Amazon has brought Apple Music to Alexa smart speakers for the first time in the UK. The feature was already available in the US but is slowly rolling out across the world. It means that people are no longer limited to only Amazon Music and Spotify as ways for Alexa to play music. Apple Music will work like those same services, allowing people to ask for a song or radio station and have it play from Apple Music. We'll tell you what's true.

Nearly half a million songs that were thought to have been lost when MySpace accidentally deleted its archive of tracks have been rediscovered. The files – which are now available to listen to – were kept by coincidence and have been shared with the world once again. But they only represent the tiniest sliver of the total number of tracks that were deleted during the accidental clearance. Together they amount to less than one per cent of the estimated 50 million tracks that disappeared during a server migration at MySpace. We'll tell you what's true.

Twitter has been forced to backtrack after the French government accidentally fell foul of its own law designed to prevent the spread of fake news. The #OuiJeVote (Yes, I Vote) campaign was rejected by the social media giant as it risked contravening a law introduced in December, that requires paid-for political content on the platform to be transparent about who funds it, even though the campaign is aimed at encouraging people to vote. Twitter's decision was criticised by the French government information service (GIS), which planned to pay for the sponsored tweets. We'll tell you what's true. You can form your own view.

Two Chinese software developers are trying to harness the power of open source software to improve working conditions for coders. Last weekend, Katt Gu and Suji Yan, published the "Anti-996 License," which requires any company that uses the project's software to comply with local labor laws as well as International Labour Organization standards, including the right for workers to collectively bargain and a ban on forced labor. The license is part of the growing Anti-996 Movement in China, which refers to a common schedule of working from 9 am to 9 pm, six days a week. This grueling schedule is allegedly widespread in the Chinese tech startup industry, according to a story in the South China Morning Post last month. Last week, one or more anonymous activists launched a website called 996.ICU, detailing Chinese labor laws that a 996 schedule may violate, including provisions that generally limit work to 44 hours a week and require overtime pay.

MARKETING isn't what it used to be with technology as an option in the toolbox. Conventional approaches that worked just a few years back are largely ineffective now. As the use of artificial intelligence (AI) in marketing rises, so do data privacy concerns. Despite that, AI may be exactly what will overcome data privacy concerns in marketing for businesses. What needs to be clear is that it's not AI that's driving most digital marketing campaigns right now. Instead, today's marketing efforts are based on algorithms.

Apple could finally be bringing back one of its most beloved phones. Rumours suggest that the company is working on a smaller version of its future handset, apparently in line with the size of the iPhone SE. The first version of that handset – which was much smaller than the other phones it was making at the time, as well as being low cost – proved an unexpected hit, but has gone largely unmentioned ever since. Apple released the first iPhone SE in 2016. It immediately found favour, particularly with people who because of small hands or for other reasons were turned off by the increasing size of Apple's phones.

Beats has introduced its own version of Apple's hugely popular AirPods, just days after they were updated. The new Powerbeats Pro earphones pack in all of the same technology found in Apple's own completely wireless AirPods. Primarily, that means Apple's H1 chip, which allows the earphones to quickly and easily connect to iPhone and other Apple products. But Beats also suggested that the earphones will include better sound than their Apple counterparts. We'll tell you what's true.

Success of deep learning techniques have renewed the interest in development of dialogue systems. However, current systems struggle to have consistent long term conversations with the users and fail to build rapport. Topic spotting, the task of automatically inferring the topic of a conversation, has been shown to be helpful in making a dialog system more engaging and efficient. We propose a hierarchical model with self attention for topic spotting. Experiments on the Switchboard corpus show the superior performance of our model over previously proposed techniques for topic spotting and deep models for text classification. Additionally, in contrast to offline processing of dialog, we also analyze the performance of our model in a more realistic setting i.e. in an online setting where the topic is identified in real time as the dialog progresses. Results show that our model is able to generalize even with limited information in the online setting.

This paper presents Automatic Algorithm Discoverer (AAD), an evolutionary framework for synthesizing programs of high complexity. To guide evolution, prior evolutionary algorithms have depended on fitness (objective) functions, which are challenging to design. To make evolutionary progress, instead, AAD employs Problem Guided Evolution (PGE), which requires introduction of a group of problems together. With PGE, solutions discovered for simpler problems are used to solve more complex problems in the same group. PGE also enables several new evolutionary strategies, and naturally yields to High-Performance Computing (HPC) techniques. We find that PGE and related evolutionary strategies enable AAD to discover algorithms of similar or higher complexity relative to the state-of-the-art. Specifically, AAD produces Python code for 29 array/vector problems ranging from min, max, reverse, to more challenging problems like sorting and matrix-vector multiplication. Additionally, we find that AAD shows adaptability to constrained environments/inputs and demonstrates outside-of-the-box problem solving abilities.

Bayesian Matrix Factorization (BMF) is a powerful technique for recommender systems because it produces good results and is relatively robust against overfitting. Yet BMF is more computationally intensive and thus more challenging to implement for large datasets. In this work we present SMURFF a high-performance feature-rich framework to compose and construct different Bayesian matrix-factorization methods. The framework has been successfully used in to do large scale runs of compound-activity prediction. SMURFF is available as open-source and can be used both on a supercomputer and on a desktop or laptop machine. Documentation and several examples are provided as Jupyter notebooks using SMURFF's high-level Python API.