Tokenization mania incoming.Stablecoin supercycle is in progress.Powered by Circle, Tether, Ethereum, Aptos, zkSync, Ethena, Sky, Aave, Chainlink, Morpho, Frax, RedStone, Maple, Securitize, Paxos, Ondo, Plasma, and many more. https://t.co/zwbqenR2D5 ...

RT Tom Murphy (@TomMurphyTweets)The Leader in the Tokenization Race. ...

RT nairolf (@0xNairolf)i love tokenization as much as i hate itit’s *the* concept that will have us go mainstream, im 110% sure about thatbut im also certain that this will be used by TradFi to dump billions of illiquid shit to retailwhat to do ...

The current crypto VC investing barbell:1) Tokenization & stablecoins:There is a new cohort of founders entering the industry with backgrounds from Stripe, PayPal, Meta and others. These founders are extremely impressive on paper, have strong experience with fintech and understand how to build real revenue-producing businesses at scale.Investing in this category requires an understanding of traditional payment rails, the entire money transfer process and where there is room for disruption. It also requires ...

RT Tom Murphy (@TomMurphyTweets)Be a real shame if one tokenization company had the largest funds across multiple asset classes (including tokenized stocks), the trust of the world’s biggest asset managers and the full end to end tokenization stack and squad to continue scaling. https://t.co/O3NzYBO4EF ...

Core Viewpoint - The article discusses the trade-offs between State Space Models (SSM) and Transformers, arguing that tokenization is a limitation that SSM can overcome, leading to better computational efficiency and modeling capabilities [1][3][61]. Group 1: State Space Models (SSM) - SSM is defined as a modern version of recurrent neural networks (RNN) with key features that allow it to match the language modeling performance of Transformers [8][10]. - A significant characteristic of SSM is that its hidden state dimension is greater than the input and output dimensions, allowing for better context storage [9][10]. - The model's state update function must be expressive enough to accurately encode and retrieve necessary information, which is achieved through dynamic transfer matrices in selective SSM [11][12]. - Mamba, a specific SSM, integrates parallelization and memory management techniques to enhance computational efficiency [13][14]. - The article highlights that SSMs can outperform Transformers in language modeling tasks when computational resources are matched [53][56]. Group 2: Transformers - Transformers excel in tasks requiring fine-grained operations on individual tokens, but they suffer from quadratic complexity, limiting their efficiency [82][86]. - The article argues that Transformers have an inductive bias that affects their modeling capabilities, making them sensitive to the resolution and semantic content of the data [83][85]. - Despite their strengths, Transformers are not the ultimate solution for all modeling tasks, and there is still significant work to be done in the field [89]. Group 3: Tokenization - Tokenization is a critical step in language modeling, but it introduces limitations in understanding language details [39][40]. - The article posits that removing tokenization could lead to better model performance and aligns with the essence of deep learning, which aims to minimize manual feature engineering [44][45]. - The author suggests that without tokenization, models could learn more effective patterns directly from raw data, enhancing their capabilities [46][52].

Bitwise calls ETH, SOL, XRP, LINK the ‘cleanest’ plays as tokenization narrative builds https://t.co/9nCkf8Nv5R ...

Tokenization is like memecoin launchpads for TradFi. ...

NEW YORK, NY, July 08, 2025 (GLOBE NEWSWIRE) -- Blue Gold Limited (Nasdaq: BGL) ("Blue Gold" or the “Company”), a next-generation gold development and technology company, today announced the formation of its inaugural Advisory Board for Blockchain Evolution. The initiative supports Blue Gold’s mission to pioneer the digitization of real-world assets (RWAs), including gold, while responding to the accelerating demand for decentralized financial instruments. The newly established Advisory Board will provide s ...

Core Insights - Upexi, Inc. reported a successful June 2025, with an 8% increase in its SOL balance and an 8% staking yield [2][7] - The company is focused on enhancing visibility and raising capital for shareholder benefits through various initiatives [2] Treasury Update - As of June 30, 2025, Upexi held 735,692 SOL, an increase of 8.2% from 679,677 SOL on May 28 [7] - The net asset value of the SOL holdings is approximately $113.8 million, based on a price of $154.74 per SOL [7] - Each common share represents approximately 0.0192 SOL or $2.97 [7] - Nearly all treasury SOL are staked, earning an ~8% yield [7] - About 58% of the portfolio consists of locked SOL purchased at a discount, providing built-in gains [7] Business Initiatives - Upexi's equity options are now listed on Nasdaq, enhancing visibility and liquidity [7] - The company is partnering with Superstate to tokenize its equity, allowing for 24/7 trading and broader investor access [7] - Upexi joined Webull's Corporate Connect Service Platform to increase market awareness among Webull's 24 million users [7] Solana Network Performance - Solana recorded significant growth in key metrics, including a 200% year-over-year increase in daily active addresses [9] - Daily transactions reached $3.0 billion, a 67% increase, while DEX volumes surged by 347% to $182 billion [9] - Application revenue grew by 33% to $147 million [9] Price Movement - SOL started June at $157 and ended nearly unchanged at $155, with a low of $132 on June 22 and a high of $165 on June 10 [8]