This space is dedicated to exploring the vast and ever-evolving world of legal and artificial intelligence, sharing insights, breakthroughs, and stories from the forefront of legal AI innovation.
December 2, 2024
In 2025, more law firms will adopt AI tools modeled on their best lawyers to scale expertise and tackle tasks like investigations, compliance checks and due diligence. This growing trend toward proprietary AI systems will enable firms to deliver faster, smarter services while empowering lawyers to handle greater workloads without additional effort. As AI continues to reshape traditional revenue streams, firms will innovate by offering AI-driven legal services on demand, setting the stage for new ways to monetize expertise. Simultaneously, clearer regulations will emerge to ensure responsible and transparent use of AI in legal practice.
November 26, 2024
Generic legal AI can’t match your expertise. TrueLaw’s Expert Language Models (ELM™) are custom-built by your firm, for your firm, using Learning via Expert Feedback (LEF) technology. Tailored, trusted, and seamlessly integrated—AI that scales your impact without compromise.
November 19, 2024
As large language models (LLMs) hit a performance plateau, the future of AI lies in Expert Language Models™ (ELM™)—custom AI systems fine-tuned with enterprise-specific data and expertise. ELMs bridge the gap between generalized AI and real-world applications, delivering precision and efficiency in specialized tasks.
October 28, 2024
In the digital era, legal teams grapple with an ever-growing volume of data, making efficient information retrieval and enrichment crucial for informed decision-making. Knowledge management teams at large law firms can utilize Large Language Models (LLMs) to enrich data, thereby unlocking deeper insights, optimizing workflows, and reducing manual workload. This article explores how LLMs can revolutionize the handling of large-scale data enrichment within legal contexts, focusing on the enrichment processes and the benefits they confer.
October 4, 2024
Contextual Legal RAG, developed by TrueLaw's research team, is a novel approach to AI-powered legal information retrieval. It enhances traditional Retrieval-Augmented Generation by incorporating legal-specific context, aiming to improve the accuracy and relevance of legal research. This method shows promise for applications in case law research, contract analysis, and regulatory compliance, with its effectiveness currently under evaluation.
October 7, 2024
Advanced AI models like O1 have significantly improved response quality, but in the legal industry, the true value lies in effective retrieval systems. This article explores why investing in proprietary retrieval stacks is essential for law firms to fully leverage AI capabilities. We delve into the nuances of different retrieval needs, the limitations of current AI models in exhaustive searches like e-discovery, and how law firms can navigate these challenges to enhance their operations with AI.
This guide provides legaltech innovators with practical techniques to reduce hallucinations in Legal AI tools. The article breaks down strategies into beginner, intermediate, and advanced levels, offering methods such as allowing AI to acknowledge uncertainty, using direct quotes from legal texts, and fine-tuning models for specific legal tasks. These approaches help ensure that AI outputs are accurate, reliable, and aligned with the rigorous standards required in legal practice.
Discover how LLM distillation can revolutionize legal tech with Llama 3.1. This game-changing AI technique creates powerful, efficient legal tools by compressing large language models into smaller, specialized versions. Learn why Llama 3.1's open-source nature is perfect for developing custom legal AI solutions. Explore cutting-edge distillation methods, practical implementation strategies, and critical ethical considerations for law firms and legal departments. From automated contract analysis to AI-powered legal research, see how distilled LLMs are transforming legal practice. Understand the challenges and opportunities in this rapidly evolving field, and why collaboration between tech experts and lawyers is crucial.
August 23, 2024
The Legal AI Agent Framework is designed to help AI technology creators streamline and automate legal processes. By integrating AI-driven components with human oversight, this framework enhances efficiency in tasks like contract review, legal research, and document drafting. It offers a structured approach to managing legal tasks, ensuring accuracy and reliability. Discover how this framework can revolutionize legal operations and support the development of cutting-edge legal technologies. Explore practical examples of assistive legal AI agents and learn how they can transform your legal practice.
August 20, 2024
Discover how TrueLaw is pioneering the fine-tuning of AI models using law firms' internal data and expertise. Fine-tuning offers a powerful, efficient, and cost-effective approach to legal AI, providing firms with proprietary AI IP that outperforms general-purpose models. Learn how this emerging technology is transforming legal tasks like contract analysis, legal research, regulatory compliance, litigation support, and e-discovery. Fine-tuned models are smaller, faster, and more accurate, giving law firms a strategic advantage in the competitive legal landscape. Explore the future of legal AI with TrueLaw’s innovative approach.
July 2, 2024
Fine-tuning LLMs is essential for law firms when tasks require specialized legal knowledge, proprietary data, or customized outputs. It enhances AI capabilities for niche legal domains like financial crime investigation and e-discovery. However, for general tasks and well-documented legal knowledge, the base model often suffices, making fine-tuning unnecessary.
August 1, 2024
AI and Large Language Models (LLMs) can both increase and decrease litigation. They introduce new legal challenges and enhance detection of violations, potentially leading to more lawsuits. However, they also improve compliance, streamline dispute resolution, and promote fairer decisions, which can reduce legal conflicts. Key factors influencing this impact include regulatory frameworks and public trust. Organizations can minimize litigation risks by implementing robust compliance programs, maintaining transparency, mitigating biases, continuously monitoring AI systems, prioritizing ethical AI development, and engaging with regulators. These strategies help build trust and ensure long-term success in an AI-driven world
Model distillation offers a potent solution for e-discovery in law firms, allowing the creation of smaller, faster, and more efficient models tailored to specific legal cases. These distilled models are not only cost-effective but also enhance precision and recall by being customized to a firm’s unique legal playbook, outperforming standard large language models in targeted tasks.
May 28, 2024
In the legal AI domain, creating hallucination-free LLMs is theoretically impossible due to their probabilistic nature. Instead of aiming for AI to handle all legal work independently, the focus should shift towards developing tools that enhance human-AI collaboration. This involves building verification tools that link AI-generated outputs to specific sections of source material, highlight discrepancies, and incorporate user feedback. By maximizing precision and ensuring 100% recall, these tools can significantly improve the efficiency and accuracy of legal AI systems. The future of legal AI lies in integrating human expertise with advanced technology to deliver superior legal services.
May 16, 2024
In the evolving landscape of artificial intelligence, legal AI autonomous agents represent a new and promising concept for law firms, enhancing workflows and managing data efficiently. This article explores the frameworks for compound legal AI systems, explaining each component in detail and demonstrating how they integrate into law firm operations.
March 23, 2024
For law firms aiming to harness their internal knowledge, the retrieval stack in Large Language Models (LLMs) is key. The magic lies in customized Retrieval-Augmented Generation (Legal-RAG) systems, optimizing search by prioritizing precision and contextual accuracy. These systems can transform how firms manage and utilize their data, ensuring that even the most buried details are accessible.
March 16, 2024
Explore the necessity for law firms to ground their generative AI (GenAI) in their unique knowledge, enabling them to craft tailored legal solutions that resonate with their established practices and client needs, thus ensuring more effective, precise, and innovative legal services.
The legal landscape is undergoing a seismic shift, propelled by the transformative power of Artificial Intelligence (AI). While the promise of AI is tantalizing, the journey to full-fledged adoption is intricate, demanding a nuanced approach. This article serves as a comprehensive guide for law firms contemplating their AI journey, offering actionable insights into each phase and helping them discern their next strategic moves.
March 5, 2024
TrueLaw partners with NIST to promote AI safety and contribute legal AI expertise in developing AI standards, conducting research, and shaping policy.
The advent of Large Language Models (LLMs) has heralded a new era in legal practice. These AI-driven tools promise efficiency and innovation, yet they pose significant ethical considerations, particularly when it comes to client confidentiality. Let's explore how law firms can harness the power of LLMs while maintaining the sanctity of ethical walls and client privacy.
The legal tech landscape is rapidly evolving, with AI playing a pivotal role in transforming traditional processes. This article delves into the modern AI stack for legal applications, focusing on three primary components: Retrieval, Generation, and Feedback. We'll explore the techniques, their costs, and their potential use cases.
Artificial Intelligence (AI) has brought transformative changes across professional fields. However, while the capabilities of models like OpenAI's Generative Pre-trained Transformer (ChatGPT) are undeniably impressive, their limitations become apparent in specialized sectors like law. As we stand at the intersection of legal practice and AI, it's clear that a shift in approach should occur. Our focus must transition from general large language models to domain-specific Large Legal Language Models (LLLMs).
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