Dogecoin’s 38% surge reflects strong market demand, with spot-buyer volumes taking charge since March.
A bullish MACD crossover has traders predicting a 180% rally, with targets at $0.65 and $1.
Dogecoin’s (DOGE) price rallied in lockstep with Ethereum over the past 7 days, gaining 38% in May, which is its strongest monthly performance this year. According to CoinGecko, DOGE recorded $4.7 billion in trading volume over the past 24 hours, ranking fifth among the top cryptocurrencies (excluding stablecoins).
The memecoin’s market strength has been coupled with strong onchain insights. Data from CryptoQuant noted that DOGE’s spot taker 90-day cumulative volume delta (CVD), which measures the net difference between buying and selling volume over 90 days, has been “taker buyer dominant.” It indicates more aggressive buying than selling, a pattern last seen in November 2024, leading to DOGE’s breakout rally of 385% to $0.48 in Q4, 2024.
DOGE spot taker CVD. Source: CryptoQuant
Similarly, the long-term holder net unrealized profit/loss (NUPL), which tracks unrealized profits or losses for DOGE holders with a lifespan of at least 155 days, recently crossed 0.5 for the first time since March 1, 2025, turning to optimistic or “belief” sentiment. A NUPL above 0.5 means most holders are in profit, signaling confidence and a reduced likelihood of selling. This optimism reinforces price stability, as holders could refrain from selling and hold out for higher gains.
The above metrics suggest strong market demand, with investors actively accumulating Dogecoin, which likely contributed to its recent gains.
With a favorable market structure, anonymous technical analyst Trader Tardigrade revealed a bullish outlook involving the DOGE/BTC trading pair. The chart reflected a previous rally where DOGE surged 30,000% from $0.0024 to $0.739, suggesting a similar setup.
DOGE/BTC analysis by Trader Tardigrade. Source: X.com
Historically, Dogecoin and Bitcoin share a strong correlation—around 0.67 over the past three months, per Macroaxis data—meaning BTC’s movements often dictate DOGE’s trajectory. The analyst predicts BTC’s surge could be followed by a sideways phase, triggering a massive DOGE rally for weeks.
In a separate analysis, Trader Tardigrade also noted that the immediate target for Dogecoin remains $1, after the memecoin exhibited a weekly MACD bullish crossover for the third time since 2024. As illustrated in the chart, each bullish crossover has been followed by a breakout, with prices jumping 180% between January 2024 and March 2024, and a whopping 385% between September 2024 and December 2024.
Crypto trader Javon Marks outlined a similar target for Dogecoin, forecasting an immediate target of $0.65, which will be its highest price since May 2021. Marks said,
“$DOGE (Dogecoin) now showing MAJOR STRENGTH after setting Higher Lows! $0.6533 can be coming in another nearly +180% upside and prices could even break above, bringing $1+ into play.”
This article does not contain investment advice or recommendations. Every investment and trading move involves risk, and readers should conduct their own research when making a decision.
Update May 13, 12:33 am UTC: This article has been updated to include more information from Curve Finance.
Decentralized finance (DeFi) protocol Curve Finance has warned that a hacker has again hijacked its domain name system (DNS), sending users to a malicious website.
In the second attack on its infrastructure in a week, the “curve.fi DNS might be hijacked. Don’t interact!” the team said in a May 12 warning to X.
In a follow-up post to a user asking whether it was a hack or a hijack, the Curve Team said the website “Points to the wrong IP” when users try to visit. A DNS works like a directory that translates domain names into IP addresses.
The team also said in another update that the “Password is secure,” its two-factor authentication was set up a “long time ago,” and a question has been sent to the “registrar now.”
”While all smart contracts are safe, the domain name points to a malicious site which can drain your wallet! We are investigating and working on recovering the access. No sign of a compromise on our side,” Curve said.
Users who attempted to use the platform had their funds drained into a pool operated by the attackers.
Cointelegraph has contacted Curve Finance for comment.
Curve Finance potential front-end attack
Onchain security firm Blockaid also detected unusual activity from the Curve website recently, warning users to stay away and avoid interacting for now.
It could be a case of a “potential frontend attack,” according to the security firm, which is when hackers target the part of the website users interact with, such as the buttons, forms, or text on the site, to steal sensitive data.
“If you’re connected, please refrain from signing transactions and avoid interactions with the DApp until the issue is resolved. We’re working closely with affected partners. More updates soon,” Blockaid said.
“To clarify: the incident was limited strictly to the X account. No other Curve accounts were affected. No security issues were found on our side, no user funds were impacted, and there were no victims of phishing links that the hacker posted,” the team said in a follow-up May 6 post.
Aave, a decentralized finance (DeFi) protocol, has reached a new record of funds onchain, according to data from DefiLlama.
In an X post, Aave said it topped $40.3 billion in total value locked (TVL) on May 12. Onchain data reveals that Aave v3, the latest version of the protocol, has approximately $40 billion in TVL.
Aave is a DeFi lending protocol that lets users borrow cryptocurrency by depositing other types of cryptocurrency as collateral. Meanwhile, lenders earn yield from borrowers.
“With these milestones, Aave is proving its dominance in the Lending Space,” DeFi analyst Jonaso said in a May 12 X post. TVL represents the total value of cryptocurrency deposited into a protocol’s smart contracts.
Related: AAVE soars 13% as buyback proposal passes among tokenholders
Breaking all-time highs
In December, Aave achieved an all-time high TVL largely because the price of Ether (ETH) rose roughly 60% from the prior month. Ether and its staking derivatives make up nearly half of Aave’s TVL, according to data from DefiLlama.
This time around, Aave’s all-time high TVL is also driven by inflows of deposits by users.
In Ether-denominated terms, Aave’s TVL rose from around 6 million ETH at the start of 2025 to nearly 10 million ETH on May 12. Measuring TVL in ETH accounts for the impact of fluctuating cryptocurrency prices.
Aave says its net deposits broke $40 billion this week. Source: Aave
Before US President Donald Trump prevailed in the November election, Ether traded at less than $2,500. It peaked at almost $4,000 the following month, according to data from Google Finance.
In the past month, Ether has also clocked substantial gains, rising from around $1,500 per Ether 30 days ago to roughly $2,500 as of May 12, according to data from Google Finance.
The price of Aave’s native AAVE (AAVE) token has risen approximately 25% in the past seven days, reflecting a buoyant crypto market and ongoing TVL inflows, according to data from CoinMarketCap.
Hungry to learn more about Anthropic, directly from Anthropic? You aren’t alone if so, which is why we’re so delighted to announce that Anthropic co-founder and Chief Science Officer Jared Kaplan is joining the main stage at TechCrunch Sessions: AI on June 5 at UC Berkeley’s Zellerbach Hall. And TechCrunch Sessions: AI is right around […]
An analysis by Epoch AI, a nonprofit AI research institute, suggests the AI industry may not be able to eke massive performance gains out of reasoning AI models for much longer. As soon as within a year, progress from reasoning models could slow down, according to the report’s findings. Reasoning models such as OpenAI’s o3 […]
AllTrails, the hiking and biking companion that was named 2023’s iPhone App of the Year, is launching a new premium membership called “Peak” that includes an upgraded feature set. This $80-per-year subscription will introduce AI tools to build custom routes and provide real-time trail condition forecasts, trail traffic heatmaps, and a feature that lets you […]
Microsoft is hosting its annual Build developer conference next week from May 19 to 22. The event is guaranteed to include announcements regarding new AI integrations, services, and apps, including for Windows. At last year’s Build, Microsoft announced an integration of Copilot into Microsoft Teams, Copilot+ AI-powered PCs, Windows Volumetric Apps for Meta Quest headsets, […]
Federal safety investigators have sent Tesla a detailed list of questions on its upcoming robotaxi service as part of an investigation into how the company’s “Full Self-Driving (Supervised)” software operates in low-visibility conditions. The National Highway Traffic Safety Administration’s Office of Defects Investigation wants the additional information about Full Self-Driving (Supervised) — or “FSD” — […]
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.
How a new type of AI is helping police skirt facial recognition bans
Police and federal agencies have found a controversial new way to skirt the growing patchwork of laws that curb how they use facial recognition: an AI model that can track people based on attributes like body size, gender, hair color and style, clothing, and accessories.
The tool, called Track and built by the video analytics company Veritone, is used by 400 customers, including state and local police departments and universities all over the US. It is also expanding federally.
The product has drawn criticism from the American Civil Liberties Union, which—after learning of the tool through MIT Technology Review—said it was the first instance they’d seen of a nonbiometric tracking system used at scale in the US. Read the full story.
—James O’Donnell
If you’re interested in reading more about facial recognition and police tech, check out:
+ How the largest gathering of US police chiefs is talking about AI. Officers training in virtual reality, cities surveilled by webs of sensors, and AI-generated police reports are all a sign of what’s to come. Read the full story.
+ Clear, the company that has helped millions of people cut security lines, wants to give you a frictionless future—in exchange for your face. Read the full story.
+ Why the movement to limit face recognition tech might finally get a win. Read the full story.
+ Uber’s facial recognition is locking Indian drivers out of their accounts— and some people are finding their accounts permanently blocked. Read the full story.
The must-reads
I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology.
1 The US and China have struck a deal to slash tariffs For the next 90 days, at least. (Politico) + But America’s 30% tariffs are still extremely high. (FT $) + China has agreed to cut its levies from 125% to 10%. (CNN)
2 OpenAI is negotiating a future IPO with Microsoft While still preserving Microsoft’s access to the startup’s AI models. (FT $) + Meanwhile, Microsoft is constantly racing to stay ahead of hackers. (Bloomberg $)
3 DOGE cuts leave US workers at increasing risk of developing silicosis The lung disease is deadly—and preventable. (The Atlantic $) + Can AI help DOGE slash government budgets? It’s complex. (MIT Technology Review)
4 Scammers are posing as lawyers on TikTok to trick undocumented migrants Immigration scams have skyrocketed since Trump took office. (WP $) + An extensive sextortion network on TikTok is targeting American kids. (The Guardian) + AI-powered fraud is everywhere right now. (Wired $)
5 Weather balloons are being phased out in favor of AI tools Severe budget cuts mean that fewer balloon flights are being scheduled. (Semafor) + Trump’s tariffs will deliver a big blow to climate tech. (MIT Technology Review)
6 Amazon Web Service depends on this mysterious chip startup Annapurna, the company behind Amazon’s cloud success, is vital to its future. (WSJ $)
7 Inside the quest to create the perfect solid-state battery Massachusetts start-up Factorial wants to overhaul EVs’ image. (NYT $) + But tariffs are bad news for batteries. (MIT Technology Review)
8 A colossal data center in North Dakota is sitting empty It’s struggling to find a major tech customer to lease it. (The Information $) + China built hundreds of AI data centers to catch the AI boom. Now many stand unused. (MIT Technology Review)
9 Housewives make up Vietnam’s latest wave of gig workers They’re storing goods in their fridges while they’re at home to cut costs. (Rest of World)
10 Professional writers love Substack They’re using the medium to experiment with exciting new styles. (New Yorker $) + Niche newsletters are big business these days. (NYT $)
Quote of the day
“It feels a bit like a prisoner seeing their triple life sentence reduced to a single one.”
—Katja Bego, a senior research fellow at Chatham House, comments on the agreement between the US and China to cut tariffs from 145% to 30% in a post on Bluesky.
One more thing
The $100 billion bet that a postindustrial US city can reinvent itself as a high-tech hub
On a day in late April, a small drilling rig sits at the edge of the scrubby overgrown fields of Syracuse, New York, taking soil samples. It’s the first sign of construction on what could become the largest semiconductor manufacturing facility in the United States.
The CHIPS and Science Act was widely viewed by industry leaders and politicians as a way to secure supply chains, and make the United States competitive again in semiconductor chip manufacturing.
Now Syracuse is becoming an economic test of whether, over the next several decades, aggressive government policies—and the massive corporate investments they spur—can both boost the country’s manufacturing prowess and revitalize neglected parts of the country. Read the full story.
—David Rotman
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.)
+ Stuck on which PC game to play? This list of the 100 best is a great place to start. + Mari Salonen is the undisputed queen of pom poms. + I like the look of this Swedish princess cake. + Check out all the filming locations in the new Netflix show The Four Seasons—from Puerto Rico to Mount Peter.
Police and federal agencies have found a controversial new way to skirt the growing patchwork of laws that curb how they use facial recognition: an AI model that can track people using attributes like body size, gender, hair color and style, clothing, and accessories.
The tool, called Track and built by the video analytics company Veritone, is used by 400 customers, including state and local police departments and universities all over the US. It is also expanding federally: US attorneys at the Department of Justice began using Track for criminal investigations last August. Veritone’s broader suite of AI tools, which includes bona fide facial recognition, is also used by the Department of Homeland Security—which houses immigration agencies—and the Department of Defense, according to the company.
“The whole vision behind Track in the first place,” says Veritone CEO Ryan Steelberg, was “if we’re not allowed to track people’s faces, how do we assist in trying to potentially identify criminals or malicious behavior or activity?” In addition to tracking individuals where facial recognition isn’t legally allowed, Steelberg says, it allows for tracking when faces are obscured or not visible.
The product has drawn criticism from the American Civil Liberties Union, which—after learning of the tool through MIT Technology Review—said it was the first instance they’d seen of a nonbiometric tracking system used at scale in the US.They warned that it raises many of the same privacy concerns as facial recognition but also introduces new ones at a time when the Trump administration is pushing federal agencies to ramp up monitoring of protesters, immigrants, and students.
Veritone gave us a demonstration of Track in which it analyzed people in footage from different environments, ranging from the January 6 riots to subway stations. You can use it to find people by specifying body size, gender, hair color and style, shoes, clothing, and various accessories. The tool can then assemble timelines, tracking a person across different locations and video feeds. It can be accessed through Amazon and Microsoft cloud platforms.
VERITONE; MIT TECHNOLOGY REVIEW (CAPTIONS)
In an interview, Steelberg said that the number of attributes Track uses to identify people will continue to grow. When asked if Track differentiates on the basis of skin tone, a company spokesperson said it’s one of the attributes the algorithm uses to tell people apart but that the software does not currently allow users to search for people by skin color. Track currently operates only on recorded video, but Steelberg claims the company is less than a year from being able to run it on live video feeds.
Agencies using Track can add footage from police body cameras, drones, public videos on YouTube, or so-called citizen upload footage (from Ring cameras or cell phones, for example) in response to police requests.
“We like to call this our Jason Bourne app,” Steelberg says. He expects the technology to come under scrutiny in court cases but says, “I hope we’re exonerating people as much as we’re helping police find the bad guys.” The public sector currently accounts for only 6% of Veritone’s business (most of its clients are media and entertainment companies), but the company says that’s its fastest-growing market, with clients in places including California, Washington, Colorado, New Jersey, and Illinois.
That rapid expansion has started to cause alarm in certain quarters. Jay Stanley, a senior policy analyst at the ACLU, wrote in 2019 that artificial intelligence would someday expedite the tedious task of combing through surveillance footage, enabling automated analysis regardless of whether a crime has occurred. Since then, lots of police-tech companies have been building video analytics systems that can, for example, detect when a person enters a certain area. However, Stanley says, Track is the first product he’s seen make broad tracking of particular people technologically feasible at scale.
“This is a potentially authoritarian technology,” he says. “One that gives great powers to the police and the government that will make it easier for them, no doubt, to solve certain crimes, but will also make it easier for them to overuse this technology, and to potentially abuse it.”
Chances of such abusive surveillance, Stanley says, are particularly high right now in the federal agencies where Veritone has customers. The Department of Homeland Security said last month that it will monitor the social media activities of immigrants and use evidence it finds there to deny visas and green cards, and Immigrations and Customs Enforcement has detained activists following pro-Palestinian statements or appearances at protests.
In an interview, Jon Gacek, general manager of Veritone’s public-sector business, said that Track is a “culling tool” meant to speed up the task of identifying important parts of videos, not a general surveillance tool. Veritone did not specify which groups within the Department of Homeland Security or other federal agencies use Track. The Departments of Defense, Justice, and Homeland Security did not respond to requests for comment.
For police departments, the tool dramatically expands the amount of video that can be used in investigations. Whereas facial recognition requires footage in which faces are clearly visible, Track doesn’t have that limitation. Nathan Wessler, an attorney for the ACLU, says this means police might comb through videos they had no interest in before.
“It creates a categorically new scale and nature of privacy invasion and potential for abuse that was literally not possible any time before in human history,” Wessler says. “You’re now talking about not speeding up what a cop could do, but creating a capability that no cop ever had before.”
Track’s expansion comes as laws limiting the use of facial recognition have spread, sparked by wrongful arrests in which officers have been overly confident in the judgments of algorithms. Numerous studies have shown that such algorithms are less accurate with nonwhite faces. Laws in Montana and Maine sharply limit when police can use it—it’s not allowed in real time with live video—while San Francisco and Oakland, California have near-complete bans on facial recognition. Track provides an alternative.
Though such laws often reference “biometric data,” Wessler says this phrase is far from clearly defined. It generally refers to immutable characteristics like faces, gait and fingerprints rather than things that change, like clothing. But certain attributes, such as body size, blur this distinction.
Consider also, Wessler says, someone in winter who frequently wears the same boots, coat, and backpack. “Their profile is going to be the same day after day,” Wessler says. “The potential to track somebody over time based on how they’re moving across a whole bunch of different saved video feeds is pretty equivalent to face recognition.”
In other words, Track might provide a way of following someone that raises many of the same concerns as facial recognition, but isn’t subject to laws restricting use of facial recognition because it does not technically involve biometric data. Steelberg said there are several ongoing cases that include video evidence from Track, but that he couldn’t name the cases or comment further. So for now, it’s unclear whether it’s being adopted in jurisdictions where facial recognition is banned.
