Hi, AI Futurists!

According to Sam Altman, the CEO of OpenAI and possibly the most influential person in the AI Age, “Compute is going to be the currency of the future, maybe the most precious commodity in the world.”

Why Compute is the Currency of the AI Age

By definition, LLMs (Large Language Models) require a large number of parameters to make complex decisions or create advanced solutions. For instance, GPT-3 uses 175 billion parameters, while GPT-4 uses 1 trillion parameters, resulting in a context window of 3,000 words for GPT-3.5 compared to 25,000 words for GPT-4.

The Overwhelming Cost of Training an AI Model

With so much hype in creating AI businesses, companies around the world need immense computational power (GPUs) to train their AI models. Large companies have the advantage of having the capital to buy thousands of GPUs in advance, with each NVIDIA GPU costing around $73,000.

The New Business Model for AI Companies Taking Shape

This brings an unfair competitive advantage for big players, as small companies without the funds can’t even start their businesses. The solution lies in leasing GPUs and letting companies use them, a model led by VCs like Andreessen Horowitz. In return, these VCs own equity in the company.

Without further ado, let’s get started with how compute will become the currency driving new businesses and shaping the future.

TODAY ON THE BIG AI IDEA

• Capitalizing on Compute: How VCs are Increasing Their Stake in the AI Space While Powering Startups

• GPU-Rental Business:Alternative Models for AI Innovation

• Government-Driven AI Compute Market:Leveling the Playing Field

Capitalizing on Compute:How VCs are Increasing Their Stake in the AI Space While Powering Startups

As the tech landscape evolves, compute power has become a critical resource, especially for AI startups.

The massive computational demands to train AI models create a significant barrier to entry, giving an unfair competitive advantage to large companies that can afford thousands of GPUs.

Smaller startups often struggle to access the necessary resources, hindering innovation and growth in the AI space.

VCs Fueling the AI Compute Race

Several venture capital firms are stepping in to level the playing field by providing GPUs to AI startups. Here’s a look at the most active VCs in this space:

• Andreessen Horowitz:This VC giant is stockpiling thousands of Nvidia GPUs to lease to AI startups in exchange for equity.

• Nat Friedman and Daniel Gross: These investors have committed to providing thousands of GPUs to portfolio companies at below-market rates.

• Conviction Partners: This firm is also ensuring startups get access to AI chips through initiatives similar to those of Andreessen Horowitz.

• Index Ventures: Partnering with Oracle, Index Ventures is offering Nvidia chips to emerging AI startups at no cost, easing the entry barrier.

The Impact on the AI Space

The actions of these VCs are reshaping the AI landscape in several ways:

• Increased Access to Resources: Startups now have more opportunities to access the compute power necessary for AI development.

• Accelerated Innovation: With more companies able to train models, the pace of AI advancements is likely to increase.

• Shift in Competitive Dynamics: The traditional competitive advantage of large companies is being challenged as smaller firms gain access to critical resources.

• Enhanced Investment Returns: VCs providing GPUs gain equity in potentially high-growth startups, boosting their returns.

As the demand for compute power continues to rise, venture capital firms are playing a crucial role in democratizing access to this vital resource.

By stockpiling and leasing GPUs, these VCs are not only supporting AI startups but also reshaping the competitive landscape of the AI industry.

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