the-events-calendar domain was triggered too early. This is usually an indicator for some code in the plugin or theme running too early. Translations should be loaded at the init action or later. Please see Debugging in WordPress for more information. (This message was added in version 6.7.0.) in /home3/aijournc/public_html/wp-includes/functions.php on line 6114rocket domain was triggered too early. This is usually an indicator for some code in the plugin or theme running too early. Translations should be loaded at the init action or later. Please see Debugging in WordPress for more information. (This message was added in version 6.7.0.) in /home3/aijournc/public_html/wp-includes/functions.php on line 6114pods domain was triggered too early. This is usually an indicator for some code in the plugin or theme running too early. Translations should be loaded at the init action or later. Please see Debugging in WordPress for more information. (This message was added in version 6.7.0.) in /home3/aijournc/public_html/wp-includes/functions.php on line 6114Smart data platform DefinedCrowd today announced<\/a> they have successfully raised $50.5m in a Series B funding round with new investors Hermes GPE and Semapa Next taking part alongside existing investors Bynd Venture Capital, EDP Ventures, Evolution Equity Partners, IronFire Ventures, Kibo Ventures, and Portugal Ventures. <\/p>\n\n\n\n The additional capital will be used to enhance their suite of products, increase available resources for R&D of new initiatives and services to add value to customers, and expand their international client list. <\/p>\n\n\n\n This Series B funding round brings DefinedCrowd’s total raised capital to $63.4m over a five year period and is also the largest Series B funding round to be raised by a female-founded AI company in the US giving kudos to women in technology<\/a>. <\/p>\n\n\n\n Daniela Braga, CEO and founder of DefinedCrowd said: “It\u2019s amazing to think of how far we have come in such a short time. A few years ago, I saw the gap between the AI models data scientists wanted to develop and the training data available to build them.”<\/p>\n\n\n\n