Employees who frequently interact with artificial intelligence systems are more likely to experience loneliness that can lead to insomnia and increased after-work drinking, according to research published by the American Psychological Association.
Researchers conducted four experiments in the U.S., Taiwan, Indonesia and Malaysia. Findings were consistent across cultures. The research was published online in the Journal of Applied Psychology. — Read More
The Study
Daily Archives: June 13, 2023
Geoffrey Hinton – Two Paths to Intelligence
Why trying to “shape” AI innovation to protect workers is a bad idea
Instead, we should empower workers and create mechanisms for redistribution.
I’ve been to a number of meetings and panels recently where intellectuals from academia, industry, media, and think tanks gather to discuss technology policy and the economics of AI. Chatham House Rules prevent me from saying who said what (and even without those rules, I don’t like to name names), but one perspective I’ve encountered increasingly often is the idea that we should try to “shape” or “steer” the direction of AI innovation in order to make sure it augments workers instead of replacing them. And the economist Daron Acemoglu has been going around advocating very similar things recently:
According to Acemoglu and [his coauthor] Johnson, the absence of new tasks created by technologies designed solely to automate human work will…simply dislocate the human workforce and redirect value from labour to capital. On the other hand, technologies that not only enhance efficiency but also generate new tasks for human workers have a dual advantage of increasing marginal productivity and yielding more positive effects on society as a whole… — Read More
Perfectly Secure Steganography Using Minimum Entropy Coupling
Steganography is the practice of encoding secret information into innocuous content in such a manner that an adversarial third party would not realize that there is hidden meaning. While this problem has classically been studied in security literature, recent advances in generative models have led to a shared interest among security and machine learning researchers in developing scalable steganography techniques. In this work, we show that a steganography procedure is perfectly secure under Cachin (1998)’s information theoretic-model of steganography if and only if it is induced by a coupling. Furthermore, we show that, among perfectly secure procedures, a procedure is maximally efficient if and only if it is induced by a minimum entropy coupling. These insights yield what are, to the best of our knowledge, the first steganography algorithms to achieve perfect security guarantees with non-trivial efficiency; additionally, these algorithms are highly scalable. To provide empirical validation, we compare a minimum entropy coupling-based approach to three modern baselines — arithmetic coding, Meteor, and adaptive dynamic grouping — using GPT-2, WaveRNN, and Image Transformer as communication channels. We find that the minimum entropy coupling-based approach achieves superior encoding efficiency, despite its stronger security constraints. In aggregate, these results suggest that it may be natural to view information-theoretic steganography through the lens of minimum entropy coupling. — Read More
Meta’s Open-Source ‘MusicGen’ AI Is Like ChatGPT for Tunes
Meta has released another open-source AI model trained on hundreds of thousands of music tracks online.
AI has managed to intrude on most artistic endeavors, and now it’s fully come for the music industry. Meta has now announced the release of the open source version of its music generation AI model that uses simple prompts to generate music like ChatGPT or other large language model-based AI generate text.
… [T]he model uses an EnCodec audio tokenizer based on a transformer language model. Users can demo MusicGen through Hugging Face’s API, though, generating some music could take some time depending on how many users are using it at once. You can use the Hugging Face site to create your own instance of the model for much faster outputs. Otherwise, you can download the code and run it yourself if you have the know-how and the rig to support it. — Read More
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