NLPatent is an industry leading AI-based patent search and analytics platform trusted by Fortune 500 companies, Am Law 100 firms, and research universities around the world. The platform takes an AI-first approach to patent search; it's built from a proprietary Large Language Model trained on patent data to truly understand the language of patents and innovation.
PQAI stands for Patent Quality Artificial Intelligence. It is a free, open-source, natural language-based patent search platform developed by AT&T and the Georgia Intellectual Property Alliance. PQAI is designed as a collaborative initiative to build a shared AI-based tool for prior art searching.
Solve Intelligence is an AI-powered platform designed for intellectual property legal professionals, specializing in streamlining the patenting process. Founded in 2023 and based in San Francisco, the company develops AI tools specifically for patent attorneys, focusing on user-centric design and practical application.
Amplified AI is an intellectual property (IP) technology company offering AI-powered search and collaboration tools. It helps researchers and innovators research, document, and share technical intelligence within their teams by organizing and curating global patent and scientific information.
Ambercite AI is a patent search tool that utilizes artificial intelligence (AI) and network analytics to identify patents similar to a given set of starting patents. It differs from traditional patent searching methods that rely on keywords and patent class codes by using citation patterns, patent text, and metadata to find relevant patents and reduce false positives.
PatentPal is an AI-powered platform designed to streamline the patent drafting process for legal professionals. It utilizes generative AI to automate the creation of patent applications, including generating descriptions, figures, and supporting documents from a set of claims. PatentPal aims to save time for patent attorneys and agents, allowing them to focus on higher-value aspects of their work. It can export drafts into formats like Word, Visio, or PowerPoint.
Bloomberg Law's comprehensive analysis examines how generative AI technologies can help legal teams solve common contract workflow challenges including slow drafting processes, inefficient storage systems, and communication difficulties. The assessment details how AI contract management technology solutions improve contract performance, fulfill professional obligations, and mitigate risks while automating routine tasks throughout the contract lifecycle. This authoritative legal technology analysis emphasizes that while contract management tools can incorporate AI for automation, successful implementation requires strategic integration with existing workflows and proper understanding of AI capabilities versus human legal expertise requirements.
BMC Medical Ethics' comprehensive analysis examines the disruptive potential of AI in healthcare while addressing the lack of professional training in AI usage, providing ethical and legal frameworks for healthcare professionals navigating the AI transformation. The research analyzes literature on healthcare AI ethics and law, creating categories of frequently cited issues while proposing improvements to help professionals manage AI implementation challenges. This peer-reviewed biomedical ethics study emphasizes how classical legal regimes struggle to incorporate AI realities and require constant adaptation, highlighting risk-based regulatory approaches like the EU AI Act as potential solutions to balance innovation promotion with harm prevention.
Microsoft Research's expert panel discussion features bioethicist Vardit Ravitsky, Stanford physician-scientist Dr. Roxana Daneshjou, and NAM advisor Laura Adams examining responsible AI implementation in medicine from governance and fairness perspectives. The analysis highlights critical bias mitigation work, including research showing how large language models propagate race-based medicine and dermatology AI performance disparities across skin tones. This cutting-edge healthcare AI ethics discussion emphasizes the need for proactive bioethics guidance as AI reshapes healthcare relationships while acknowledging AI's potential to address healthcare system inefficiencies and physician burnout despite bias and hallucination challenges.
SSRN's academic analysis explores how AI technologies including machine learning algorithms and smart contracts challenge traditional legal principles in contract formation, interpretation, performance, and enforcement while introducing complexities around legal responsibility. The research discusses AI's capacity for autonomous negotiation, impartial contract interpretation, and blockchain-enabled agreement enforcement, proposing frameworks to integrate AI into contract law while ensuring fairness and accountability. This scholarly legal analysis emphasizes the crucial balance between technological advancement and legal principles as AI continues evolving, demonstrating how emerging technologies require adaptive regulatory approaches to maintain contract law effectiveness.
AMA's analysis reveals growing physician acceptance of AI while emphasizing the need for responsible, transparent development as the Trump administration shifts toward deregulation and Congress considers a 10-year moratorium on state AI regulation. The assessment highlights federal gaps filled by state action and details AMA policy recommendations for ethical, equitable AI implementation in healthcare settings. This medical profession perspective demonstrates the tension between innovation promotion and regulatory oversight as physicians call for mandatory transparency requirements and proper regulation beyond voluntary standards to ensure AI tools serve patient care effectively.
Holland & Knight's regulatory analysis tracks federal and state efforts to regulate AI deployment in healthcare utilization management and prior authorization processes, with CMS clarifying that Medicare Advantage plans cannot rely solely on AI for medical necessity determinations. The assessment details Colorado's Consumer Protections Act and various state healthcare AI bills while emphasizing that AI can assist coverage decisions but requires human oversight and clinical judgment. This specialized healthcare law analysis provides crucial compliance guidance for managed care plans and utilization management organizations navigating the evolving regulatory landscape around AI in healthcare coverage decisions.