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Zero Trust Hash Validation for DePIN Networks

Zero Trust Hash Validation for DePIN Networks

Verifiable Cryptographic Obfuscation Methods Using PUF and LPN Encryption

The USPTO published patent application US20260100853A1 for verifiable cryptographic obfuscation methods using physically unclonable functions (PUF) and Learning Parity with Noise (LPN) encryption. The invention covers systems that verify obfuscation integrity by comparing corrected and corrupted PRG outputs via Hamming distance analysis. Technology companies and patent professionals should review for prior art and licensing implications.

Verifiable Cryptographic Obfuscation Patent Using Physically Unclonable Function

The USPTO published patent application US20260100854A1 for Vipin Singh Sehrawat's verifiable cryptographic obfuscation system using physically unclonable functions (PUFs). The patent covers methods for generating error vectors via PUF circuits to enable LPN encryption verification of PRG outputs using Hamming distance analysis.

Two-Fold Digital Credential Verification and Signing Methods

USPTO published patent application US20260100851A1 disclosing methods and systems for issuing certificate-type digital credentials and electronically signing documents. The invention requires two-fold verification comprising credential validity checks (proof, expiration, revocation) plus verification that a trusted issuer exists within a parent-child relationship. Both credential types can be organized in a digital identity hierarchy using distributed ledger technology.

Secure Passkey Enrollment Using Digital Wallet Credentials

Secure Passkey Enrollment Via Digital Wallet Credentials

Human-in-the-Loop AI Training for Agentic Automation Patent Application

USPTO published patent application US20260099135A1 by UiPath, Inc. covering human-in-the-loop automation training using AI for agentic automation systems. The invention enables a listener to monitor user or AI agent interactions with computing systems and improve or personalize automation based on those interactions.

Neural Network Quantum Error Correction Decoding Method and Apparatus

USPTO published patent application US20260099754A1 by Tencent Technology (Shenzhen) on April 9, 2026. The application covers neural network-based methods for quantum error correction decoding, including error syndrome acquisition, feature extraction via neural network decoder, and error result determination for quantum circuits.

LLM Unlearning via Loss Adjustments - Accenture Global Solutions

USPTO published patent application US20260099772A1 by Accenture Global Solutions Limited disclosing a system and method for large language model unlearning via a forget data only loss adjustment (FLAT) function. The invention involves accessing forget data samples, associating template responses via LLMs, and training a target LLM using loss adjustments to maximize divergence between template and forget answers.

AI Models for Edge Case Driving Scenarios

The USPTO published patent application US20260099762A1 from AUTOBRAINS TECHNOLOGIES LTD describing methods for generating AI models for autonomous driving using clustered driving scenario data to enhance decision-making in edge case scenarios.

Hierarchical Speech Analysis Method for Age, Gender, and Emotion Detection

USPTO published patent application US20260100196A1 for Tencent America LLC, covering a hierarchical speech analysis method using two-stage neural networks to detect speaker age, gender, and emotion from voice signals. The first learning stage performs initial detection while the second stage refines these attributes. This patent application relates to AI-driven speech processing technology.