Probabilistic inference serves as a popular model for neural processing. It is still unclear, however, how approximate probabilistic inference can be accurate and scalable to very high-dimensional continuous latent spaces. Especially as typical posteriors for sensory data can be expected to exhibit complex latent dependencies including multiple modes. Here, we study an approach that can efficiently be scaled while maintaining a richly structured posterior approximation under these conditions. As example model we use spike-and-slab sparse coding for V1 processing, and combine latent subspace selection with Gibbs sampling (selectand-sample).

Strong coverage and a long run time make this pool-cleaning robot a compelling alternative to pricier models. Great performance for the price (assuming you can grab it on sale). Floats when cleaning is complete. Basket can be harder to clean than expected. Minimal intelligence (though it doesn't seem to need it).

McDonald's boss on abuse claims: 'I don't want to talk about the past' The boss of McDonald's UK and Ireland has said she doesn't want to talk about the past when asked about allegations of abuse at the fast-food chain. Lauren Schultz told the BBC what had happened in recent years was unacceptable but said we have drawn a line under it. A BBC investigation in 2023 heard from more than 100 McDonald's workers in the UK claiming they faced a toxic culture of sexual assault, harassment, racism, and bullying. Last year, staff said they still faced sexual abuse and harassment. The UK equality watchdog agreed tougher measures with the company to protect staff in November, including new sexual harassment training.

Anthropic is investigating a claim that a small group of people gained access to its Claude Mythos model - the cyber-security tool which the AI firm says is too powerful to release to the public. We're investigating a report claiming unauthorized access to Claude Mythos Preview through one of our third-party vendor environments, the company said in a statement. It was in response to a Bloomberg report that users in a private forum managed to access the model without the normal permissions. There is deep unease about Mythos' capabilities - though the UK's top cyber official has said advanced AI tools could be a net positive if the technology was secured from misuse. There is currently no suggestion that malicious actors have managed to get hold of the model, and Anthropic says it does not have evidence its systems are affected.

Pose your questions ahead of our May 8 livestream about the trial that could determine the fate of OpenAI. Two of Big Tech's most influential billionaires, Sam Altman and Elon Musk, will go head-to-head in a highly anticipated trial beginning April 27. In Musk v. Altman a judge, advised by a jury, will ultimately determine whether OpenAI has strayed from its founding mission to ensure that artificial general intelligence (AGI) benefits humanity, and the ruling could influence how the world's leading AI developer controls and distributes its technology. For now, you can learn more about the trial here . On May 8, a panel of WIRED experts will go live to answer your questions about this consequential case.

The framework of normalizing flows provides a general strategy for flexible variational inference of posteriors over latent variables. We propose a new type of normalizing flow, inverse autoregressive flow (IAF), that, in contrast to earlier published flows, scales well to high-dimensional latent spaces. The proposed flow consists of a chain of invertible transformations, where each transformation is based on an autoregressive neural network. In experiments, we show that IAF significantly improves upon diagonal Gaussian approximate posteriors. In addition, we demonstrate that a novel type of variational autoencoder, coupled with IAF, is competitive with neural autoregressive models in terms of attained log-likelihood on natural images, while allowing significantly faster synthesis.

Neural Information Processing Systems http://nips.cc/

Neural Information Processing Systems http://nips.cc/

Neural Information Processing Systems http://nips.cc/