According to @OpenAI, Denise Dresser, former CEO of Slack, has been appointed as Chief Revenue Officer at OpenAI to lead global revenue strategy and customer support at scale. This move is expected to strengthen OpenAI’s enterprise sales capabilities and accelerate the adoption of generative AI solutions in large organizations. Dresser’s deep experience in enterprise SaaS and customer experience is anticipated to help OpenAI expand its AI business offerings and enhance support for enterprise clients, positioning the company for further commercial growth in the rapidly evolving AI market (source: OpenAI, https://openai.com/index/openai-appoints-denise-dresser/).

According to @karpathy, building large language models (LLMs) like ChatGPT involves a systematic process that includes data collection, model architecture design, large-scale training, and deployment. Karpathy emphasizes starting with massive, high-quality text datasets for pretraining, leveraging transformer-based architectures, and employing distributed training on powerful GPU clusters to achieve state-of-the-art results (Source: @karpathy via X.com). For practical applications, he highlights the importance of fine-tuning on domain-specific data to enhance performance in targeted business use-cases such as customer support automation, code generation, and content creation. This step-by-step methodology offers substantial opportunities for organizations looking to develop proprietary AI solutions and differentiate in competitive markets (Source: @karpathy, 2024).