EDITOR’ S QUESTION running costs. Such constraints are hard to accept and that led to better architectures and training strategies. Parameter efficient tuning, pruning, quantization, knowledge distillation and context length interpolation are some of the methods widely studied for efficient LLM utilization.
The strengths and, more importantly, the weaknesses of these language models are not yet fully explored. Industry benchmarks are crucially important as we navigate to the world that really exists.
These benchmarks are important because( 1) they ground us in terms of what is feasible, and( 2) they point out areas where the model either requires improvement or is not most effective or efficient.
The lasting value of LLMs will be the ability to create computer interfaces based on natural language. Humans who previously were unable to perform certain tasks because they were lacking domain-specific knowledge or technical skills will be able to invoke actions that cross several computational systems and obtain information which they previously could not access. LLMs will retain desirable characteristics in terms of natural language processing while their size will continue to shrink, ultimately finding their way onto every device.
Beyond execution of NLP tasks, primarily as the Input / Output interface of natural language for computing systems, LLMs will be integrated with other software components to which they will delegate actions that the LLM would execute. These delegations will be made to more specialized software that can execute tasks( other than NLP) more efficiently and effectively. At a high level, that could be achieved by augmenting the design of applications that are LLM-centric today through extensions that enhance comprehension.
As AI hype subsides, innovation continues and the winners in this next phase of innovation will make decisions based on the world that really exists. That is a world where we recognize that LLMs are not the way to“ general artificial intelligence” but instead are powerful foundations for computer interfaces based on natural language – that is going to be the lasting value of LLMs. p
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