arXiv:2607.02118v1 Announce Type: new Abstract: Scientific Fitness Coaching (SFC) is typically delivered by human professionals, making it costly and inaccessible to many. While recent advances in Large Language Models (LLMs) show considerable promise for more inclusive fitness coaching, directly deploying prevailing general-purpose LLMs in SFC reveals critical limitations. These models often lack sufficient domain-specific knowledge integration, leading to weak performance on complex SFC scenarios. In this paper, we introduce FitOne, a series of fitness LLMs (with 8B and 32B parameters) desig
The proliferation of general-purpose LLMs has highlighted their limitations in specialized domains, necessitating targeted fine-tuning for practical applications.
Domain-specific LLMs like FitOne demonstrate a pathway to commercializing AI in niche sectors, making specialized services more accessible and cost-effective.
The deployment of highly specialized AI models will shift the delivery of expert services, potentially democratizing access to amenities like personalized fitness coaching.
- · AI developers
- · Fitness tech companies
- · Consumers seeking affordable coaching
- · Data providers in niche domains
- · General-purpose LLM providers in specific verticals
- · Human professionals in routine coaching roles
Specialized AI models will improve performance and efficiency in their target domains, outperforming general models.
This specialization will fragment the AI market, leading to a proliferation of domain-specific models and platforms.
The success of niche LLMs could encourage further investment into 'micro-AI' applications across countless industries, leading to deeper automation of services.
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Read at arXiv cs.AI