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million pages from 39,796 books and converted it all into machine-readable text files. Case law books waiting to be scanned. Harvard would contribute the law books and run the scanning process inside the law library. We’d already tackled many of the toughest challenges: We didn’t know precisely which books to scan.
In today’s episode, we’ll be diving into the fascinating world of one of the most advanced machinelearning tools out there: ChatGPT. Professor Hoofnagle] 03:03 ChatGPT is the newest iteration of a machinelearning technology that can generate text. Or it could be books. And how often does this happen?
They are releasing a new book, The Legal Singularity: How Artificial Intelligence Can Make Law Radically Better later this year. Naming the book “The Legal Singularity” is a big claim by the authors, so we asked them to explain what they meant by it. Marlene Gebauer 1:03 So before we dive into the book, Abdi. Thanks, Marlene.
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. And that was there was a site that basically took the GPT and allowed it digest books. And then it allowed for a chat interface with the, with the book itself.
Every day we hear another horror story of a business or government entity being hit with ransomware. EDR uses sophisticated techniques such as artificial intelligence, machinelearning and heuristics to determine what would be considered normal operations for your computer systems.
Legal Research and Data Analytics: Gone are the days of poring over endless law books and case files in dusty libraries. Through machinelearning algorithms, e-discovery platforms can quickly identify patterns and connections in data. Technology has revolutionized legal research, making it faster and more efficient.
Marlene Gebauer 9:21 So Jordan, or Oren, or both of you, and I’m very interested in hearing the answer to this this question because, you know, just we’ve heard so much about these certifications in the past. So I think it’s going to be in cyber privacy, in machinelearning everything. We’d love to hear from you.
million pages from 39,796 books and converted it all into machine-readable text files. Case law books waiting to be scanned. Harvard would contribute the law books and run the scanning process inside the law library. We’d already tackled many of the toughest challenges: We didn’t know precisely which books to scan.
Continuous learning and adaptation are not just advantageous, they are essential. I am quite sure we are all going to hear a lot more about this topic soon in the legal and compliance industry, especially when UX/UI design will be better recognised as a driving force for successful legal tech products.
They are releasing a new book, The Legal Singularity: How Artificial Intelligence Can Make Law Radically Better later this year. Naming the book “The Legal Singularity” is a big claim by the authors, so we asked them to explain what they meant by it. Marlene Gebauer 1:03 So before we dive into the book, Abdi. Thanks, Marlene.
How we’re unique: Starting from basic marketplace, Amazon+Uber for lawyers, approach, AppearMe is implementing machinelearning to automate routine legal work, minimize errors and missed deadlines by targeting the $65B litigation support market and offering free case management tools (a $1.1B We offer managed hearing services.
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 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. We’d love to hear from you. If you enjoy the show, share it with a colleague.
Marlene Gebauer 9:21 So Jordan, or Oren, or both of you, and I’m very interested in hearing the answer to this this question because, you know, just we’ve heard so much about these certifications in the past. So I think it’s going to be in cyber privacy, in machinelearning everything. We’d love to hear from you.
How we’re unique: Starting from basic marketplace, Amazon+Uber for lawyers, approach, AppearMe is implementing machinelearning to automate routine legal work, minimize errors and missed deadlines by targeting the $65B litigation support market and offering free case management tools (a $1.1B We offer managed hearing services.
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. We’d love to hear from you. If you enjoy the show, share it with a colleague.
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.
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 with technology, you there’s a great book you’ve probably read it’s from Paul, Dorothy human plus machine, and they show a lot of example where the computer they’ll slide 80% And then the human is also 80%. So you’re probably familiar with that yourself when you’re using this machinelearning.
There are many different ways that one can approach this problem, both from a technical approach different techniques, and machinelearning techniques that one can can use. Because I can hear my, my IT security guy screaming right now. As a special treat, we wrap up the interview with a demonstration of Paxton.AI’s capabilities.
There are many different ways that one can approach this problem, both from a technical approach different techniques, and machinelearning techniques that one can can use. Because I can hear my, my IT security guy screaming right now. As a special treat, we wrap up the interview with a demonstration of Paxton.AI’s capabilities.
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