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How Invert uses meta-learning to leverage old bioprocess dataWith meta-learning techniques, Invert’s ML team was able to reduce new data needs by as much as 90% by leveraging old data from different, but loosely related, bioprocess programs.
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Given the glaring challenge of managing bioprocess data, the question remains: Why have bioprocess data solutions been historically overlooked?
Suhas Guruprasad, the Head of AI at Invert, dives into the evolution of artificial intelligence, distinguishing between the actual capabilities of AI and the often exaggerated hype surrounding it.
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Exciting news! Invert is launching a Q&A series, Pioneers in Bioprocessing, to chat with experts in bioprocessing and biotechnology to discuss their work, the potential of the bioeconomy at large, and the personal viewpoints of the individuals who make this work possible.
The transfer of institutional data and knowledge is critical to the development of biotechnologies, bioproducts, and biotherapeutics.
For biotech and synthetic biology companies, there’s always A LOT of work to do. As these companies quickly learn, trying to handle everything in-house–from strain design and high-throughput screening to process development and beyond–can spread funding and resources thinly.
