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Inside the crypto restaurant after the cryptocurrency crash

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When you are bored and hungry First opened in Long Beach In April, the burger joint didn’t just embrace the aesthetics of crypto culture. It was all in the digital money part, too.

Sure, meme-y references to missiles And the bulls Spreading on the walls, bored monkeys – those cartoon monkeys owned by celebrities like Paris Hilton and Post Malone described As six-figure investments – cups and trays covered. But customers were also offered the option to pay for their meals in cryptocurrency. The restaurant was putting their bitcoin where his mouth was, so to speak.

Even three months later, in the midst of the cryptocurrency crash with some investors looking for the door, that wasn’t always the case.

During the afternoon lunch rush, when the cashier stamped paper bags with the fast-food restaurant’s logo, double menus hung above his head – listing Bored & Hungry’s meat- and plant-based options, respectively – prices only showed in the old – dollar made American.

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Burger: $9.25. Pepper Fries: $3.50. Monkey-shaped soda: $3.50.

Missing: Any mention of Ethereum or Apcoin, the two currencies that the popup boasted about would make history by accepting them as payment.

An employee who declined to be named said the store does not accept crypto payments. “Not today — I don’t know,” they said, refusing to say how long the store has stopped accepting cryptocurrencies or whether that option will eventually return.

Owner Andy Nguyen did not respond to repeated emails. The company’s co-founder Kevin Seo later said that the restaurant had shut down its crypto-payments system “from time to time” for upgrades but that it currently accepts Ethereum and Apicoin.

With both coins down more than 60% since early April and subject to daily double-digit fluctuations, it would be understandable for any company to be reluctant to accept them in place of dollars. But utility may also be a factor. At the grand opening of the restaurant, employee He told the Times That cryptocurrency payments were impractical and largely ignored by customers.

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Restaurateur Andy Nguyen says he paid more than $330,000 to purchase the various types of monkey-themed NFTs that form the basis of his restaurant’s brand.

(Brian Contreras/Los Angeles Times)

After nearly three months, it was hard to find a sponsor who somehow cared more about the restaurant’s fidelity to the crypto cause.

“Yes, Ethereum is a currency in a way that you can exchange [nonfungible tokens, or] NFTs and other things…but in terms of buying food and all that, maybe not,” said one crypto enthusiast, Mark Coloma, feasting on french fries outside a restaurant. “People want to hold on to their Ethereum. They won’t want to use it.”

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Michael Powers, 46, of Long Beach, was less familiar with the episode. He came to Bored & Hungry quite often – as often as two or three times a week, at his discretion – but although the monkey-themed signs were the first thing that attracted him to him, little did he know the place was the subject of NFT until his sons explained to him.

Powers’ first foray into cryptocurrency, a Dogecoin investment promoted by Elon Musk, has not ended well, and he is not planning to try again. I’ve been “filled up” with cryptocurrency — but not from burgers, he said, which serves up an upscale contraption on In-N-Out “animal style” sandwiches. (The chopped onion and creamy sauce is a nice touch, by the way, that’s not subject to extreme fluctuations in value or expensive transfer fee.)

Another Long Beach local, Richard Rubalcaba, 30, said he bought ethereum after meeting other crypto investors during the four-hour wait for Bored & Hungry’s opening. But he paid on this visit also in US dollars.

“I do not know how [crypto purchases] It will work, with a meltdown.”

Environmental coding system is Currently in free fallwith prominent companies either taking drastic steps to stave off disaster or simply collapse altogether, while cryptocurrencies themselves Plunge in value.

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The two electronic currencies that Bored & Hungry initially accepted, raised And the epicoin, to about 23% and 17% from their highest levels over the past year, respectively. It is estimated that the value of the entire sector is less than a third of what it was in early 2022.

Nor were the non-fungible codes that form the backbone of the Bored & Hungry brand immune. A sort of digital trading card series built around anthropomorphic monkey graphics, boring monkeys count the likes of Justin Bieber and Snoop Dogg among those. friends; Some have sold for Millions of dollars. However, they are facing the same thing now market pressure Like the rest of the cryptocurrency economy.

According to crypto news outlet Decrypt, the cheapest NFT available on the chain (i.e. “the floor”) has fallen below $100,000 for the first time since last summer, and the project as a whole has recently seen its value nearly halve compared to a month-long cycle.

This only increases the urgency of attracting new buyers to the monkey “community”.

The exterior of the Bored & Hungry fast food restaurant in Long Beach.

Diners can get a meat or veggie burger at Bored & Hungry — but when a reporter asked if cryptocurrency could be used for payment, he was told no.

(Brian Contreras/Los Angeles Times)

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One customer—Lindsey, 33, of San Pedro—said she knows nothing about coding but came to Bored & Hungry because she’s a fan of their vegan brand. But she said the scene in the restaurant made her want to learn more about the ecosystem.

“I’m pretty outside of the cryptocurrency world and all that stuff, so I will definitely go home and Google,” said Lindsey, who declined to give her last name.

Nick Jackson, 29, another local, said he was more interested in collecting Yu-Gi-Oh trading cards — but added that previous visits to Bored & Hungry had prompted him to start looking for Ethereum and abicoin as well.

Jessica Perez, 24, from Gardena doesn’t follow crypto either but has been on a return trip to Bored & Hungry. She and her friends love burgers, said she, “We’re staying this up there with In-N-Out, and maybe even better.”

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Perez has no immediate plans to invest in cryptocurrency but says she will consider it. She said the restaurant was “a good way to promote cryptocurrency.”

Maybe that’s what Nguyen was thinking when he passed out Over $330,000 The various NFTs for the monkeys displayed in his restaurant.

Crypto skeptics have long warned that someone might be left with the bag when the hype cycle itself ends. It’s better to have a burger and fries in a bag than nothing at all.

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This stunning crypto character home is for sale

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Her first foray into the rental market was to advertise her landlord’s properties on Airbnb. She decided to make the cannabis rental themed, decorating it with ganja leaves and providing visitors with free joints upon arrival.

But she said, “He was kind of a brawler.” Visitors from out of town were being robbed in the neighborhood, and there were parties with strippers that annoyed the locals. In the end, I decided to close it.

Levi got into crypto in 2017, after a teenage acquaintance advised her to buy bitcoin. “I’m like, ‘You’re 17.’ Like what the hell, you know? And he’s like, ‘Download Coinbase! Buy Bitcoin! “

“I wanted it to be a bit extravagant and tacky, but in a good way,” she said. “You know, like, crypto overload.” She added that the neighbors weren’t happy with the influx of hard-line cryptocurrency, which was another reason she eventually decided to sell the place. (She said the city council contacted her about the complaints.)

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As for her next project? It’s a pancake delivery company called boffins, which launched smoothly. The selling point is that the pastries are delivered by huge men in branded tank tops.

She said, “You know, delivering flowers on Mother’s Day is great, but imagine a hot guy bringing you a cake. That would be fun!”

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Health tech products that I think are going to explode this year

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While I’m still skeptical of the accuracy of this kind of AI, I visited two other models who analyzed my skin with wildly variable results—one told me I had 25-year-old skin, the other 42-year-old. About my eye bags but it gave me higher ratings for purity and softness then fully recommended products Skin care routine It meets my skin type. I don’t know who to trust, if anyone is.

Similar technology can also monitor internal health. I tested a platform that scans your face to determine your risk level for various health issues (including mental health) from estimated blood pressure, heart rate, and other vital signs. I have nothing to compare it to, so it’s hard to say how accurate it is, but it’s another sign that we’ll see more options for assessing our health from home to share with doctors or receive AI-generated feedback.

Smart home tools for proactive healthcare

Speaking of assessing our health from home, I predict that smart health and fitness monitoring devices will skyrocket in 2023.

We’ve already seen an influx of wearables Fitness and sleep monitoringheart rate, blood pressure, and even blood oxygen levels — all of which can be used to alert us to potential problems before a visit to the doctor. I attended a session where he was the CEO Aura ring He talked about the usefulness of the smart ring, particularly for sleep and for “digital birth control,” or cycle tracking via wearable devices, which he believes will become more prominent in the future.

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Taking wearables even further, a medical officer from Healthify explained how people can use a continuous glucose monitor, or continuous glucose monitor, along with a human coach or AI facilitated from an app to help them understand their metabolic panel. them and the best way to eat and work for them. Corpses.

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How computers learned to be predictors of the COVID-19 outbreak

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Imagine a time when your virus-blocking face covering was like a parachute. Most days, it stays in your locker or stowed somewhere in your car. But when the COVID-19 outbreak is in the forecast, you can use it.

Moreover, the intense viral forecast may prompt you to choose an outdoor table when meeting a friend for coffee. If contracting the coronavirus has the potential to make you seriously ill, you can choose to work from home or attend church services online until the threat has passed.

Such a future assumes that Americans will heed public health warnings about a pandemic virus — and that’s a big deal if. It also assumes a system that can reliably predict impending outbreaks with few false alarms, and with enough timing and geographic accuracy that the public can trust its predictions.

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A group of would-be forecasters says it has the makings of such a system. they Suggestion To build a viral weather report published this week in the journal Science Advances.

Like the meteorological models driving weather forecasts, the COVID-19 outbreak prediction system emerges from a river of data fed by hundreds of local and global information streams. They include time-stamped online searches for symptoms such as chest tightness, loss of smell, or fatigue; geotagged tweets that include terms like “corona,” “pandemic,” or “panic buying”; location data aggregated from smartphones that reveal how many people are traveling; and a drop in online requests for directions, indicating fewer people are getting out.

The resulting volume of information is far greater than humans can manage, let alone interpret. But with the help of powerful computers and software trained to winnow, interpret and learn from the data, the map is beginning to emerge.

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If you check this map against historical data—in this case, two years of epidemiological experience in 93 counties—and update accordingly, you might have the makings of an outbreak forecasting system.

This is exactly what the team from Northeastern University is leading Computer scientist it’s over. In their attempt to create an early warning system for the COVID-19 outbreak, the study authors built a “machine learning” system capable of chewing through millions of digital traces, integrating new local developments, improving its focus on subtle signs of disease, and issuing timely notifications of impending local surges of COVID. -19.

Of his many Internet searches, one proved to be an especially good warning sign of an impending outbreak: “How long will COVID last?”

Tested against real data, the researchers’ machine-learning method predicted an increase in local virus prevalence up to six weeks early. Alarm bells were going off almost at the point where every infected person was likely to spread the virus to at least one other person.

After testing the prediction of 367 actual outbreaks countywide, the program provided accurate early warnings for 337 – or 92% – of them. Of the 30 remaining outbreaks, 23 have been identified just as they would have become apparent to human health officials.

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Once the Omicron variant began spreading widely in the United States, the early warning system was able to detect early evidence of 87% of outbreaks county.

A predictive system with these capabilities could be useful to local, state, and national public health officials who need to plan for COVID-19 outbreaks and warn vulnerable citizens that the coronavirus threatens an imminent local resurgence.

But “we’re looking beyond” COVID, he said Mauricio Santayanawho runs Northeastern’s Machine intelligence group to improve health and the environment.

“Our work aims to document technologies and approaches that may be useful not only for this, but for the next pandemic,” he said. “We’re gaining the trust of public health officials, so they won’t need any more convincing” when yet another disease begins to spread across the country.

This may not be an easy sell for the state’s public health agencies and the Centers for Disease Control and Prevention, which have all struggled to keep up with pandemic data and incorporate new ways to track the spread of the virus. The CDC’s inability to adapt and communicate effectively during the pandemic has led to some “dramatic and very public missteps,” said Dr. Rochelle Walensky, the agency’s administrator, I acknowledge. And she warned that only a “changing culture” would prepare the federal agency for the next pandemic.

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CDC’s lackluster efforts to develop prediction tools haven’t paved the way for easy acceptance either. 2022 Assess Of the forecasting efforts used by the CDC it concluded that most “failed to reliably predict rapid changes” in COVID-19 cases and hospitalizations. The authors of this assessment cautioned that the systems developed to date “should not be relied upon to make decisions about the possibility or timing of rapid changes in trends.”

Anas Barryan expert in machine learning at New York University, called the new early warning system “very promising,” though it was “still experimental.”

“The machine learning methods presented in the paper are good, mature and well-researched,” said Barry, who was not involved in the research. But he warned that in a once-in-a-lifetime emergency such as a pandemic, it would be dangerous to rely too heavily on a new model to predict events.

For starters, Barry noted, the coronavirus’ first encounter with humanity didn’t yield the long historical record needed to fully test the model’s accuracy. And the three-year period of the pandemic gave researchers little time to recognize the “noise” that comes when too much data is thrown into a jar.

The centers for disease control and state health departments have begun to use epidemiological techniques such as phylodynamic gene sequencing And Wastewater monitoring To monitor the spread of the Corona virus. Using machine learning to predict the location of upcoming viral spikes, Santillana said, could take another leap of imagination for these agencies.

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In fact, accepting early warning tools like the one developed by Santillana’s group may require some leaps of faith, too. As computer programs digest large amounts of data and begin to discern patterns they can reveal, they often generate surprising “features” — variables or search terms that help predict an important event, such as a viral mutation.

Even if these visible signs prove to accurately predict such an event, their relevance to a public health emergency may not be immediately apparent. A sudden signal may be the first sign of a new trend – for example, a previously unseen symptom caused by a new variant. But they may also seem so random to public health officials that they cast doubt on the software’s ability to predict an imminent outbreak.

My review, said Santillana, who also teaches at the Harvard School of Public Health early work of his group She responded suspiciously to some of the signals that appeared as warning signs of an upcoming outbreak. Santayana said one of them — the tweets referring to “panic buying” — seemed like a false signal from machines that ran into a random event and imparted meaning to it.

He defended the inclusion of the “panic buying” signal as a signal of an imminent outbreak domestically. (After all, the early days of the pandemic were marked by lack of basic elements Including rice and toilet paper.) But he acknowledged that the “black box” early warning system could face resistance from public health officials who need to trust its forecasts.

“I think the concerns of decision makers are a legitimate concern,” Santayana said. “When we find a signal, it has to be reliable.”

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