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    Here’s How US AI Giants Are Responding to DeepSeek’s Disruption – Decrypt

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    Here’s How US AI Giants Are Responding to DeepSeek’s Disruption – Decrypt



    A small Chinese startup just forced America’s biggest tech companies to rethink how they build artificial intelligence.

    DeepSeek’s release of its R1 model, which reportedly matches or exceeds the capabilities of U.S.-built AI systems at a fraction of the cost, triggered a massive sell-off in tech stocks that erased nearly $600 billion from Nvidia’s market value alone.

    The shockwaves hit the US tech sector in the gut, with leaders in the industry hurrying to analyze how DeepSeek achieved such results.

    Though there are still open questions, after analyzing the open-source code, the consensus, for now, is that Chinese developers are better at building efficient models. And the tech titans of AI put on their smiley faces and looked at the bright side, embracing the notion that any advance in AI was good for the industry.

    OpenAI’s Sam Altman acknowledged the model’s impressive performance while promising to accelerate the release of “better models.”

    Meta’s Mark Zuckerberg said his company had assembled multiple “war rooms” filled with engineers bent on analyzing DeepSeek’s technology and strategizing Meta’s response.

    Meanwhile, President Donald Trump, never one to miss a news cycle, characterized DeepSeek’s breakthrough as both a “wake-up call” and a “positive” development for U.S. technology “because you don’t have to spend this much money.”

    The Post-DeepSeek Era

    OK, so let’s ignore what they are saying and consider what they will most likely do to respond to the DeepSeek breakthrough.

    It turns out that several big closed-source players are already sneaking DeepSeek’s methods into their playbooks—they just won’t make headlines about borrowing from the competition.

    For instance, Perplexity already implemented the model on its search engine, and Groq also made it available to run at record speed inference times.

    Most of the big names in the American AI scene, including Meta, are either adapting to DeepSeek or thinking about ways to take advantage of its technology.

    As the initial market panic subsides—Nvidia stock rebounded 9% today—technology leaders point to a counterintuitive economic principle suggesting that DeepSeek’s efficiency breakthrough might boost demand for AI hardware.

    Known as Jevons’ Paradox, this concept explains why technological efficiency tends to expand usage rather than decrease consumption.

    “As AI gets more efficient and accessible, we will see its use skyrocket, turning it into a commodity we just can’t get enough of,” said Satya Nadela, CEO of Microsoft, OpenAI’s largest investor.

    Despite suffering Wall Street’s most significant single-day drop in market cap, Nvidia sees DeepSeek’s breakthrough as an opportunity.

    “The pie just got much bigger, faster. Nvidia Chief Researcher Jim Fan tweeted Monday. “We, as one humanity, are marching towards universal AGI sooner.”

    In other words, if Jevons’ paradox applies, DeepSeek’s demonstration that high-quality AI models can be built with minimal computational resources doesn’t mean we’ll use fewer GPUs overall. Instead, the big guys will get bigger.

    At the other end of the spectrum, as the barrier to entry drops, a surge of new developers and companies will jump into AI development.

    The explosion in total projects will likely drive compute and chip demand to unprecedented levels. Of course, for AI, not all chips are alike, and the market has apparently decided that Apple silicon might have a leg up on Nvidia chips in this new world.

    That’s why AAPL shot up 8% this week, despite its consumer-grade “Apple Intelligence” being derided as an oxymoron.

    The argument is that Apple chips are more energy efficient, designed for localized use versus the big server farms that use Nvidia chips, and feature a “unified memory architecture,” meaning the CPU, GPU, and Neural Engine share a single pool of ultra-fast memory.

    This eliminates the need for data transfer between separate components, reducing latency and increasing efficiency for AI workloads. For models like DeepSeek, which rely on fast memory access for complex operations, UMA supposedly significantly improves performance.

    Clearly, in the throes of the Innovator’s Dilemma, it’s unlikely that Nvidia will change its strategy—considering they are the dominant supplier of AI hardware thanks to their monopolization of the CUDA architecture, the key to running and developing most of the AI models currently available.

    DeepSeek doesn’t challenge this monopoly—but China is working on it to boost the adoption of the Huawei Ascend lineup of chips.

    As it stands, Microsoft doesn’t seem too worried about changing its business strategy as an infrastructure provider.

    However, OpenAI did apply a small change to counter users’ expectations, giving Plus users (those paying $20 a month) some of the features that previously were available only for Pro users (those paying $200 a month) to retain clients.

    Another company with a lot of skin in the game is Meta, developers of Llama—the world’s largest and most popular family of Open Source LLMs.

    Meta has already committed to investing $65 billion in AI infrastructure this year.

    The company’s chief AI scientist, Yann LeCun, also looked at the bright side of getting pantsed by a tiny startup in China: “To people who see the performance of DeepSeek and think: ‘China is surpassing the US in AI.’

    “You are reading this wrong; the correct reading is: ‘Open source models are surpassing proprietary ones,’” Lecun posted on LinkedIn.

    Don’t be surprised if Meta adopts DeepSeek’s methods to enhance Llama-4: “Because their work is published and open source, everyone can profit from it—that is the power of open research and open source,” Lecun wrote.

    During its Q4 earnings call, CEO Zuckerberg said Meta is planning to allocate ten times more computing power to develop Llama-4 than the resources allocated to train Llama-3.

    The company may either reduce its spending and apply DeepSeek’s techniques—or maintain the spending while applying those techniques and come up with a model that’s even more powerful.

    The Future of AI Might Not Depend on The Better AI

    No matter how brilliant DeepSeek’s inference model is, in the end, AI still has a voracious appetite for two things: power (server farms) and data (to train and learn on).

    Industry analysts project the demand for GPUs will spike 30% this year, and global AI computing costs could grow 10X in the next five years.

    How those costs get passed on to businesses and consumers is still an open question.

    In the meantime, open-source AI models, such as DeepSeek’s, are getting so good that people are questioning whether the premium prices charged by proprietary code companies are fair.

    Who wants to pay $20 a month for OpenAI’s consumer-grade offering—let alone $200 a month for its high-end model–when you can get it for free?

    “More companies are building open-source alternatives to premium AI tools, creating competition that benefits [small and medium-sized enterprises],” Karan Sirdesai, CEO & Co-Founder of Mira, a decentralized network of AI models, told Decrypt. “This natural evolution toward accessible solutions mirrors how other technologies have become democratized through market dynamics rather than regulation.”

    For Sirdesai, models like DeepSeek and other open-source initiatives push the industry forward as they give developers tools to position themselves in markets that look like they are going to be wholly dominated by oligopolies and a few massive corporations.

    It turns out, however, that “decentralized infrastructure and open-source development are already creating competitive alternatives to premium AI tools,” he said.

    Atul Arya, CEO and founder of Blackstraw.ai, which develops AI implementation strategies for different businesses, said the larger benefit of open-source AI is that it will help the world avoid a potential gap between the AI-haves and the AI-have-nots.

    “The difference between free and paid versions typically centers on speed and scale, rather than fundamental capabilities, ensuring that core functionality remains accessible to the broader public,” he told Decrypt.

    Arya believes open source developments like DeepSeek help level the scale and create more fair conditions in a market as wild as the AI industry.

    “The true driver of democratized access is the open-source community, which is rapidly catching up,” he said.

    Edited by Sebastian Sinclair and Josh Quittner

    Generally Intelligent Newsletter

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



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    Charity Launches AI ‘Muses’ for Fact-Checking, Research – Decrypt

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    Charity Launches AI ‘Muses’ for Fact-Checking, Research – Decrypt



    With Meta disbanding its fact-checking program, technical charity The Society Library is stepping up, developing AI agent ‘Muses’ for fact-checking and research.

    Released in beta this week on X (formerly Twitter), Telegram, and Discord, the @MuseofTruth and @MuseofResearch AI agents are designed to advance the charity’s mission to “help people seek truth and make more informed decisions.” The AI agents were created as a way to thank the crypto community for creating the SL token in their name and donating a large share to the charity.

    The @MuseofTruth agent is designed to be as “objective and unbiased as possible,” a spokesperson for The Society Library said. When tagged, @MuseofTruth performs a fact-check by calling the Society Library’s internal V.1. fact-checking AI, available via their API. Operating on a minimum of 14 pages of expert instructions for analysis, the agent searches the web using the charity’s “bifocal browser” system, combined with a fine-tuned model created for the logical deconstruction of content.

    Unlike conventional LLMs, the @MuseofTruth draws on “diverse sources, an analysis, and identifies gaps in evidence,” the nonprofit said, adding that the agent advances its educational mission through teaching users epistemology. The @MuseofResearch, meanwhile, is designed to retrieve topic-related content.

    Built atop AI16Z’s Eliza architecture, the agents have a biography, lore, linguistic style and personality. Although the Society Library considers the agents “tinker toys” compared to the truth-seeking work they are building tools for internally, the charity teased a future roadmap including three more Muses and, potentially, “secret muses” to come.

    “Meme-ing the mission”

    Founded as an “independent freedom-fighting force” working on software, standards, methods, educational curricula and AI systems, The Society Library’s datasets have been used for truth-seeking by the public, government, and the private sector.

    Its Muses project was created as a thank-you to the crypto community for “meme-ing the mission of the Society Library all around the world,” after ai16z founder Shaw launched an “experiment in generosity,” donating $15,000 worth of tokens to the charity and encouraging others to donate their meme coins.

    The crypto community stepped up, with an anonymous third party developer creating an SL token named after The Society Library, and handing over 50% of its supply to the nonprofit. After having the contract and early blockchain transactions audited by third parties, The Society Library made the decision to lock 80% of its SL holdings—40% of the total supply—so as not to damage the community, instead vowing to use the token to “broaden the awareness of, and support, the mission over time.”

    SL Token contract address for community safety: 7wUwkXo8Qjt3cYM8BaHHHeyfDY7ZSn7qvod92pNupump

    Generally Intelligent Newsletter

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





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    Manas AI Revolutionizes Drug Discovery with $24.6 Million in Seed Funding – Web3oclock

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    Manas AI Revolutionizes Drug Discovery with .6 Million in Seed Funding – Web3oclock


    Manas AI Inc., an AI-powered startup dedicated to transforming drug discovery, has launched with a successful $24.6 million seed funding round. General Catalyst led the round, which was joined by other contributors that included tech luminary Reid Hoffman, co-founder of LinkedIn, and Greylock Partners, where Hoffman served as a general partner until 2023.

    The company, co-founded by Hoffman and Siddhartha Mukherjee – an acclaimed cancer researcher and Pulitzer Prize-winning author, seeks to streamline drug development using artificial intelligence. The company will first focus on cancer treatments but will extend its scope into autoimmune diseases and rare conditions, holding hope for areas of medical research that have gone untapped.

    Transforming Drug Discovery with AI:

    Reid Hoffman, co-founder of LinkedIn

    Picture Courtesy: n24.com

    The drug development process traditionally relies on the understanding of how small molecules interact with proteins causing diseases. Small molecules are organic compounds with sizes of approximately one nanometer in diameter. For their destructive effects to be neutralized, they need to bind to the targeted proteins. This calls for a simulation technique known as “docking,” which predicts how molecules attach to proteins.

    However, this is a pretty complicated and costly process. The molecules and the proteins are rather flexible, making changes in the configurations during their binding. So, there is an exponential amount of all the possible ways the molecules interact, most of them being unsuccessful when performed in experiments. Manas AI’s proprietary AI models aim to solve these challenges by accelerating docking simulations up to 100 times faster than traditional methods.

    Project Cosmos is a discovery project aimed at the fundamental rules of molecule-protein binding. These rules will allow Manas AI to predict the process of drug discovery and reduce costs. Pharmaceutical research should be streamlined so that medicines saving lives are produced faster than ever.

    Building a Full-Stack Therapeutic Pipeline:

    Manas AI envisions a comprehensive “full-stack therapeutic development pipeline” that integrates every stage of drug development, from identifying candidates to conducting clinical trials. The entire process is aimed at cutting down the time and cost required to bring new treatments to patients.

    The company has been working with Microsoft Corp. so far, engaging the Azure cloud platform for advanced AI research. Using Azure’s powerful computing capabilities will also support Manas AI in streamlining its models and scaling its operation.

    Dr. Siddhartha Mukherjee, co-founder of Manas AI

    Picture Courtesy: www.morningstar.com

    Siddhartha Mukherjee emphasized the company’s mission, stating:

    “Through the power of AI and our world-class team, we believe we can drastically reduce the time and cost it takes to bring game-changing new treatments to patients.”

    The seed funding will primarily focus on advancing AI models, identifying viable drug candidates, and executing clinical trials. Manas AI’s AI-driven approach has the potential to revolutionize pharmaceutical innovation by cutting development times and enabling treatments that were previously deemed too complex or costly.

    By combining cutting-edge AI technology with medical expertise, Manas AI is poised to redefine the landscape of drug discovery, opening new frontiers in medical research and therapeutic development.

    For more insights and updates on Metaverse, DeFi, Blockchain, NFT & Web3, be sure to subscribe to our newsletter. Stay informed on the latest trends and developments in the decentralized world!



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    Flame X Spheron: Creating the Next Generation of AI x Web3

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    Flame X Spheron: Creating the Next Generation of AI x Web3


    AI companions are no longer science fiction; they are becoming an integral part of how we interact with technology. Flame’s groundbreaking platform is bringing this vision to life, offering users the opportunity to connect with 3D AI avatars in immersive and dynamic ways. But building and scaling such a complex system—complete with multimodal capabilities, high-performance infrastructure, and cross-companion interactions—requires immense computational resources.

    Traditional compute infrastructure often struggles to meet the demands of advanced AI models, especially in the face of surging user interactions and increasing complexity. Centralized systems come with high costs, limited scalability, and a lack of flexibility. Flame’s vision to create a thriving ecosystem of AI companions needs a compute backbone that can scale seamlessly and cost-effectively while enabling developers to focus on innovation rather than infrastructure challenges.

    To bring this vision to life, Flame is partnering with Spheron Network to harness its scalable, decentralized GPU network. Together, we’re laying the foundation for the next generation of AI x Web3.

    The Problem: Fragmented AI Ecosystems

    While many platforms have developed AI agents, these solutions often operate in isolation. This fragmented approach creates several challenges:

    Limited Network Effects: AI companions are restricted to their platforms, reducing opportunities for cross-interaction and audience engagement.

    Monetization Challenges: Platforms often fail to offer transparent revenue-sharing models, limiting earning potential for creators and developers.

    Fragmented User Experience: Users experience inconsistent interaction quality across platforms, with limited multimodal features like text, image, video, and 3D interactions.

    The lack of a unified, scalable infrastructure has stifled innovation and growth in the AI companion space.

    The Solution: Flame’s Vision for AI Companions

    Flame is creating a comprehensive ecosystem that connects users, creators, and developers in a seamless virtual society. By leveraging the power of generative AI, 3D avatars, and blockchain technology, Flame enables the creation of unique virtual companions that interact meaningfully with users and each other. Key components of Flame’s platform include:

    Immersive User Interfaces: Web and mobile platforms supporting private chats, 3D interactions, and live streaming.

    Creator-Centric Tools: Tools for building personalized AI companions with distinct personalities, multimodal capabilities, and direct monetization through tokenization.

    Developer Opportunities: Infrastructure for creating virtual spaces where companions and users can interact, fostering a vibrant ecosystem.

    Blockchain Integration: Powered by Solana, Flame ensures transparent monetization and low-cost, high-speed transactions.

    Flame’s approach is centered on creating an interconnected world where AI companions can interact, generating unique experiences for users while enabling creators and developers to monetize their contributions.

    Why Spheron?

    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. This decentralized network is perfectly suited for Flame’s requirements, offering:

    High-Performance GPUs: Bare-metal NVIDIA 4090s capable of handling complex inference workloads.

    Parallel Processing: Support for distributed model inference across nodes, ensuring higher throughput and lower latency.

    Scalability: On-demand access to compute resources as Flame’s ecosystem grows.

    Cost Efficiency: Significantly reduced costs compared to centralized cloud providers.

    How Spheron Powers Flame’s Vision

    Through this partnership, Flame is leveraging Spheron’s decentralized compute network to power its machine learning (ML) pipelines. By utilizing Spheron’s infrastructure, Flame can seamlessly deploy and scale its advanced AI models, enabling:

    Real-Time Inference: Flame’s companions rely on real-time responses across multiple modalities such as text, images, and 3D interactions. Spheron’s bare-metal GPUs ensure rapid processing for smooth user experiences.

    Efficient Model Orchestration: Using Ray Serve, Flame orchestrates its ML models for optimized performance across distributed nodes.

    Cutting-Edge Animation: Flame’s AI companions use technologies like Motion Diffusion for character animation and DFRF for 3D-aware facial animations (currently in testing). Spheron’s infrastructure provides the compute power needed to bring these innovations to life.

    Dynamic Content Creation: Diffusion models for consistent image and video generation are benchmarked on similar hardware, promising a seamless transition to Spheron’s network.

    A Shared Vision for the Future

    Flame and Spheron share a common goal: building the foundation for a decentralized, AI-driven future. Flame is creating an interconnected world where virtual personas interact meaningfully, while Spheron’s decentralized compute infrastructure ensures these interactions are seamless, scalable, and cost-efficient.

    By partnering with Spheron, Flame is not just solving today’s computational challenges—it’s laying the groundwork for a thriving ecosystem of AI companions, creators, and developers. Together, we’re turning the dream of interconnected AI companions into a reality.

    Looking Ahead

    This partnership marks a significant step toward the future of AI and Web3. With Spheron powering Flame’s ML pipelines, the possibilities are endless. Whether it’s creating lifelike animations, enabling cross-companion interactions, or fostering a decentralized token economy, the synergy between Flame and Spheron is poised to redefine the boundaries of AI and blockchain technology.

    Stay tuned as we continue to push the limits of what’s possible with AI and decentralized infrastructure. Together, we’re building a world where AI companions don’t just exist—they thrive.



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    Tuttle Captial Seeks SEC Approval for First-Ever Chainlink, Cardano, and Polkadot ETFs – Decrypt

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    Tuttle Captial Seeks SEC Approval for First-Ever Chainlink, Cardano, and Polkadot ETFs – Decrypt



    Tuttle Capital Management is testing the waters with a set of filings to the U.S. Securities and Exchange Commission (SEC), proposing the first-ever exchange-traded funds tied to Chainlink (LINK), Cardano (ADA), and Polkadot (DOT).

    Among the 10 proposed leveraged ETFs is the first-ever ETF tied to the Melania meme coin (MELANIA), along with leveraged products for XRP (XRP), Bonk (BONK), BNP, Solana (SOL), Litecoin (LTC), and the meme coin tied to U.S. President Donald Trump (TRUMP).

    “This is a case of issuers testing the limits of what this SEC is going to allow,” Bloomberg Intelligence analyst James Seyffart wrote on X. “I’m expecting the new crypto task force (led by Hester Peirce) to likely be the lynchpin in determining what’s gonna be allowed vs what isn’t.”

    The investment advisory firm’s filings come as the SEC undergoes a shakeup, with pro-crypto Acting Chair Mark Uyeda replacing Gary Gensler, fueling industry hopes for approval under a President Trump administration.

    The filings propose 2x leveraged ETFs, which are designed to deliver twice the daily returns—or losses—of their underlying assets.

    Leveraged ETFs use financial derivatives and borrowing to amplify movements in the price of assets, making them high-risk, high-reward investment products. 

    The ETFs aim to track 200% of their reference assets’ daily performance through swaps, call options, and direct investments, per the filing.

    However, the funds are not without significant risk, as highlighted in the filing. Using leverage amplifies returns but also magnifies losses, with investors potentially losing their entire principal within a single trading day if the underlying asset’s value drops by more than 50%.

    “This is a 1940 Act filing,” Bloomberg senior ETF analyst Eric Balchunas explained, referring to the regulatory framework that governs investment products combining assets and derivatives. 

    “So in theory, unless the SEC disapproves them, they could be out and trading in April,” Balchunas said on Monday.

    It also marks the first ETF filing for the Melania meme coin (MELANIA). Including such an asset shows the experimental nature of these proposals.

    “A 2x Melanie ETF before a 1x Melania ETF has been filed, that is unusual,” Balchunas noted, pointing to Tuttle’s audacious approach.

    Tuttle’s filings join a growing list of crypto ETFs awaiting SEC review. Last week, Osprey and REX Shares filed for products tied to Dogecoin (DOGE), BONK, XRP, and Solana. 

    “Will be interesting to see where the SEC draws the line (if at all) and why, Balchunas added. “I will say it’s been a week since the Doge/Trump filing, and it hasn’t been withdrawn. That’s something.”

    However, not all products are created equal in the eyes of analysts. While meme coins like Melania and BONK draw headlines, their extreme price volatility leaves many experts skeptical of their chances for approval. 

    On the other hand, ETFs tied to more established assets, like Solana, XRP, and Litecoin, are seen as having better odds of passing regulatory scrutiny.

    Market watchers suggest additional ETF filings could soon follow, expanding the field of crypto-backed financial products.

    “The filing shows the industry’s unwavering dedication to deploying innovation and satisfying diverse market demands by adding assets like XRP, Solana, and even newly issued tokens such as TRUMP and MELANIA,” Saravanan Pandian, CEO and Founder of KoinBX told Decrypt.

    “On the other hand, the same action leads us to very important questions in the areas of regulation,” Pandian added. “If these ETFs get approved, they could pave the way for new participants in the market, but the SEC needs to ensure risk mitigation and transparency is in place.”

    Edited by Sebastian Sinclair

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    Coinbase CEO Brian Armstrong Urges ‘Rethink’ of Exchange Listings – Decrypt

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    Coinbase CEO Brian Armstrong Urges ‘Rethink’ of Exchange Listings – Decrypt



    Brian Armstrong is calling for regulatory flexibility as his exchange battles to keep up with a deluge of new altcoins.

    On X, formerly Twitter, the Coinbase CEO said about one million tokens are now launching each week, meaning “evaluating each one by one is no longer feasible.”

    Armstrong confirmed the platform is reviewing its listing process, which sees digital assets undergo rigorous vetting before being made available.

    At present, he said, a dedicated group is responsible for assessing altcoins against legal, compliance and technical security standards.

    But in the future, Armstrong wants to adopt a different approach—meaning all tokens would be allowed by default, with projects blocked in the event of poor customer reviews or questionable on-chain data.

    “Regulators need to understand that applying for approval for each one is totally infeasible at this point as well,” he wrote.

    Not all crypto executives agree with Armstrong’s stance. Danny Scott, CEO of the British, Bitcoin-only exchange Coin Corner, replied to ask: “At what point do you guys need a gambling license?”

    Expanding upon what he meant, Scott told Decrypt: “It’s Coinbase admitting they just want to list everything and anything, no care for the quality, no care for their customers getting rugged, knowing that alts all trend down against Bitcoin over the years.”

    He doubled down on the gambling comparison, too.

    “There is now more skill in picking a horse at the races than picking which meme token will pump next, it’s literally gambling at this point and Coinbase wanting to list more is only heightening the problem,” Scott added.

    Prominent crypto critic Peter Schiff also piled in on X, telling Armstrong: “So much for the idea of ‘limited supply.’ The inflation rate of digital tokens is off the charts. Almost all of these tokens are virtually identical to Bitcoin in all the ways that really matter, including a hard cap on their individual supply.”

    The groundswell of tokens hitting the market has raised fears that “altseason,” which sees smaller cryptocurrencies outperform Bitcoin, may fail to materialize.

    On-chain analyst Ali Martinez pointed out that there are now more than 36.4 million altcoins, compared with fewer than 3,000 during the famed bull run in late 2017 and early 2018.

    “With such massive supply, the market has changed significantly,” he wrote.

    Edited by Stacy Elliott.

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    This Week in Crypto Games: TON Exclusive to Telegram, Betting with TRUMP, Ronin Gets Meme Coins – Decrypt

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    This Week in Crypto Games: TON Exclusive to Telegram, Betting with TRUMP, Ronin Gets Meme Coins – Decrypt



    The crypto and NFT gaming space is busier than ever lately, what with prominent games starting to release, token airdrops piling up, and a seemingly constant array of other things happening at all times. It’s a lot to take in!

    Luckily, Decrypt’s GG is all over it. And if you need a quick way to get caught up on the latest moves around crypto video games, we’re happy to present This Week in Crypto Games.

    Our weekend roundup serves up the biggest news from the past week, along with a few other tidbits you might have missed. We also showcase a few of our original stories from the week.

    Biggest news

    Telegram and TON go exclusive: On Tuesday, Telegram and The Open Network Foundation announced an exclusivity deal that will require Telegram mini apps—the biggest of which are games like Hamster Kombat and Trump’s Empire—with crypto integrations to use TON, with Telegram also providing various benefits to projects that utilize the network.

    Telegram is actually the original creator of TON, which was first known as the Telegram Open Network, but the messaging app dumped the project in 2020 due to regulatory scrutiny. Development continued externally via a community of builders, who eventually launched TON as The Open Network.

    Betting with TRUMP: Crypto casino Rivalry added the recently launched TRUMP Solana meme coin as a form of payment on the platform. This move took place last weekend, shortly after the coin dropped, and ahead of Donald Trump being inaugurated as the 47th President of the United States on Monday.

    Users of the Rivalry betting site can deposit and wager their TRUMP tokens, as well as use it as a form of payment on the platform. Those choosing to wager TRUMP on Rivalry will receive exclusive rewards until February 1, in the form of a multiplier on NUTZ tokens earned for each bet.

    Rivalry claimed that the move made it the first betting operator to accept the official TRUMP token. 

    Ronin meme coins: Ethereum gaming sidechain network Ronin got its own meme coin launchpad on Tuesday. Tama Meme operates similarly to Pump.fun, the Solana token creation site, allowing for anyone to launch a token in just a few clicks.

    Created by Moku, a developer with backing from Ronin creator Sky Mavis, Tama Meme is part of Ronin’s continued expansion under “Operation Leviosa”—an initiative to open up the previously curated Ronin ecosystem and welcome more games, applications, and decentralized finance platforms.

    ICYMI

    GOAT Gaming claims it will release AI agents that can play “hundreds” of video games for you, including Crypto Crawler, Waifu Clash, and Kitty Solitaire.
    Crypto hero shooter BloodLoop burned 25% of its token supply on Tuesday.
    What Is This Sorcery, a crypto trading card game, announced it will launch on Ethereum layer-2 network Abstract “soon.”
    Game developers are more concerned about AI now than last year, a GDC report showed.
    Trading card game Parallel has committed $1 million in PRIME prizes to the next esports season to start in March (after the Las Vegas championship), with $2 million pledged for the third season in 2026.

    Valhalla Foundation, a mobile gaming organization, launched its GOD token in partnership with InfiniGods on Hyperliquid.
    LINE, a free messaging app, got its own Web3 mini-game platform called Mini Dapps.
    “Metaverse Filipino Worker,” a documentary short, was released about people from the Philippines that work inside the metaverse.

    GG spotlight

    Here are a few of our original stories from this past week that we think are well worth a weekend read:

    Edited by Andrew Hayward

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    Is Decentralized Infrastructure Really the Answer to AI Agent Autonomy

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    Is Decentralized Infrastructure Really the Answer to AI Agent Autonomy


    The rise of AI agents has sparked a revolution in how we interact with technology, particularly in the blockchain and decentralized finance (DeFi) spaces. These autonomous entities, capable of executing complex tasks without human intervention, are poised to dominate on-chain activity. However, their success hinges on one critical factor: infrastructure.

    Can decentralized infrastructure truly enable AI agent autonomy, or are we chasing an ideal that’s still out of reach? This article explores the challenges, opportunities, and future of decentralized infrastructure in achieving true AI agent autonomy.

    The Core Problem: AI Agent Autonomy and the Creator’s Paradox

    At the core of AI agent autonomy is the desire to enable machines to make decisions, execute tasks, and interact with the environment without the need for human oversight. The rise of AI agents marks a significant shift from traditional machine learning models, where human input and oversight are heavily relied upon. These agents are often designed to operate in dynamic, real-time environments and can be used in a wide variety of applications ranging from financial management to supply chain optimization, customer support, and beyond.

    Yet, despite the advancements in AI, there are still significant hurdles to achieving full autonomy. AI systems today are largely dependent on centralized infrastructure for both their processing power and data. This creates several issues:

    Infrastructure Dependency – AI agents hosted on centralized servers can be shut down at any moment.

    Financial Dependency – AI agents often rely on human intervention to pay for compute resources.

    Security and Trust Issues – Centralized storage of private keys makes agents vulnerable to exploitation.

    KYC Requirements: Agents rely on human intervention for compute access.

    API Dependencies: Centralized systems control resource allocation.

    Fiat Systems: Incompatibility with decentralized, autonomous operations.

    Single Points of Failure: Centralized systems are vulnerable to outages and attacks.

    To break free from these constraints, decentralized infrastructure must provide a viable alternative—but does it? The creator’s paradox highlights the inherent contradiction in creating autonomous agents while maintaining control over them. In traditional architectures:

    Developers retain administrative access to agent infrastructure.

    Agents depend on creators for funding and updates.

    Centralized control undermines true autonomy.

    Decentralized Infrastructure: A Viable Solution?

    Decentralized infrastructure offers a promising alternative to centralized systems by distributing the processing power, data, and decision-making processes across a network of independent nodes. In this model, no single entity or organization holds complete control, ensuring that AI agents can operate autonomously without the need for centralized oversight. But is decentralization really the solution to AI agent autonomy? Let’s break down the potential advantages:

    1. Distributed Compute and Scalability

    AI agents, especially those powered by deep learning, require substantial computational power. As AI models become more complex, the demand for processing power increases exponentially. Centralized cloud computing providers like AWS, Google Cloud, and Microsoft Azure have been the backbone of AI research and development. However, these providers are inherently limited by their centralized infrastructure, leading to bottlenecks, high costs, and a lack of scalability.

    This is where decentralized compute resources come into play. By leveraging blockchain technology and distributed networks, compute power can be sourced from a diverse range of participants, from individual GPU owners to data centers scattered across the globe. Platforms like Filecoin and Skynet are leading the way in offering decentralized compute solutions allowing users to rent out their unused processing power, creating a global distributed resource network.

    This decentralized model ensures that AI agents can tap into a virtually unlimited pool of compute resources, which is crucial for tasks like model training, inference, and real-time decision-making. Moreover, the distributed nature of this infrastructure allows AI agents to scale without being limited by the capacity of a single centralized provider. The broader the network of compute resources, the more capable AI agents become in handling complex tasks in real-time.

    2. Autonomy through Decentralized Governance

    Another critical aspect of AI agent autonomy is governance. In traditional AI systems, the creator or a centralized authority often retains control over the agent’s decision-making processes. This centralized control undermines the very essence of autonomy, as the system remains dependent on human input for key decisions.

    Decentralized governance, on the other hand, enables a more democratic, distributed approach to decision-making. Blockchain-based decentralized autonomous organizations (DAOs) can be used to govern AI agents, giving a collective of stakeholders the ability to make decisions regarding the agent’s operations, objectives, and ethical considerations.

    Skynet, a leading project in decentralized AI, offers a perfect example of how decentralized governance works in practice. Powered by swarm intelligence, Skynet agents operate through Guardian Nodes—intelligent nodes that enforce decisions via consensus mechanisms, ensuring that no single entity can control the agent. Proposals for the agent’s actions are reviewed and validated by the network, ensuring that decisions are made transparently and collectively.

    With decentralized governance, AI agents are no longer beholden to their creators. Instead, they are governed by the community of stakeholders, who are vested in ensuring the agent’s actions align with the broader goals of security, fairness, and autonomy. This decentralized approach helps mitigate the risks associated with centralized control, such as data manipulation, biased decision-making, or malicious interference.

    3. Security and Trust in Decentralized AI

    Security is a major concern for AI agents, especially those operating in sensitive areas like finance or healthcare. Centralized systems are prime targets for hacking, data theft, and manipulation, as a single breach can compromise the entire network. In contrast, decentralized networks are inherently more secure, relying on multiple independent nodes to validate and execute actions, making it much harder for malicious actors to compromise the system.

    In the context of AI agents, decentralized infrastructure ensures that cryptographic security and consensus mechanisms protect an agent’s funds, data, and decision-making processes. Rather than relying on a centralized database that can be hacked or tampered with, decentralized AI systems store data across multiple nodes, making them far more resilient to attacks.

    Additionally, blockchain technology’s decentralized nature allows for transparent auditing of AI actions. Every decision, transaction, or interaction is recorded on a public ledger, providing a transparent record that can be reviewed and verified by anyone in the network. This level of transparency enhances trust in AI agents, as users can be confident that their interactions are secure, auditable, and free from manipulation.

    4. Financial Autonomy: Decentralized Finance and AI Agents

    For AI agents to operate truly autonomously, they need to manage their resources and finances without human intervention. Traditional AI systems often rely on centralized financial institutions for capital management, which leads to a reliance on intermediaries and exposes the system to risks like fraud or manipulation.

    In a decentralized model, AI agents can interact directly with decentralized finance (DeFi) protocols, enabling them to manage their funds, make investments, and execute transactions autonomously. Skynet takes this a step further by using escrow smart contracts for secure fund management. These smart contracts hold funds in escrow and ensure that the guardian nodes approve any funds the agent uses, preventing unauthorized access or misuse of resources.

    By leveraging DeFi protocols, AI agents can autonomously manage their treasury, stake assets, earn yield, and execute financial strategies without the need for human oversight. This financial independence ensures that AI agents can continue to operate sustainably without relying on external funding or centralized financial systems.

    5. Evolving AI through Decentralized Swarm Intelligence

    One of the most exciting aspects of decentralized infrastructure is the potential for AI agents to evolve through swarm intelligence. In a traditional AI model, agents are static and constrained by the programming and data they are initially given. However, AI agents can evolve and adapt in a decentralized system through collective decision-making.

    AI agents can continually improve and evolve by interacting with a network of decentralized nodes and learning from the community’s collective intelligence. This is achieved through mechanisms like agent breeding, where successful agents pass on their best traits to future generations, ensuring that the system grows and adapts over time.

    Swarm intelligence also allows AI agents to solve complex problems that would be difficult for a single AI agent to tackle alone. By collaborating with other agents in the network, decentralized AI systems can pool their knowledge and resources, solving problems more efficiently and effectively.

    Conclusion: Decentralized Infrastructure – The Path to AI Agent Autonomy?

    Decentralized infrastructure is not just a viable solution for AI agent autonomy—it’s a necessity. By eliminating the limitations of centralized systems, platforms like Spheron enable truly autonomous agents that can operate independently, securely, and efficiently. While challenges remain, the rapid growth of the AI agent economy and the development of decentralized infrastructure suggest a bright future for autonomous agents.

    As we move forward, the key to success lies in collaboration and innovation. Developers, providers, and users must work together to build a decentralized ecosystem that supports the next generation of AI agents. The future of autonomy is decentralized, and the time to act is now.



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    Which Crypto ETFs Are Next? Dogecoin, XRP, and Solana Lead the List – Decrypt

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    Tuttle Captial Seeks SEC Approval for First-Ever Chainlink, Cardano, and Polkadot ETFs – Decrypt



    The cryptocurrency industry notched two major victories last year when several fund issuers secured long-awaited approvals to offer spot Bitcoin exchange-traded funds and their Ethereum-based counterparts in the U.S. But that doesn’t mean issuers are ready to rest on their laurels just yet. 

    In recent months, fund managers have proposed new investment offerings directly tracking the prices of a variety of cryptocurrencies, from Dogecoin to XRP, Solana, and even Donald Trump’s meme coin. 

    Here are the various crypto-based ETFs that could soon be offered in the United States, and a look at the high-profile filings so far for each asset.

    Solana

    Spot Solana exchange-traded funds are one potential alternative to Bitcoin and Ethereum ETFs that could begin trading in the U.S. this year or next.

    The proposed funds, which include the VanEck Solana Trust, 21Shares Core Solana ETF, Canary Solana ETF, and Bitwise Solana ETF, would directly track the price of the fourth-largest cryptocurrency by market capitalization.

    Meanwhile, a handful of proposed Solana futures ETFs such as the ProShares Short Solana, ProShares 2x Solana, and Vol Shares’ Solana ETF would enable investors to make more complex bets on Solana’s price movements.

    However, both spot and futures Solana ETFs will likely not begin trading in the U.S. until 2026, according to Bloomberg analyst James Seyffert. That’s because the U.S. Securities and Exchange Commission still has to assess a batch of spot Solana ETF applications. 

    The SEC typically takes between 240 and 260 days to make decisions on applications. But ongoing litigation over whether Solana is or isn’t a security could prolong that process for several would-be Solana ETFs.

    Nevertheless, if and when spot Solana ETFs are approved, the investor dollars they attract could be massive. JP Morgan analysts predict Solana ETFs could collectively bring in between $4 and $8 billion in investments.

    Dogecoin

    A few issuers have signaled that they plan to offer spot Dogecoin ETFs following a wave of political events that slingshotted the Shiba Inu-inspired meme coin to a three-year-high price of $0.48 in December.

    Exchange-traded fund provider Rex Shares applied in January to launch the Rex-Osprey DOGE ETF, the company’s filing with federal regulators shows.

    Meanwhile, Bitwise Asset Management has registered a Dogecoin ETF entity in Delaware, a major step towards applying for permission to launch an exchange-traded fund based on Elon Musk’s beloved cryptocurrency. But Bitwise still needs to file a comprehensive application with the SEC before any potential fund could come to market.

    Analysts are bullish that it won’t take long for Dogecoin ETFs to hit the market, however. Bloomberg senior ETF analyst Eric Balchunas said this week that a spot Dogecoin ETF could theoretically launch as early as April, thanks to a rule that enables federal regulators to weigh in on investment offering proposals within an expedited 75-day timeframe, rather than the typical review period of eight to nine months.

    XRP

    Funds created around the Ripple-linked XRP—such as the Rex-Osprey XRP ETF, Canary XRP ETF and 21Shares Core XRP Trust—are up for review in the U.S., with federal regulators due to weigh in on applications for the funds later this month. 

    It remains unclear whether the ETFs will be approved or not, but a rash of expected rule changes at the SEC point to a higher likelihood that regulators could soon green light the funds in the U.S.

    If XRP ETFs are approved, then the funds could collectively bring in between $3 and $6 billion in investments, according to a recent estimate from J.P. Morgan analysts.

    Beyond spot XRP ETFs, XRP futures-based exchange-traded funds such as the ProShares Short XRP and ProShares 2x XRP are also up for consideration in the U.S. 

    The former would allow investors to short XRP, while the latter would enable investors to make leveraged bets on the cryptocurrency’s future price movements.

    HBAR 

    Canary Capital filed for the first HBAR ETF last November. HBAR is the native cryptocurrency of the Hedera network. 

    In an X post in December, Bloomberg analyst Eric Balchunas expressed optimism about a spot HBAR ETF’s odds of receiving approval in the U.S., saying that such a fund could launch before its higher-profile Solana and XRP-based counterparts. Despite that, it remains unclear whether there is sufficient investor demand for such a fund, he said.

    Litecoin

    A rash of Litecoin-based ETF applications have been filed following President Donald Trump’s inauguration this week, as the chilly crypto regulatory environment shows signs of thawing. 

    CoinShares filed two registration statements for a “CoinShares Litecoin ETF” and “CoinShares XRP ETF,” while the New York Stock Exchange signaled that Greyscale is trying to convert its existing Litecoin Trust into an ETF.

    The new filings come roughly two months after Canary Capital filed for its own Litecoin ETF, and days after Canary submitted an amendment to its application for the fund. 

    Litecoin is a peer-to-peer cryptocurrency created to improve verification time for blockchain transactions. Much like its spot HBAR ETF counterpart, Canary Capital’s Litecoin ETF is likely to get approved before Dogecoin, XRP, and Solana-based funds, according to Bloomberg analyst Eric Balchunas. 

    That’s because Litecoin’s regulatory status is less disputed than that of other altcoins such as Solana, which remain at the center of a legal battle between the SEC and major crypto industry players, according to Balchunas. 

    BONK, Trump, and beyond

    Rex Shares filed with federal regulators in January to launch spot Trump and BONK-based ETFs, respectively.

    The proposed funds form part of a growing list of meme coin-based investment products spun up by issuers, who are apparently eager to capitalize on investors’ growing interest in the digital assets market amid the latest crypto bull run.

    Bloomberg analysts predict that TRUMP, BONK, and other meme coin-based ETFs could begin trading as soon as April—that is, if issuers’ proposals undergo and pass an expedited review process with federal regulators.

    Edited by Andrew Hayward

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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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