Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
DETAILED ACTION
The action is in response to claims dated 3/23/2023
Claims pending in the case: 1-19
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claim(s) 1-19 rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor, or for pre-AIA the applicant regards as the invention.
Claim(s) 1,6, 12, 15 in the relevant part read: “generator … that produces fingerprint data” or similar. Based on the claim language, it is unclear what is being referred to as “fingerprint data”. Since the specification defines “point fingerprint” the applicant is requested to clarify the limitation using the term that has been defined in the specification. Since this appears to be a term not common in the art, the term “fingerprint data” has been found to be unclear. As such, a person of reasonable skill in the art would not be apprised of the metes and bounds of the invention.
Claim(s) 1,6, 12, 15 in the relevant part read: “a machine learning trainer module … receives the fingerprint data from the training data generator module and produces the device state” or similar. Based on the claim language, it is unclear what this “device” is and what is being referred to as “device state”. As per the specification paragraph [124], device is a quantum dot device. However, quantum dot device state may be represented by several parameters as size, material, energy, mass etc. It is not clear what in this limitation represents device state. As such, a person of reasonable skill in the art would not be apprised of the metes and bounds of the invention.
Claim(s) 1, 12 further read: “a recognition module in communication with the machine learning trainer module and a measurement module and that receives the device state from the machine learning trainer module, receives ray-based data from the measurement module, and produces recognition data based on the device state and the ray-based data” or similar. Since the specification does not provide a definition for recognition data, based on the claim language, it is unclear what is being referred to as “recognition data”. As such, a person of reasonable skill in the art would not be apprised of the metes and bounds of the invention.
A reasonable interpretation for the purpose of examination was not possible.
Claim(s) 1, 12 further read: “a prediction module in communication with the comparison module and that receives the comparison data from the comparison module and produces prediction data for the device based on the comparison data”. Based on the claim language, it is unclear what constitutes “prediction data” i.e. what is being predicted. As such, a person of reasonable skill in the art would not be apprised of the metes and bounds of the invention.
A reasonable interpretation for the purpose of examination was not possible.
Claim(s) 1, 12 further read: “recognition module performs recognition on the ray- based data using the device state”. Based on the claim language, it is unclear what is being recognized. As such, a person of reasonable skill in the art would not be apprised of the metes and bounds of the invention.
A reasonable interpretation for the purpose of examination was not possible.
Claim(s) 6, further read: “a charging module in communication with the device and that sets the charging energy for each quantum well of the device and defines a state action for each of the quantum wells by sending charging data to the device”. Based on the claim language, it is unclear what is being referred to as “state action”. It is unclear if setting the charging energy itself is the defined state action or if “state action” is a separate action based on it. As such, a person of reasonable skill in the art would not be apprised of the metes and bounds of the invention.
Claim(s) 6, 15 further read: “acquires state data from the device for a selected state recognizer”. Based on the claim language, it is unclear what is being referred to as “a selected state recognizer”. It is unclear what is this state recognizer and what criteria is being used to select a specific one. As such, a person of reasonable skill in the art would not be apprised of the metes and bounds of the invention.
All claims dependent on this/these claim(s) are also rejected under 35 U.S.C. 112(b) due to the virtue of their respective direct and indirect dependencies.
A reasonable interpretation of all the limitations for the purpose of search and examination was not possible.
Claim Rejections using prior arts
Regarding Independent claims 1, 6, 12 and 15, a reasonable interpretation of the limitations in the independent claim 1 was not possible for the purpose of examination. Please refer to the 112(b) rejection above. Thus a detailed rejection using prior art could not be presented.
Based on an overall search of the concept explained in the specification, the examiner found art, NPL “Ray-based classification framework for high-dimensional data”, published in Oct 2020 where a new concept of a framework for classifying, named, ray-based classification has been introduced. However this art is by the same inventor and not a prior art based on the filing date.
The most relevant prior art found during search that appear to read on the inventive concept are-
NPL “Auto-tuning of double dot devices in situ with machine learning” by Zwolak et. al. published Jan 2020. Section II and section III teach autotuning by using a classifier information.
NPL "Machine learning techniques for state recognition and auto-tuning in quantum dots" by Kalantre et.al published Feb 2018. Section VI teaches auto-tuning. Subsection A teaches state learning that is used for tuning which is discussed in section B.
Please refer to the highlighted sections in the attached prior arts, the examiner finds may read on the limitations.
To help further prosecution, the applicant is requested to address the 112b rejections by clarifying the terms used in the limitations to adequately explain the concepts of the invention so that a more comprehensive search and claim mapping may be performed.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure in attached 892.
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/Mandrita Brahmachari/Primary Examiner, Art Unit 2144