linkedin post 2019-04-10 04:06:38

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ADAM & EVE. "Towards Robot Scientists for autonomous scientific discovery. We describe our two prototype Robot Scientists: Adam and Eve. Adam has recently proven the potential of such systems by identifying twelve genes responsible for catalysing specific reactions in the metabolic pathways of the yeast Saccharomyces cerevisiae. This work has been formally recorded in great detail using logic." https://lnkd.in/dHmK73K View in LinkedIn
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linkedin post 2019-04-10 04:04:49

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"ROBOT SCIENTISTS could provide a useful tool for managing such data and knowledge, making scientific procedures easier and more efficient. This kind of learning will become even more important as we move further towards integrative and predictive biology in the era of Web 2.0 and the Semantic Web." https://lnkd.in/dMfcK8Q View in LinkedIn
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linkedin post 2019-04-12 04:02:49

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ABE ROBOT EXPERIMENTS. "In order to give ABE the ability to run experiments like Adam, Wikswo’s group is currently developing “laboratory-on-a-chip” technology that can be controlled by Eureqa. This will allow ABE to design and perform a wide variety of basic biology experiments. Their initial effort is focused on developing a microfluidics device that can test cell." metabolism.".” https://lnkd.in/eGii4i4 View in LinkedIn
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linkedin post 2019-04-12 04:01:34

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BREAKTHROUGH MACHINE. "The research is being heralded as a potential breakthrough for science in the Petabyte Age, where computers try to find regularities in massive datasets that are too big and complex for the human mind and its standard computational tools." (Eurequa). https://lnkd.in/dEC3j_P View in LinkedIn
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linkedin post 2019-04-12 03:59:12

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"IN JUST OVER a day, a powerful computer program accomplished a feat that took physicists centuries to complete: extrapolating the laws of motion from a pendulum’s swings. Developed by Cornell researchers, the program deduced the natural laws without a shred of knowledge about physics or geometry." (Eurequa). https://lnkd.in/dEC3j_P View in LinkedIn
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linkedin post 2019-04-11 10:26:20

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HOURS VS MONTHS. "But the win-loss record was not the most impressive takeaway from the competitions. While teams of humans sweat their predictive algorithms for months leading up to competition, the Data Science Machine took somewhere between two and 12 hours to produce each of its entries." https://lnkd.in/dG_krDG View in LinkedIn
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