VC Firms Break Taboo, Back Both OpenAI and Anthropic in AI Race

Silicon Valley's venture capital landscape is undergoing a seismic shift as major firms break a long-standing taboo by investing in competing AI startups OpenAI and Anthropic simultaneously. This strategic pivot reflects the intensifying AI arms race and the massive capital requirements needed to compete in the foundation model space.

The End of the "One Startup Per Category" Rule

For decades, venture capital firms operated under an unwritten rule: pick one horse per category and ride it to victory. This approach helped maintain clear allegiances and avoid conflicts of interest. However, the AI race has fundamentally altered this calculus.

Bloomberg reports that some of the biggest VC firms are now backing both OpenAI and Anthropic, recognizing that the AI foundation model market may support multiple winners rather than a single dominant player. This shift comes as both companies require billions in funding to train increasingly large models and build the infrastructure needed to compete.

Why VCs Are Changing Their Approach

The decision to invest in competing AI companies stems from several factors:

Massive Capital Requirements: Training frontier AI models costs hundreds of millions to billions of dollars. VCs need to ensure their portfolio companies have access to sufficient capital, even if that means backing multiple players in the same space.

Uncertain Market Dynamics: Unlike traditional software markets, the AI foundation model space remains highly uncertain. No one knows which architectural approaches, safety philosophies, or business models will ultimately prevail.

Strategic Value Beyond Financial Returns: Many VCs view their investments in AI companies as strategic bets on the future of technology, not just financial opportunities. Having exposure to multiple approaches provides valuable insights and relationships.

The Scale of Investment Needed

The capital requirements for AI companies have grown exponentially. OpenAI's latest funding round reportedly values the company at over $150 billion, while Anthropic has raised billions from investors including Amazon and Google. These valuations reflect the enormous costs of:

• Training runs costing $100M+ each
• Building and maintaining massive GPU clusters
• Hiring top AI research talent
• Scaling inference infrastructure

Implications for the AI Ecosystem

This shift in VC strategy has several implications for the broader AI ecosystem:

Increased Competition: With more well-funded players, the competition for AI supremacy will likely intensify, potentially accelerating innovation but also increasing the risk of market fragmentation.

Consolidation Pressure: Despite the influx of capital, the market may still consolidate around a few dominant players due to the winner-take-all dynamics of foundation models.

New Investment Models: VCs may need to develop new frameworks for evaluating and managing investments in competing AI companies, balancing financial returns with strategic considerations.

The Broader AI Landscape

The VC shift comes amid rapid developments across the AI industry:

Open Source Competition: Chinese startup Zhipu AI launched GLM-5, claiming best-in-class performance among open-source models. The company plans to raise prices by 30% due to surging demand.

Enterprise AI: Microsoft is pursuing "true self-sufficiency" in AI by building enterprise and healthcare-focused models, reducing reliance on OpenAI.

Government Involvement: The Pentagon is pushing OpenAI, Anthropic, and others to make their AI tools available on classified networks without standard user restrictions.

Regulatory Scrutiny: The FTC is urging Apple to review its News platform's curation practices following studies claiming bias in content promotion.

What This Means for Startups

For AI startups, the changing VC landscape presents both opportunities and challenges:

Opportunities: More capital availability and willingness to back competing approaches could benefit innovative startups with novel approaches.

Challenges: Increased competition for talent and compute resources, plus the difficulty of standing out in an increasingly crowded field.

Looking Ahead

The breaking of the "one startup per category" taboo signals a fundamental shift in how venture capital approaches high-stakes, capital-intensive markets like AI. As the technology continues to evolve and the stakes grow higher, we can expect further innovation in investment strategies and potentially new models for funding and scaling AI companies.

The AI race is reshaping not just technology but the very foundations of how innovation is funded and commercialized. Whether this leads to a more vibrant ecosystem with multiple successful players or simply accelerates the path to consolidation remains to be seen.