Lawsuit Litigation Machine learning 
Brett Trout
APRIL 21, 2025
Machine Learning Training Patents :Focused on optimizing live event schedules using machine learning models trained on historical data.? The claims involved applying generic machine learning to steps like collecting event parameters, training machine learning models, and generating optimized schedules or network maps.?
Colin S. Levy
NOVEMBER 5, 2024
Leveraging Litigation Analytics Litigation is data-intensive, and making sense of this data is crucial for managing risks effectively. GCs and their teams should begin by gathering and analyzing historical litigation data, not as a one-time exercise but as an ongoing practice.
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Eric Goldman
JULY 14, 2023
This long-running lawsuit started in 2019. When I first blogged this case in January 2021, I wrote: This lawsuit, like many others before it, claims that UGC services like YouTube commit illegal discrimination based on how they moderate content.
Clio
APRIL 17, 2025
This often involves artificial intelligence (AI) , data mining, machine learning, and other technologies. Predictive analytics can also guide whether to settle or proceed to court on a file based on analysis of past settlements, litigation costs, and opposing counsels behavior. How does predictive analytics work in litigation?
Percipient
JANUARY 20, 2025
Machine Learning Machine learning helps AI get smarter and more effective over time by learning from historical data. For instance, machine learning can predict litigation risks based on similar cases, identify trends that might impact a client, or flag unusual clauses in contracts that might need extra attention.
The North Carolina Journey of Law and Technology
FEBRUARY 19, 2024
Understanding Litigation Finance Litigation finance is when a third-party invests in a lawsuit in hopes of sharing in the profits of a successful verdict. litigation finance companies exist. billion in capital to litigation matters. billion in capital to litigation matters.
Lineal Services
AUGUST 11, 2023
Learn how to improve legal outcomes as you tackle the challenges of acquiring electronic evidence and understand the disruptive effects of AI and machine learning on eDiscovery. Predictive Coding: Based on a collection of training data, this approach uses machine learning algorithms to forecast the relevance of texts.
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