风险投资减缓投资Web3?

阿法兔研究笔记Publicado em 2022-09-06Última atualização em 2022-09-06

Resumo

从2022年Q3的风险投资数据表明,与近几个季度和2021年热度最高的时期相比,近期风险投资以区块链为重点的初创企业的投资正在急剧收缩。

在区块链世界中,极速波动的商业周期是行业的一部分,在狂热和消费时期过后,C端活动会减少,常见的观点是,市场繁荣期为Web3产品和相关服务带来了新的用户,而随后的萧条期则是大家更安静、开始以建设和研发为重点的工作。本文还是建议大家以辨证的态度去看待,不过,通过观察这个分析,大家可以对目前的市场有一些新的认知。

核心观点

从2022年Q3的风险投资数据表明,与近几个季度和2021年热度最高的时期相比,近期风险投资以区块链为重点的初创企业的投资正在急剧收缩。

来自Crunchbase和PitchBook的数据表明,近几个季度,风险投资进到Web3的资本总额约100亿美元。投资Web3的美元价值可能会减少一半以上,如果将2022年第三季度的数据与今年早期季度的融资数据进行比较,呈现典型的减缓态势。

关于Web3初创企业、市场和货币的探讨

在区块链世界中,极速波动的商业周期是行业的一部分,在狂热和消费时期过后,C端活动会减少,常见的观点是,市场繁荣期为Web3产品和相关服务带来了新的用户,而随后的萧条期则是大家更安静、开始以建设和研发为重点的工作。

下图是Coinbase在近期的披露中对这种模式的描述。

图片来源:Coinbase

不管你怎么看这个问题,似乎在这个以Build为主要模式的时刻,提供的资本确实较少。并且,任何风险投资基金领域在Q3没有那么活跃,还是可以理解的。因为上一波的初创企业和风险投资人都在消化之前的狂热周期。因此,对Web3初创企业或金融科技领域减少投资,并不奇怪。

在风险投资市场普遍放缓的情况下,为什么要特别关注Web3和区块链世界?之所以关注,是因为构建去中心化应用程序和基础设施的公司能够比其他行业冲的更快,并保持良好的业绩,但是遇到熊市,也可能面临更大的收缩。

数据情况

首先,目前创业公司的融资情况在全球范围内正在放缓,但并不是灾难性的。但是在综合数据中,我们发现了一些令人印象深刻的数据。例如,根据CB Insights,金融科技融资额从2021年第四季度的1362笔融资Deal,总共约384亿美元,下降到2022年Q2的1225笔Deal,约为204亿美元。Retail Tech在2021年Q2达到顶峰,共946笔交易,约为299亿美元,2022年第二季度只有710笔,约为132亿美元。

鉴于这样的情况,对Web3初创公司的投资并不令人惊讶。但是根据Crunchbase的数据统计,到2022年Q2,有关Web3融资的关键数据:

2021年第一季度:95亿美元

2021年第二季度:64亿美元

2021年第三季度:71亿美元

2021年第四季度:98亿美元

2022年第一季度:86亿美元

2022年第二季度:66亿美元

将2022第二季度与2021年第二季度进行比较时,Crunchbase数据集显示,今年第三季度,Web3创业公司融资额仅为7.19亿美元,尽管今年第三季度还没过完,但是已经过去三分之二了。

当然,风险投资数据很可能是不稳定的,所以把Crunchbase的图表与另一个数据来源(Pitchbok)进行比较,在PitchBook上查询了所有被称为 "Web3 "的风险投资轮次和专注于增长的VCPE交易,也发现了类似的数据迹象。

但是,虽然PitchBook证实了Crunchbase的数据,统计了第三季度区块链和Web3公司的总融资额约为24亿美元,PitchBook在2022年第一季度关于Web3融资数据是104亿美元。

无论是Crunchbase还是PitchBook,很明显,Web3的融资情况确实有下降的趋势。从资本市场的角度来看,如果投资不足,很可能意味着用于建设加密货币原生服务所需的人员和工具的资金并不充沛。当然,仍有部分资金在流动,不过因为很多公司在牛市备足了粮草,许多Web3初创公司仍然具备充足的资金。

那么,像A16Z这样募集了大量加密基金的公司呢?

早在2021年中期,A16Z就宣布专门投资Web3的22亿美元基金时,A16Z不仅投的更多、更快,也会努力解决监管环境问题(雇佣前监管负责人作为合伙人、给国会提案)。

简而言之,a16z似乎不仅对web3公司下赌注,还在努力确保整个加密赛道市成功。A16Z今年募了一个新的、更大的基金,还是比较执着的,在竞争对手收紧钱袋子的时候,a16z还是继续加码。也许在市场放缓时加大投资会给公司带来回报,因为如果a16z最终是正确的,它将会赚很多很多钱,但是其他风险投资公司貌似并不一定是这样。

Leituras Relacionadas

The War Without a Unified Name: The Domestic Tech Giants' World Model Landscape

The article outlines the diverse and fragmented landscape of "World Models" in China's tech industry, where major players are pursuing similar goals under different names like world foundational models, physical AI, or integrated within autonomous driving and embodied intelligence systems. The core aim is to enable AI to create an internal, dynamic environment for simulation, reasoning, and learning, reducing reliance on infinite real-world data. This "data engine" allows for unlimited generation, experimentation, and iteration. The report categorizes the approaches of different companies: * **Internet Giants:** Alibaba is developing models for linguistic, virtual, and physical worlds (Qwen-AgentWorld, HappyOyster, Qwen-RobotWorld). Tencent's HY-World focuses on 3D, game, and social scenarios. ByteDance leverages its vast video data for a potential "digital twin" model. Huawei integrates its model into industrial applications like smart cars and robotics without separately branding it. Baidu embeds world model capabilities within its Apollo autonomous driving and Ernie systems. * **Automakers:** Companies like NIO, Li Auto, XPeng, and Geely are using world models as virtual "driving schools" and "testing grounds." They generate complex scenarios (e.g., rain, snow) to train and validate autonomous driving systems in simulation, aiming for more capable and safer AI drivers. * **Autonomous Driving Suppliers:** Firms such as Momenta, Horizon Robotics, Haomo.ai, and DeepRoute.ai are building the underlying "world engines." They focus on large-scale video generation for simulation, reinforcement learning, and enhancing end-to-end autonomous driving models, often integrating these capabilities into commercial products. While startups bring focus and innovation, they face challenges like limited data, compute resources, and deployment channels. Large companies possess these advantages and are rapidly transitioning world models from research projects into core business infrastructure powering products in vehicles, games, and industry. The conclusion is that world models represent an evolution and convergence of existing AI fields into crucial industrial infrastructure, moving the competition from simply building a model to effectively deploying it to understand and interact with the physical world.

marsbitHá 11m

The War Without a Unified Name: The Domestic Tech Giants' World Model Landscape

marsbitHá 11m

The Crypto Industry Enters the 'Show Me' Era: Vision Alone Is No Longer Enough

The crypto industry has entered a "Show Me" era, where grand visions and white papers are no longer sufficient to gain traction. This shift is driven by increased skepticism, high-profile bad actors, and notably, the serious entry of traditional finance (TradFi) institutions like BlackRock, Fidelity, and JPMorgan Chase, which are launching real, scaled products such as tokenized funds and blockchain-based settlement. This raises the bar for what constitutes a credible project. The communication dynamic has fundamentally changed. The focus is no longer on "what you are building" but on "what you have built and who is using it." Startups must now provide a "proof stack": verifiable data like mainnet transaction volume and active wallets, genuine partnerships with signed contracts, and evidence of organic product-market fit from real users, not just investors. Announcements must be backed by concrete, chain-verifiable evidence. For communication strategies, this means leading with proven facts and hard data—even if modest—rather than speculative narratives. A compelling story must be grounded in demonstrated results. While vision remains important, the balance has inverted from 80% vision/20% substance to the opposite. This higher threshold ultimately benefits builders with genuine traction, filtering out noise and allowing their real signals to stand out clearly. The "Show Me" era is a permanent maturation, demanding that communication strategies prove value, not just promise it.

链捕手Há 42m

The Crypto Industry Enters the 'Show Me' Era: Vision Alone Is No Longer Enough

链捕手Há 42m

Meta Follows the Trend into Prediction Markets: Can It Avoid Repeating the Failure of the Metaverse?

Meta, the tech giant behind Facebook, has reportedly formed a team to develop "Arena," a new application focused on prediction markets. Users would use platform points to place bets on outcomes in politics, sports, and global events. This move follows Meta's massive, nearly $900 billion, losses from its heavily-invested metaverse division, Reality Labs. The prediction market industry is already showing strong demand, with leading platforms like Kalshi and Polymarket facilitating hundreds of billions in annual volume. Meta, with its 3.56 billion daily active users across its apps, possesses the unprecedented scale to bring this niche activity to a mainstream audience, similar to its past success in cloning features like Stories and Reels. However, Arena faces significant hurdles. Meta plans to start with a points-based system to avoid strict financial regulations, but this may dilute the core incentive of accurate prediction that real-money markets provide. More critically, Meta enters the space with a major trust deficit stemming from its past regulatory battles, notably the failed Libra/Diem stablecoin project, and its controversial history with political content and misinformation. The prediction market sector itself is under increasing regulatory scrutiny, with recent CFTC actions including fines and the first-ever insider trading case. While Meta's vast user base offers a unique opportunity to expand the market, its success hinges on navigating complex regulations and rebuilding the credibility necessary for a platform dealing with sensitive topics like elections. The outcome could range from Meta dramatically growing the industry to Arena becoming a high-profile regulatory target before it can scale.

Foresight NewsHá 59m

Meta Follows the Trend into Prediction Markets: Can It Avoid Repeating the Failure of the Metaverse?

Foresight NewsHá 59m

Trading

Spot
Futuros
活动图片