AI/ML platforms, trade secrets can include the structure of the AI/ML model, proprietary training data, a particular method of using the AI/ML …

Artificial intelligence is rapidly changing supply logistics, intelligence gathering, sensors, and military robots through the application as commonly …

Recent model-based Recommender Systems (RecSys) algorithms emphasize on the use of features, also called side information, in their design similar to algorithms in Machine Learning (ML). In contrast, some of the most popular and traditional algorithms for RecSys solely focus on a given user-item-rating relation without including side information. The goal of this case study is to provide a performance comparison and assessment of RecSys and ML algorithms when side information is included. We chose the Movielens-100K data set since it is a standard for comparing RecSys algorithms. We compared six different feature sets with varying quantities of features which were generated from the baseline data and evaluated on a total of 19 RecSys algorithms, baseline ML algorithms, Automated Machine Learning (AutoML) pipelines, and state-of-the-art RecSys algorithms that incorporate side information. The results show that additional features benefit all algorithms we evaluated. However, the correlation between feature quantity and performance is not monotonous for AutoML and RecSys. In these categories, an analysis of feature importance revealed that the quality of features matters more than quantity. Throughout our experiments, the average performance on the feature set with the lowest number of features is about 6% worse compared to that with the highest in terms of the Root Mean Squared Error. An interesting observation is that AutoML outperforms matrix factorization-based RecSys algorithms when additional features are used. Almost all algorithms that can include side information have higher performance when using the highest quantity of features. In the other cases, the performance difference is negligible (<1%). The results show a clear positive trend for the effect of feature quantity as well as the important effects of feature quality on the evaluated algorithms.

Textual knowledge bases such as Wikipedia require considerable effort to keep up to date and consistent. While automated writing assistants could potentially ease this burden, the problem of suggesting edits grounded in external knowledge has been under-explored. In this paper, we introduce the novel generation task of *faithfully reflecting updated information in text* (FRUIT) where the goal is to update an existing article given new evidence. We release the FRUIT-WIKI dataset, a collection of over 170K distantly supervised data produced from pairs of Wikipedia snapshots, along with our data generation pipeline and a gold evaluation set of 914 instances whose edits are guaranteed to be supported by the evidence. We provide benchmark results for popular generation systems as well as EDIT5 -- a T5-based approach tailored to editing we introduce that establishes the state of the art. Our analysis shows that developing models that can update articles faithfully requires new capabilities for neural generation models, and opens doors to many new applications.

Digital audio signal reconstruction of a lost or corrupt segment using deep learning algorithms has been explored intensively in recent years. Nevertheless, prior traditional methods with linear interpolation, phase coding and tone insertion techniques are still in vogue. However, we found no research work on reconstructing audio signals with the fusion of dithering, steganography, and machine learning regressors. Therefore, this paper proposes the combination of steganography, halftoning (dithering), and state-of-the-art shallow (RF- Random Forest regression) and deep learning (LSTM- Long Short-Term Memory) methods. The results (including comparing the SPAIN, Autoregressive, deep learning-based, graph-based, and other methods) are evaluated with three different metrics. The observations from the results show that the proposed solution is effective and can enhance the reconstruction of audio signals performed by the side information (e.g., Latent representation and learning for audio inpainting) steganography provides. Moreover, this paper proposes a novel framework for reconstruction from heavily compressed embedded audio data using halftoning (i.e., dithering) and machine learning, which we termed the HCR (halftone-based compression and reconstruction). This work may trigger interest in optimising this approach and/or transferring it to different domains (i.e., image reconstruction). Compared to existing methods, we show improvement in the inpainting performance in terms of signal-to-noise (SNR), the objective difference grade (ODG) and the Hansen's audio quality metric.

AI21 Labs is an artificial intelligence startup whose mission is to reimagine the way we read and write by making the machine a thought partner to …

Amazon Prime Day is here. The mega-retailer's two-day sales event for Prime subscribers is in full swing, and there are plenty of deals on some of our favorite gear and gadgets, from Alexa-enabled speakers to robot vacs to laptops and tablets. The WIRED Gear team tests products year-round. We sorted through hundreds of thousands of deals by hand to make these picks. Crossed out products are out of stock or no longer discounted. Our Amazon Prime Day coverage page has the latest stories, and our Prime Day Shopping Tips will help you avoid bad deals. You can also get a 1-year subscription to WIRED for $5 here. Updated July 12: We've added 7 new deals and crossed out any that are no longer available. We've also updated prices and link throughout. If you buy something using links in our stories, we may earn a commission. This helps support our journalism. Prime Day is the best time to pick up a new Amazon device, whether that's a Kindle, Fire tablet, or Echo speaker--they're unlikely to get cheaper than this.

Opinion If the soap opera of Microsoft's relationship with open source had a theme tune, it'd be "The Long and Winding Goad". To a company whose entire existence depended on market control, open source's radical freedoms were an existential, cancerous threat. In return, open source was only too happy to play the upstart punk movement to Microsoft's bloated prog rock. In the end, both sides accepted the inevitable. Redmond wasn't going to control the cloud and mobile the way it controlled business IT, and the cloud and mobile loved open source. Interoperability was more profitable than insults.

Amazon Prime Day is here. The mega-retailer's two-day sales event for Prime subscribers is in full swing, and there are plenty of deals on some of our favorite gear and gadgets, from Alexa-enabled speakers to robot vacs to laptops and tablets. The WIRED Gear team tests products year-round. We sorted through hundreds of thousands of deals by hand to make these picks. Crossed out products are out of stock or no longer discounted. Our Amazon Prime Day coverage page has the latest stories, and our Prime Day Shopping Tips will help you avoid bad deals. You can also get a 1-year subscription to WIRED for $5 here. If you buy something using links in our stories, we may earn a commission. This helps support our journalism. Prime Day is the best time to pick up a new Amazon device, whether that's a Kindle, Fire tablet, or Echo speaker--they're unlikely to get cheaper than this. For a complete list, read our Best Prime Day Deals on Amazon Devices roundup.

If drone photography is something you've always wanted to try, one of Amazon's Prime Day deals may be your ticket into the hobby. The retailer has discounted the DJI Mini 2 Fly More Combo to $479, down from $599. The bundle comes with almost everything you need to get the most out of DJI's entry-level drone, including two spare batteries, a charging hub and a carrying case for the aircraft. At $479, you're effectively paying $60 more than it would cost to buy the standard $419 Mini 2 kit on its own. While Engadget hasn't had a chance to review the Mini 2, it's widely considered one of the best beginner drones you can buy. It can also capture smooth 4K video at 30 frames per second, thanks to a 12-megapixel sensor.