HPE wants to turn supercomputing leadership into gen AI profits

HPE’s announcement of an AI cloud for large language models highlights a differentiated strategy that the company hopes will lead to sustained momentum in its high performance computing business. While we think HPE has some distinct advantages with respect to its supercomputing IP, the public cloud players have a substantial lead in AI with a point of view that generative AI is fully dependent on the cloud and its massive compute capabilities. The question is can HPE bring unique capabilities and a focus to the table that will yield competitive advantage and ultimately, profits in the space?

In this Breaking Analysis we unpack HPE’s LLM-as-a-service announcements from the company’s recent Discover conference and we’ll try to answer the question: Is HPEs strategy a viable alternative to today’s public and private cloud gen AI deployment models, or is it ultimately destined to be a niche player in the market? To do so we welcome to the program CUBE analyst Rob Strechay and Vice President / principal analyst from Constellation Research, Andy Thurai. 
World’s Top Performing Supercomputers: 

https://twitter.com/wholemarsblog/status/1671721744623874048?s=46&t=AqnHczjrru-dQaVNpPGp7w



HPE’s Slingshot interconnect architecture:

https://www.nextplatform.com/2022/01/31/crays-slingshot-interconnect-is-at-the-heart-of-hpes-hpc-and-ai-ambitions/



How Cray makes Ethernet suitable for HPC: 

https://www.nextplatform.com/2019/08/16/how-cray-makes-ethernet-suited-for-hpc-and-ai-with-slingshot/


The generative AI stack according to Andreesen Horowitz:

https://a16z.com/2023/06/20/emerging-architectures-for-llm-applications/