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BRIDGING CONCEPTS. “We establish the following dictionary: Particle momentum mode Neural degree of freedom; Ocillator energy gap Excitation energy threshold of neuron; Mode occupation number Excitation level of neuron; Gravitational interaction among particles Excitatory synaptic connection among neurons; Black hole state Critical state of highly excited low threshold neurons.” https://onlinelibrary.wiley.com/doi/full/10.1002/prop.201800007?casa_token=nn-sqzr1LtkAAAAA%3Axz_GSzZ1qHcoqtsAnyUFHP7LE4hzmCqVF57CqUh5T7pkS8T48kTAc_oyaUb3Ticpy78QnB1xd9Jk4mw View in LinkedIn

JOINING THE DOTS. “Thus, it appears that the neural network – when translated in quantum field theoretic language – can exhibit some intrinsic holographic properties, such as, the emergence of the gapless neurons inhabiting a lower dimensional surface with the resulting micro‐state entropy that scales as the corresponding area. This is something highly reminiscent of gravitational systems, such as, the black holes or the AdS space.” https://onlinelibrary.wiley.com/doi/full/10.1002/prop.201800007?casa_token=nn-sqzr1LtkAAAAA%3Axz_GSzZ1qHcoqtsAnyUFHP7LE4hzmCqVF57CqUh5T7pkS8T48kTAc_oyaUb3Ticpy78QnB1xd9Jk4mw View in LinkedIn

NEURONS AND BLACK HOLES. “In this paper we shall attempt to take one more step and try to see if a neural network can possess some additional informational characteristics that are usually considered to be the defining properties of black holes.” https://onlinelibrary.wiley.com/doi/full/10.1002/prop.201800007?casa_token=nn-sqzr1LtkAAAAA%3Axz_GSzZ1qHcoqtsAnyUFHP7LE4hzmCqVF57CqUh5T7pkS8T48kTAc_oyaUb3Ticpy78QnB1xd9Jk4mw View in LinkedIn

ENHANCED NEURONS. “Instead of storing patterns in the local minima of the energy function, as, for example, in usual treatments of the Hopfield model, the enhanced memory points can be identified among the highly excited critical states, where set of neurons becomes gapless.” https://onlinelibrary.wiley.com/doi/full/10.1002/prop.201800007?casa_token=nn-sqzr1LtkAAAAA%3Axz_GSzZ1qHcoqtsAnyUFHP7LE4hzmCqVF57CqUh5T7pkS8T48kTAc_oyaUb3Ticpy78QnB1xd9Jk4mw View in LinkedIn

QUANTUM NEURAL NETWORK. “The general message is that for gravity‐like synaptic connections in a quantum neural network the information storage mechanisms can become potentially richer than in more conventional approaches.” https://onlinelibrary.wiley.com/doi/full/10.1002/prop.201800007?casa_token=nn-sqzr1LtkAAAAA%3Axz_GSzZ1qHcoqtsAnyUFHP7LE4hzmCqVF57CqUh5T7pkS8T48kTAc_oyaUb3Ticpy78QnB1xd9Jk4mw View in LinkedIn

Spring has not yet exhausted her abundant show. View in LinkedIn

SO ENDS this first of two weekends on the taste of heavy water. “Less than a century ago, the discovery of the hydrogen isotope deuterium – 2H, but often simplified to D – revealed the existence of another kind of water with the chemical formula 2H2O or simply D2O. A typical hydrogen atom contains one proton within its nucleus. The deuterium isotope, however, has a neutron in addition to the proton, giving the hydrogen atom a greater mass. Hence, water formed with this type of heavy hydrogen is usually called... heavy water.” This has taste, very surprisingly. https://lnkd.in/dUTFQQG View in LinkedIn

AVOIDANCE. “Previous reports have shown that on longer timescales than those reported here mice learned to avoid D2O, as it is poisonous to them in larger quantities. It is not clear what is the cue that enables the avoidance learning, but it is evident that the early response to D2O is not attractive, suggesting that it is not eliciting sweet taste in mice.” https://lnkd.in/dzPDm5w View in LinkedIn

MOUSE DATA. “The results of the drinking experiments are presented in Fig. 3a–c, with a snapshot of the experimental setup shown in Fig. 3d. In cages where mice were offered both normal water and heavy water (Fig. 3a) consumption of D2O was within statistical error the same as that of H2O.” https://lnkd.in/dzPDm5w View in LinkedIn

ORDER DERIVATIVES. “Aristotle's theory of gravity was first‐order in derivatives; force is equal to mass times velocity. The complexity‐based theory looks more like a second order theory because complexity and it's rate of change are independent variables.” https://onlinelibrary.wiley.com/doi/full/10.1002/prop.201500092?casa_token=8OO3b1OY4e4AAAAA%3ARqriAgTwtxnvsxl09CqnNy79m7l4ye7ZrkZxcLtObB9kHsTwYgzBuIV2X-xXQ7ezoR6VQPfQLCS-vnI View in LinkedIn