文/北京集佳知识产权代理有限公司 葛琛琛
近年来,随着越来越多新兴科技的涌现,专利申请的主题也变得广泛。随之而来的是,专利适格性的问题由于不断变化而备受关注。2014年,美国最高院提出采用“两步法”准则审查专利是否满足专利法101条,也就是专利适格性问题。但是,“两步法”准则对于审查是否具有专利适格性的操作要求并不明确。对此,在2019年1月,美国专利商标局向审查员发布了关于如何针对专利适格性审查权利要求的新指南,该指南重点关注专利适格性分析中的步骤2A。在步骤2A分析中,当审查员认定是抽象概念时,需要回答的关键问题是该抽象概念是否指向实际应用。
下面我们分享两件Patent Trial and Appeal Board 审理决定的案例来了解步骤2A的审查实践。
一、案例1:Appeal 2024-000087 Application 16/474,477【1】
案例涉及减速器的故障诊断装置领域,权利要求1如下:
1.A failure diagnosis system comprising:
a mechanical apparatus including:
a motor;
a reduction gear driven by the motor, the reduction gear being configured to slow down rotation power of the motor and transmit the rotation power to an operating part of the mechanical apparatus;
an encoder configured to detect a rotational position of the motor; and
a sensor configured to detect a motor current supplied to the motor, the motor current being one of load current of the motor and a current value having a correlation with the load current;
a processor programmed to:
acquire rotation speed data of the motor based on a
signal from the encoder;
identify an acceleration/deceleration period during which operation of the mechanical apparatus accelerates and/or decelerates based on the acquired rotation speed data based on the signal from the encoder;
generate a group of time series rotation speed data by sequentially sampling the portion of the acquired rotation speed data from the identified acceleration/deceleration period acquired based on the signal from the encoder;
...
make a determination of whether the reduction gear indicates a sign of failure induced by abrasion based on a comparison between a given amplitude threshold and the extracted peak value in a change in frequency spectrum of the motor current with respect to a change in a rotation speed of the motor during the acceleration/deceleration period; and
an outputter that outputs a result of the determination of whether the reduction gear indicates the sign of failure.
审查员认为权1属于抽象概念中的数学概念或心理活动,且该抽象概念没有指向实际应用,因为权1中所述处理器(processor)仅是用于执行通用计算机指令的通用计算机装置,而至于权1中的motor, reduction gear, encoder, and sensor 仅是用于无关紧要的额外解决方案活动的数据收集步骤。
但PTAB 认为,权1不涉及数学概念。虽然权1中的一系列决策是基于数学概念,但并没有出现数学概念本身。即使权1中涉及了抽象概念,但该抽象概念也指向改进减速器故障检测技术的实际应用。虽然权1的处理器是一个通用的计算机组件,但执行该处理器可以改进技术。所以,根据新修改指南在Step2A中的Prong 2的判断,权1符合101的规定,属于可专利的客体。
二、案例2:Appeal 2024-000046 Application 15/793,455【1】
案例涉及基于内核的机器学习系统生成输入的方法领域,权利要求1如下:
1. A method, comprising:
performing a classification operation on a first item,
including:
generating, by processing circuitry of a computer configured to operate a kernel-based machine learning classifier, a plurality of diagonal matrices, each of the plurality of diagonal matrices having non-diagonal elements that are zero and diagonal elements that have values distributed according to a specified probability distribution function and having a dimension based on a specified dimension;
producing, by the processing circuitry, a plurality of orthogonal matrices, each of the plurality of orthogonal matrices having mutually orthogonal rows;
for each of the plurality of diagonal matrices, forming, by the processing circuitry, a plurality of matrix pairs, each of the plurality of matrix pairs including (i) that diagonal matrix, and (ii) a respective orthogonal matrix of the plurality of orthogonal matrices;
generating, by the processing circuitry, a product of each of the plurality of matrix pairs to produce a linear transformation matrix;
obtaining, by the processing circuitry, an input vector representing the first item from a database, the input vector having the specified dimension;
using the linear transformation matrix to produce an approximated feature vector for the input vector, the approximated feature vector including a nonlinear function of inner products of row vectors of the linear transformation matrix and the input vector; and
providing the approximated feature vector as input into the kernel-based machine learning classifier; and
determining, by the processing circuitry, whether the first item has a particular classification based on an output of the kernel-based machine learning classifier.
审查员将斜体部分认为是属于抽象概念,黑体部分属于高度概括的附加元素,下划线部分是无关紧要的额外解决方案的活动。
PTAB则是通过以下步骤对权1进行判断:
1)步骤 1(Statutory category法定分类)
根据101法条规定的可专利的四类中,可以确认属于方法。
2)步骤 2A(i)(does the claim recite a judicial exception?权利要求是否属于司法例外?)
部分权1特征如下:
“generating . . . a product of each of the plurality of matrix pairs to produce a linear transformation matrix . . .
using the linear transformation matrix to produce an approximated feature vector for the input vector . . .”
认同审查员意见为数学概念,但是仅是数学概念不足以被认为不具有专利适格性。
另有部分权1特征如下:
“performing a classification operation on a first item . . .
generating . . . a plurality of diagonal matrices . . .
producing . . . a plurality of orthogonal matrices . . .
for each of the plurality of diagonal matrices, forming . . . a plurality of matrix pairs . . .
providing the approximated feature vector as input . . . ; and
determining . . . whether the first item has a particular classification based on an output of the kernel-based machine learning classifier.”
PTAB假定这些特征属于抽象概念中的心理活动。
3)步骤2A(ii)(is the judicial exception integrated into a practical application?该司法例外是否指向实际应用?)
PTAB同意审查员认为“processing circuitry”和“database”是高度概括的元素仅涉及执行通用指令的通用的计算机,认为“obtaining . . . an input vector representing the first item . . . , the input vector having the specified dimension”是无关紧要的额外解决方案活动。
但是,PTAB认为“providing the approximated feature vector as input into the kernel-based machine learning classifier”和 “determining, by the processing circuitry, whether the first item has a particular classification based on an output of the kernel-based machine learning classifier”是将矩阵和向量的乘法这个抽象概念指向实际应用,即:根据称为结构化正交随机特征(SORF)的新框架生成针对高斯内核的无偏估计器;使用该无偏估计器来从数据库中选择的项目进行分类操作。这种实际应用提高了某一特定机器的性能。因此,这些额外的限制通过提高机器学习分类器的内存使用和准确性,为机器学习系统的技术领域提供了改进。所以根据新修改指南在Step2A中的Prong 2的判断,权1符合101的规定,属于可专利的客体。
三、总结
从上述两个案例可以看出,当被审查员认为是抽象概念时,可以根据步骤2A的判断步骤去整理答复思路,也就是该抽象概念是否指向实际应用,在这里,两案例中的抽象概念指向的实际应用,均是在其技术或技术领域内取得有益效果或改进。新指南中也指出,如果抽象概念在应用领域没有改进,则不被视为指向实际应用。
以上是近期PTAB针对101问题审查的两件案例,希望能为代理人在处理相关问题时提供启发。
参考文献:
【1】https://developer.uspto.gov/ptab-web/#/search/decisions