by: Mitchell Sutika-Sipus, Chief Solutions Architect<\/p>\n\n\n\n
I have been building data science and A.I. companies since 2007. I started my first company in a refugee camp in East Africa, when I realised the United Nations lacked the quality data needed to supply 370,000 displaced persons with minimum shelter, water, and sanitation. Later, I pursued a PhD at Carnegie Mellon University to combat disinformation within machine learning \u2013 and concurrently \u2013 to launch my PhD research as a startup. Years after that, another company I founded was acquired because we invented novel solutions to help companies find new customers, expand sales, and achieve non-linear growth.<\/p>\n\n\n\n
These companies were not built in a vacuum. They were possible because of my close relationships within Carnegie Mellon University, the Massachusetts Institute of Technology, Columbia University, and the University of Cincinnati. If you pay attention to other blogs or social media posts by AutogenAI, you\u2019ll note that our company is continually present on college campuses in the United States and throughout the world.<\/p>\n\n\n\n
One of the most powerful ways to build an effective business and to benefit society is to first discover and access information that few others have observed. AutogenAI started when our CEO, Sean Williams, first learnt about Large Language Models from a close friend at Google Deep Mind. After building a successful career as a proposal writer, Sean founded AutogenAI before the rest of us knew about ChatGPT, and by creating the world\u2019s first AI proposal company.<\/p>\n\n\n\n
\u201cLab to Market,\u201d is not a new business model. It is readily repeatable. But to work, it requires conditions that nurture commercialisation and growth. We see an opportunity for the White House to craft the best conditions for students and businesses to work together, to commercialise research, and launch new products. Tax credits for core infrastructure, or benefits to companies that support national security, are obvious paths to bolster the economy while building a robust AI sector within the United States. Mores so, encouraging universities to support student entrepreneurship and corporate collaboration is a sure path to prosperity.<\/p>\n\n\n\n
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by: Mitchell Sutika-Sipus, Chief Solutions Architect I have been building data science and A.I. companies since 2007. I started my first company in a refugee camp in East Africa, when I realised the United Nations lacked the quality data needed to supply 370,000 displaced persons with minimum shelter, water, and sanitation. Later, I pursued a PhD at…<\/p>\n","protected":false},"author":5,"featured_media":3613,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"footnotes":""},"categories":[10],"tags":[],"class_list":["post-3612","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-proposal-writing"],"acf":[],"yoast_head":"\n