Critics say it’s a 'good excuse'

More companies are announcing AI-driven layoffs from Salesforce to Accenture.

Twenty20

From tech to airlines, large global companies have been slashing staff as the real-world impact of artificial intelligence plays out, spooking employees. But critics say AI has become an easy excuse for firms looking to downsize.

Last month, tech consultancy firm Accenture announced a restructuring plan that includes quick exits for workers that aren’t first able to reskill on AI. Days later, Lufthansa said it was going to eliminate 4,000 jobs by 2030 as it leans on AI to increase efficiency.

Salesforce also laid off 4,000 customer support roles in September, saying that AI can do 50% of the work at the company. Meanwhile, fintech firm Klarna has reduced staff by 40% as it aggressively adopts AI tools.

Language-learning platform Duolingo has stated that it will gradually stop relying on contractors and use AI to fill the gaps.

The headlines are grim, but Fabian Stephany, assistant professor of AI and work at the Oxford Internet Institute, said there might be more to job cuts than meets the eye.

Previously there may have been some stigma attached to using AI, but now companies are “scapegoating” the technology to take the fall for challenging business moves such as layoffs.

“I’m really skeptical whether the layoffs that we see currently are really due to true efficiency gains. It’s rather really a projection into AI in the sense of ‘We can use AI to make good excuses,'” Stephany said in an interview with CNBC.

Companies can essentially position themselves at the frontier of AI technology to appear innovative and competitive, and simultaneously conceal the real reasons for layoffs, according to Stephany.

“There might be various other reasons why companies are having to get rid of part of their workforce … Duolingo or Klarna are really prime candidates for this because there has been overhiring during Corona [Covid-19 pandemic] as well,” the professor said.

Some companies that flourished during the pandemic “significantly overhired” and the recent layoffs might just be a “market clearance.”

“It’s to some extent firing people that for whom there had not been a sustainable long term perspective and instead of saying “we miscalculated this two, three years ago, they can now come to the scapegoating, and that is saying ‘it’s because of AI though,'” he added.

This pattern has sparked conversation online. One founder, Jean-Christophe Bouglé even said in a popular LinkedIn post that AI adoption is at a “much slower pace” than is being claimed and in large corporations “there’s not much happening” with AI projects even being rolled back due to cost or security concerns.

“At the same time there are announcements of big layoff plans ‘because of AI.’ It looks like a big excuse, in a context where the economy in many countries is slowing down, despite what the incredible performance of stock exchanges suggest,” said Bouglé, who co-founded Authentic.ly.

Feeding the fear of AI

Jasmine Escalera, a careers expert, said this concealment is “feeding the fear of AI” with employees globally concerned about their jobs being replaced as a result of AI.

“So we already know that employees are scared because companies are not being honest, open and communicative about how they’re implementing AI,” Escalera told CNBC Make It. “Now companies are openly stating ‘We’re doing this [layoffs] because of AI’ so it’s feeding the frenzy.”

Escalera said big companies need to be more responsible as they set the tone for what’s the norm in business decision making and avoid greenlighting “bad behavior.”

A Salesforce spokesperson clarified to CNBC that the company deployed its own AI agent, Agentforce, which reduced the number of customer support cases and eliminated the need to “backfill support engineer roles,” they said.

View taken inside a Lufthansa Airbus A350 airplane on March 19, 2025.

Lufthansa to cut 4,000 jobs as airline turns to AI to boost efficiency

“We’ve successfully redeployed hundreds of employees into other areas like professional services, sales, and customer success,” the Salesforce spokesperson added.

Klarna directed CNBC to its co-founder and CEO Sebastian Siemiatkowski’s comments on X where he explained that the company shrank its workforce from 5,500 to 3,000 people in two years but “AI is only part of that story.”

Siemiatkowski linked the workforce reduction to slimming down its analytics team to one “success team,” with many then leaving by natural attrition as well as the reduction of the company’s customer success team.

Lufthansa and Accenture declined to comment on the matter and did not share any further details on their AI restructuring strategy. Duolingo did not respond to CNBC’s request for comment.

Mass AI layoffs are not here

The Budget Lab, a non-partisan policy research center at Yale University, released a report on Wednesday which showed that U.S. labor has actually been little disrupted by AI automation since the release of ChatGPT in 2022.

The lab examined U.S. labor market data from November 2022 to July 2025 using a “dissimilarity index” which measured how much the occupational mix—the share of workers in different jobs—has shifted since AI’s debut and compared it to other technological shifts such as the introduction of computers and the internet. It found that AI hasn’t yet caused widespread job losses.

Additionally, New York Fed economists released research in early September which showed that AI use amongst firms “do not point to significant reductions in employment” across the services and manufacturing industry in the New York–Northern New Jersey region.

It found that 40% of service firms said they were using AI this year, up from 25% last year, while manufacturing firms saw a similar jump from 16% last year to 26% this year, but very few were using AI to layoff workers.

Only 1% of the services firm reported AI as the reason for laying off workers in the past six months, down from 10% that had laid off workers using AI in 2024. Meanwhile, 12% of services firms said AI made them hire less workers in 2025.

By contrast, 35% of services firms have used AI to retrain employees and 11% have hired more as a result.

Stephany said there isn’t much evidence from his research that shows large levels of technological unemployment due to AI.

“Economists call this structural unemployment, so the pie of work is not big enough for everybody anymore and so people will lose jobs definitely because of of AI, I don’t think that this is happening on a mass scale,” he said.

He added that concerns about technology putting an end to human work can be seen throughout history.

“It reoccurred this century alone a dozen times, you can go back to ancient times where Roman emperors put hold to certain machines because they were worried about this and always the contrary happened. The machine made companies, industries more productive.

“It allowed for the emergence of entirely new jobs. If you think about the internet 20 years ago, nobody would have known what a social media influencer is, what an app developer is because it didn’t exist.”

Read more about companies conducting AI layoffs below:

A logo sits illuminated at the Accenture booth in Mobile World Congress 2025 on March 03, 2025 in Barcelona, Spain.

Accenture plans on ‘exiting’ staff who can’t be reskilled on AI amid restructuring strategy

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Close to half of Kalshi user base experienced glitches, delays during Saturday college football games

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Close to half of Kalshi user base experienced glitches, delays during Saturday college football games

The Kalshi logo arranged on a laptop in New York, US, on Monday, Feb. 10, 2025.

Gabby Jones | Bloomberg | Getty Images

Close to half of Kalshi’s user base experienced glitches and delays on Saturday during college football games, a major source of trades, as some said they were temporarily unable to process orders.

In a message sent to a user obtained by CNBC, the predictions market service’s website apologized for any inconvenience and said it was “looking into” the issues traders were experiencing. 

“The Exchange is experiencing temporary delays,” the message read. “Balances and positions may not be accurately reflected at this time.” 

One user shared a screen recording and screenshots with CNBC that showed they were unable to see their balance or bets while the issues persisted.

A number of users on X reported the website was down when they were trying to place bets on college football games, with some saying they had open orders that wouldn’t process. When CNBC visited the website, it wouldn’t load, showing only a green K with a spinning circle around it for more than 20 minutes. The platform later loaded.

“Earlier today, Kalshi experienced minor glitches that temporarily affected some user experiences. No exchange outage occurred, no funds were affected, and the issues are now resolved,” the company said in a statement.

Earlier, a spokesperson denied there was an outage and said the exchange “never stopped functioning properly.” He added that there has been no impact on clearing, advanced trading, or institutional trading.

“There were some glitches and delays on our web and app product, which affected less than half of our user base,” the spokesperson said. 

A little over a week ago, Kalshi announced a $300 million Series D funding round that valued the company at $5 billion, more than double its $2 billion valuation in June after its Series C round. 

The round was co-led by Andreessen Horowitz (a16z) and Sequoia Capital, with participation from Paradigm. Additional backers included Coinbase Ventures, General Catalyst, Spark Capital and CapitalG. 

The company, founded in 2018, rose to prominence by offering bettors the ability to trade on a wide range of real-world events, from football games to who President Donald Trump could pardon this year.

WATCH: Kalshi CEO on $2B valuation: We’re one of the fastest growing companies in America

Kalshi CEO on hitting $2B valuation: We're one of the fastest growing companies in America

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AI headshots are changing the way job seekers are seen and get hired in tough labor market

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AI headshots are changing the way job seekers are seen and get hired in tough labor market

AI headshots are becoming popular on LinkedIn and in professional portfolios as job seekers look for affordable profile pictures to give them an edge.

Since first impressions happen almost entirely through a screen, a clean, appealing photo is as important as a strong resume. And in a competitive job market, a good headshot can make a big difference. But professional photography has long been a financial barrier for many job applicants with an average starting cost for a professional headshot in the U.S. that can easily run up to hundreds of dollars.

Now job seekers are using fast and inexpensive AI tools to replace costly studio sessions.

“When I was at Yale, it was $200 for a 15-minute session for students,” said Melanie Fan, head of growth at Plush, an AI-powered online search platform for personalized shopping. “It was really expensive. The process of getting the pictures back, rendering them, looking at which ones I looked the best in, and then sending it back to the photographer for edit.”

This frustration has fueled the explosion of AI headshot tools like InstaHeadshots, PhotoPacksAI, HeadshotPro and Aragon AI, services that promise a professional image in minutes starting at under $50. Users simply upload selfies, pick a background, and receive dozens and no photographer is needed.

“After I changed my LinkedIn photo, the amount of inbound I’ve been getting from companies has skyrocketed,” Fan said. “Three to four times more messages from companies.”

Design company Canva recently launched its own AI headshot feature, with the goal of offering users a quick way to create realistic headshots and still be able to retouch or restyle them.

According to a recent Canva job market research report, 88% of job seekers believe a polished digital presence influences hiring decisions, which is up 45% from the year before. This is in line with the general uptick in use of AI as part of the application and hiring process, with 90% of hiring managers saying they have used AI to help with the hiring process, and 96% of job seekers who used AI in the application process saying they received callbacks.

Danny Wu, Canva’s head of AI products, said the goal wasn’t to replace real photography, but to make high quality imagery attainable to everyone no matter the budget or location. Once a user uploads an image, Canva can use AI for adjusting or changing the background, placing something in a different place, and for styling. “This is just a more accessible way to get professional and unique headshots,” Wu said.

Risks and questions about authenticity among HR recruiters

Anyone with a phone can get a LinkedIn-ready headshot, but the technology’s rapid adoption has created new questions about ethics and trust. Many candidates fear looking fake or deceptive and recruiters are on the lookout for AI-generated portraits that look overly smooth or stylized, saying authenticity matters the most.

“It is perceived as risky to use an AI headshot,” said Sam DeMase, ZipRecruiter career expert. “While recruiters accept them, a bad AI-generated headshot will put off most recruiters,” DeMase said. “A poorly done AI-generated headshot is easily recognized, reads as inauthentic, and can hurt the candidate’s chances of being selected.”

However, recruiters are struggling to tell if a headshot is AI produced, and the technology will only get better. “It’s becoming more and more difficult to tell whether a headshot has been enhanced or generated by AI,” DeMase added.

Chris Bora, founder and principal AI architect of Bora Labs and a former Meta engineer, said he built his own headshot generator, Nova Headshot, after being disappointed by existing options. “Some made me look taller and skinnier,” Bora said. “The other ones, they made me look lighter, so it wasn’t really me,” he said. “You don’t need to spend thousands to look professional anymore. You just need a tool that makes you look like yourself on your best day. With Nova, it takes less than ten minutes,” Bora said.

Amber Collins, an AI headshot user, said she still feels uneasy about it, especially since not every app gets it right. “There are a lot of bad apps out there,” Collins said. “Seven fingers, half a necklace, and the rest of it is gone from your neck. I feel guilty using AI. There’s a stigma. I’d 100% prefer to get actual get headshots done,” Collins said.

But ultimately, she says, the benefits outweighed the risks. “In this economy, you have to be mindful of where you’re going to put your money. I don’t need to have my face out there excessively, but having a couple of really good, solid, professional looking headshots is worth it to me,” Collins said.

Wu said the goal for job applicants seeking a headshot should be to use Canva’s tool to balance realism and creativity without losing their identity.

The tension between tech innovation and accessibility on the one hand, and authenticity on the other, will remain.

A LinkedIn spokesperson told CNBC what while the platform does allow the use of tools, including AI, to enhance or create profile photos, “the photo must reflect your likeness.”

“Profile photos that don’t comply with our user agreement or professional community policies may be removed,” the LinkedIn spokesperson said.

DeMase noted that many job candidates remain hesitant to use an AI headshot. “A headshot is one of the few places you can inject humanity into the job search,” he said.

But with job seekers now able to provide the appearance they had access to the same studio lighting, camera, and editing team as the pros, the trend is unlikely to stop.

A recent survey found that headshot use among job seekers is the highest within the Gen Z and millennial generations. And while recruiters may say they still prefer real photos, AI headshots are becoming harder to spot, and less likely to even be reviewed by humans in the first stages of the application process. A recent study from the HR trade group SHRM found that 66% of human resource professionals are using AI to generate their job descriptions, and 44% are using the technology to review or screen applicant resumes.

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