A baby boy born over the weekend holds the new record for the “oldest baby.” Thaddeus Daniel Pierce, who arrived on July 26, developed from an embryo that had been in storage for 30 and a half years.

“We had a rough birth but we are both doing well now,” says Lindsey Pierce, his mother. “He is so chill. We are in awe that we have this precious baby!”

Lindsey and her husband, Tim Pierce, who live in London, Ohio, “adopted” the embryo from a woman who had it created in 1994. She says her family and church family think “it’s like something from a sci-fi movie.” 

“The baby has a 30-year-old sister,” she adds. Tim was a toddler when the embryos were first created.

“It’s been pretty surreal,” says Linda Archerd, 62, who donated the embryo. “It’s hard to even believe.”

Three little hopes

The story starts back in the early 1990s. Archerd had been trying—and failing—to get pregnant for six years. She and her husband decided to try IVF, a fairly new technology at the time. “People were [unfamiliar] with it,” says Archerd. “A lot of people were like, what are you doing?”

They did it anyway, and in May 1994, they managed to create four embryos. One of them was transferred to Linda’s uterus. It resulted in a healthy baby girl. “I was so blessed to have a baby,” Archerd says. The remaining three embryos were cryopreserved and kept in a storage tank.

That was 31 years ago. The healthy baby girl is now a 30-year-old woman who has her own 10-year-old daughter. But the other three embryos remained frozen in time.

Archerd originally planned to use the embryos herself. “I always wanted another baby desperately,” she says. “I called them my three little hopes.” Her then husband felt differently, she says. Archerd went on to divorce him, but she won custody of the embryos and kept them in storage, still hopeful she might use them one day, perhaps with another partner.

That meant paying annual storage fees, which increased over time and ended up costing Archerd around a thousand dollars a year, she says. To her, it was worth it. “I always thought it was the right thing to do,” she says. 

Things changed when she started going through menopause, she says. She considered her options. She didn’t want to discard the embryos or donate them for research. And she didn’t want to donate them to another family anonymously—she wanted to meet the parents and any resulting babies. “It’s my DNA; it came from me … and [it’s] my daughter’s sibling,” she says.

Then she found out about embryo “adoption.” This is a type of embryo donation in which both donors and recipients have a say in whom they “place” their embryos with or “adopt” them from. It is overseen by agencies—usually explicitly religious ones—that believe an embryo is morally equivalent to a born human. Archerd is Christian.

There are several agencies that offer these adoption services in the US, but not all of them accept embryos that have been stored for a very long time. That’s partly because those embryos will have been frozen and stored in unfamiliar, old-fashioned ways, and partly because old embryos are thought to be less likely to survive thawing and transfer to successfully develop into a baby.

“So many places wouldn’t even take my information,” says Archerd. Then she came across the Snowflakes program run by the Nightlight Christian Adoptions agency. The agency was willing to accept her embryos, but it needed Archerd’s medical records from the time the embryos had been created, as well as the embryos’ lab records.

So Archerd called the fertility doctor who had treated her decades before. “I still remembered his phone number by heart,” she says. That doctor, now in his 70s, is still practicing at a clinic in Oregon. He dug Archerd’s records out from his basement, she says. “Some of [them] were handwritten,” she adds. Her embryos entered Nightlight’s “matching pool” in 2022.

Making a match

“Our matching process is really driven by the preferences of the placing family,” says Beth Button, executive director of the Snowflakes program. Archerd’s preference was for a married Caucasian, Christian couple living in the US. “I didn’t want them to go out of the country,” says Archerd. “And being Christian is very important to me, because I am.”

It took a while to find a match. Most of the “adopting parents” signed up for the Snowflakes program were already registered at fertility clinics that wouldn’t have accepted the embryos, says Button. “I would say that over 90% of clinics in the US would not have accepted these embryos,” she says.

Expecting parents Tim and Lindsey Pierce.
Lindsey and Tim Pierce at Rejoice Fertility.
COURTESY LINDSEY PIERCE

Archerd’s embryos were assigned to the agency’s Open Hearts program for embryos that are “hard to place,” along with others that have been in storage for a long time or are otherwise thought to be less likely to result in a healthy birth.

Lindsey and Tim Pierce had also signed up for the Open Hearts program. The couple, aged 35 and 34, respectively, had been trying for a baby for seven years and had seen multiple doctors.

Lindsey was researching child adoption when she came across the Snowflakes program. 

When the couple were considering their criteria for embryos they might receive, they decided that they’d be open to any. “We checkmarked anything and everything,” says Tim. That’s how they ended up being matched with Archerd’s embryos. “We thought it was wild,” says Lindsey. “We didn’t know they froze embryos that long ago.”

Lindsey and Tim had registered with Rejoice Fertility, an IVF clinic in Knoxville, Tennessee, run by John Gordon, a reproductive endocrinologist who prides himself on his efforts to reduce the number of embryos in storage. The huge numbers of embryos left in storage tanks was weighing on his conscience, he says, so around six years ago, he set up Rejoice Fertility with the aim of doing things differently.  

“Now we’re here in the belt buckle of the Bible Belt,” says Gordon, who is Reformed Presbyterian. “I’ve changed my mode of practice.” IVF treatments performed at the clinic are designed to create as few excess embryos as possible. The clinic works with multiple embryo adoption agencies and will accept any embryo, no matter how long it has been in storage.

A portrait of Linda Archerd.
COURTESY LINDA ARCHERD

It was his clinic that treated the parents who previously held the record for the longest-stored embryo—in 2022, Rachel and Philip Ridgeway had twins from embryos created more than 30 years earlier. “They’re such a lovely couple,” says Gordon. When we spoke, he was making plans to meet the family for breakfast. The twins are “growing like weeds,” he says with a laugh.

“We have certain guiding principles, and they’re coming from our faith,” says Gordon, although he adds that he sees patients who hold alternative views. One of those principles is that “every embryo deserves a chance at life and that the only embryo that cannot result in a healthy baby is the embryo not given the opportunity to be transferred into a patient.”

That’s why his team will endeavor to transfer any embryo they receive, no matter the age or conditions. That can be challenging, especially when the embryos have been frozen or stored in unusual or outdated ways. “It’s scary for people who don’t know how to do it,” says Sarah Atkinson, lab supervisor and head embryologist at Rejoice Fertility. “You don’t want to kill someone’s embryos if you don’t know what you’re doing.”

Cumbersome and explosive

In the early days of IVF, embryos earmarked for storage were slow-frozen. This technique involves gradually lowering the temperature of the embryos. But because slow freezing can cause harmful ice crystals to form, clinics switched in the 2000s to a technique called vitrification, in which the embryos are placed in thin plastic tubes called straws and lowered into tanks of liquid nitrogen. This rapidly freezes the embryos and converts them into a glass-like state. 

The embryos can later be thawed by removing them from the tanks and rapidly—within two seconds—plunging them into warm “thaw media,” says Atkinson. Thawing slow-frozen embryos is more complicated. And the exact thawing method required varies, depending on how the embryos were preserved and what they were stored in. Some of the devices need to be opened while they are inside the storage tank, which can involve using forceps, diamond-bladed knives, and other tools in the liquid nitrogen, says Atkinson.

Sarah Atkinson, lab supervisor and head embryologist at Rejoice Fertility, directly injects sperm into two eggs to fertilize them.
COURTESY OF SARAH ATKINSON AT REJOICE FERTILITY.

Recently, she was tasked with retrieving embryos that had been stored inside a glass vial. The vial was made from blown glass and had been heat-sealed with the embryo inside. Atkinson had to use her diamond-bladed knife to snap open the seal inside the nitrogen tank. It was fiddly work, and when the device snapped, a small shard of glass flew out and hit Atkinson’s face. “Hit me on the cheek, cut my cheek, blood running down my face, and I’m like, Oh shit,” she says. Luckily, she had her safety goggles on. And the embryos survived, she adds.

The two embryos that were transferred to Lindsey Pierce.

Atkinson has a folder in her office with notes she’s collected on various devices over the years. She flicks through it over a video call and points to the notes she made about the glass vial. “Might explode; wear face shield and eye protection,” she reads. A few pages later, she points to another embryo-storage device. “You have to thaw this one in your fingers,” she tells me. “I don’t like it.”

The record-breaking embryos had been slow-frozen and stored in a plastic vial, says Atkinson. Thawing them was a cumbersome process. But all three embryos survived it.

The Pierces had to travel from their home in Ohio to the clinic in Tennessee five times over a two-week period. “It was like a five-hour drive,” says Lindsey. One of the three embryos stopped growing. The other two were transferred to Lindsey’s uterus on November 14, she says. And one developed into a fetus.

Now that the baby has arrived, Archerd is keen to meet him. “The first thing that I noticed when Lindsey sent me his pictures is how much he looks like my daughter when she was a baby,” she says. “I pulled out my baby book and compared them side by side, and there is no doubt that they are siblings.”

She doesn’t yet have plans to meet the baby, but doing so would be “a dream come true,” she says. “I wish that they didn’t live so far away from me … He is perfect!”

“We didn’t go into it thinking we would break any records,” says Lindsey. “We just wanted to have a baby.”

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OpenAI is launching Study Mode, a version of ChatGPT for college students that it promises will act less like a lookup tool and more like a friendly, always-available tutor. It’s part of a wider push by the company to get AI more embedded into classrooms when the new academic year starts in September.

A demonstration for reporters from OpenAI showed what happens when a student asks Study Mode about an academic subject like game theory. The chatbot begins by asking what the student wants to know and then attempts to build an exchange, where the pair work methodically toward the answer together. OpenAI says the tool was built after consulting with pedagogy experts from over 40 institutions.

A handful of college students who were part of OpenAI’s testing cohort—hailing from Princeton, Wharton, and the University of Minnesota—shared positive reviews of Study Mode, saying it did a good job of checking their understanding and adapting to their pace.

The learning approaches that OpenAI has programmed into Study Mode, which are based partially on Socratic methods, appear sound, says Christopher Harris, an educator in New York who has created a curriculum aimed at AI literacy. They might grant educators more confidence about allowing, or even encouraging, their students to use AI. “Professors will see this as working with them in support of learning as opposed to just being a way for students to cheat on assignments,” he says.

But there’s a more ambitious vision behind Study Mode. As demonstrated in OpenAI’s recent partnership with leading teachers’ unions, the company is currently trying to rebrand chatbots as tools for personalized learning rather than cheating. Part of this promise is that AI will act like the expensive human tutors that currently only the most well-off students’ families can typically afford.

“We can begin to close the gap between those with access to learning resources and high-quality education and those who have been historically left behind,” says OpenAI’s head of education. Leah Belsky.

But painting Study Mode as an education equalizer obfuscates one glaring problem. Underneath the hood, it is not a tool trained exclusively on academic textbooks and other approved materials—it’s more like the same old ChatGPT, tuned with a new conversation filter that simply governs how it responds to students, encouraging fewer answers and more explanations. 

This AI tutor, therefore, more resembles what you’d get if you hired a human tutor who has read every required textbook, but also every flawed explanation of the subject ever posted to Reddit, Tumblr, and the farthest reaches of the web. And because of the way AI works, you can’t expect it to distinguish right information from wrong. 

Professors encouraging their students to use it run the risk of it teaching them to approach problems in the wrong way—or worse, being taught material that is fabricated or entirely false. 

Given this limitation, I asked OpenAI if Study Mode is limited to particular subjects. The company said no—students will be able to use it to discuss anything they’d normally talk to ChatGPT about. 

It’s true that access to human tutors—which for certain subjects can cost upward of $200 an hour—is typically for the elite few. The notion that AI models can spread the benefits of tutoring to the masses holds an allure. Indeed, it is backed up by at least some early research that shows AI models can adapt to individual learning styles and backgrounds.

But this improvement comes with a hidden cost. Tools like Study Mode, at least for now, take a shortcut by using large language models’ humanlike conversational style without fixing their inherent flaws. 

OpenAI also acknowledges that this tool won’t prevent a student who’s frustrated and wants an answer from simply going back to normal ChatGPT. “If someone wants to subvert learning, and sort of get answers and take the easier route, that is possible,” Belsky says. 

However, one thing going for Study Mode, the students say, is that it’s simply more fun to study with a chatbot that’s always encouraging you along than to stare at a textbook on Bayesian theorem for the hundredth time. “It’s like the reward signal of like, oh, wait, I can learn this small thing,” says Maggie Wang, a student from Princeton who tested it. The tool is free for now, but Praja Tickoo, a student from Wharton, says it wouldn’t have to be for him to use it. “I think it’s absolutely something I would be willing to pay for,” he says.

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This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology.

This startup wants to use the Earth as a massive battery

Texas-based startup Quidnet Energy just completed a test showing it can store energy for up to six months by pumping water underground.

Using water to store electricity is hardly a new concept—pumped hydropower storage has been around for over a century. But the company hopes its twist on the technology could help bring cheap, long-duration energy storage to new places. Read the full story.

—Casey Crownhart

What you may have missed about Trump’s AI Action Plan

The executive orders and announcements coming from the White House since Donald Trump returned to office have painted an ambitious vision for America’s AI future, but the details have been sparse. 

The White House’s AI Action Plan, released last week, is meant to fix that. Trump wants to boost the buildout of data centers by slashing environmental rules; withhold funding from states that pass “burdensome AI regulations”; and contract only with AI companies whose models are “free from top-down ideological bias.”

But if you dig deeper, certain parts of the plan that didn’t pop up in any headlines reveal more about where the administration’s AI plans are headed. Here are three of the most important issues to watch.

—James O’Donnell

This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here.

The must-reads

I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology.

1 Democrats aren’t happy about Trump’s China chip U-turn
They’re worried about the security implications of approving exporting Nvidia chips. (WP $)
+ They claim the Trump administration is using export controls as a bargaining chip. (The Hill)
+ Meanwhile, both parties are planning new bills targeting China. (Reuters)

2 US tariffs are at their highest level since before WWII
Trump’s tariff wall appears likely to trigger a global reordering of trade. (FT $)
+ But who picks up the bill? (The Guardian)
+ Sweeping tariffs could threaten the US manufacturing rebound. (MIT Technology Review)

3 Utility companies want Big Tech to pay more for their data centers
Otherwise, rates may end up rising for regular customers. (WSJ $)
+ The data center boom in the desert. (MIT Technology Review)

4 Citizen science is on the rise across the US
Platform iNaturalist is playing a key role in helping to identify new species. (NYT $)
+ How nonprofits and academia are stepping up to salvage US climate programs. (MIT Technology Review)

5 Anthropic is cracking down on Claude power users
Some of its customers are running its AI coding tool 24/7. (TechCrunch)
+ That’s seriously bad news for the environment. (Engadget)
+ We did the math on AI’s energy footprint. Here’s the story you haven’t heard. (MIT Technology Review)

6 MAHA might resurrect psychedelic therapy
Last year, the FDA rejected MDMA therapy. Now, it might get thrown a lifeline. (Wired $)
+ People are using AI to ‘sit’ with them while they trip on psychedelics. (MIT Technology Review)

7 Waymo is launching its robotaxi service in Dallas
In a new partnership with car rental firm Avis, not Uber. (Reuters)
+ It’s expanding steadily, unlike its rival Tesla. (Forbes $)

8 How a promising young coder wound up at DOGE
Luke Farritor has assessed, slashed, and dismantled at least 10 departments. (Bloomberg $)
+ The foundations of America’s prosperity are being dismantled. (MIT Technology Review)

9 This Californian startup’s robot kills fish the Japanese way 🐟
The method is considered the most humane way to kill them. (Semafor)

10 AI is making online shopping hyper-personalized 🛍
By serving up results for searches like “revenge dress to wear to a party in Sicily.” (CNN)

Quote of the day

“Now I’ll click the ‘Verify you are human’ checkbox…this step is necessary to prove I’m not a bot.”

—OpenAI’s new ChatGPT Agent explains how it passes a common internet security checkpoint designed to catch bots just like it, Ars Technica reports.

One more thing

How gamification took over the world

It’s a thought that occurs to every video-game player at some point: What if the weird, hyper-focused state I enter when playing in virtual worlds could somehow be applied to the real one?

Often pondered during especially challenging or tedious tasks in meatspace (writing essays, say, or doing your taxes), it’s an eminently reasonable question to ask. Life, after all, is hard. And while video games are too, there’s something almost magical about the way they can promote sustained bouts of superhuman concentration and resolve.

For some, this phenomenon leads to an interest in flow states and immersion. For others, it’s simply a reason to play more games. For a handful of consultants, startup gurus, and game designers in the late 2000s, it became the key to unlocking our true human potential. But instead of liberating us, gamification turned out to be just another tool for coercion, distraction, and control. Read the full story.

—Bryan Gardiner

We can still have nice things

A place for comfort, fun and distraction to brighten up your day. (Got any ideas? Drop me a line or skeet ’em at me.)

+ USPS is taking votes from the public to bring back their favorite stamps (thanks Amy!)
+ Here’s how to make your morning toast that bit more interesting.
+ The long-awaited Madonna biopic is still happening, apparently.
+ Bad news for matcha fans—there’s a global shortage 🍵

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A number of the executive orders and announcements coming from the White House since Donald Trump returned to office have painted an ambitious vision for America’s AI future—crushing competition with China, abolishing “woke” AI models that suppress conservative speech, jump-starting power-hungry AI data centers. But the details have been sparse. 

The White House’s AI Action Plan, released last week, is meant to fix that. Many of the points in the plan won’t come as a surprise, and you’ve probably heard of the big ones by now. Trump wants to boost the buildout of data centers by slashing environmental rules; withhold funding from states that pass “burdensome AI regulations”; and contract only with AI companies whose models are “free from top-down ideological bias.”

But if you dig deeper, certain parts of the plan that didn’t pop up in any headlines reveal more about where the administration’s AI plans are headed. Here are three of the most important issues to watch. 

Trump is escalating his fight with the Federal Trade Commission

When Americans get scammed, they’re supposed to be helped by the Federal Trade Commission. As I wrote last week, the FTC under President Biden increasingly targeted AI companies that overhyped the accuracy of their systems, as well as deployments of AI it found to have harmed consumers. 

The Trump plan vows to take a fresh look at all the FTC actions under the previous administration as part of an effort to get rid of “onerous” regulation that it claims is hampering AI’s development. The administration may even attempt to repeal some of the FTC’s actions entirely. This would weaken a major AI watchdog agency, but it’s just the latest in the Trump administration’s escalating attacks on the FTC. Read more in my story

The White House is very optimistic about AI for science

The opening to the AI Action Plan describes a future where AI is doing everything from discovering new materials and drugs to “unraveling ancient scrolls once thought unreadable” to making breakthroughs in science and math

That type of unbounded optimism about AI for scientific discovery echoes what tech companies are promising. Some of that optimism is grounded in reality: AI’s role in predicting protein structures has indeed led to material scientific wins (and just last week, Google DeepMind released a new AI meant to help interpret ancient Latin engravings). But the idea that large language models—essentially very good text prediction machines—will act as scientists in their own right has less merit so far. 

Still, the plan shows that the Trump administration wants to award money to labs trying to make it a reality, even as it has worked to slash the funding the National Science Foundation makes available to human scientists, some of whom are now struggling to complete their research. 

And some of the steps the plan proposes are likely to be welcomed by researchers, like funding to build AI systems that are more transparent and interpretable.

The White House’s messaging on deepfakes is confused

Compared with President Biden’s executive orders on AI, the new action plan is mostly devoid of anything related to making AI safer. 

However, there’s a notable exception: a section in the plan that takes on the harms posed by deepfakes. In May, Trump signed legislation to protect people from nonconsensual sexually explicit deepfakes, a growing concern for celebrities and everyday people alike as generative video gets more advanced and cheaper to use. The law had bipartisan support.

Now, the White House says it’s concerned about the issues deepfakes could pose for the legal system. For example, it says, “fake evidence could be used to attempt to deny justice to both plaintiffs and defendants.” It calls for new standards for deepfake detection and asks the Department of Justice to create rules around it. Legal experts I’ve spoken with are more concerned with a different problem: Lawyers are adopting AI models that make errors such as citing cases that don’t exist, which judges may not catch. This is not addressed in the action plan. 

It’s also worth noting that just days before releasing a plan that targets “malicious deepfakes,” President Trump shared a fake AI-generated video of former president Barack Obama being arrested in the Oval Office.

Overall, the AI Action Plan affirms what President Trump and those in his orbit have long signaled: It’s the defining social and political weapon of our time. They believe that AI, if harnessed correctly, can help them win everything from culture wars to geopolitical conflicts. The right AI, they argue, will help defeat China. Government pressure on leading companies can force them to purge “woke” ideology from their models. 

The plan includes crowd-pleasers—like cracking down on deepfakes—but overall, it reflects how tech giants have cozied up to the Trump administration. The fact that it contains almost no provisions challenging their power shows how their investment in this relationship is paying off.

This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here.

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The Texas-based startup Quidnet Energy just completed a test showing it can store energy for up to six months by pumping water underground.

Using water to store electricity is hardly a new concept—pumped hydropower storage has been around for over a century. But the company hopes its twist on the technology could help bring cheap, long-duration energy storage to new places.

In traditional pumped hydro storage facilities, electric pumps move water uphill, into a natural or manmade body of water. Then, when electricity is needed, that water is released and flows downhill past a turbine, generating electricity. Quidnet’s approach instead pumps water down into impermeable rock formations and keeps it under pressure so it flows up when released. “It’s like pumped hydro, upside down,” says CEO Joe Zhou.

Quidnet started a six-month test of its technology in late 2024, pressurizing the system. In June, the company was able to discharge 35 megawatt-hours of energy from the well. There was virtually no self-discharge, meaning no energy loss, Zhou says.

Inexpensive forms of energy storage that can store electricity for weeks or months could help inconsistent electricity sources like wind and solar go further for the grid. And Quidnet’s approach, which uses commercially available equipment, could be deployed quickly and qualify for federal tax credits to help make it even cheaper.

However, there’s still a big milestone ahead: turning the pressurized water back into electricity. The company is currently building a facility with the turbines and support equipment to do that—all the components are available to purchase from established companies. “We don’t need to invent new things based on what we’ve already developed today,” Zhou says. “We can now start just deploying at very, very substantial scales.”

That process will come with energy losses. Energy storage systems are typically measured by their round-trip efficiency: how much of the electricity that’s put into the system is returned at the end as electricity. Modeling suggests that Quidnet’s technology could reach a maximum efficiency of about 65%, Zhou says, though some design choices made to optimize for economics will likely cause the system to land at roughly 50%.

That’s less efficient than lithium-ion batteries, but long-duration systems, if they’re cheap enough, can operate at low efficiencies and still be useful for the grid, says Paul Denholm, a senior research fellow at the National Renewable Energy Laboratory.

“It’s got to be cost-competitive; it all comes down to that,” Denholm says.

Lithium-ion batteries, the fastest-growing technology in energy storage, are the target that new forms of energy storage, like Quidnet’s, must chase. Lithium-ion batteries are about 90% cheaper today than they were 15 years ago. They’ve become a price-competitive alternative to building new natural-gas plants, Denholm says.

When it comes to competing with batteries, one potential differentiator for Quidnet could be government subsidies. While the Trump administration has clawed back funding for clean energy technologies, there’s still an energy storage tax credit, though recently passed legislation added new supply chain restrictions.

Starting in 2026, new energy storage facilities hoping to qualify for tax credits will need to prove that at least 55% of the value of a project’s materials are not from foreign entities of concern. That rules out sourcing batteries from China, which dominates battery production today. Quidnet has a “high level of domestic content” and expects to qualify for tax credits under the new rules, Zhou says.

The facility Quidnet is building is a project with utility partner CPS Energy, and it should come online in early 2026. 

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Advanced NotebookLM Use Cases You Can Apply Today by Social Media Examiner

Are you looking for ways to leverage AI that go beyond basic text generation? Wondering how to turn mountains of content and notes into actionable insights and marketing materials without spending countless hours reading and analyzing? Unlike ChatGPT or Claude, NotebookLM doesn’t pull from the internet. It pulls from your documents, your files, and your […]

The post Advanced NotebookLM Use Cases You Can Apply Today appeared first on Social Media Examiner.

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