背靠 8 亿月活社交巨头，TON 生态将昙花一现还是高歌猛进？

白话区块链Опубликовано 2023-10-08Обновлено 2023-10-08

Введение

今年 Telegram Bot 赛道的火热，使得其依附的平台 Telegram 相关概念也被带动起来，TON 在短时间冲到市值 No.9（目前回落至 No.11）突然从不知名蹿入大家视野。

再加上近期 TOKEN2049 峰会上，Telegram 官方表示通过 TON 将 Telegram 转为 Web3 的入口，使得 Telegram 相关概念得到广泛关注，为TON的热度再添一把火，当然，目前对于 Telegram 将来的发展褒贬不一，有看好的，认为生态会出现泼天的财富效应；也有人认为雷声大雨点小。

今天，我们来简单了解下 Telegram 和TON在区块链行业的发展历程。

Telegram 折戟区块链

Telegram 拥有全球范围内庞大的用户基础，注册用户量 13 亿，其中许多用户来自俄罗斯、伊朗、印度和其他亚洲和欧洲国家。据 Telegram 创始人 7 月 18 在其个人频道中表示，Telegram 每天都有超过 250 万新用户注册，月活已超过 8 亿。

2023 年 1 月 statista 整理数据显示，这一数据是 X （原 Twitter）的 1.4 倍（5.56 亿）、微信的 0.61 倍（13.09 亿）、Facebook 的 0.86 倍（9.31 亿），超过抖音（7.15 亿）。目前作为 Crypto 必备 app 之一，拥有庞大的 Crypto 用户基础。

Telegram 早早就看好区块链赛道，早在 2017 年，Telegram 就发布了名为 Telegram Open Network（TON）的白皮书。TON 被设计为一个去中心化的区块链平台，旨在提供安全、高性能的区块链解决方案，以支持 Telegram 的通信和服务。

为了支持 TON 的开发和推出，2018 年 Telegram 进行了 2 轮筹款。从 175 位投资人手中筹得 17 亿美元，这使得 TON 成为当时最大规模的融资之一，Token Gram 预估总市值 295 亿美元，大概是当时以太坊市值两倍，仅次于比特币，可见当时热度之高。

Telegram 原计划 2019 年 3 月进行 Gram Token 发行，然而，区块链计划受到了美国证券交易委员会（SEC）的起诉，SEC 声称 Telegram 的Token销售违反了美国的证券法规。

最终，法院支持了 SEC 的观点，禁止 Telegram 在美国境内发行其加密货币 Gram，并要求退还投资者的款项。迫于法院的判决，2020 年 5 月 13 日，Telegram 创始人 Pavel Durov 宣布终止 TON 的研究与开发。并开始退还投资者的部分款项，这对 Telegram 的区块链野心构成了重大打击。

尽管终止了 TON，Telegram 仍然在区块链领域寻找机会。他们推出了 Telegram Passport 和 Telegram Payments 功能。Telegram Passport 允许用户在不同的区块链身份验证服务之间共享身份信息，而 Telegram Payments 则提供了一种在 Telegram 平台上进行支付的方式。表明了他们对区块链技术在用户身份验证和金融领域的潜力的关注。

根据一些报道，Telegram 正在考虑为其聊天应用程序添加加密货币适配器。这意味着用户可以在 Telegram 平台上直接进行加密货币交易，而无需离开应用程序。还有报道称，Telegram 考虑将加密货币钱包整合到其聊天应用程序中。这将使用户能够在 Telegram 内部存储和发送加密货币，进一步促进加密货币的采用和使用。这一系列操作为后续 Telegram 与 The Open Network 的合作埋下了伏笔。

TON 接力 Telegram？

在 2020 年 5 月，TON 技术研发团队 TON Labs 宣布了 TON 项目的代码开源并终止项目的开发，随后，由软件开发者、13 位验证者和用户组成的去中心化社区 Free TON 发布分叉版本「Free TON Blockchain」的区块链，Token名称为「Ton Crystals」。

根据 TON Labs 的公告，该社区还将向用户免费提供 85％的 TON Token。Free TON 社区表示，任何人都可以加入该网络。目前 Ton Crystals 官方长时间停止更新，价格也查不到，差不多处于凉凉的状态。

2021 年 5 月，Telegram 社区自发成立的 Newton 开发者社群开始继续研究 TON 并推进 TON 项目的发展。

2021 年，Newton 更名为 TON Foundation，TON 也由原来的 Telegram Open Network 更改为 The Open Network，链上的加密Token也变成了 TON，其目标是成为最易使用的支付方式。从 2020 年 6 月开始，TON 总供应量 98.55％开放挖矿，两年后，所有TON全部被产出。

在 2022 年 4 月 12 日，TON Foundation 启动其生态系基金，并获得一些机构的 2.5 亿美元投资，该基金主要用于资助 TON 生态项目的发展。在 TON Foundation 的推动下，TON陆续上线一些平台。

TON最初是为了服务 Telegram 而创建的，尽管在过程中遇到了一些阻碍，但 Telegram 用户迟早都会接触到TON生态系统。其他区块链项目在获取新用户方面面临的主要困难是使用难度高以及进入门槛高。但 TON 与 Telegram 应用基本无缝地连接在一起，难度大大降低。2022 年 4 月，TON 基金会宣布为 Telegram 提供钱包机器人，意味着 Telegram 用户可以直接在 Telegram 中收发TON 和兑换其它加密资产。

随着这几年的发展，社区持续为TON增加更多使用场景，如 DeFi、定期补贴计划等，扩大用户群体。TON逐渐成为生态的基础货币，在 DeFi、NFT 等领域不断扩大应用场景。

总体来说，Telegram 打造 TON 失败被 SEC 阻断，但 TON 技术开源得到社区支持，成功独立发展壮大。然而，Telegram 创始人在宣布不再参与 TON 的开发时，明确表示不会对基于 TON 构建的技术网络有任何联系或支持，正因为 Telegram 创始人的表态，使得该项目被大家所忽视，没有官方支持，大家的普遍观点便是，师出无名，做起来的可能性极低。

现状

Telegram 创始人的态度在这几年间逐渐发生转变，从早期的排斥不认可，官方不会有任何支持，到 2022 年 8 月开始公开赞赏 TON 的域名拍卖。他提出 Telegram 也可以考虑为用户名、群组和频道建立拍卖市场，同时试着采用TON作为这些未来市场的底层区块链支持。

Token 2049 活动中，Telegram 官方与 TON 基金会官宣合作关系，Telegram 整合 TON 所推出的自托管加密钱包「TON Space」，允许直接在 Telegram 菜单中访问 Wallet，完成 Crypto 自循环。

TON Space 用户可以通过 Telegram 账户与 TON 生态应用无缝连接，用户可以直接从基于 TON 的去中心化应用（dApp）中连接到 TON Space，并享受其提供的功能和服务。TON Space 充当区块链账户，支持生态系统中的TON等资产。有人将 TON Space 之于 Telegram，跟微信支付之于腾讯对比，来说明这次合作的重要性。

虽然，目前媒体对于 Telegram 的生态讨论热度很高，但在双方宣布合作之后，生态发展其实并没有带来多少增长，据 defillima 的数据显示，目前 Ton 的 TVL 仅为 1686 万，并没有明显的资金流入。

Ton 的 TVL 变化来源：hellobtc.pro

有人认为TON短期亮眼的表现完全是因为 Telegram Bot 的原因，官方的合作并没有起到多大作用。而且目前TON生态表现一般，大多项目属于复刻以太坊生态，并没有任何亮眼之处，但也有人持相反观点，认为将来生态会有爆款出现，毕竟月活 8 亿，是个很恐怖的数字，和推特微信处于同一个量级，而且是 Crypto 用户聚集地，TON生态值得关注。

小结

以上，便是目前 Telegram 与TON 生态的发展，目前，TON市值排在 12 位，一些人认为这是项目方强控的结果，大多筹码集中在项目方手中，至于是否值得关注，则见仁见智。

Похожее

Silicon Valley 'Startup Guru' Steve Hoffman: Web3 + AI Could Be a Trap

Silicon Valley investor and "Godfather of Startups" Steve Hoffman warns that combining Web3 with AI is likely a trap, not a promising venture. In an interview, Hoffman argues that while AI is a foundational technology touching all industries, Web3 adds complexity, friction, and regulatory risk without solving mainstream consumer or business needs. He advises founders to focus on deep, specialized applications where startups can out-iterate giants, rather than on generic features easily replicated by large tech companies. Hoffman observes that Silicon Valley will lead foundational AI research, while China excels at rapid, large-scale application and commercialization, particularly in robotics. He stresses that AI-driven autonomous agents capable of collaborative, multi-step tasks are 2-4 years away, which will cause significant job displacement. The solution is not to slow AI but to redesign business models around human-AI collaboration and reform social systems like education and retraining. For startups, Hoffman recommends focusing on vertical, expertise-heavy domains to build defensibility. He sees major opportunities in AI fraud detection and cybersecurity. Key founder mindsets include systemic thinking over feature-focus, relentless customer centricity, building adaptive teams, and deeply understanding AI's capabilities and limits. Hoffman is also leading a non-profit initiative to establish university centers aimed at training future leaders in responsible, human-value-aligned AI innovation.

marsbit18 мин. назад

Silicon Valley 'Startup Guru' Steve Hoffman: Web3 + AI Could Be a Trap

marsbit18 мин. назад

Token Inefficient, Economy Tokenless

The article "Tokens Aren't Economical, Economics Aren't Tokenized" analyzes a pivotal shift in the AI industry from a technology-driven narrative to one dominated by capital efficiency. It highlights two concurrent trends: a severe capital shortage due to the exorbitant and recurring costs of compute (e.g., OpenAI's high burn rate) and a wave of corporate spin-offs where major tech companies are separating their AI units (like Kuaishou's Kling and Baidu's Kunlunxin). The core argument is that AI's "anti-internet" business model, where user growth increases costs rather than profits, has created a disconnect between high valuations and actual cash flow. Spin-offs address this by allowing AI assets to be valued independently. Within a parent company, they are seen as cost centers, but as standalone entities, they are priced based on their growth potential and scarcity in the primary market, leading to massive valuation premiums (e.g., Kling's estimated value tripling post-spin-off). The industry is at an inflection point, moving from "model worship" to "value realization." The competition is evolving from a pure compute (GPU) race to a broader focus on systemic efficiency and full-stack engineering (involving CPUs and orchestration) to achieve viable commercialization. The year 2026 is framed as a critical moment where the industry must definitively answer how to economically translate AI capability into tangible business value, reshaping the sector's future power structure.

marsbit23 мин. назад

marsbit23 мин. назад

Crossing the 'Memory Wall': The Wafer-Level Revolution and Computing Power Routes in the AI Inference Era

In 2026, a historic shift occurred in AI as major cloud providers' inference spending surpassed training spending for the first time, signaling a move from "building large models" to "using large models." This shifts the core challenge from computing power to the "memory wall"—the bottleneck of data movement (model weights, activations, KV Cache) between external DRAM and processors, where energy and latency from data transfer far exceed computation itself. Companies like Nvidia face GPU idle time due to bandwidth limits. In contrast, Cerebras Systems adopts a radical "wafer-scale" approach with its Wafer-Scale Engine (WSE). Instead of cutting a silicon wafer into many chips, Cerebras uses almost the entire wafer as one massive chip (WSE-3). This design provides 44GB of on-chip SRAM, delivering memory bandwidth thousands of times higher than traditional HBM (e.g., 21 PB/s vs. Nvidia B200). For LLM inference, weights are streamed layer-by-layer from external MemoryX storage to the chip, avoiding HBM bottlenecks. This results in token generation speeds 1.5–5 times faster than Nvidia's B200 in some models and significant advantages in first-token latency and long-context tasks. Additionally, Cerebras's architecture offers much lower interconnect power consumption (0.15 pJ/bit vs. GPU's ~10 pJ/bit). However, Cerebras faces challenges: SRAM scaling has slowed with advanced nodes, limiting future capacity gains; the chip requires specialized liquid cooling and custom software stacks; and its external I/O bandwidth (150 GB/s) is low compared to NVLink, hindering multi-system scaling for very large models. Competition is intensifying. Major players are pursuing three paths: 1) Developing proprietary inference ASICs (e.g., Google TPU, Microsoft Maia), 2) Leveraging advanced packaging (e.g., TSMC's SoW) to democratize wafer-scale-like integration, potentially eroding Cerebras's process advantage within a few years, and 3) Exploring optical interconnects for ultimate bandwidth. Commercially, Cerebras is transitioning from a hardware vendor to a service provider, facing the immense challenge of building high-power, specialized data centers to meet large contracts (e.g., 250MW/year from 2026–2028). In conclusion, the AI inference era presents a fundamental architectural trade-off. Cerebras opts for extreme physical optimization for low-latency, single-task performance, while Nvidia prioritizes versatility and massive cluster throughput. The path forward remains uncertain, with technology and business models still evolving in the race toward advanced AI.

marsbit28 мин. назад

Crossing the 'Memory Wall': The Wafer-Level Revolution and Computing Power Routes in the AI Inference Era

marsbit28 мин. назад

Has Bitcoin's 'Rebound Ended', Officially Entering the Late Bear Market Phase?

**Title: Has Bitcoin's Rebound Ended, Entering the Late Bear Market Phase?** **Summary:** Bitcoin's price has declined by 13% this week, signaling a potential return to late-stage bear market conditions. The price fell to around $67k, positioned between the Realized Price and Realized Cap Weighted Average. For the first time since early 2022, the Short-Term Holder cost basis has dropped below this key average, confirming a hallmark of late-cycle bear markets. Profitability metrics have collapsed sharply. The 7-day average of the Realized Profit/Loss ratio plummeted from a local high of 3.16 to 0.29, mirroring the February panic sell-off. Critically, the 90-day average never breached the threshold of 2, indicating the recent rally to $82k was a bear market bounce, not a structural shift. Realized losses surged to $1.35 billion daily, with $770 million coming from Long-Term Holders selling at a loss. This accelerating redistribution of supply from weak to strong hands is a necessary but ongoing process for a market bottom. The rally stalled almost precisely at the aggregate cost basis (~$83k) of US spot Bitcoin ETF investors, turning that level into strong resistance and leaving the average ETF holder underwater again. Spot market flows have turned decisively negative, showing sellers are dominating order books despite the price drop. While a significant futures long liquidation event cleared over $400 million in leverage, providing a potential reset, sustained spot demand is yet to materialize. Options markets continue to price in higher future volatility (Implied Volatility) than recent price action (Realized Volatility) has shown, with a persistent skew towards put options, indicating ongoing demand for downside protection. In conclusion, multiple metrics point to a fragile market structure. Resistance at the ETF cost basis, accelerating realized losses, dominant spot selling, and cautious options pricing all suggest the bear market trend persists. A sustainable recovery likely requires a resurgence of spot demand, ETF holders returning to profit, and a clear reduction in selling pressure.

marsbit29 мин. назад

Has Bitcoin's 'Rebound Ended', Officially Entering the Late Bear Market Phase?

marsbit29 мин. назад

TechFlow Intelligence Agency: Anthropic Calls for Global Pause in AI Development While Preparing for Trillion-Dollar IPO; SpaceX IPO Roadshow Heats Up, But S&P 500 Rejects Fast-Track Inclusion

In today's TechFlow Intelligence Briefing, several major tech stories highlight a growing theme of trust and credibility gaps across AI, crypto, and finance. AI company Anthropic has publicly called for a global pause in AI development, citing risks from Claude's "recursive self-improvement." Ironically, this coincides with reports the company is preparing for a massive IPO targeting a near $1 trillion valuation. This perceived hypocrisy, coupled with widespread user complaints about Claude's declining performance, is sparking debate over whether the safety warning is genuine or a competitive tactic. Meanwhile, in a substantive security move, Anthropic open-sourced a framework for AI-powered vulnerability discovery. In the crypto market, Bitcoin's price drop below $61,000 triggered over $1.16 billion in liquidations, flipping the market into a state where more BTC is held at a loss than at a profit, a historical bearish signal. On the corporate front, SpaceX's highly anticipated IPO is generating immense Wall Street excitement, with Goldman Sachs projecting 100x revenue growth by 2030. However, the S&P 500 has refused to fast-track the company's inclusion post-IPO, potentially limiting immediate institutional demand. Separately, ByteDance's AI app Doubao lost over 6 million monthly active users after introducing a subscription model, highlighting the challenges of AI monetization. Other notable developments include Nvidia certifying HBM4 memory from Samsung, SK Hynix, and Micron; Cloudflare's acquisition of front-end tooling company VoidZero; and its CEO warning that bot traffic now exceeds human traffic online. The underlying narrative connects these events: a trust crisis. From AI firms' contradictory actions and crypto volatility to the clash between SpaceX's hyped narrative and institutional rules, a pattern is emerging where stated intentions and actual practices are increasingly misaligned.

marsbit44 мин. назад

TechFlow Intelligence Agency: Anthropic Calls for Global Pause in AI Development While Preparing for Trillion-Dollar IPO; SpaceX IPO Roadshow Heats Up, But S&P 500 Rejects Fast-Track Inclusion

marsbit44 мин. назад

Торговля

Спот

Фьючерсы

Обсуждения

Добро пожаловать в Сообщество HTX. Здесь вы сможете быть в курсе последних новостей о развитии платформы и получить доступ к профессиональной аналитической информации о рынке. Мнения пользователей о цене на TON (TON) представлены ниже.

背靠 8 亿月活社交巨头，TON 生态将昙花一现还是高歌猛进？

Введение

Похожее

Silicon Valley 'Startup Guru' Steve Hoffman: Web3 + AI Could Be a Trap

Token Inefficient, Economy Tokenless

Crossing the 'Memory Wall': The Wafer-Level Revolution and Computing Power Routes in the AI Inference Era

Has Bitcoin's 'Rebound Ended', Officially Entering the Late Bear Market Phase?

TechFlow Intelligence Agency: Anthropic Calls for Global Pause in AI Development While Preparing for Trillion-Dollar IPO; SpaceX IPO Roadshow Heats Up, But S&P 500 Rejects Fast-Track Inclusion

Торговля

Популярные статьи

Как купить TON

Обсуждения

Топ вопросы

Популярные категории

Популярные теги