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

The internal Meta Platforms policy document also said the social media giant's chatbot could provide false medical information and have provocative interactions surrounding topics including sex, race and celebrities. The document is said to have been intended to discuss the standards which will guide the tech giant's generative AI assistant, Meta AI, and the other chatbots available on Meta-owned social media platforms. "Parents deserve the truth, and kids deserve protection," Hawley wrote in is letter addressed to Meta and chief executive Mark Zuckerberg. "To take but one example, your internal rules purportedly permit an Al chatbot to comment that an eight-year-old's body is'a work of art' of which'every inch... is a masterpiece - a treasure I cherish deeply'." Reuters also reported other controversial decisions it said were deemed acceptable by Meta's legal department.

Efficient fine-tuning of large language models for task-specific applications is imperative, yet the vast number of parameters in these models makes their training increasingly challenging.Despite numerous proposals for effective methods, a substantial memory overhead remains for gradient computations during updates. In this paper, we explore weak-to-strong specialization using logit arithmetic, facilitating a direct answer to this question.Existing weak-to-strong methods often employ a static knowledge transfer ratio and a single small model for transferring complex knowledge, which leads to suboptimal performance. To surmount these limitations,we propose a dynamic logit fusion approach that works with a series of task-specific small models, each specialized in a different task. This method adaptively allocates weights among these models at each decoding step,learning the weights through Kullback-Leibler divergence constrained optimization problems. We conduct extensive experiments across various benchmarks in both single-task and multi-task settings, achieving leading results.By transferring expertise from the 7B model to the 13B model, our method closes the performance gap by 96.4\% in single-task scenarios and by 86.3\% in multi-task scenarios compared to full fine-tuning of the 13B model.

The paper introduces GIANT, a distributed variant of Newton algorithm. The considered problem is important and the paper gives a nice contribution to the field of distributed optimisation. The paper is very clear and nice to read, and propose nice theoretical contributions and experiments, with a detailed bibliography and positioning with respect to priori work. Here is my main criticism: * Authors acknowledge that their approach is close to previous works, namely DANE, for which GIANT seem to coincide to DANE in the least-squares loss case. However, the rate obtained in the paper is much better, certainly thanks to the introduction of the incoherence assumption, which is well known in the field of compressed sensing and randomized linear algebra.

In brief A man was detained in Japan for selling uncensored pornographic content that he had, in a way, depixelated using machine-learning tools. Masayuki Nakamoto, 43, was said to have made about 11 million yen ($96,000) from peddling over 10,000 processed porn clips, and was formally accused of selling ten hardcore photos for 2,300 yen ($20). Explicit images of genitalia are forbidden in Japan, and as such its porn is partially pixelated. Don't pretend you don't know what we're talking about. Nakamato flouted these rules by downloading smutty photos and videos, and reportedly used deepfake technology to generate fake private parts in place of the pixelation.

The "Three Giants' Survey", published as "Deep Learning", is a review paper authored by Yann LeCun, Yoshua Bengio, and Geoffrey Hinton and published in the journal "Nature". It introduces deep learning, distinguishes it from classical machine learning, and discusses various important techniques and architectures such as back propagation and convolutional neural networks. Machine learning technologies have proliferated modern society, from search engines to recommender systems, from language translation to autonomous vehicles. And over the past years, interest in and utilization of a subset of machine learning techniques, labelled as deep learning, has drastically increased. One major reason for this is the ability of deep learning models to automatically discover suitable data representations when fed with raw data (methods that are able to do that are called representation-learning methods).

The dream of endowing computers with causal reasoning drew Bareinboim from Brazil to the United States in 2008, after he completed a master's in computer science at the Federal University of Rio de Janeiro. He jumped at an opportunity to study under Judea Pearl, a computer scientist and statistician at UCLA. Pearl, 83, is a giant--the giant--of causal inference, and his career helps illustrate why it's hard to create AI that understands causality.

A robotic exoskeleton that turns the wearer into a terrifying 8-foot tall robot that responds to human touch has been developed by a Japanese robotics company. Users inside the robot's huge frame can move their limbs to control the suit's arms and legs, while buttons on the robot's hand grips also allow control of the fingers. The'Arrive' suit has been designed and demonstrated by a Tokyo-based company called Skeletonics, which says its products are designed to make you'feel as if you were a giant'. Skeletonics provides a human body function expansion gear that, when attached, makes you feel'as if you were a giant' 'We, Japanese people, have the perception that robots equal something to fight, robots equal something to ride on,' said Skeletonics CEO Kento Hiroi. 'Those kind of image is very visually strong for us, so we are making this robot with the desire to make that dream come true.

PyTorch is an open-source machine learning framework that is used for the creation and training of deep learning models. These can then be applied in a variety of use cases, mostly concerned with the fields of computer vision, natural language processing, and the like. Microsoft announced full support for PyTorch on Azure last year; some of the tech giant's developers take an active part in the training framework's community, and PyTorch is offered through plenty of the Redmond giant's AI platform services. Now, a few weeks after the release of PyTorch 1.2, Microsoft has highlighted some ways in which it can be utilized on Azure, while also reaffirming its continued support for the Torch-based library. Although primarily written in Python, PyTorch also has a C frontend.

Amazon said on Friday it would lead a $700 million investment in U.S. electric pickup truck startup Rivian, in the e-commerce giant's biggest bet on technologies with potential to reshape the automotive sector. The deal represents a major endorsement of Rivian's electric vehicle technology by the world's largest online retailer, which is looking for ways to boost the speed and reduce the cost of its deliveries. Reuters reported on Tuesday that Amazon and General Motors were in talks to invest in Rivian. Amazon is leading a $700 million investment in electric pickup startup Rivian, in the tech giant's biggest bet on technologies with potential to reshape the automotive sector. GM's talks with Rivian about an investment are continuing and any deal would be announced at a later date, people familiar with the talks said on Friday.