Parsing the Mindboggling Cost of Ownership of Generative AI
By Lauro Rizzatti, VSORA
EETimes (November 2, 2023)
The latest algorithms, such as GPT-4, pose a challenge to the current state-of-the-art processing hardware, and GenAI accelerators aren’t keeping up. In fact, no hardware on the market today can run the full GPT-4.
Current large language model (LLM) development focuses on creating smaller but more specialized LLMs that can run on existing hardware is a diversion. The GenAI industry needs semiconductor innovations in computing methods and architectures capable of delivering performance of multiple petaFLOPS with efficiency greater than 50%, reducing latency to less than two second per query, constraining energy consumption and shrinking cost to 0.2 cent per query.
Once this is in place–and it is only matter of time–the promise of transformers when deployed on edge devices will be fully exploited.
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