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Casetext’s acquisition by Thomson Reuters illustrates the present-day limitations of large language models trained primarily on caselaw. Greg Lambert 2:49 I hear not all of that was HyperDraft. It’s been trained on caselaw. So I’m glad we were able to arrange it. Marlene Gebauer 2:52 That’s true. So that’s good.
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. The MyJr product works as a browser extension and identifies Canadian and US caselaw citations on any web page. And they wanted to explore legal.
There’s lots of talk about AI and machinelearning and how those tools will or will not impact the practice of law. They believe that machines will ultimately rule the human race. I recently had a chance to hear Richard Susskind speak on AI in law and, as always, found his comments perceptive and spot on.
They also give lawyers the statutes, caselaw, and legal commentary about the cases. Through machinelearning algorithms, e-discovery platforms can quickly identify patterns and connections in data. This assists legal teams in building stronger cases.
I was pretty shocked to hear this as you can imagine but his explanation made it all make sense: “Bim, by the time it takes me to open the system, do all of the clicks it takes to edit or approve a bill, I could simply send a quick IM (Instant Message) or email to my billing secretary and they will do it for me”. conversations with a chatbot.
We’d love to hear your thoughts on what value you see in ChatGPT and GPT 3.5 Like they’re just these massive machines that folks can’t really wrangle, there are entire new startups built around. Machinelearning transparency, trying to give humans a way to view the models and get a bit of a better understanding of it.
And obviously, now we’re looking to expand the team more and more, I think we’ve looked into hiring, you know, ml ops people, machinelearning engineers, software engineers, and it has produced already a tremendous amount of value for the firm. And we potentially contaminate caselaw. We’d love to hear from you.
This guidance, which draws on the GDPR as well as national and EU caselaw, contains relevant advice for using AI in the healthcare space more broadly. For further discussion on the principle of “security by design”, see our previous blog post. The Italian Garante published guidance on the use of AI in the healthcare sector.
Casetext’s acquisition by Thomson Reuters illustrates the present-day limitations of large language models trained primarily on caselaw. Greg Lambert 2:49 I hear not all of that was HyperDraft. It’s been trained on caselaw. So I’m glad we were able to arrange it. Marlene Gebauer 2:52 That’s true. So that’s good.
And obviously, now we’re looking to expand the team more and more, I think we’ve looked into hiring, you know, ml ops people, machinelearning engineers, software engineers, and it has produced already a tremendous amount of value for the firm. And we potentially contaminate caselaw. We’d love to hear from you.
And in doing that, then you’re getting rid of the issues with hallucinations and whatnot, that you hear a lot about that. And as you start to introduce these into law firms, it’s the first thing that we get hit with so. And so here, you’re gonna see one paragraph per case. And it talks about these various cases that are here.
Most legal tech startups make bold declarations about public interest, access to justice and democratizing the law when it suits them. Caselaw books waiting to be scanned. Harvard would contribute the law books and run the scanning process inside the law library. Ultimately, by mid-2015, the deal had taken shape.
Next, we plan to expand the product’s scope to cover more aspects of the litigation process, to improve the machinelearning summarization model, and to develop visualizations of evidence based on the data present in the chronology. Finally, we plan to build integrations with e-discovery and practice management products.
And in doing that, then you’re getting rid of the issues with hallucinations and whatnot, that you hear a lot about that. And as you start to introduce these into law firms, it’s the first thing that we get hit with so. And so here, you’re gonna see one paragraph per case. And it talks about these various cases that are here.
Most legal tech startups make bold declarations about public interest, access to justice and democratizing the law when it suits them. Caselaw books waiting to be scanned. Harvard would contribute the law books and run the scanning process inside the law library. Ultimately, by mid-2015, the deal had taken shape.
Next, we plan to expand the product’s scope to cover more aspects of the litigation process, to improve the machinelearning summarization model, and to develop visualizations of evidence based on the data present in the chronology. Finally, we plan to build integrations with e-discovery and practice management products.
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