Crypto index funds ‘a big deal’ as market complexity grows: Bitwise CIO

cointelegraphPubblicato 2025-12-09Pubblicato ultima volta 2025-12-09

Introduzione

Bitwise CIO Matt Hougan predicts crypto index funds will surge in popularity in 2026 as investors seek diversified exposure amid growing market complexity. He argues that predicting individual token performance is nearly impossible due to regulatory, macroeconomic, and execution variables. Instead, he advocates for market-cap-weighted crypto index funds to capture broad growth without risking wrong bets on specific chains. Hougan believes the market could grow up to 20 times in a decade, driven by tokenization, stablecoins, DeFi, and other emerging use cases. Despite recent market gains fueled by pro-crypto policies, uncertainty around tariffs and interest rates persists.

Funds that track a basket of cryptocurrencies are likely to rocket in popularity next year as investors look to get easy exposure to a broader range of digital assets, according to Bitwise’s investment chief Matt Hougan.

“Crypto index funds are going to be a big deal in 2026,” Hougan said in a note on Monday. “The market is getting more complex and the use cases are multiplying.”

He added that while the overall crypto market is poised to grow, it isn’t possible to predict which tokens will perform, so owning a fund that tracks the market is a “great place to start,” although it’s “not right for everyone.”

Many exchange-traded fund issuers, including Bitwise, offer funds that track multiple cryptocurrencies, drawing inspiration from indexes such as the S&P 500, which track the top 500 companies on US stock exchanges.

Multi-crypto ETFs already exist, with some going live in the US earlier this year that hold crypto in proportion to each token’s market capitalization. However, these have seen relatively modest inflows as they largely hold Bitcoin (BTC), which currently dominates nearly 60% of the market, per CoinGecko.

“Buy the market” as crypto is unknowable

Hougan said that despite his experience and network of experts within crypto, he can’t say “with confidence which chain will win, or precisely how things will turn out.”

“At this stage of crypto’s development, I’d argue it’s unknowable,” he added. “Outcomes will be shaped by regulation, execution, macro conditions, the actions of a few key individuals, luck, and a hundred other variables.”

“Forecasting all of that correctly would require supernatural foresight.”

Crypto markets rallied from November 2024 to January through Donald Trump’s presidential election and inauguration and have remained elevated on his pro-crypto policies.

However, crypto has felt the negative effects of sweeping US tariffs and uncertainty over further interest rates cuts as traditional finance becomes more involved in the market.

“Given that uncertainty, my approach is simple: I buy the market,” Hougan said. “Specifically, I buy a market-cap-weighted crypto index fund.”

He added that crypto “will be far more important in 10 years than it is today,” and the market could grow up to 20 times over that time.

Hougan pointed to Securities and Exchange Commission chair Paul Atkins’ comment on Wednesday that the US financial system could embrace tokenization in a “couple of years.”

Related: Bank of America backs 1%–4% crypto allocation, opens door to Bitcoin ETFs

“Stablecoins will matter more. Tokenization will matter more. Bitcoin will matter more. And I think a dozen other major use cases will follow: prediction markets, decentralized finance (DeFi), privacy tech, digital identity,” Hougan said.

“I don’t want to risk picking the wrong chain,” he added. “Imagine correctly calling a market that goes up 100,000x—and still underperforming because you backed the wrong horse.”

“So I use a crypto index fund as the core of my portfolio,” Hougan said, “knowing that, however crypto evolves, I’ll own exposure to the potential winners.”

Magazine: Solana vs Ethereum ETFs, Facebook’s influence on Bitwise — Hunter Horsley

Letture associate

Gensyn AI: Don't Let AI Repeat the Mistakes of the Internet

In recent months, the rapid growth of the AI industry has attracted significant talent from the crypto sector. A persistent question among researchers intersecting both fields is whether blockchain can become a foundational part of AI infrastructure. While many previous AI and Crypto projects focused on application layers (like AI Agents, on-chain reasoning, data markets, and compute rentals), few achieved viable commercial models. Gensyn differentiates itself by targeting the most critical and expensive layer of AI: model training. Gensyn aims to organize globally distributed GPU resources into an open AI training network. Developers can submit training tasks, nodes provide computational power, and the network verifies results while distributing incentives. The core issue addressed is not decentralization for its own sake, but the increasing centralization of compute power among tech giants. In the era of large models, access to GPUs (like the H100) has become a decisive bottleneck, dictating the pace of AI development. Major AI companies are heavily dependent on large cloud providers for compute resources. Gensyn's approach is significant for several reasons: 1) It operates at the core infrastructure layer (model training), the most resource-intensive and technically demanding part of the AI value chain. 2) It proposes a more open, collaborative model for compute, potentially increasing resource utilization by dynamically pooling idle GPUs, similar to early cloud computing logic. 3) Its technical moat lies in solving complex challenges like verifying training results, ensuring node honesty, and maintaining reliability in a distributed environment—making it more of a deep-tech infrastructure company. 4) It targets a validated, high-growth market with genuine demand, rather than pursuing blockchain integration without purpose. Ultimately, the boundaries between Crypto and AI are blurring. AI requires global resource coordination, incentive mechanisms, and collaborative systems—areas where crypto-native solutions excel. Gensyn represents a step toward making advanced training capabilities more accessible and collaborative, moving beyond a niche controlled by a few giants. If successful, it could evolve into a fundamental piece of AI infrastructure, where the most enduring value in the AI era is often created.

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Gensyn AI: Don't Let AI Repeat the Mistakes of the Internet

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Why is China's AI Developing So Fast? The Answer Lies Inside the Labs

A US researcher's visit to China's top AI labs reveals distinct cultural and organizational factors driving China's rapid AI development. While talent, data, and compute are similar to the West, Chinese labs excel through a pragmatic, execution-focused culture: less emphasis on individual stardom and conceptual debate, and more on teamwork, engineering optimization, and mastering the full tech stack. A key advantage is the integration of young students and researchers who approach model-building with fresh perspectives and low ego, prioritizing collective progress over personal credit. This contrasts with the US culture of self-promotion and "star scientist" narratives. Chinese labs also exhibit a strong "build, don't buy" mentality, preferring to develop core capabilities—like data pipelines and environments—in-house rather than relying on external services. The ecosystem feels more collaborative than tribal, with mutual respect among labs. While government support exists, its scale is unclear, and technical decisions appear driven by labs, not state mandates. Chinese companies across sectors, from platforms to consumer tech, are building their own foundational models to control their tech destiny, reflecting a broader cultural drive for technological sovereignty. Demand for AI is emerging, with spending patterns potentially mirroring cloud infrastructure more than traditional SaaS. Despite challenges like a less mature data industry and GPU shortages, Chinese labs are propelled by vast talent, rapid iteration, and deep integration with the open-source community. The competition is evolving beyond a pure model race into a contest of organizational execution, developer ecosystems, and industrial pragmatism.

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Why is China's AI Developing So Fast? The Answer Lies Inside the Labs

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3 Years, 5 Times: The Rebirth of a Century-Old Glass Factory

Corning, a 175-year-old glass company, is experiencing a dramatic revival as a key player in AI infrastructure, driven by surging demand for high-performance optical fiber in data centers. AI data centers require vastly more fiber than traditional ones—5 to 10 times as much per rack—to handle high-speed data transmission between GPUs. This structural demand shift, coupled with supply constraints from the lengthy expansion cycle for fiber preforms, has created a significant supply-demand gap. Nvidia has invested in Corning, along with Lumentum and Coherent, in a $4.5 billion total commitment to secure the optical supply chain for AI. Corning's competitive edge lies in its expertise in producing ultra-low-loss, high-density, and bend-resistant specialty fiber, which is critical for 800G+ and future 1.6T data rates. Its deep involvement in co-packaged optics (CPO) with partners like Nvidia further solidifies its position. While not the largest fiber manufacturer globally, Corning's revenue from enterprise/data center clients now exceeds 40% of its optical communications sales, and it has secured multi-year supply agreements with major hyperscalers including Meta and Nvidia. Financially, Corning's optical communications revenue has surged, doubling from $1.3 billion in 2023 to over $3 billion in 2025. Its stock price has risen nearly 6-fold since late 2023. Key future catalysts include the rollout of Nvidia's CPO products and the scale of undisclosed customer agreements. However, risks include high current valuations and potential disruption from next-generation technologies like hollow-core fiber. The company's long-term bet on light over electricity, maintained even through the telecom bubble crash, is now being validated by the AI boom.

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3 Years, 5 Times: The Rebirth of a Century-Old Glass Factory

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