TCO
Taubman Centers Inc.
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Apparently the deal with NVIDIA was rushed ahead of AMD, it’s was half baked announcement. OpenAI got a better deal with AmD with better TCO. Why they need to stuck with nvidia

The misunderstanding here is in the media. Media thinks Blackwell and Rubin are GPUs but Jensen clearly talks about the solutions behind them. Rubin is making racks even denser and packing more special chips into a system.
So the 10x isn't from the chip itself which is probably more like 1.5-2x but with new components, new density, new networking and new SW to make state of the art training and inferencing 10x faster as a whole.
The single rack Rubin will certainly not be 10x but the data cetner Rubin will. This is also why Nvidia can easily maintain high margins because their customers spend billions for TCO in data centers. If Nvidia can make a Rubin data center 10x more efficient then they can easily ask 2x price for it.

The utilization of the GPU's increases and the marginal cost of the energy (TCO/FLOP) decreases. As of today, I bet some new chip SKU's and AZ combinations see just 10-20% utilization in the quieter periods of the year. Amy is saying that although the chips age, their utilization trends higher and that counterbalances the depreciation cost.
Energy is not the only marginal cost. Opex costs are not fully amortized. There *is* a marginal cost to every chip past just the energy.

Apparently the deal with NVIDIA was rushed ahead of AMD, it’s was half baked announcement. OpenAI got a better deal with AmD with better TCO. Why they need to stuck with nvidia

The misunderstanding here is in the media. Media thinks Blackwell and Rubin are GPUs but Jensen clearly talks about the solutions behind them. Rubin is making racks even denser and packing more special chips into a system.
So the 10x isn't from the chip itself which is probably more like 1.5-2x but with new components, new density, new networking and new SW to make state of the art training and inferencing 10x faster as a whole.
The single rack Rubin will certainly not be 10x but the data cetner Rubin will. This is also why Nvidia can easily maintain high margins because their customers spend billions for TCO in data centers. If Nvidia can make a Rubin data center 10x more efficient then they can easily ask 2x price for it.

The utilization of the GPU's increases and the marginal cost of the energy (TCO/FLOP) decreases. As of today, I bet some new chip SKU's and AZ combinations see just 10-20% utilization in the quieter periods of the year. Amy is saying that although the chips age, their utilization trends higher and that counterbalances the depreciation cost.
Energy is not the only marginal cost. Opex costs are not fully amortized. There *is* a marginal cost to every chip past just the energy.

Microsoft is down because it was revealed 45% of their 625B backlog is obligations to OpenAI. A similar story that we have seen for Oracle and AMD. Worries about concentration risk and OpenAI's ability to meet their obligations.
However, if you assume OpenAI's revenue growth trajectory continues (and accelerates as seen with Anthropic's recent projections) and they can continue to raise capital then this could be incredibly bullish for AMD. It makes it more likely in my mind that Microsoft will buy AMD hardware that is co-designed with OpenAI's models to offer superior TCO. The \~300B worth of OpenAI spend should be hosted on AMD hardware optimized for those workloads.

https://x.com/semivision_tw/status/2016885087892332901?s=46
“what the company needs most now are customer orders.”
WTF?
You mean customers want TCO? Lower power consumption? Integrated disaggregation? Rational thermals? Superior HBM? Open source stack?