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About the project
Our Mission
"The Next Big Breakthrough in AI Will Be Around Language" - Harvard Business Review
While data might be the new oil, the dataset is the refined gasoline that powers every Machine Learning (ML) and AI operation.
We focus on context-controlled NLP/NLU (Natural Language Processing/Understanding) and feature engineering for hidden relationship detection in data related to space biosciences. Our platform powers advanced approaches in Artificial Intelligence (AI) and Machine Learning (ML) using experimental and formal language models including well-known models such as OpenAI's GPT-3 (2020), Google's BERT (2018), word2vec (2013) combined with experimental methods developed at Lawrence Berkeley National Laboratory (2008) Biosciences division.
Our platform powers research groups in space biosciences along with data vendors, funds and institutions by generating on-demand NLP/NLU correlation matrix datasets. We are particularly interested in how we can get machines to trade information with one another or exchange and transact data in a way that minimizes a selected loss function. Our objective is to enable any group analyzing data to save time by testing a hypothesis or running experiments with higher throughput. This can increase the speed of innovation, novel scientific breakthroughs and discoveries. For a little more on who we are, see our latest reddit AMA on r/AskScience (here)!
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$48 080.06
$3 303.69