Edge is a company based in San Francisco that specializes in AI-driven patent writing tools. Edge aims to streamline the patent drafting process, helping inventors and legal professionals create high-quality patents more efficiently. The company's software assists in drafting claims, descriptions, and backgrounds for patents, potentially reducing errors and improving the overall quality of patent applications.
Garden Intelligence is an AI-powered platform designed to streamline and enhance the patent process for various stakeholders, including R&D organizations, inventors, patent prosecutors, and litigators. It combines AI reasoning models, a patent search index, and web scraping to provide tools for tasks such as invalidity searches, claim chart generation, and infringement analysis.
DeepIP, an AI-powered personal assistant designed to streamline the patent drafting process and manage responses to office actions. It aims to free intellectual property (IP) practitioners from tedious tasks, allowing them to focus on delivering greater value to their clients. DeepIP can summarize lengthy documents quickly, providing essential insights at a glance.
Patlytics a company specializing in AI-powered patent intelligence solutions. Patlytics offers a platform that assists with various aspects of the patent lifecycle, including patent drafting, prosecution, litigation, and portfolio management. The platform leverages AI and large language models (LLMs) to streamline patent-related processes and enhance efficiency for IP professionals.
Patented AI provides an essential tool to help individuals and companies protect against inadvertently sharing personal identifying information, trade secrets, and all other sensitive data with virtually all LLMs, enabling individuals across all industries to get on-device sensitive data checks and protection.
IP Copilot is an AI-powered platform designed to revolutionize intellectual property (IP) management, helping organizations discover, capture, curate, and protect their IP more efficiently. It uses AI to streamline the invention disclosure process, perform real-time prior art searches, and facilitate quick filing decisions.
AP News reports on UK High Court Justice Victoria Sharp's warning that lawyers citing AI-generated fake cases pose 'serious implications for the administration of justice and public confidence in the justice system.' The case highlights growing global judicial concerns about AI misuse in court proceedings, with judges threatening prosecution for attorneys who fail to verify AI-generated research accuracy. This breaking news story exemplifies the urgent need for regulatory frameworks and professional standards governing AI use in legal practice as courts worldwide grapple with maintaining integrity in an AI-enhanced justice system.
ABA's comprehensive legal analysis covers the busiest year in AI legal history, examining copyright battles between algorithmic infringement allegations and fair use defenses while tracking bias, transparency, and privacy litigation trends. The report details landmark cases including USA v. Michel, where criminal convictions involved experimental GenAI program usage, and emphasizes how trial courts are creating de facto AI legal rules absent comprehensive congressional regulation. This authoritative judicial overview demonstrates that judges and bar regulators are increasingly focused on ethical GenAI use rules as litigation shapes AI law development through case-by-case precedent.
Copyright Alliance's comprehensive litigation review tracks over thirty GAI copyright lawsuits including landmark cases like Andersen v. Stability AI and Kadrey v. Meta, with key developments including DMCA dismissals and fair use arguments by defendants. The analysis highlights critical 2024 court rulings that hint at judicial leanings while noting the consolidation of similar cases and the high-stakes nature of these disputes for both creators and AI developers. This detailed case tracking demonstrates how copyright litigation will be pivotal in shaping GAI's future, with courts beginning to address fundamental questions about training data use and fair use defenses.
ABA Journal's technology analysis reveals that 2024 marked a year of contradictions, with rapid AI integration into legal technology that remained largely surface-level despite unprecedented software update rates from vendors. The assessment details how AI transformed deposition analysis, brief drafting, pretrial discovery, and law practice management while noting that usage stabilized after initial rapid adoption. This practitioner-focused review emphasizes the ongoing challenges of leveraging accessible data for analytics and high costs of mainstream AI models, while highlighting AI's growing impact on litigation strategy and case management efficiency.
GWU Law's comprehensive litigation database tracks ongoing and completed AI cases from complaint forward, covering everything from algorithmic bias in hiring and criminal sentencing to autonomous vehicle liability and AI authorship disputes. This unique academic resource provides broad coverage of AI legal disputes including statistical analysis and data protection cases relevant to AI projects, serving as a critical research tool for understanding litigation trends. The database demonstrates the rapidly expanding scope of AI-related legal challenges across multiple domains and its systematic documentation reveals patterns in how courts are addressing novel AI legal questions.
White & Case's regulatory tracker reveals that over 40 state AI bills were introduced in 2023, with Connecticut and Texas enacting AI discrimination assessment statutes, while federal agencies apply existing authorities like the FTC's Rite Aid facial recognition settlement. The analysis highlights how comprehensive state privacy laws like California's CPPA and Illinois's biometric privacy act create overlapping AI compliance requirements, demonstrating the complex regulatory patchwork facing businesses. This authoritative legal tracking emphasizes the practical enforcement reality that existing civil rights, privacy, and consumer protection laws fully apply to AI deployment despite the absence of comprehensive federal AI legislation.