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Capabilities 45 results

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Artificial Intelligence (AI)

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....Read more

Industry

Technology, Media & Telecommunications

Insights & News 686 results

Competition Corner

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July 28, 2025

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9 Min Read

New Legislation and Enforcement Initiatives: The State Enforcement Future and Impact

As federal antitrust enforcement continues to evolve, adjust priorities, and in some cases, stall out, states are increasingly enhancing their enforcement focus, resources, and law.

Competition Corner

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July 15, 2025

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3 Min Read

Colorado Becomes Second State to Enact a Broad Premerger Notification Requirement Covering All Industries

Colorado recently became the second state, after Washington, to enact the Uniform Antitrust Premerger Notification Act (UAPNA) and establish a general state-level premerger notification requirement. 

In the Media

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July 14, 2025

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1 Min Read

Sara Susnjar and Cari Stinebower Discuss Trump’s First 100 Days and the Impact on European and American Markets with NextStep Magazine

Winston & Strawn partners Sara Susnjar and Cari Stinebower were featured in a Q&A with NextStep Magazine, where they discussed the impacts of Trump administration decisions made in his first 100 days in office on company and investor strategies. In the Q&A they provide insights on topics including slowed M&A activity in Europe and how American investors are reacting; how new policies may impact French investments in American companies in the long term; issues related to artificial intelligence, sanctions, and digital assets; and advice they would give to companies aiming for international growth....Read more
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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....Read more

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Artificial Intelligence Policies

Site Content

What Is Generative AI?

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]...Read more
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