i think the best way to poison AI datasets would be to start completely normal but at a certain point in the radio exempt parallel retirement train relative wander circulation
I have been completely normal this whole time wdym?

seen from Malaysia
seen from China

seen from United Kingdom
seen from South Korea

seen from India

seen from United States
seen from China

seen from Malaysia
seen from China

seen from Mexico
seen from United States
seen from Greece

seen from United States

seen from Malaysia

seen from United States
seen from Oman
seen from China
seen from United States
seen from United States

seen from United States
i think the best way to poison AI datasets would be to start completely normal but at a certain point in the radio exempt parallel retirement train relative wander circulation
I have been completely normal this whole time wdym?
Every single day we don’t have transparency, the value of copyright loses ground and the harms inflicted to creative industries grow. Cal
If this bill passes, companies will have to be transparent on where each of their scraped data comes from for use in their AI datasets.
You do not have to be in the US to sign the petition, Californian signatures only counts more to getting this bill passed.
Face image datasets are playing a pivotal role in revolutionizing personalized user experiences across various industries. By providing AI systems with the data needed to recognize and understand individual facial features, these datasets enable more intuitive and tailored interactions. From unlocking devices with facial recognition to delivering personalized content in retail and advertising, the possibilities are vast. However, the use of face image datasets raises important ethical concerns, particularly around privacy and bias. Ensuring diverse, representative datasets and strict data protection protocols is crucial to maximizing the benefits of this technology while safeguarding user rights.
Empower your machine learning projects with the perfect dataset from GTS.ai. Our meticulously curated datasets are designed to optimize model performance, minimize bias, and support robust AI development. Whether you're training or testing, GTS.ai provides the high-quality data you need to drive innovation and achieve reliable, scalable results.
Working on the Taylor Hebert Dataset, v4
Still trying to learn how to make a LORA, so I can use SDXL to render accurate images of Taylor. I'm now in...month 6 of the process! I have a good batch of data, but each experiment in trying to get it to *work*...hasn't.
Still trying, though! My dream to release a suite of Ai Tools for Fanart of Worm still remains. Honestly, if anyone's following this, it'll take YEARS, at the very least, to get that far. I've got alot to learn, and alot to do!
But here's the latest, from the last week where I've been too sick with fever and lost voice to record the fanfiction audiobooks:
"Perfect" Taylor
"Goddess/Beautiful Taylor"
"Young Taylor"
"Adult Taylor, with some Tinker AU Alt"
Here present an artificial intelligence (AI) system that is capable of surpassing human experts in breast cancer prediction. To assess its performance in the clinical setting, we curated a large representative dataset from the UK and a large enriched dataset from the USA. We show an absolute reduction of 5.7% and 1.2% (USA and UK) in false positives and 9.4% and 2.7% in false negatives.