"From Slavery in North Korea to Jeff Bezos’s Gulfstream: The Intersection of Oppression and Technology"

"From Slavery in North Korea to Jeff Bezos’s Gulfstream: The Intersection of Oppression and Technology"

In today's world, oppression takes on many forms. From unequal pay for women to limited opportunities for advancement, the fight for equality and justice is ongoing. But as I delved deeper into the issue, I realized that true freedom of thought can only be achieved by disconnecting from the noise of the mainstream media and connecting with the wisdom of the past.

In the realm of technology, the demand for high-performance GPUs has skyrocketed. Startups are utilizing large open-source models for fine-tuning, while established companies are building new models from scratch. The Nvidia H100 GPUs have emerged as the go-to choice for their speed and efficiency in both training and inference for language model models (LLMs). The H100's superior memory bandwidth, FLOPS, and compute performance make it the preferred option for companies looking to maximize their performance per dollar.

But why aren't more companies using AMD GPUs? The answer lies in the time it takes to make the switch. While theoretically possible, the reality is that the development time required to get everything working with AMD GPUs can delay a company's entry into the market. CUDA, NVIDIA's proprietary parallel computing platform, has become the industry standard, creating a moat around the company and making it difficult for competitors to penetrate the market.

The battle between H100s and A100s is an ongoing one. While A100s offer faster performance for certain tasks, such as 16-bit inference, H100s are favored for their scalability and faster training times. This is crucial for startups looking to compress time to launch or train their models. The cost of these GPUs can be significant, with a single DGX H100 box with 8 H100 GPUs priced at $460k, including required support. However, startups can benefit from the Inception discount, which can save them up to $50k on each DGX H100 box.

So how many GPUs do companies actually need? The numbers are staggering. GPT-4, for example, was likely trained on anywhere between 10,000 to 25,000 A100s. Large companies like Meta, Tesla, and Stability AI have thousands of A100s in their arsenal. Inflection used 3,500 H100s for their GPT-3.5 equivalent model. The demand for H100s is projected to be in the hundreds of thousands, with estimates ranging from 432k to over 1 million H100s needed by various companies and cloud providers.

Producing these GPUs is no small feat. TSMC, the manufacturer of H100s, takes approximately 6 months from production to packaging and testing before the GPUs are ready to be sold to customers. One of the bottlenecks in the process is the CoWoS (3D stacking) packaging at TSMC.

The big clouds, such as Azure, Oracle, Lambda Labs, AWS, and Google Cloud, have all launched their H100 previews at different times. Nvidia allocates GPUs per customer, with a preference for customers with strong brand names or startups with a proven track record. They also consider the end customer, as they want to ensure that their GPUs are being used by reputable companies rather than direct competitors.

In conclusion, the intersection of oppression and technology highlights the importance of fighting for equality and justice in all aspects of society. The demand for high-performance GPUs reflects the growing need for advanced technology in various industries. As we navigate this landscape, it is crucial to stay informed, think critically, and support initiatives that promote inclusivity and fairness.

Actionable Advice:

1. Stay informed about the latest advancements in technology and their impact on society. This will help you understand the challenges and opportunities that arise in different industries.
2. Support companies and initiatives that prioritize diversity and equality. By championing these causes, we can create a more inclusive and fair world for everyone.
3. Continuously seek knowledge from the great minds of the past. By disconnecting from the noise of the daily news cycle and connecting with timeless wisdom, we can develop a deeper understanding of the problems we face and find innovative solutions.

Remember, the fight against oppression and the pursuit of technological advancement go hand in hand. By working together, we can create a future where equality and innovation thrive.