Appeal 2007-1088
Application 10/006,959
machine and the delivered neural network model on the test machine)
are the same before further updating the delivered neural network
model on the test machine. Furthermore, “the model development
machine 104 may function as a test machine 606” implies that they
may be the same machine. In other words, during the baseline
training stage, a machine having a trained baseline neural network
would be a mode development machine. Later on, when the same
machine having the same trained baseline neural network is ready to
have a fine-tuning at the specific work site it functions as a test
machine. Accordingly, in view of the specification, Jelley’s steps for
training a neural network anticipate the argued limitation.
We are not persuaded by Appellants’ remarks beginning at page 2 of
the Reply Brief that the Examiner has mischaracterized Appellants’ claimed
invention. Appellants argue Appellants’ disclosure rather than the claimed
invention when they characterize claims 1 and 7 as requiring separate
machines and separate models. The claim language does not preclude the
Examiner’s view that the same machine and model can function at different
times as the claimed “model development machine having a first at least one
model” and as the claimed “at least one test machine having a second at least
one model.” Appellants (Reply Br. 3) take issue with the Examiner’s above-
quoted interpretation of “[i]n some circumstances, the model development
machine 104 may function as a test machine 606” (Specification para. 29) to
mean “these two models (i.e., the neural network model on the model
development machine and the delivered neural network model on the test
machine) are the same” (Answer 10). However, Appellants have not
provided an alternative explanation of the meaning of that statement in the
Specification. We also agree with the Examiner’s above-noted conclusion
that the language “delivering a neural network model from the model
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Last modified: September 9, 2013