Site Search
Professionals 128 results
Capabilities 48 results
Industry
Industry
Development & Protection of AI Technologies
Our Intellectual Property (IP) and Privacy teams work closely together to counsel clients in building, protecting, and commercializing proprietary AI technologies and data; the use of third party or open source AI technologies and data; and the implications that these activities may have under privacy laws.
Experience 35 results
Experience
|January 19, 2026
Winston Advises smartTrade Technologies Group on the Acquisition of kACE
A cross-border team from advised smartTrade Technologies Group (“smartTrade”), a leading provider of multi-asset electronic trading and payments solutions, on its acquisition of kACE Financial (“kACE”), formerly known as Fenics, a well-established provider of technology solutions for FX and interest rate derivatives pricing, analytics, and workflow management.
Experience
|September 22, 2025
Winston Paris advised the founders and shareholders of Bylaw, on its acquisition by Septeo
Founded in 2019 by Adrien Aboudaram and Tuan Ardouin, Bylaw has developed next-generation AI technology to automate the processing of legal and financial documents. With a team primarily dedicated to R&D, the legaltech company aims to become the leading AI reference for regulated professions.
Experience
|July 31, 2025
Nscale Forms $1 Billion AI Data Center Joint Venture with Aker
Winston & Strawn LLP represented Nscale Global Holdings Ltd. in connection with the formation of a 50/50 joint venture with Aker ASA to develop Stargate Norway, a $1 billion AI data center project in partnership with OpenAI. The facility will be located near Narvik, Northern Norway, and will be powered entirely by renewable hydropower.
Insights & News 710 results
Recognitions
|January 26, 2026
|1 Min Read
Keerthika Subramanian Invited to Become a Fellow of the American Bar Foundation
Winston & Strawn is proud to announce that partner Keerthika Subramanian has been invited to become a Fellow of the American Bar Foundation (ABF), a prestigious, invitation-only honor recognizing exceptional leadership, professional achievement, and dedication to the legal profession. Fellowship in the ABF is limited to the top one percent of lawyers, judges, and legal academics in the United States.
Seminar/CLE
|January 20, 2026
Winston & Strawn and RSM US LLP are co-hosting the annual NYC SBIC Fund Conference on Tuesday, January 20, 2026.General and limited partners, chief financial officers, and controllers of small business investment company (SBIC) funds are invited to a half-day seminar covering various topics related to SBIC fund operations, including:
Other Results 28 results
Site Content
What Is Artificial Intelligence (AI)?
The definition of artificial intelligence, also known as AI, is the capability of computers or robots to execute tasks that humans normally do. The meaning of AI can also include the development of computer systems that perform intellectual processes. In other words, machines perform tasks intelligently, such as reasoning and generalizing. Narrow AI is a type of artificial intelligence where the focus is placed on specific tasks. An example of this would be a virtual assistant who has targeted abilities, such as the ability to respond to questions. Strong AI is machine intelligence featuring human cognitive capabilities, such as the ability to make judgments, find solutions, or communicate. Today, it’s important to understand what artificial intelligence systems are commonly used for, including visual perception, speech recognition, and decision-making.
Site Content
Generative AI tools can create new content, such as text, computer code, images, audio, sound, and video, in response to a user’s prompt, often in the form of a short written description of the desired output. Generative AI tools are based on machine learning, trained using enormous amounts of data.[1] Generative AI tools are built on a system of inputs and outputs. First, the tool goes through a machine learning period whereby it is trained to generate predictive models and creative outputs through a large data set, often varied and diverse but tailored to the goal of the tool (i.e., customer service, generating scientific or marketing models, etc.). For in-house tools, this can be done with the company’s own data; for larger tools such as ChatGPT, this is done with the creator’s data set.[2] Once the tool has been trained, the individual user “inputs” a short prompt for the tool to synthesize and produce an “output.” Inputs are often retained on the servers controlled by the company that supports the tool, for monitoring of the tool’s performance and, in some cases, continued learning. The “outputs” are created by combining the machine learning during the training period with the inputs to produce an output.[3]