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PatentNext Summary: AI-related inventionshave experienced explosive growth. In view of this, the USPTO hasprovided guidance in the form of an example claim and an"informative" PTAB decision directed to AI-related claimsthat practitioners can use to aid in preparing robust patent claimson AI-related inventions.

Artificial Intelligence (AI) has experienced explosive growthacross various industries. From Apple's Face ID (facerecognition), Amazon's Alexa (voice recognition), to GM Cruise(autonomous vehicles), AI continues to shape the modern world.SeeArtificialIntelligence.

It comes as no surprise, therefore, that patents related toAI inventions have also experienced explosivegrowth.

Indeed, in the last quarter of 2020, the United States Patentand Trademark Office (USPTO) reported that patent filings forArtificial Intelligence (AI) related inventions more than doubledfrom 2002 to 2018.SeeOffice of the ChiefEconomist, Inventing AI: Tracking The Diffusion Of ArtificialIntelligence With Patents, IP DATA HIGHLIGHTS No. 5 (Oct.2020).

During the same period, however, the U.S. Supreme Court'sdecision inAlice Corp. v. CLS BankInternationalcast doubt on the patentability ofsoftware-related inventions, which AI sits squarelywithin.

Fortunately, since the SupremeCourt'sAlice decision, the Federal Circuitclarified (on numerous occasions) that software-related patents areindeed patent-eligible. SeeAre Software InventionsPatentable?

More recently, in 2019, the United States Patent and TrademarkOffice (USPTO) provided its own guidance on the topic of patentingAI inventions. See2019 Revised Patent Subject Matter EligibilityGuidance. Below we explore these examples.

As part of its 2019 Revised Patent Subject Matter EligibilityGuidance (the "2019 PEG"), the USPTO provided severalexample patent claims and respective analyses under thetwo-partAlicetest.SeeSubjectMatter Eligibility Examples: Abstract Ideas.

One of these examples ("Example 39") demonstrated apatent-eligible artificial intelligence invention. In particular,Example 39 provides an example AI hypothetic invention labeled"Method for Training a Neural Network for FacialDetection" and describes an invention for addressing issues ofolder facial recognition methods that suffered from the inabilityto robustly detect human faces in images where there are shifts,distortions, and variations in scale in scale and rotation of theface pattern in the image.

The example inventive method recites claim elements fortraininga neural networkacross twostages of training set data so as to minimize false positives forfacial detection. The claims are reproduced below:

collecting a set of digitalfacial images from a database;

applying one or moretransformations to each digital facial image includingmirroring, rotating, smoothing, or contrast reduction to create amodified set of digital facial images;

creating a first trainingset comprising the collected set of digital facial images, themodified set of digital facial images, and a set of digitalnon-facial images;

training the neural networkin a first stage using the first training set

creating a second trainingset for a second stage of training comprising the first trainingset and digital non-facial images that are incorrectly detected asfacial images after the first stage of training;and

training the neural networkin a second stage using the second training set.

The USPTO's analysis of Example 39 informs that the aboveclaim is patent-eligible (and not "directed to" anabstract idea) because the AI-specific claim elements do not recitea mere "abstract idea." SeeHow to Patent Software Inventions: Show an"Improvement". In particular, while some ofthe claim elements may be based on mathematical concepts, suchconcepts are not recited in the claim. Further, the claim does notrecite a mental process because the steps are not practicallyperformed in the human mind. Finally, the claim does not recite anymethod of organizing human activity, such as a fundamental economicconcept or meaning interactions between people. Because the claimsdo not fall into one of these three categories, then, according tothe USPTO, then the claim is patent-eligible.

As a further example, the Patent Trial and Appeal Board (PTAB)more recently applied the 2019 PEG (as revised) inanexparteappeal involving anartificial intelligence invention.Seeex parte Hannun (formerly Ex parteLinden), 2018-003323 (April 1,2019)(designated by the PTAB as an"Informative" decision).

InHannun, the patent-at-issuerelated to "systems and methods for improving thetranscription of speech into text." The claims includedseveral AI-related elements, including "a set of trainingsamples used to traina trained neural networkmodel" as used to interpret a string of charactersfor speech translation. Claim 11 of the patent-at-issue isillustrative and is reproduced below:

receiving an inputaudio from a user; normalizing the input audio to make a totalpower of the input audio consistent with a set of training samplesused to train a trained neural networkmodel;

generatinga jitter set of audio files from the normalized input audio bytranslating the normalized input audio by one or more timevalues;

for eachaudio file from the jitter set of audio files, which includes thenormalized input audio:

generatinga set of spectrogram frames for each audio file; inputting theaudio file along with a context of spectrogram frames into atrained neural network; obtaining predicted character probabilitiesoutputs from the trained neural network;and

decoding atranscription of the input audio using the predicted characterprobabilities outputs from the trained neural network constrainedby a language model that interprets a string of characters from thepredicted character probabilities outputs as a word orwords.

Applying the two-partAlicetest, theExaminer had rejected the claims finding them patent-ineligible asmerely abstract ideas (i.e., mathematical concepts and certainmethods of organizing human activity without significantlymore.)

The PTAB disagreed. While the PTAB generally agreed that thepatentspecificationincluded mathematicalformulas, such mathematical formulas were"notrecited in theclaims." (original emphasis).

Nor did the claims recite "organizing human activity,"at least because, according to the PTAB, the claims were directedto a specific implementation comprising technical elementsincluding AI and computer speech recognition.

Finally, and importantly, the PTAB noted the importance ofthespecificationdescribing how the claimedinvention provides animprovementto thetechnical field of speech recognition, with the PTAB specificallynoting that "the Specification describes thatusingDeepSpeech learning,i.e.,a trained neural network, along with alanguage model 'achieves higher performance than traditionalmethods on hard speech recognition tasks while also being muchsimpler.'"

For each of these reasons, the PTAB found the claims of thepatent-at-issue inHannunto bepatent-eligible.

Each of Example 39 and the PTAB's informative decisionofHannundemonstrates theimportance of properly drafting AI-related claims (and, in general,software-related claims) to follow a three-part pattern ofdescribing an improvement to the underlying computing invention,describe how the improvement overcomes problems experienced in theprior art, and recite the improvement in the claims. For moreinformation, seeHow to Patent Software Inventions: Show an"Improvement".

The content of this article is intended to provide a generalguide to the subject matter. Specialist advice should be soughtabout your specific circumstances.

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How To Patent An Artificial Intelligence (AI) Invention: Guidance From The US Patent Office (USPTO) - Intellectual Property - United States - Mondaq...