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Dogecoin (DOGE) Cryptocurrency

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Dogecoin (DOGE) is a cryptocurrency that started as a joke but has grown into a serious digital currency with a significant following and market value. Created in December 2013 by software engineers Billy Markus and Jackson Palmer, Dogecoin is based on the popular “Doge” meme featuring a Shiba Inu dog.

History and Origins
Creation: Dogecoin was created to poke fun at the speculative nature of cryptocurrencies at the time. Markus and Palmer envisioned Dogecoin as a fun, light-hearted alternative to Bitcoin.
Launch: The coin was officially launched on December 6, 2013. The initial buzz around its launch was driven by the vibrant community on social media platforms like Reddit and Twitter.
Technology
Blockchain: Dogecoin operates on its own blockchain, similar to Bitcoin and other cryptocurrencies. It uses a public ledger to record transactions.
Algorithm: Dogecoin utilizes the Scrypt hashing algorithm, which is different from Bitcoin’s SHA-256. Scrypt allows for faster and more efficient mining but is less secure against certain types of attacks.
Mining: Dogecoin mining involves solving complex mathematical problems to validate transactions on the network. It initially had a block time of 1 minute, but this was later reduced to 60 seconds to improve transaction speed.
Inflationary Model: Unlike Bitcoin, which has a capped supply of 21 million coins, Dogecoin does not have a maximum supply. Approximately 5 billion Dogecoins are added to the circulating supply each year.
Economics
Market Capitalization: Dogecoin’s market cap has seen significant fluctuations over the years. It achieved a notable surge in 2021, largely due to high-profile endorsements and social media trends.
Supply: As mentioned, Dogecoin has an uncapped supply. This means it does not have a hard limit on the number of coins that can be mined. The current annual inflation rate is around 5 billion coins per year.
Price Volatility: Dogecoin has been highly volatile, experiencing dramatic price swings. This volatility is influenced by factors such as market sentiment, social media trends, and endorsements from public figures.
Community and Culture
Community: Dogecoin has one of the most active and enthusiastic communities in the cryptocurrency world. The Dogecoin community is known for its sense of humor and philanthropy.
Philanthropy: The community has organized several charitable events and fundraisers. Notable examples include raising funds to send the Jamaican bobsled team to the 2014 Winter Olympics and funding clean water projects in Kenya.
Meme Culture: Dogecoin’s identity is heavily tied to internet meme culture. The Shiba Inu “Doge” meme remains central to its brand and appeal.
Use Cases
Tipping: One of the most popular uses of Dogecoin is as a tipping currency on social media platforms. Users tip others as a reward for good content.
Charitable Donations: The Dogecoin community often engages in charitable donations and fundraisers, leveraging the currency for good causes.
Microtransactions: Dogecoin is well-suited for microtransactions due to its low transaction fees and fast processing times.
Development and Governance
Development Team: Dogecoin’s development has been relatively sporadic compared to other major cryptocurrencies. It does not have a formal development team or governance structure.
Forks and Updates: Dogecoin has undergone several updates and forks since its inception, though development activity has been less frequent in recent years.
Community-Driven Governance: Decisions about the future of Dogecoin are largely driven by the community. There is no formal governance model in place, making it more decentralized in terms of decision-making.
Challenges and Criticisms
Security Concerns: The use of the Scrypt algorithm makes Dogecoin less secure than Bitcoin. There have been concerns about the network’s vulnerability to 51% attacks.
Inflationary Supply: The uncapped supply of Dogecoin means it does not have a built-in scarcity mechanism, which can lead to long-term inflationary pressures.
Perception: Being originally conceived as a joke, Dogecoin struggles with the perception that it is not a serious investment. This can impact its adoption and long-term viability.
High-Profile Endorsements and Media Attention
Elon Musk: One of the most influential figures in Dogecoin’s rise to prominence is Elon Musk. The Tesla and SpaceX CEO frequently tweets about Dogecoin, driving significant market movements.
Media Coverage: Dogecoin has received extensive media coverage, particularly during its price surges. This coverage has both positive and negative effects on its public perception.
Future Prospects
Adoption: Dogecoin’s future largely depends on its adoption as a means of payment and its acceptance by merchants. Increased usage in real-world transactions could solidify its position.
Development: Continued development and improvements to its technology and security are essential for Dogecoin’s sustainability.
Regulatory Environment: Like all cryptocurrencies, Dogecoin’s future will be influenced by the regulatory landscape. Governments around the world are still developing their approaches to cryptocurrency regulation.
Conclusion
Dogecoin’s journey from a joke to a mainstream cryptocurrency is a testament to the power of community and the unpredictable nature of digital assets. While it faces significant challenges, its strong community and high-profile endorsements provide it with a unique position in the cryptocurrency landscape.

Detailed Analysis and Breakdown
1. Technical Specifications
Consensus Mechanism: Dogecoin uses a proof-of-work (PoW) consensus mechanism, similar to Bitcoin. However, its PoW algorithm is based on Scrypt, which makes it less resource-intensive and more accessible to miners with consumer-grade hardware.
Transaction Speed: Dogecoin transactions are confirmed approximately every minute, which is much faster than Bitcoin’s 10-minute confirmation time. This speed makes Dogecoin more practical for everyday transactions and tipping.
Block Reward: Initially, Dogecoin’s block reward was designed to be random, but it was later changed to a fixed reward of 10,000 DOGE per block. This fixed reward contributes to the inflationary nature of the currency.
2. Community and Culture
Reddit and Social Media: The Dogecoin community thrives on platforms like Reddit, Twitter, and Discord. Subreddits such as r/dogecoin are hubs for discussion, news, and community activities.
Philanthropic Efforts: Notable charitable endeavors include:
Doge4Water: A campaign that raised over $30,000 to build water wells in Kenya.
Nascar Sponsorship: Funding driver Josh Wise to participate in the 2014 Talladega race.
Charity Tipping: Encouraging the use of Dogecoin to tip for charitable causes online.
Meme Integration: The Doge meme, featuring phrases like “such wow” and “very crypto,” is integral to Dogecoin’s identity and marketing.
3. Economic Model
Inflationary Nature: Dogecoin’s inflationary supply model ensures that there will always be a steady supply of new coins. This is intended to maintain liquidity and prevent the hoarding behavior often seen with deflationary assets like Bitcoin.
Market Behavior: The price of Dogecoin has been highly reactive to social media trends and public endorsements, particularly from figures like Elon Musk. This has led to significant price volatility, with rapid price increases and sharp corrections.
Use in Transactions: Despite its volatility, Dogecoin is used for microtransactions and tipping due to its low fees and quick transaction times. Its use in charitable donations also highlights its utility beyond mere speculation.
4. Challenges and Criticisms
Security Vulnerabilities: Dogecoin’s reliance on the Scrypt algorithm and its relatively lower hash rate compared to more established cryptocurrencies make it susceptible to 51% attacks, where a single entity could potentially control the majority of the network’s mining power.
Development Stagnation: For several years, Dogecoin’s development was slow, with few updates or improvements. This has raised concerns about its long-term sustainability and ability to adapt to changing technological and regulatory landscapes.
Perception as a Joke: Despite its popularity, Dogecoin still faces skepticism due to its origins as a joke. This perception can hinder its acceptance by serious investors and institutional entities.
5. High-Profile Endorsements and Media Impact
Elon Musk’s Influence: Musk’s tweets about Dogecoin often result in significant price movements. His playful and sometimes cryptic comments have both boosted and destabilized the market, illustrating the power of celebrity influence in the cryptocurrency space.
SNL Appearance: Musk’s appearance on “Saturday Night Live” in May 2021 brought Dogecoin further into the mainstream spotlight. While the price saw a temporary spike leading up to the event, it also experienced a significant drop afterward.
Mainstream Media: Coverage by mainstream financial media has increased Dogecoin’s visibility but also subjected it to scrutiny. Articles range from praise for its community-driven initiatives to critiques of its speculative nature.
6. Future Prospects
Merchant Adoption: Increasing the number of merchants who accept Dogecoin as a form of payment is crucial for its growth. Efforts to integrate Dogecoin into payment systems and platforms are ongoing.
Technological Improvements: Enhancing the security and scalability of the Dogecoin network is necessary to ensure its long-term viability. Potential upgrades could include changes to the consensus algorithm or additional features to enhance functionality

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Did xAI lie about Grok 3’s benchmarks?

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Debates over AI benchmarks — and how they’re reported by AI labs — are spilling out into public view.

This week, an OpenAI employee accused Elon Musk’s AI company, xAI, of publishing misleading benchmark results for its latest AI model, Grok 3. One of the co-founders of xAI, Igor Babushkin, insisted that the company was in the right.

The truth lies somewhere in between.

In a post on xAI’s blog, the company published a graph showing Grok 3’s performance on AIME 2025, a collection of challenging math questions from a recent invitational mathematics exam. Some experts have questioned AIME’s validity as an AI benchmark. Nevertheless, AIME 2025 and older versions of the test are commonly used to probe a model’s math ability.

xAI’s graph showed two variants of Grok 3, Grok 3 Reasoning Beta and Grok 3 mini Reasoning, beating OpenAI’s best-performing available model, o3-mini-high, on AIME 2025. But OpenAI employees on X were quick to point out that xAI’s graph didn’t include o3-mini-high’s AIME 2025 score at “cons@64.”

What is cons@64, you might ask? Well, it’s short for “consensus@64,” and it basically gives a model 64 tries to answer each problem in a benchmark and takes the answers generated most frequently as the final answers. As you can imagine, cons@64 tends to boost models’ benchmark scores quite a bit, and omitting it from a graph might make it appear as though one model surpasses another when in reality, that’s isn’t the case.

Grok 3 Reasoning Beta and Grok 3 mini Reasoning’s scores for AIME 2025 at “@1” — meaning the first score the models got on the benchmark — fall below o3-mini-high’s score. Grok 3 Reasoning Beta also trails ever-so-slightly behind OpenAI’s o1 model set to “medium” computing. Yet xAI is advertising Grok 3 as the “world’s smartest AI.”

Babushkin argued on X that OpenAI has published similarly misleading benchmark charts in the past — albeit charts comparing the performance of its own models. A more neutral party in the debate put together a more “accurate” graph showing nearly every model’s performance at cons@64:

But as AI researcher Nathan Lambert pointed out in a post, perhaps the most important metric remains a mystery: the computational (and monetary) cost it took for each model to achieve its best score. That just goes to show how little most AI benchmarks communicate about models’ limitations — and their strengths.





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The pain of discontinued items, and the thrill of finding them online

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We’ve all been there. A favorite item is suddenly unavailable for purchase. Couldn’t the manufacturer have given you advance warning?

Whether owing to low sales, changing habits, production costs, or even because something is a little wrong with your favorite product (shh), discontinued items are part of life. In a weekend piece, the New York Times delves into the not-so-dark underbelly of online places where shoppers find these items, share tips and yes, find emotional support.

The story highlights a padded laptop bag made by Filson that a super fan now hunts “down everywhere” to snag as many as possible “before everyone figures out how great they are.” It points to Discontinued Beauty, a site whose offerings are old to visitors but new to the site. Among its latest products: an “essential protein restructurizer” by Redkin priced at an eye-popping $169.95. (The newest version of the product costs shoppers $32.)

Could it be dangerous to use these discontinued products? Who cares, suggests one creative director, who tells the Times about a lip pencil the beauty company NARS no longer sells and she has found elsewhere. “Now, do I know the proper way to store this for optimal conditions? No,” she says. “They’re under my sink.”  



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US AI Safety Institute could face big cuts

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The National Institute of Standards and Technology could fire as many as 500 staffers, according to multiple reports — cuts that further threaten a fledgling AI safety organization.

Axios reported this week that the US AI Safety Institute (AISI) and Chips for America, both part of NIST, would be “gutted” by layoffs targeting probationary employees (who are typically in their first year or two on the job). And Bloomberg said some of those employees had already been given verbal notice of upcoming terminations.

Even before the latest layoff reports, AISI’s future was looking uncertain. The institute, which is supposed to study risks and develop standards around AI development, was created last year as part of then-President Joe Biden’s executive order on AI safety. President Donald Trump repealed that order on his first day back in office, and AISI’s director departed earlier in February.

Fortune spoke to a number of AI safety and policy organizations who all criticized the reported layoffs.

“These cuts, if confirmed, would severely impact the government’s capacity to research and address critical AI safety concerns at a time when such expertise is more vital than ever,” said Jason Green-Lowe, executive director of the Center for AI Policy.



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