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MachineLearningMachinelearning helps AI get smarter and more effective over time by learning from historical data. For instance, machinelearning 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.
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And when we used to archive fields physically, and we didn’t have documentmanagement systems. And you know, I’ve been through a lot of many revolutions over the last 20 years, say documentmanagement was one nice thing, you know, the BlackBerry was one, and I think there’s been a few others.
And when we used to archive fields physically, and we didn’t have documentmanagement systems. And you know, I’ve been through a lot of many revolutions over the last 20 years, say documentmanagement was one nice thing, you know, the BlackBerry was one, and I think there’s been a few others.
This protects the researcher from the AI “creating” the answer from all the non-relevant information it has collected in its large language model of machinelearning. They do AI machinelearning proofs of concepts for governments and large companies and so on. Lachance is working to use the GPT 3.5 I mean, this is yes.
And then after that, I made my way into the world of legal tech, working in data science for a company called RPI x, which was involved in serving the General Counsel’s Office of large tech firms on intellectualproperty matters. So work they’re developing natural language processing algorithms, working with with patent data.
In addition to marketing, we plan to polish the product’s “crown jewel,”, email parsing, to make it work perfectly with a variety of different document types. Finally, we plan to build integrations with e-discovery and practice management products. Our sales team has a strong focus on law firms with 50+ lawyers.
And then after that, I made my way into the world of legal tech, working in data science for a company called RPI x, which was involved in serving the General Counsel’s Office of large tech firms on intellectualproperty matters. So work they’re developing natural language processing algorithms, working with with patent data.
In addition to marketing, we plan to polish the product’s “crown jewel,”, email parsing, to make it work perfectly with a variety of different document types. Finally, we plan to build integrations with e-discovery and practice management products. This ensures immediate utility without disrupting established workflows.
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