In crowded voice AI market, OpenAI bets on instruction-following and expressive speech to win enterprise adoption - VentureBeat
<a href="https://news.google.com/rss/articles/CBMi1gFBVV95cUxOY1UwYjJyMzRFVVJpSldYT2FkWXh6MWJNV0NmRXdJald2T0oxcXJKQkpUUVVmcEZncHMyUnMzYVZKeHZSRmJ3bVQtUmluRmZPNjRFdEstQU9KMFYtYV9faXR2SjMwZXlRcU1UcUdtNXgxaWtpd1BtaVpfNjNCcVg4STNTZy1MdXBBdUNZNGtYajVlbTRYck5pYzhZZHNDOWM3Q0ZpRmNFLVNKaW05WElVeVFYV1A4MVZQU2daMWIyXzRxODZkZzd2ekJPSTBvZTBEMU45TEt3?oc=5" target="_blank">In crowded voice AI market, OpenAI bets on instruction-following and expressive speech to win enterprise adoption</a> <font color="#6f6f6f">VentureBeat</font>
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When cooperation is beneficial to all agents
arXiv:2604.02862v1 Announce Type: cross Abstract: Within a general semimartingale framework, we study the relationship between collective market efficiency and individual rationality. We derive a necessary and sufficient condition for the existence of (possibly zero-sum) exchanges among agents that strictly increase their indirect utilities and characterize this condition in terms of the compatibility between agents' preferences and collective pricing measures. The framework applies to both continuous- and discrete-time models and clarifies when cooperation leads to a strict improvement in each participating agent's indirect utility.
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