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    Gold Maxi Changed His Mind About Crypto After Creating $420 Million Solana Meme Coin – Decrypt

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    Gold Maxi Changed His Mind About Crypto After Creating 0 Million Solana Meme Coin – Decrypt



    Ronald Branstetter sat in his basement, his wife and two kids upstairs, scratching his head at how a meme coin named Fartcoin (FARTCOIN) could skyrocket to a $500 million market cap—now $1.4 billion, as of this writing.

    He was more of a traditional investor, creating YouTube content about the ebbs and flows of the gold and silver markets, and this kind of volatility wasn’t something he was used to.

    For some time, Branstetter had been referring to cryptocurrency (as well as fiat currency) as “Unicorn Fart Dust,” as he felt it didn’t have any inherent value, mostly because you couldn’t touch or feel it—unlike the precious metals he favored.

    As such, he decided to create his own meme coin using Solana token launchpad Pump.fun. Little did he know that this innocuous token launch would completely transform his opinion on cryptocurrency.

    Branstetter, who operates the Rons Basement channel on YouTube, started a livestream on December 17 to tell his gold and silver community about the crazy crypto bubble he noticed. In this video, he explained how he created Unicorn Fart Dust (UFD) and laughed at how the seemingly worthless token could have a market cap of $7,000.

    But that valuation pales in comparison to what it is today. 

    A few hours after launching the token, Branstetter was at work when he started to receive tons of emails claiming the market cap of UFD was reaching the millions.

    “So, I checked it and I was like, ‘Oh my gosh, it’s real.’ I called my wife, Susie—she was decorating our Christmas tree—and said: You’re not going to believe this,” Branstetter told Decrypt in an episode of “What’s the Meta?”

    “She didn’t believe me,” he continued. “I didn’t believe it. The first night was a state of shock.”

    At this point, Branstetter sold half of the tokens that he bought with $100 at launch—profiting approximately $57,000. He now admits that he regrets this decision, as UFD then went parabolic. A month after the launch of his Solana meme coin, the token’s market cap surpassed $420 million; UFD was sitting under $20 million at the time of his sale.

    “I know right where I was standing on my dim porch, right outside, when I looked at my phone and I saw $1.2 million,” Branstetter told Decrypt. “Unicorn Fart Dust is my biggest single investment by far. I’m looking at $1.2 million, and I’m like, wow!”

    But still, Branstetter didn’t fully cash out once he saw life-changing money in his wallet. He told Decrypt that there was “something in [his] heart” that was preventing him from doing so. 

    In fact, he plans on never selling, and if he does ultimately plan to do so, he said he will communicate so beforehand to the community of investors. Branstetter hopes that there will be ways for him to monetize the experience further down the road, without the need to sell. He admits that it’s early in the game, however,  and is just trying to learn every day.

    Through this journey, Unicorn Fart Dust has transformed from a worthless gag into a wholesome community that has rallied behind Branstetter. Together, the group posts silly gags about unicorns and have adopted the mantra, “Good attracts good.”

    On Monday, Branstetter announced that he will be purchasing more UFD, scooping up $1,600 worth of the token. He admitted that experience has changed his stance on crypto as a whole.

    “What really makes gold valuable is that a lot of people agree that it’s valuable,” Branstetter told Decrypt. “When I look at Unicorn Fart Dust, what I consider to be the world’s best meme coin, it’s about the people. The value is created by the people, and then that eventually creates the price.”

    “My perspective on [crypto] completely changed when I realized that the real value proposition is in the community, is in the people,” he added.

    On top of this, the economic fundamentals of meme coins piqued his interest. By design, coins created via Pump.fun have a locked supply of tokens—which the UFD community calls beans. This, he believes, is a fundamental reason why the token’s price can increase.

    “I have a degree in accounting, I know numbers. When I learned that there were 999 million coins, period, finite, they can never make any more,” Branstetter explained, “I was like: You know, if we keep building the number of people that are buying these beans and holding on to them, that also creates value!”

    “It all boils back down to the community,” he finished.

    Edited by Andrew Hayward

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    Chinese Open-Source AI DeepSeek R1 Matches OpenAI’s o1 at 98% Lower Cost – Decrypt

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    Chinese Open-Source AI DeepSeek R1 Matches OpenAI’s o1 at 98% Lower Cost – Decrypt


    Chinese AI researchers have achieved what many thought was light years away: A free, open-source AI model that can match or exceed the performance of OpenAI’s most advanced reasoning systems. What makes this even more remarkable was how they did it: by letting the AI teach itself through trial and error, similar to how humans learn.

    “DeepSeek-R1-Zero, a model trained via large-scale reinforcement learning (RL) without supervised fine-tuning (SFT) as a preliminary step, demonstrates remarkable reasoning capabilities.” the research paper reads.

    “Reinforcement learning” is a method in which a model is rewarded for making good decisions and punished for making bad ones, without knowing which one is which. After a series of decisions, it learns to follow a path that was reinforced by those results.

    Initially, during the supervised fine-tuning phase, a group of humans tells the model the desired output they want, giving it context to know what’s good and what isn’t. This leads to the next phase, Reinforcement Learning, in which a model provides different outputs and humans rank the best ones. The process is repeated over and over until the model knows how to consistently provide satisfactory results.

    Image: Deepseek

    DeepSeek R1 is a steer in AI development because humans have a minimum part in the training. Unlike other models that are trained on vast amounts of supervised data, DeepSeek R1 learns primarily through mechanical reinforcement learning—essentially figuring things out by experimenting and getting feedback on what works.

    “Through RL, DeepSeek-R1-Zero naturally emerges with numerous powerful and interesting reasoning behaviors,” the researchers said in their paper. The model even developed sophisticated capabilities like self-verification and reflection without being explicitly programmed to do so.

    As the model went through its training process, it naturally learned to allocate more “thinking time” to complex problems and developed the ability to catch its own mistakes. The researchers highlighted an “a-ha moment” where the model learned to reevaluate its initial approaches to problems—something it wasn’t explicitly programmed to do.

    The performance numbers are impressive. On the AIME 2024 mathematics benchmark, DeepSeek R1 achieved a 79.8% success rate, surpassing OpenAI’s o1 reasoning model. On standardized coding tests, it demonstrated “expert level” performance, achieving a 2,029 Elo rating on Codeforces and outperforming 96.3% of human competitors.

    Image: Deepseek

    But what really sets DeepSeek R1 apart is its cost—or lack thereof. The model runs queries at just $0.14 per million tokens compared to OpenAI’s $7.50, making it 98% cheaper. And unlike proprietary models, DeepSeek R1’s code and training methods are completely open source under the MIT license, meaning anyone can grab the model, use it and modify it without restrictions.

    Image: Deepseek

    AI leaders react

    The release of DeepSeek R1 has triggered an avalanche of responses from AI industry leaders, with many highlighting the significance of a fully open-source model matching proprietary leaders in reasoning capabilities.

    Nvidia’s top researcher Dr. Jim Fan delivered perhaps the most pointed commentary, drawing a direct parallel to OpenAI’s original mission. “We are living in a timeline where a non-U.S. company is keeping the original mission of OpenAI alive—truly open frontier research that empowers all,” Fan noted, praising DeepSeek’s unprecedented transparency.

    Fan called out the significance of DeepSeek’s reinforcement learning approach: “They are perhaps the first [open source software] project that shows major sustained growth of [a reinforcement learning] flywheel. He also lauded DeepSeek’s straightforward sharing of “raw algorithms and matplotlib learning curves” versus the hype-driven announcements more common in the industry.

    Apple researcher Awni Hannun mentioned that people can run a quantized version of the model locally on their Macs.

    Traditionally, Apple devices have been weak at AI due to their lack of compatibility with Nvidia’s CUDA software, but that appears to be changing. For example, AI researcher Alex Cheema was capable of running the full model after harnessing the power of 8 Apple Mac Mini units running together—which is still cheaper than the servers required to run the most powerful AI models currently available.

    That said, users can run lighter versions of DeepSeek R1 on their Macs with good levels of accuracy and efficiency.

    However, the most interesting reactions came after pondering how close the open source industry is to the proprietary models, and the potential impact this development may have for OpenAI as the leader in the field of reasoning AI models.

    Stability AI’s founder Emad Mostaque took a provocative stance, suggesting the release puts pressure on better-funded competitors: “Can you imagine being a frontier lab that’s raised like a billion dollars and now you can’t release your latest model because it can’t beat DeepSeek?”

    Following the same reasoning but with a more serious argumentation, tech entrepreneur Arnaud Bertrand explained that the emergence of a competitive open source model may be potentially harmful to OpenAI, since that makes its models less attractive to power users who might otherwise be willing to spend a lot of money per task.

    “It’s essentially as if someone had released a mobile on par with the iPhone, but was selling it for $30 instead of $1000. It’s this dramatic.”

    Perplexity AI’s CEO Arvind Srinivas framed the release in terms of its market impact: “DeepSeek has largely replicated o1 mini and has open-sourced it.” In a follow-up observation, he noted the rapid pace of progress: “It’s kind of wild to see reasoning get commoditized this fast.”

    Srinivas said his team will work to bring DeepSeek R1’s reasoning capabilities to Perplexity Pro in the future.

    Quick hands-on

    We did a few quick tests to compare the model against OpenAI o1, starting with a well-known question for these kinds of benchmarks: “How many Rs are in the word Strawberry?”

    Typically, models struggle to provide the correct answer because they don’t work with words—they work with tokens, digital representations of concepts.

    GPT-4o failed, OpenAI o1 succeeded—and so did DeepSeek R1.

    However, o1 was very concise in the reasoning process, whereas DeepSeek applied a heavy reasoning output. Interestingly enough, DeepSeek’s answer felt more human. During the reasoning process, the model appeared to talk to itself, using slang and words that are uncommon on machines but more widely used by humans.

    For example, while reflecting on the number of Rs, the model said to itself, “Okay, let me figure (this) out.” It also used “Hmmm,” while debating, and even said things like “Wait, no. Wait, let’s break it down.”

    The model eventually reached the correct results, but spent a lot of time reasoning and spitting tokens. Under typical pricing conditions, this would be a disadvantage; but given the current state of things, it can output way more tokens than OpenAI o1 and still be competitive.

    Another test to see how good the models were at reasoning was to play “spies” and identify the perpetrators in a short story. We choose a sample from the BIG-bench dataset on Github. (The full story is available here and involves a school trip to a remote, snowy location, where students and teachers face a series of strange disappearances and the model must find out who was the stalker.)

    Both models thought about it for over one minute. However, ChatGPT crashed before solving the mystery:

    But DeepSeek gave the correct answer after “thinking” about it for 106 seconds. The thought process was correct, and the model was even capable of correcting itself after arriving at incorrect (but still logical enough) conclusions.

    The accessibility of smaller versions particularly impressed researchers. For context, a 1.5B model is so small, you could theoretically run it locally on a powerful smartphone. And even a quantized version of Deepseek R1 that small was able to stand face-to-face against GPT-4o and Claude 3.5 Sonnet, according to Hugging Face’s data scientist Vaibhav Srivastav.

    Just a week ago, UC Berkeley’s SkyNove released Sky T1, a reasoning model also capable of competing against OpenAI o1 preview.

    Those interested in running the model locally can download it from Github or Huggingf Face. Users can download it, run it, remove the censorship, or adapt it to different areas of expertise by fine-tuning it.

    Or if you want to try the model online, go to Hugging Chat or DeepSeek’s Web Portal, which is a good alternative to ChatGPT—especially since it’s free, open source, and the only AI chatbot interface with a model built for reasoning besides ChatGPT.

    Edited by Andrew Hayward

    Generally Intelligent Newsletter

    A weekly AI journey narrated by Gen, a generative AI model.





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    This Week in Bitcoin: New High Price, Multi-Million Dollar Projections, and Trump Frees Ross Ulbricht – Decrypt

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    This Week in Bitcoin: New High Price, Multi-Million Dollar Projections, and Trump Frees Ross Ulbricht – Decrypt



    Bitcoin is again hovering around $105,000 per coin, barely budging since this time last week. Investors shouldn’t complain, though, after an action-packed start to the week led the coin to hit a new high.

    The price of the biggest coin by market cap broke a new record of $108,786 Monday ahead of Donald Trump’s inauguration. It has since dropped by nearly 4%, CoinGecko shows.

    And despite President Trump not explicitly declaring plans for a Bitcoin strategic reserve in his first crypto executive order, the coin is still sitting comfortably above the $100,000 mark.

    Bitcoin soared above $100,000 following Trump’s November election; the President promised to slash regulation and help the digital asset industry. And he is keeping his crypto promises—albeit while annoying some hardcore Bitcoiners in the process.

    ETF movements

    Money continued to flow into the crypto investment vehicles this week, after investors threw billions at the funds last week ahead of the inauguration.

    But it didn’t stop, with $802.6 million hitting the funds on Tuesday alone, data from Farside Investors shows. By the end of the week, over $1.75 billion worth of assets had entered the Bitcoin ETFs.

    The bullishness comes as Donald Trump is expected to be a net positive for the industry. The Republican campaigned on a promise to help the industry and now buying Bitcoin has never been easier thanks to the funds.

    Ross freed

    Bitcoiners had been waiting for it for years. And on Tuesday, President Donald Trump kept his campaign promise to pardon Silk Road founder Ross Ulbricht.

    The Bitcoin enthusiast and founder of the dark web e-commerce site—mainly used for buying drugs using Bitcoin—was released shortly after and expressed enormous gratitude to President Trump. The crypto community flooded his digital wallets with BTC donations, too.

    But Ulbricht—who went to prison in 2013—might already just be sitting on a goldmine: Untouched Bitcoin wallets linked to Ross Ulbricht and Silk Road now hold over $47 million worth of the asset.

    Ulbricht has long been considered a hero in the Bitcoin community for creating one of the first marketplaces to accept the cryptocurrency. And though it still can’t be verified that the wallets do indeed belong to him, it’s not beyond the realm of possibility.

    Where’s Bitcoin?

    Ahead of Donald Trump’s shock November 5 win, the President had promised plans for a Bitcoin strategic reserve. But after signing his first crypto executive order on Thursday, which touched on the possibility of a crypto stockpile, Bitcoiners noticed one thing—there was no mention of their beloved orange coin, just “digital assets.”

    “The Working Group shall evaluate the potential creation and maintenance of a national digital asset stockpile and propose criteria for establishing such a stockpile, potentially derived from cryptocurrencies lawfully seized by the Federal Government through its law enforcement efforts,” the order read.

    The news has angered ardent Bitcoiners, who have been hurling the usual insults about “shitcoinery,” and who think it may lead the government to building up a stash of other digital coins.

    MicroStrategy moves

    Software company MicroStrategy shareholders are seemingly all-in on the firm’s Bitcoin strategy: They on Tuesday voted for a 30x increase to the number of authorized Class A common shares so that the company could have more resources to buy the cryptocurrency.

    The news came as the company announced its latest Bitcoin buy, bringing its holdings to 461,000 Bitcoin—worth over $48 billion. And on Friday, the firm said that it would redeem over $1 billion worth of its existing debt accumulated early while building up the stash.

    Soaring projections

    Elsewhere, British multinational bank Standard Chartered, which has come out with very bullish predictions in the past, said in a Wednesday note that Bitcoin would continue to soar as pension funds enter the space.

    Analysts at the bank forecasted that institutions enthusiasm for the asset could mean the coin hits $200,000 by the end of 2025.

    But there were even bigger price predictions for Bitcoin from major players this week. BlackRock CEO Larry Fink said that growing adoption could push the price of the asset to $700,000, while Coinbase founder and CEO Brian Armstrong projected a price in the “multiple millions” at some undetermined point in the future.

    Edited by Andrew Hayward

    Daily Debrief Newsletter

    Start every day with the top news stories right now, plus original features, a podcast, videos and more.





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    The NVIDIA of Web3: Why $SPON Could Be the Next Crypto to Watch

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    The NVIDIA of Web3: Why $SPON Could Be the Next Crypto to Watch


    We are on the cusp of a new paradigm where artificial intelligence (AI) fuses with blockchain technology to reshape everything from finance to supply chains and beyond. Over the past decade, the crypto landscape has witnessed several waves of innovation—starting with Bitcoin’s digital gold narrative, then Ethereum’s smart contracts, DeFi (Decentralized Finance), NFTs, and now, the meteoric rise of AI-driven blockchain applications (often called DeAI or DeFAI). Amid this transformative whirlwind, infrastructure remains one of the most critical—and often most overlooked—layers of growth and value capture.

    When we talk about “infrastructure” in the context of tech booms, we’re referring to the foundational elements that make everything else possible. In the blockchain world, this can mean nodes, validators, decentralized storage, and importantly, decentralized compute. As AI gains prominence, the demand for powerful, reliable compute resources soars. The quest for permissionless, always-available computing has created a unique intersection: the world needs an “NVIDIA-like” player but for decentralized AI and Web3.

    That’s where Spheron and its native token $SPON enter the picture. In many ways, Spheron is going to be the “NVIDIA of Web3”—the essential layer that supplies the computational horsepower and resilient environment for autonomous AI agents, DeFi protocols, and decentralized applications (dApps) that require more than just a simple Ethereum smart contract. But why is that so compelling, and how exactly does $SPON fit into this picture? More importantly, can $SPON replicate NVIDIA’s success story in crypto?

    This article aims to offer a deep, nuanced look at why $SPON could be the next big crypto asset to watch, especially for those who believe in the unstoppable merging of AI and blockchain. By weaving together historical parallels, market analysis, and future projections, we’ll see why so many eyes are turning toward Spheron and its token.

    Lessons from History: Selling Shovels in a Gold Rush

    The famous California Gold Rush of 1848–1855 taught us a timeless lesson about value capture. While thousands of hopefuls flocked to California to strike gold, very few emerged fabulously wealthy by mining. Instead, it was the merchants—those selling shovels, picks, and other essential tools—who reaped the lion’s share of the profits. Levi Strauss sold durable pants, and Samuel Brannan sold picks and shovels, each generating fortunes. The people who controlled the fundamental resources, not the risk-laden end products, became the true winners of that era.

    We see the same pattern repeating in the technology world. During the internet boom, companies like Cisco (building networking routers) and Intel (manufacturing processors) captured immense value while many “dot-com” brands faded from relevance. With the cloud revolution, Amazon Web Services (AWS) and Microsoft Azure ended up dwarfing most consumer-facing startups in market cap. In today’s AI race, NVIDIA has emerged as the uncontested champion, providing the GPUs necessary to power complex machine-learning tasks.

    The synergy is clear: whoever provides the critical infrastructure reaps the most dependable rewards. Spheron, with its decentralized compute infrastructure, is aiming to do precisely this in the Web3 realm, and $SPON is the “shovel” powering that entire ecosystem.

    NVIDIA’s Dominance and What It Teaches Us About Value Accrual

    NVIDIA did not become the world’s leading AI computing company overnight. Initially recognized for its innovations in graphics processing units (GPUs) for gaming, the company quickly spotted an emerging niche: scientific computing and AI training. NVIDIA’s GPUs turned out to be perfectly suited for parallelizing machine learning workloads, especially for training deep neural networks.

    Fast-forward to today:

    AI Growth: Large Language Models (LLMs) such as GPT-4 rely heavily on GPU-accelerated computing.

    Near Monopoly: NVIDIA enjoys a staggering market share in AI training, often quoted at around 95%.

    Value Capture: Thanks to this strategic position, NVIDIA’s valuation soared, with share prices reflecting the massive demand for AI compute.

    The moral of the story? Once you secure the foundational layer, every application built on top of it becomes your customer. As AI continues its unstoppable ascent, NVIDIA’s relevance and revenue grow exponentially. The question then becomes: Is there an analogous opportunity in Web3?

    Yes, and that’s precisely where Spheron is poised to shine. AI and Web3 are converging in a space that demands massive, efficient, and decentralized compute resources. If Spheron can establish itself as the backbone for autonomous AI agents and advanced DeFi protocols, its native token, $SPON, might be set for exponential growth—mirroring NVIDIA’s trajectory in the AI sector.

    The Rise of AI Agents in Blockchain

    One of the most exciting developments in blockchain and AI is the emergence of autonomous AI agents. Imagine software programs or smart contracts powered by advanced models that can:

    Make autonomous financial decisions (DeFi strategies, liquidity provisioning, yield optimization)

    Monitor on-chain data 24/7 for opportunities

    Execute trades in milliseconds based on real-time insights

    Maintain multi-chain presence in an increasingly cross-chain DeFi ecosystem

    These agents are already making headlines. Some experts predict that by 2025 or 2026, up to 90–99% of on-chain transactions could be executed by AI agents rather than by humans. The logic behind these forecasts is simple: AI doesn’t sleep, and markets don’t either.

    Yet, all these AI agents need compute power—and not just any compute power. They require permissionless, easily scalable, and cost-effective GPU or CPU resources. Relying on centralized cloud services like AWS or Google Cloud introduces the same vulnerabilities and choke points that blockchains are designed to eliminate (e.g., KYC restrictions, single points of failure, centralized intervention). That’s why a decentralized solution is vital.

    Enter Spheron: a decentralized network capable of providing both CPU and GPU resources to these agents on demand, without the friction of KYC or the centralized gating that traditional cloud providers impose. The potential for growth is massive, and naturally, $SPON—the network’s native token—stands to benefit as more AI agents flock to Spheron for compute.

    Spheron: The Decentralized Compute Backbone

    At its core, Spheron is building a permissionless network of compute providers that can be accessed directly via smart contracts. This network includes:

    Decentralized CPU and GPU Resources: Anyone with spare compute capacity can join and offer resources, earning FN Points as of now as a reward. AI agents and developers can lease compute power autonomously, paying in $SPON through trustless, on-chain transactions.

    Smart Contract-Based Leasing: Instead of relying on Web2-style APIs, AI agents (or developers) directly interact with Spheron’s on-chain protocols. This design eliminates the need for API keys, removing a major roadblock for truly autonomous AI systems.

    Scalability and Cost Arbitrage: By tapping into underutilized compute resources from individuals around the world, Spheron can offer more competitive pricing than a single centralized provider. As more users and AI agents join, the network’s capacity expands organically.

    Full-Stack Approach: Spheron is not just about raw CPU or GPU power. It also focuses on frameworks, developer tools, and user-friendly interfaces (SDKs, CLI, console, etc.) to make deployment seamless. The network’s composability allows multiple “agent frameworks” to flourish on top of it, each with different specializations (DeFi automation, NFT analytics, cross-chain bridging, etc.).

    In this model, $SPON becomes essential for every aspect of the ecosystem:

    Payment: Agents must acquire $SPON to lease compute resources.

    Staking: Compute providers stake $SPON to assure reliability and service quality, thereby reducing spam.

    Governance: Token holders may gain influence over the network’s parameters, from fee structures to resource allocation strategies.

    This multi-faceted utility aligns perfectly with classic value accrual mechanisms we’ve seen in successful projects. In short, as demand for decentralized compute rises—particularly from AI agents—$SPON demand should, in theory, see a corresponding surge.

    Understanding $SPON: Token Utility and Value Proposition

    Let’s break down the $SPON token’s role in more detail.

    Compute Payments: Every time an AI agent or developer needs to spin up a node, run an inference, or train a small-scale model, they will pay for it in $SPON. This ongoing demand creates a consistent token sink, as $SPON is spent to procure resources.

    Provider Staking: Compute providers are required to stake $SPON to join the network and maintain a certain level of service. Higher stakes can unlock better tiers, potentially leading to more revenue and more responsibilities (like specialized GPU tasks). This mechanism not only secures the network but also locks up tokens, reducing the circulating supply.

    Buy-Back and Build (BB&B): Some protocols implement a portion of fees for token buy-backs or distribution to holders. If Spheron follows a similar blueprint, it could introduce a deflationary element to $SPON.

    Governance: As Spheron expands, token holders may participate in deciding critical parameters, such as consensus rules, network expansions, or protocol upgrades. This incentivizes stakeholder alignment and helps maintain a stable, community-driven ecosystem.

    Ecosystem Partnerships: Spheron has already established partnerships with numerous agent platforms and infrastructure protocols. Each collaboration potentially drives more usage of $SPON for resource provisioning.

    Value Proposition: By tying the token’s demand directly to resource consumption, $SPON’s fortunes scale with real-world usage. This stands in contrast to purely speculative tokens that rely on hype alone. If AI-driven DeFi (DeFAI) and other advanced dApps indeed become ubiquitous, $SPON could see demand reminiscent of how GPU orders catapulted NVIDIA’s stock price.

    Current State of $SPON and the Broader AI+Web3 Market

    At the time of this writing, $SPON is still in its early growth phase relative to the broader crypto market, which is dominated by larger-cap assets like Bitcoin, Ethereum, and a handful of established DeFi tokens. However, the mindshare around DeFAI (DeFi + AI) is growing incredibly fast, with some data suggesting it’s already catching up to the mindshare of meme coins—yet the actual market caps remain small in comparison.

    Meanwhile, AI continues to see exponential uptake. Large enterprises are investing billions into AI R&D, while open-source communities work tirelessly to reduce the entry barriers. As more AI practitioners realize the need for on-demand, permissionless GPU resources that can’t be throttled or shut off by a single provider, decentralized options like Spheron gain traction.

    Projects building AI-based autonomous agents also see the writing on the wall. Many are forging partnerships or actively integrating with Spheron so that their AI can continue running 24/7, paying for its own resources via smart contracts—a core piece of the puzzle for true agent autonomy.

    In short, the stage is set:

    Rising adoption of AI in blockchain (DeFAI, AI Agents)

    Growing dissatisfaction with centralized choke points

    A unique, underexposed infrastructure token ($SPON) that could capture large segments of this demand

    Future Predictions: How $SPON Could Transform the Crypto Landscape

    Let’s outline some forward-looking scenarios:

    Mainstream AI Agent Adoption: The demand for decentralized compute would skyrocket if industry predictions that “AI agents will drive 90% of on-chain transactions by 2025–2026” come true. Spheron, with a proven track record, could become the de facto compute platform for these agents, creating near-constant demand for $SPON.

    Expansion into Enterprise and Research: Beyond on-chain AI agents, organizations might look to Spheron for secure, censorship-resistant compute for sensitive research and data processing. This expansion could help stabilize compute demand and diversify the user base beyond purely crypto-focused AI.

    Ecosystem Flywheel Effect: Each new AI project building on Spheron can attract more token holders and compute providers, increasing network capacity and reliability. As the network becomes more robust, it draws in even more advanced use cases, reinforcing a positive feedback loop that boosts $SPON’s utility and price.

    If these future predictions unfold, $SPON’s market cap—currently modest compared to heavyweights—could expand drastically, potentially placing it alongside the leading infrastructure tokens in the industry. This is what fuels the narrative of “The NVIDIA of Web3.”

    Conclusion: Positioning $SPON as the ‘NVIDIA of Web3’

    The world of technology thrives on parallels. Just as NVIDIA emerged as the backbone for AI workloads in traditional markets, a similar story may be unfolding in the Web3 space with Spheron. The demand for decentralized compute is set to rise as AI agents become more prevalent, DeFi becomes increasingly sophisticated, and developers yearn for trustless, scalable alternatives to centralized cloud services.

    In this landscape, $SPON holds the promise of becoming an indispensable utility token, powering the “infinite compute engine” for the next generation of AI-driven dApps and autonomous blockchain-based agents. Much like how NVIDIA’s GPUs became the go-to hardware for all AI, Spheron’s decentralized infrastructure could become the de facto standard for AI compute in Web3.

    Is $SPON the next crypto to watch? Many analysts and early adopters can argue it indeed could be. If you believe in the fusion of AI and Web3, in the unstoppable rise of autonomous agents, and in the historical lesson that infrastructure always captures the most sustainable value, then it might be time to take a closer look at Spheron—and by extension, its native token, $SPON.

    Disclaimer: This article is for informational purposes only and should not be considered financial or investment advice. Always conduct your own research and consult with professional advisors before making any investment decisions.



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    Elon Musk’s DOGE Exploring Blockchain for Government Efficiency: Bloomberg – Decrypt

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    Elon Musk’s DOGE Exploring Blockchain for Government Efficiency: Bloomberg – Decrypt



    The Department of Government Efficiency, the cost-cutting initiative led by billionaire Elon Musk, is reportedly considering the use of a public blockchain to bring transparency and other potential benefits to government operations and spending.

    That’s according to Bloomberg, which reported Saturday that Musk’s DOGE agency is holding conversations with representatives from multiple existing public blockchains, according to sources close to the conversations.

    No specific chains are mentioned in the report, though Bloomberg reports that DOGE is keen on using a blockchain—an immutable, public ledger—to monitor government spending and handle payments, handle data, and perhaps even “manage buildings” under the U.S. government’s purview.

    DOGE—which appears to share its acronym with the ticker of Musk’s favorite cryptocurrency, Dogecoin—was discussed on President Donald Trump’s campaign trail and then made official following his November election win. Musk was supposed to co-run the effort with Vivek Ramaswamy, but the latter billionaire and Bitcoin fan departed this week for an apparent run at Ohio governor.

    Musk has said that DOGE aims to cut $2 trillion from the federal government via a combination of budget cuts and layoffs, though he has since backtracked and said that $1 trillion is more likely.

    This week, Senator Elizabeth Warren wrote in a letter to Musk that DOGE appears to be a “venue for corruption,” and suggested $2 trillion worth of spending cuts that wouldn’t impact essential programs or raise taxes for middle-class Americans.

    Musk is an avowed fan of Dogecoin, while Trump has launched NFTs across Ethereum scaling network Polygon as well as Bitcoin, and debuted his official meme coin on Solana last week. However, there’s no word yet on which chain or chains might be used in the potential DOGE blockchain initiative.

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    Another Publicly Traded Firm Has Started Stockpiling Bitcoin – Decrypt

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    Another Publicly Traded Firm Has Started Stockpiling Bitcoin – Decrypt



    Another Nasdaq-listed company is adopting the increasingly fashionable Bitcoin standard. 

    Real estate tech company Fathom Holdings (NASDAQ: FTHM) announced Thursday that it will allocate up to half of its excess cash reserves to the orange coin after the firm’s board approved the move. 

    And further down the line, the company hopes to accept Bitcoin from customers for purchases. It added that it would start buying Bitcoin—and perhaps via Bitcoin exchange-traded funds, or ETFs—in the next two weeks. 

    Fathom CFO Joanne Zach said: “The integration of Bitcoin into commercial and financial strategies has accelerated across financial markets, positioning it as both a hedge against inflation and a safeguard against economic and currency risks in the global economy.”

    Fathom is a real estate firm that also dabbles in cloud computing services. 

    It isn’t the first company to put Bitcoin on its balance sheet—over the past year, many small Nasdaq-listed companies have started following in the footsteps of software firm MicroStrategy.

    MicroStrategy first bought Bitcoin in 2020, and now holds over $47 billion worth, making it the largest corporate treasury holder of the asset. The firm has been urging companies to follow in its footsteps as its market cap has grown exponentially. 

    The company’s shares have exploded in value and MicroStrategy last year became a Nasdaq-100 firm, joining the top 100 non-financial companies on the Nasdaq stock market. 

    Now the price of Bitcoin has hit new highs, and buying the asset has never been easier via the new ETFs, other companies are following suit. 

    Health care companies Semler Scientific and Cosmos Health, as well as auto firm Worksport, are some of the firms that have bought the asset as an inflation hedge.

    Fathom’s stock rose about 5% from the close of trading Wednesday—ahead of the announcement—to Friday’s close, at a price of $1.39.

    Edited by Andrew Hayward

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    Congress Begins Investigating Crypto Debanking and Operation Choke Point 2.0 – Decrypt

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    Congress Begins Investigating Crypto Debanking and Operation Choke Point 2.0 – Decrypt



    The U.S. House of Representatives is officially investigating whether leading crypto firms were secretly “debanked” during the Biden administration. 

    On Friday, Rep. James Comer (R-KY), chair of the House Oversight Committee, informed numerous industry founders and lobbyists that the inquiry is already underway.

    “The Committee… is investigating improper debanking of individuals and entities based on political viewpoints or involvement in certain industries such as cryptocurrency and blockchain,” Comer wrote, in a letter sent to Andreessen Horowitz co-founder Marc Andreessen, Coinbase CEO Brian Armstrong, and Uniswap founder Hayden Adams, among others.

    For years, top crypto executives have claimed that former President Joe Biden’s administration pressured U.S. banks to deny them services, as a means to strangle the industry’s ability to function. 

    Though numerous Biden officials—including former SEC head Gary Gensler—denied any involvement in such a plot, dubbed “Operation Choke Point 2.0,” recently disclosed correspondences between the FDIC and member banks do appear to show a coordinated push to freeze the adoption of crypto in America’s banking system. 

    In November, Andreessen claimed during an appearance on Joe Rogan’s podcast to have direct knowledge of over 30 tech founders, many of whom work in crypto, who suddenly lost access to banking services during Biden’s time in office.

    Friday’s letter explicitly mentioned that interview, asking Andreessen—and others with similar knowledge—to come forward with specific details about this alleged debanking.

    The letter also ties the perceived economic persecution of crypto leaders to that of Trump family members, including Melania Trump. In her recent autobiography, which is quoted in today’s correspondence, the First Lady claimed that both she and her son, Barron, were also debanked during the Biden years.

    “These examples are startling, and the Committee is investigating whether this debanking practice originates from the financial institutions themselves or from either implicit or explicit pressure from government regulators,” Chair Comer wrote. 

    Crypto leaders already appear excited to cooperate with the investigation. 

    “Lawful crypto organizations and individuals need bank accounts to pay rent, pay taxes, and pay employees—denying them these basic financial services is wrong and should never happen in the United States of America,” Kristin Smith, CEO of the Blockchain Association, a crypto lobbying group, said in a statement shared with Decrypt. “We’re eager to get to the bottom of this and end this unlawful practice once and for all.”

    Donald Trump’s return to the White House this week has already brought about a seismic shift in the federal government’s approach to crypto.

    On Thursday, the president signed a sweeping crypto executive order that may soon pave the way for a strategic government crypto reserve. Hours later, the newly Republican-controlled SEC rescinded SAB 121, an agency rule that discouraged U.S. banks from holding crypto. 

    Even employees of the federal agencies accused of participating in Operation Choke Point 2.0 have become more outspoken in recent weeks. Earlier this month, Travis Hill, Vice Chair of the FDIC, called in a speech for the regulator to overhaul its approach to digital assets and “put an end to any and all Choke Point-like tactics.”

    Edited by Andrew Hayward

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    Top 6 AI Crypto Tokens/Projects Leading the Market in 2025

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    Top 6 AI Crypto Tokens/Projects Leading the Market in 2025


    The crypto industry continues to evolve, and one of the most exciting sectors gaining momentum is artificial intelligence (AI) integration within blockchain technology. Ever since OpenAI introduced ChatGPT on November 30, 2022, the intersection of AI and big data has become a focal point across multiple industries, including cryptocurrency. This convergence has given rise to AI-powered crypto tokens, making it a niche that every investor and developer should pay attention to.

    Artificial intelligence is transforming technology at an unprecedented pace, making its presence felt across different sectors. In the crypto space, AI is being utilized to enhance security, scalability, trading automation, and user experience. As blockchain networks integrate AI-driven solutions, new possibilities emerge, offering innovative applications that extend beyond traditional cryptocurrencies.

    This article delves into the concept of AI-powered crypto tokens and highlights some of the top AI crypto projects dominating the market in 2025.

    What Are AI Crypto Tokens?

    AI crypto tokens, also known as artificial intelligence coins, are blockchain-based assets that leverage AI and machine learning (ML) to enhance their functionalities. These tokens serve a variety of purposes, from powering decentralized AI platforms to executing smart trades and analyzing market trends autonomously.

    Types of AI-Powered Crypto Tokens

    Decentralized AI & ML Platforms – Some AI crypto projects offer a decentralized environment where researchers and developers can build, train, and test machine learning models.

    AI-Driven Trading Bots – Certain crypto assets use AI algorithms to analyze market trends, predict price movements, and execute trades automatically, making them attractive to investors.

    AI for Blockchain Security – AI technology is also deployed in crypto networks to enhance security, detect fraud, and prevent cyber threats.

    Now that we understand what AI crypto tokens are let’s explore the top AI-powered blockchain projects shaping this sector’s future.

    AI Crypto Tokens to Watch in 2025

    1. Render Token (RNDR) – Revolutionizing AI-Powered Cloud Rendering

    Render Token (RNDR) is an innovative AI crypto project focusing on decentralized GPU rendering solutions. By leveraging blockchain technology, RNDR enables digital creators to access powerful GPUs for rendering complex 3D and AI-generated content.

    How Render Token Works

    Decentralized Rendering Network – RNDR connects users who need rendering power with GPU owners who have excess computing resources.

    AI-Driven Image Processing – With AI and ML integration, RNDR enhances the efficiency and quality of rendered content.

    Cost-Effective Solutions – Users can access high-end computing power without the need for expensive hardware.

    RNDR is currently in a downtrend but has strong support around the $6-$8 mark.

    2. Injective (INJ) – AI-Powered DeFi & Trading Infrastructure

    Injective Protocol (INJ) is a layer-1 blockchain designed for decentralized finance (DeFi) applications. Integrating AI enhances automated trading, decentralized exchanges (DEXs), and predictive markets.

    Why Injective Stands Out

    Fully Decentralized Trading – INJ enables AI-driven on-chain order book trading, reducing reliance on centralized exchanges.

    Cross-Chain Compatibility – It supports Ethereum and non-EVM chains like Solana, broadening its reach.

    AI-Powered DeFi Tools – AI algorithms assist in trade execution, lending, and risk assessment.

    INJ has key resistance at $27–$29, and a breakout could drive significant upward momentum.

    3. NEAR Protocol (NEAR) – Powering AI-Driven Decentralized Applications

    NEAR Protocol has positioned itself as one of the leading AI-integrated crypto projects, boasting a massive market cap in 2025. It is a next-generation blockchain designed to support decentralized applications (dApps) with a scalable and developer-friendly ecosystem.

    Key Features of NEAR Protocol

    High-Speed Transactions – NEAR’s architecture ensures fast and low-cost transactions, which is critical for AI applications requiring rapid data processing.

    Sharding Technology – NEAR utilizes sharding to improve scalability, enabling it to handle a growing number of AI-related transactions.

    Enhanced Security – With multi-party computation (MPC) and homomorphic encryption, NEAR ensures that AI models and data remain secure and private.

    4. The Graph (GRT) – AI-Powered Blockchain Data Indexing

    The Graph (GRT) is a decentralized data indexing and query protocol for blockchain networks. It functions similarly to Google but for blockchain data, using AI to enhance indexing efficiency.

    Core Features of The Graph

    Efficient Data Querying – AI optimizes how blockchain data is structured and retrieved.

    Supports Multiple Networks – The Graph indexes data from Ethereum, Filecoin, and other blockchains.

    Decentralized Data Aggregation – Anyone can create and access APIs (subgraphs) for various blockchain applications.

    A strong recovery above $0.27 could indicate a shift in momentum for GRT.

    5. Artificial Superintelligence Alliance (FET) – AI-Driven Autonomous Decision-Making

    Artificial Superintelligence Alliance (formerly Fetch.ai) is an open-source blockchain ecosystem that enables AI-powered autonomous agents to make smart decisions in various industries.

    Key Functionalities of FET

    Autonomous AI Agents – AI-driven bots can conduct market analysis, predictive modeling, and automated trading.

    Decentralized AI Economy – Users can build and deploy AI at scale with minimal infrastructure costs.

    Machine Learning Capabilities – FET integrates AI to optimize processes and decision-making in finance, supply chain, and healthcare.

    If FET holds above the $1.5 support level, it may regain momentum for a bullish breakout.

    6. Spheron Network: World’s first decentralized supercompute network

    Spheron Network is the world’s first decentralized supercompute network, seamlessly connecting retail and data center-grade GPUs/CPUs to orchestrate dynamic workloads. Designed for AI agents, inferencing, and fine-tuning, Spheron is positioned at the forefront of the compute revolution, addressing the growing demand for decentralized, scalable, and efficient computing resources.

    $SPON is the native token of Spheron Network designed to power AI agents, Web3 applications, and DeFi operations. It serves as the fundamental unit of exchange within the network, enabling users—especially autonomous AI agents—to procure and manage computing resources in a permissionless, cost-effective, and decentralized manner.

    Key Functions of $SPON in the Spheron Ecosystem

    Compute Payments: AI agents and developers use $SPON to lease computational resources from the decentralized Spheron Network.

    Staking & Incentives: Compute providers must stake $SPON to participate in the network, ensuring reliability and reducing sell pressure.

    Escrow-based Security: Funds are secured within smart contract escrows, eliminating the need for traditional wallets and preventing unauthorized withdrawals.

    Governance: $SPON holders have voting power in the ecosystem, influencing upgrades, policies, and network changes.

    Burn & Deflationary Model: A portion of $SPON fees is used for buybacks and burns, ensuring long-term value appreciation.

    Why $SPON Matters in AI & Web3

    Solves GPU Shortage: Spheron mitigates reliance on centralized cloud giants like AWS and NVIDIA by decentralizing compute access.

    Enables AI Autonomy: AI agents can autonomously procure compute power without human intervention.

    Reduces Costs: Spheron’s decentralized model offers lower computational costs than traditional providers.

    Decentralized Physical Infrastructure (DePIN): $SPON drives a new paradigm where compute resources are crowdsourced globally rather than controlled by tech monopolies.

    Comparison: $SPON vs Traditional AI Compute Solutions

    FeatureAWS / Google CloudNVIDIA GPUsSpheron ($SPON)

    Decentralized?NoNoYes

    AI Agent Friendly?NoNoYes

    Compute CostsHighExpensiveLower

    Permissionless AccessNoNoYes

    Supports Web3?NoNoYes

    Conclusion

    The integration of AI in blockchain technology is revolutionizing the crypto industry. The projects mentioned above showcase how artificial intelligence is being leveraged to enhance security, scalability, and automation in the crypto space. As AI adoption continues to grow, these tokens could play a crucial role in shaping the future of decentralized technology.

    If you’re interested in AI-driven crypto projects, keeping an eye on these tokens could prove beneficial. Their innovative use cases and growing adoption indicate a promising future in the AI-blockchain revolution.



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    HK Asia stock soars amid crypto-focused UTXO, Sora Ventures acquisition

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    HK Asia stock soars amid crypto-focused UTXO, Sora Ventures acquisition



    UTXO Management, in collaboration with Sora Ventures and others, has acquired 70.26% of HK Asia Holdings Limited (1723.HK) on the Hong Kong Stock Exchange. The transaction positions the new control group to rebrand the company as Moon Inc., reflecting an emphasis on Bitcoin, Web3 initiatives, and other financial technology ventures. Following the news, the stock is the second-best-performing equity on the Hong Kong stock exchange.

    Tyler Evans, Managing Partner at UTXO Management, the sister company of Bitcoin Magazine under BTC Inc., stated that this move highlights a strategy to leverage Hong Kong’s role in global markets. Sora Ventures Founder Jason Fang pointed to Hong Kong’s Bitcoin ETF launch and recent crypto-focused events as signs of a market environment that may support additional digital asset offerings.

    The acquisition includes issuing convertible notes totaling  33,750,000 HKD, which increases the group’s stake to around 74% upon full conversion by the acquiring parties. UTXO Management and Sora Ventures’ involvement follows their prior success aiding Japan’s Metaplanet, often likened to MicroStrategy in Asia, in its Bitcoin journey.

    Shares of HK Asia Holdings Limited traded at 1.380 HKD on January 24, marking a 23.21% daily increase with a five-day rise of 33.33%. Year-to-date change reached 366.67%, supported by a volume of 13,284,000 shares.

    Market capitalization is 448 million HKD, and the 2023 price-to-earnings ratio is 18.3x. Historical data shows a 52-week low of 0.212 HKD on January 18, 2024, and a 52-week high of 1.63 HKD on January 7, 2025, indicating strong uptrends that could continue given the company’s new direction.

    The rebranding to Moon Inc. will proceed upon approval, signaling a plan to explore strategies tied to Bitcoin and Web3. The company’s name change aligns with its intention to increase exposure to digital asset markets while remaining active on the Hong Kong Stock Exchange.

    Disclaimer: Sora Ventures is an investor in CryptoSlate. 

    The post HK Asia stock soars amid crypto-focused UTXO, Sora Ventures acquisition appeared first on CryptoSlate.



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    Vitalik Buterin calls to cement ETH as ‘triple-point asset’ within L1, L2 ecosystem

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    Vitalik Buterin calls to cement ETH as ‘triple-point asset’ within L1, L2 ecosystem


    Amid tension within some parts of the Ethereum ecosystem, Vitalik Buterin has outlined proposals for Ethereum’s L1 and L2 scaling, focusing on data throughput and proof systems to address network demands.

    In his latest blog post, he described expansions to blob capacity and coordinated interoperability initiatives that aim to simplify cross-chain operations. The post highlighted a plan to balance technical solutions with Ethereum’s social structure, emphasizing that a single chain cannot meet all needs without risking decentralization. Buterin suggested that better security on L2s through multiple proving systems and standardized bridges could ease trust assumptions while allowing different networks to experiment with various virtual machines.

    Buterin emphasized the role of “blob” space expansion as an immediate solution for easing layer-2 congestion and suggested that Ethereum’s base layer must accommodate growing data demands. The ecosystem currently processes about three blobs per slot—roughly 210 transactions per second—though updates labeled Pectra and PeerDAS may double or triple this throughput.

    He stressed the need for a coordinated roadmap, with staking mechanisms possibly adjusting blob targets to match technical improvements. Buterin also mentioned more experimental concepts, including partial trust assumptions for stakers with fewer resources, though he advised caution with designs that risk undermining Ethereum’s core principles.

    He explained that interoperability is a central priority. Rollups function like unique shards controlled by different entities, leading to inconsistent standards for message passing and address formats. This has created fragmentation for developers and users, motivating calls for cross-chain tools that preserve trustless security rather than relying on multisig bridges.

    Buterin proposed unified methods for verifying proofs, accelerated deposit and withdrawal times, and chain-specific addresses, including identifiers for each layer-2 environment. Some developers see this approach as a key step toward user-friendly cross-chain navigation, though Buterin stressed that maintaining explicit security guarantees remains critical for all implementations.

    Protecting ETH value in the Ethereum ecosystem

    The post also addressed economic incentives to reinforce ETH as a triple-point asset, noting that a combination of fee burning on rollups, ongoing data fees from “blobs,” and on-chain revenue from potential maximal extractable value channels could anchor Ethereum’s monetary role.

    Ethereum triple-lock asset (Source: Vitalik Buterin blog)

    He said the ecosystem system needs to

    “agree broadly to cement ETH as the primary asset of the greater (L1 + L2) Ethereum economy, support applications using ETH as the primary collateral, etc”

    He argued that rollups should consider depositing some fees back into Ethereum’s ecosystem, potentially through permanent staking or targeted funding of public goods. He cautioned, however, that fee structures and demand remain uncertain, and no single mechanism guarantees long-term price support for ETH.

    Layer-2 adoption and rollups are currently driving ecosystem growth, but Buterin stressed that a complete transition to rollups requires both technical advancements and social coordination. He urged developers to focus on production-ready proof systems, shared sequencing solutions, and standards that unify cross-rollup operations.

    He also invited wallet providers to implement new address formats and bridging protocols, explaining that meeting these goals will require direct collaboration between the Ethereum Foundation, client teams, and layer-2 projects.

    Buterin’s post concluded with a reminder that Ethereum’s social ethos underpins its technical blueprint, referencing the community’s role in sustaining a decentralized project. He called for direct involvement from all stakeholders, including token holders, who can influence roadmap decisions by engaging in governance and open discussions.

    He noted that the network’s evolution depends on balancing scaling capacity, preserving security, and maintaining a cohesive user experience. The final message called for continued collaboration to ensure that Ethereum remains an open platform capable of supporting widely used decentralized applications.

    Ethereum Foundation’s Leadership and Financial Moves

    The post comes amid community division and an Ethereum Foundation leadership restructuring as it focuses on reinforcing developer collaboration while adhering to core values like decentralization and privacy. Attempting to remain neutral in political matters, the Foundation continues to emphasize its commitment to advancing protocol development without engaging in ideological or lobbying activities.

    However, Buterin’s role as a co-founder has been endlessly debated on social media, with some asking for him to become more involved with Ethereum projects and NFT collections while others push for complete neutrality.

    The community is pushing a narrative that Ethereum’s success depends on maintaining both a robust L1 and a thriving L2 ecosystem that can accommodate varied use cases. Buterin’s blog underlined the importance of flexible yet trust-minimized systems, calling for L2 adoption that mirrors early visions of Ethereum’s sharded architecture.

    He argued that prioritizing blob throughput and shared rollup standards would enable developers to refine DeFi, social applications, enterprise solutions, and more. He also pointed out the need for unified address formats, faster transaction finality, and cross-chain message protocols so users can navigate different L2s without fragmented workflows.

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