Nathan Lands

Easy-to-access consumer experience <> access to IP trading <> vertical integration Previously, they were a gaming-focused L1, but it is now shifting their focus to RWA and IP tokenization. First, you get the weebs to trade anime IP, and then you’ll onboard them to get high-quality RWA assets, IQ50-150 play. Just yesterday, Oasys announced a collab with Babylon, allowing users to stake directly to Oasys and utilize the liquidity for the RWA initiatives of Oasys. Crypto is becoming more mature, and buy-in and backing from conglomerates (in this case: SBI, Nexon, Bandai, etc.) is becoming critical. They enable easier integration with existing products/platforms that tap into a larger user base. NFA as always, but $OAS is an interesting one to watch in this vertical as: It’s a liquid token with ~40% free float 3,000,000,000+ $OAS is staked, earning ~10% APY

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Google DeepMind has launched Gemini 2.5 Deep Think, now available to Ultra subscribers in the Gemini app. Official announcement and more details: https://lnkd.in/egvkTt_z This is a good opportunity to better understand what do we mean by "thinking models" and why do we need them. 🤓 💡 If you have 15 minutes to spare, I strongly recommend this excellent short talk from Jack Rae (Google DeepMind's thinking tech lead): https://lnkd.in/eKjKxQVG tl;dr; *AI intelligence progress is all about removing bottlenecks* Historically, major advances in AI come from identifying core “bottlenecks” in current models, and then innovating to remove them (e.g., deep learning, attention, transformers). *Bottleneck today: test-time compute* While LLMs like Gemini and ChatGPT are powerful, they are constrained by a fixed amount of computation per user request (“test-time compute”). This limits the depth and quality of reasoning and solution generation for complex queries. *Solution: dynamic, iterative ‘thinking’ stage* Hence the “thinking stage,” where the model can iteratively loop, perform extra reasoning, and dynamically decide how much additional compute to spend based on the problem’s difficulty. This allows the model to give simple answers quickly and use “deep think” mode to spend much more time and compute on hard or valuable tasks. *Implementation: reinforcement learning for thinking* Models are trained to use this thinking stage via reinforcement learning—rewarding successful problem-solving even with vague, high-level feedback. This shapes the model’s ability to reason, self-correct, decompose problems, try alternative approaches, and use tools when needed. This generic method for training "how to think" led to emergent behaviors such as forming hypotheses, testing them, discarding wrong solutions, breaking down complex tasks, and combining different solution strategies. *Ongoing challenges: efficiency and overthinking* Research continues on making the thinking stage more efficient (avoiding overthinking, unnecessary computation) so that models automatically and adaptively choose the right level of effort for a given task, as well as data efficiency - LLMs that think incredibly deeply and data-efficiently, from a small set of input knowledge. Happy thoughts! #AI #Gemini #DeepThink #GoogleDeepMind #ArtificialIntelligence Antonio Gulli Vladimir Vuskovic

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🪙 Tether just announced a new U.S.-regulated stablecoin under the “Genius Act” — and will share reserve revenues with Anchorage Digital and Cantor Fitzgerald. For years, stablecoin issuers like Circle or Tether captured nearly all the upside from managing reserves. Now we’re seeing a shift: value is starting to flow to those building custody, compliance, and payments infrastructure — the pipes that make stablecoins usable at scale. 👉 Is this the beginning of a new equilibrium where issuers share value across the stack? Or will the center of gravity always snap back to the issuers themselves? #Stablecoins #DigitalAssets #FutureOfMoney #FinTech #Payments #Crypto #Innovation

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The senate passing the GENIUS act yesterday is not just about regulation catching up, its a warning shot. The focus on consumer protection sends a clear signal about where enforcement is headed, and compliance /AML is now baked into the stablecoin framework itself. So if you are building in stablecoins or any regulated corner of crypto, you should definitely take a note. Compliance is a moat, and you should build accordingly. https://lnkd.in/eV5QSHMh

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Great read by Sumcap highlighting DeFi's evolution through automated vaults and standards like ERC-4626, unlocking vast untapped capital while facing fragmentation, security risks, and regulatory hurdles, with hybrid CeFi-DeFi models as a potential solution - https://lnkd.in/dmJ2JTh7

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💥 Metropolis Technologies Raises $𝟭.𝟲𝗕 💥 Funding comes in 2 rounds: $500M equity round led by LionTree and $1.1B from J.P. Morgan. Metropolis is now 𝘃𝗮𝗹𝘂𝗲𝗱 𝗮𝘁 𝗮𝗿𝗼𝘂𝗻𝗱 $𝟱𝗕. With the fresh funding, the plan is to take their "recognition and payment-automation" tech beyond parking assets. This would include retail stores, drive-throughs, gas stations, hotels and partnerships with real estate/asset owner. Congrats to Alex Israel, Peter Fisher, Courtney Fukuda, Travis Kell, Ryan Hunt,Chris Sherman, Robert Bland, Paul Rooney, Lookman Olusanya and the rest of the Metropolis family. #fundraise #parkinginvestment #parking #parkingindustry #metropolois Parking Today Media Parking Network B.V. National Parking Association International Parking & Mobility Institute (IPMI) Tim Maloney Advisory Tim Maloney Reservations Lab

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