Copyright Cost Privacy Training 
Salesforce Marketing Cloud
MARCH 20, 2024
You can’t know why the AI does what it does until you understand how the LLM was trained and where its data came from. It’s estimated that Wikipedia makes up between 3%-5% of the scraped data used to train off-the-shelf LLMs. LLMs trained on this data are versatile, and can generalize their knowledge to a range of topics.
Content Standard
AUGUST 21, 2023
Download the Executive Snapshot of This Article Option 1: Public Generative AI Tools Public tools, such as ChatGPT and Google’s Bard, provide open access to pre-trained generative AI models. First, because models may have been trained on others’ copyrighted material.
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Martech
SEPTEMBER 22, 2023
In addition to the risks embedded in relying on what is essentially unconscious and amoral “intelligence,” users also face the very real prospects that copyright and privacy issues could mortally wound large language models (LLMs) like ChatGPT. LLMs have already been trained on inconceivably large datasets.
Content Standard
SEPTEMBER 19, 2023
While 68% of the execs polled by Gartner believe the benefits of generative AI outweigh the risks, it’s forecasted that trust, security, privacy, and ethical challenges loom on the horizon for many organizations developing and deploying gen-AI solutions.
Sprout Social
SEPTEMBER 26, 2023
Others jumped on the bandwagon without truly understanding migration complexities or associated costs. To gain a deeper understanding of this issue, it is important to delve into the mechanics of AI tools powered by generative pre-trained models (GPT). Yet today, cloud computing is ubiquitous.
Litmus
MAY 16, 2023
The most prevalent concerns around AI include: Privacy and surveillance Bias and discrimination Inaccurate data Copyright infringement Plagiarism Data breaches Those are some heavy-hitting issues. Plus, it promises a way to do more with less, while keeping costs down. Sounds great, right?
Spiralytics
JUNE 11, 2023
Many argue that it’s the first viral AI-generated song , receiving over 230,000 views on YouTube and 625,000 streams on Spotify before copyright strikes from Universal Music Group—the artists’ label—took it down. These instances put into question whether or not artists and content creators should copyright their voices.
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