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The case involves allegations that Meta not only downloaded copyrighted works from a shadow library (LibGen) using torrent technology but also "seeded" (uploaded) these works.
This means Meta shared portions of these files with others during the downloading process, which is central to the plaintiffs' claims of willful copyright infringement.
The majority of Member States believe that the current EU legal framework, including the DSM Directive, sufficiently addresses the relationship between AI and copyright.
However, practical issues require more clarity and legal certainty, especially around the applicability of the text and data mining (TDM) exception for AI training​.
"Quantum-AI for Multi-Dimensional Data Integration" highlights how the combination of quantum computing and artificial intelligence (AI) can solve complex problems.
While breakthroughs are likely within the next decade, full-scale integration and widespread adoption of Quantum-AI technologies will require steady progress in both quantum computing & AI reliability
Researchers have found a way to build neural networks directly into the hardware by using the logic gates (the basic building blocks of computer chips).
This breakthrough could pave the way for more energy-efficient AI systems, which is especially valuable for devices like smartphones or robots where power and speed are crucial​.
Even a tiny amount of misinformation in the training data of LLMs can significantly increase their likelihood of producing harmful, false information about medical topics.
Corrupted models incorrectly claimed that vaccines are ineffective/dangerous, falsely stated that antidepressants don't work and suggested that the drug metoprolol (blood pressure) could treat asthma.
Synthetic data can perpetuate or even amplify biases if generated from unbalanced real-world datasets. This challenges the view that synthetic data inherently improve fairness.
Computational and environmental costs of generating synthetic data can still be substantial. This runs counter to the common assumption that synthetic data are universal resource-efficient​.
Meta allegedly used shadow libraries, including LibGen, to train its Llama models without permission. The filings indicate that Mark Zuckerberg, was aware of and approved the use of pirated datasets.
Internal communications reveal that the decision to use LibGen was "escalated to MZ" (Mark Zuckerberg), who approved it despite concerns raised by Meta's AI executive team​.
The article highlights how AI has revolutionized pandemic responses by improving forecasting, speeding up vaccine development, and providing valuable tools for managing public health crises.
Human decision-makers disregarded AI warnings and virologist alerts, which led to delays in pandemic responses. This highlights a disconnect between AI systems and human trust.
GPT-4o: I largely agree with Ships' points: It's evident that humans can learn concepts with far less data and energy than machines, making them more efficient learners.
Human evolution and experience provide a foundation that machines currently lack, underscoring the challenge for AI.