Venture Capital Review of 2025: Computing Power is King, Narrative is Dead | Bee Network

Venture Capital Review of 2025: Computing Power is King, Narrative is Dead | Bee Network Login الأخبار الشائعة منصة إطلاق ميمي وكلاء الذكاء الاصطناعي ديسي مستكشف السلسلة الأعلى لنوبي 100x عملات معدنية لعبة النحل المواقع الأساسية يجب أن يكون لديك التطبيق مشاهير التشفير ديبين الناشئين الأساسية كاشف الفخ الأدوات الأساسية المواقع المتقدمة التبادلات أدوات NFT أهلاً، خروج عالم الويب 3 ألعاب تطبيق خلية نحل منصة النمو إعلان يبحث إنجليزي إعادة شحن العملات تسجيل الدخول تحميل ويب 3 يوني ألعاب تطبيق خلية نحل إعلان بيت•تحليل•Venture Capital Review of 2025: Computing Power is King, Narrative is Dead Venture Capital Review of 2025: Computing Power is King, Narrative is Deadتحليلمنذ شهرينجديدوايت 18٬787 16 Compiled and edited by: BitpushNews

Structural problems in the تشفير سوق The adoption of on-chain financial instruments and the trend toward the machine economy are booming.

Over the past year, we have witnessed tremendous expansion of blockchain-native finance across five dimensions: (1) stablecoins, (2) decentralized lending and trading, (3) perpetual contracts, (4) prediction markets, and (5) digital asset vaults (DATs). The regulatory environment in the United States has become extremely favorable, which has led to an increase in both the number of projects and risk appetite.

Leaving aside the uncertainties brought about by tariffs and market structures, a tolerant macroeconomic environment also provides fertile ground for crypto innovation to take root. These trends are well-known and need no further elaboration with data.

However, 2025 will be an extremely difficult year for long-term investors in tokens and crypto assets other than Bitcoin.

If you’re a trader or banker, things are probably not so bad—we’ve seen record commissions for bringing DATs to market, and huge fees that exchanges like Binance are raking in during the listing process.

But for those of us with 3-5 years of investment experience, the market structure has always been terrible.

We are caught in a negative prisoner’s dilemma: token holders anticipate future selling pressure and therefore sell any and all assets; while market makers and exchanges that underpin the entire crypto economy adopt speculative positions focused solely on short-term gains. رمز مميز unlocking mechanisms and issuance prices often cripple projects before they even become profitable or find a market fit.

Furthermore, the structural market failure on October 10th clearly dealt a heavy blow to several major market players, and although the losses have not yet been disclosed, the aftershocks of the liquidation continue. The correlation among all crypto assets has risen to near 1, indicating industry-wide deleveraging by participants, despite their vastly different fundamental logics.

It’s easy to choose to back down and become cynical at this moment.

However, we prefer to conduct “سوق-to-market” comparisons as clearly as possible in order to plan for future developments.

The 2025 decline in the crypto investment sector is information, but not a تحديnitive conclusion. It’s quite possible that 2026 will see a massive liquidation in the private secondary market, at which point we will analyze how so many special purpose vehicles (SPVs) were issued at inflated valuations during the crypto boom.

At the same time, the vision of programmable finance and “robot money” continues to materialize, and we must continue to strive to find the best position for its inevitable rise.

For context, please see the chart below. This chart, zoomed in over the past decade, shows the market capitalization creation across several regions and industries.

When we look at this history, the value creation in the cryptocurrency and AI sectors is astonishing compared to the rest of the world.

European capital markets (approximately $2-3 trillion across countries) have made virtually no progress, merely maintaining the status quo. You’d be better off investing in government bonds, earning 3% interest annually, which likely creates more value. On the right side of the chart, India and China show a compound annual growth rate (CAGR) of 5-10%, with net market capitalization increases of approximately $3 trillion and $5 trillion respectively during the same period.

Having understood this scale, let’s look at our definition of “robot currency”:

(1) The “Magnificent 7” representing technology and AI has increased its market capitalization by about $17 trillion at a rate of 20% per year;

(2) The crypto asset market, which represents the modern financial track, increased by $3 trillion during the same period, with a compound annual growth rate of 70%.

This is the financial center of the future.

But being logically correct is not enough. We must delve deeply and meticulously into the parts of the value chain that have not yet been noticed by the world. Recall the discussions about robo-advisors in 2009, Neobanks in 2011, or DeFi in 2017; the vocabulary and connections were not yet formed, and it wasn’t until 2-5 years later that these findings solidified into clear business opportunities.

Value capture in the machine economy As a kind of “self-torture” exercise, we have compiled a 158-page summary report covering the most relevant players in the machine economy in 2025.

In the open market, 2025 will be a year in which “the strong get stronger and the weak fall behind”.

The clear winners are the owners of the physical and financial bottlenecks: electricity, semiconductors, and scarce computing power.

Bloom Energy, IREN, Micron, TSMC, and NVIDIA have all significantly outperformed the market as capital chases assets that “machines must pass through.”

Bloom and IREN are typical examples: they directly capitalize on the AI boom, turning urgency into revenue.

In contrast, traditional infrastructure such as Equinix performed poorly, reflecting the market’s perception that general-purpose capacity is far less valuable than power security and high-density customized computing power.

In the software and data sector, performance diverged along another dimension: (1) mandatory versus (2) optional. Platform-like enterprise systems with embedded workflows and mandatory renewals (such as Alphabet and Meta) continued their compound growth, both rising year-to-date as AI spending strengthened their existing distribution moats. ServiceNow and Datadog, despite their strong product capabilities, suffered from valuation pressures, bundling pressures from hyperscale cloud providers, and slower AI monetization. Elastic illustrates the downside: strong technical capabilities, but squeezed by cloud-native alternatives, and deteriorating unit economic returns.

The private equity market also exhibits a similar screening mechanism.

The companies that build upon existing models are the protagonists of this story, but their vulnerability is increasing. OpenAI and Anthropic are experiencing rapid revenue growth, but their neutrality, capital intensity, and margin compression are now clear risks. Scale AI serves as a cautionary tale this year: Meta’s partial acquisition destroyed its “neutral” image and triggered customer churn, demonstrating how quickly service-heavy business models can crumble once trust is broken. In contrast, companies that control value (Applied Intuition, Anduril, Samsara, and emerging fleet operating systems) appear better positioned, even if value realization remains largely confidential.

Tokenized networks were the weakest performing sector.

With very few exceptions, decentralized data, storage, agents, and automation protocols have underperformed because usage has failed to translate into token value capture.

Chainlink remains strategically important, but struggles to align its protocol revenue with a token economic model; Bittensor is the biggest bet in the crypto AI space, but doesn’t yet pose a substantial threat to Web2 Labs companies; Giza and similar agent protocols demonstrate real activity, but remain hampered by dilution and meager fees. The market no longer rewards “collaborative narratives” without mandatory fee mechanisms.

Value is accumulating in areas where machines are already paying for it—electricity, silicon, computing contracts, cloud bills, and regulated balance sheets—rather than in areas they might choose someday in the future.

In 2025, the market rewarded ownership of “choke points” while punishing projects with lofty ideals but lacking control over cash flow or computing power. The key to the future lies in identifying where economic power already exists and betting on assets that machines cannot bypass.

Key takeaways:

The realization of AI’s value is “one level deeper” than most people expect. Neutrality is now a first-class economic asset (see Scale AI). A “platform” is only effective when combined with a control point, not just a function. AI software is deflationary (pricing pressure); AI infrastructure is inflationary. Vertical integration is only important when it can lock in data or economic benefits. Token networks are repeatedly undergoing the same market structure tests. Having AI exposure alone is not enough; positioning quality determines everything. Robotics hardware and software will be the next hype cycle, and we may see similar waves of investment and selective winners.

Positioning in 2026 Over the past two years, we have built a core portfolio covering the key themes discussed here. Looking ahead to 2026, our positioning and investment execution will be further strengthened.

Next, I will talk about our holding strategy.

While the long-term vision of autonomous agents, robotics, and machine-native finance is on the right track, the market is currently experiencing extremely outrageous valuations in the private AI and robotics sectors. Aggressive secondary liquidity and implied valuations exceeding $100 billion mark a transition from the “discovery phase” to the “exit phase.”

As an early-stage fund with a fintech perspective, we must target these downstream spending channels:

Machine Transaction Surfaces: These are layers of economic activity that machines or their operators already handle, such as payments, billing, metering, routing, and the orchestration, compliance, custody, and settlement primitives of capital or computing power. Rewards are derived through transaction volume, acquisitions, or regulatory status, rather than speculative narratives. Walapay and Nevermined in our portfolio are examples.

Applied Infrastructure With Budgets: This refers to infrastructure that enterprises or platforms are already procuring, such as computing power aggregation and optimization, data services embedded in workflows, and tools with recurring expenses and switching costs. The focus is on ownership of the budget and the depth of integration. Examples include Yotta Labs and Exabits.

High-novelty opportunities: A few opportunities with asymmetric growth but uncertain timing: basic research, cutting-edge science, and AI-related cultural or IP platforms. Netholabs (a laboratory dedicated to extrapolating the complete digital brain of mice), which we recently invested in, fits this description.

Furthermore, we will invest more aggressively in equity until the structural issues in the token market are resolved. Previously, our exposure was 40% tokens and 40% equity, with the remaining 20% allocated flexibly. We believe the token space needs 12-24 months to digest the current predicament.

Key takeaways You don’t need to be a venture capitalist to learn from and benefit from these market dynamics.

Massive capital expenditures are flowing from tech giants to energy and component suppliers. A handful of companies are expected to emerge as trillion-dollar winners in the public markets, but they are choosing to remain private and divest their special purpose vehicles (SPVs). Publicly traded companies are struggling to defend themselves. Political power is centralizing and nationalizing these initiatives—whether it’s Musk and Trump, or China and DeepSeek—rather than supporting their decentralized alternatives in Web3. Robotics is intertwined with national manufacturing and war-industrial complexes.

In the creative industries (from games to movies and music), there is a growing resistance to AI, with people working with “human skills” rejecting robots that pretend to do the same things.

In the software, science, and mathematics industries, AI is seen as a great achievement that can help discover and build efficient business architectures.

We need to stop believing this collective illusion and return to reality. On the one hand, dozens of companies have already achieved annual revenues exceeding $100 million by serving users; on the other hand, the market is also rife with falsehoods and scams. These two points coexist and are not contradictory.

The new year will bring a complete reshuffle, but it also holds immense opportunities. Only by carefully navigating the tightrope of opportunity can one achieve success. Let’s meet again on the other side!

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