MosaicML Proposes Modifying Chinchilla Scaling Laws to Account for Inference Costs when Determining Optimal LLM Size

LLMs represent a significant leap in understanding and generating human language. These models are instrumental in various AI applications, from automated translation to conversational agents. Their development involves a delicate balance between enhancing capabilities and managing computational costs, a challenge that continues to evolve with the technology. A central issue in LLM advancement is optimizing […]

The post MosaicML Proposes Modifying Chinchilla Scaling Laws to Account for Inference Costs when Determining Optimal LLM Size appeared first on MarkTechPost.

agents ai applications ai shorts applications artificial intelligence automated balance capabilities challenge computational conversational conversational agents costs development editors pick human inference inference costs language laws llm llms machine learning mosaicml scaling staff tech news technology translation understanding