We are excited to announce that Text IQ has been acquired by Relativity, a global legal and compliance technology company, which was recently valued at $3.6 billion. The acquisition will dramatically accelerate Text IQ's goal to help the world's largest organizations take control of their unstructured data.
We have big news!
The ABA’s recent resolution urging courts and lawyers to consider the ethical and legal consequences around using AI raises another equally important, though less frequently discussed question: Could it be unethical not to use AI?
At its 2019 annual meeting the ABA adopted Resolution No. 112 urging courts and lawyers to address the emerging ethical and legal issues relating to the usage of artificial intelligence (AI) in the practice of law including: bias, explainability and transparency of automated decisions made by AI; ethical and beneficial usage of AI; and controls and oversight of AI and the vendors that provide AI.
Data is the raw material that fuels the information age. Today’s most successful enterprises have comprehensive strategies for collecting, storing, and utilizing that data, and this gives them a huge advantage. However, in order to extract that value from our data, we need to turn it into knowledge.
What if, instead of opening files to figure out if they contain privileged or sensitive information, you could simply look at your filesystem and tell at a glance what files include what kinds of information?
What if, instead of opening files to figure out if they contain privileged or sensitive information, you could simply look at your filesystem and tell at a glance what files include what kinds of information? Or, better yet, what if we could automate this system so that we can create a comprehensive information governance strategy that marks and categorizes data in real time as it’s created?
Let’s pierce the darkness and cut to the chase. In this article, we’re taking a moonshot at demystifying AI by going to the heart of the issue: exploring artificial intelligence itself. Taking a note from Euclid’s Elements, we’ll start with a few definitions.
Let’s start by thinking about how we learn new skills. Suppose you’ve downloaded and installed a new piece of software,and you’re loading it up for the first time. When you enter the interface, everything is new. As you explore the menus, options, and functions, you start to realize just how complicated this program really is, and you feel lost and confused.
“Every block of stone has a statue inside it, and it is the task of the sculptor to discover it.” In this way, Michelangelo explained the creative process that led him to turn rough chunks of marble into some of the world’s most prized sculptures. Rather than transforming the raw materials into something new, the artist subtracted the unnecessary rock to reveal that which lay hidden inside.
Children are born with intelligence but lack knowledge. As they observe and interact with the world, experience feeds into that intelligence and gradually knowledge takes form. This, of course, is what we call learning.
With its General Data Protection Regulation, Europe is calling on United States companies to rethink some of their core business models and data processes. And as organizations contend with life after GDPR, many of them are finding that the only thing they need to change about their data strategy is... everything.
My favorite machine learning study is not from a machine learning journal, but from a study about the Ancient Chinese. This says a lot about the versatility of AI.
Last month, Text IQ hosted the first The Inevitable at the offices of Jones Day in New York City. The invite-only executive gathering was attended by Fortune 100 executives and leading Artificial Intelligence researchers to discuss AI’s evolving role in protecting highly-regulated enterprises.
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