Google will ban'sugar daddy' apps from its Google Play app store from September 1 this year, the firm has quietly revealed in an update. Sugar daddy, or'compensated sexual relationship' apps, allow older users to pay younger users in return for sexual intimacy. Users are mostly older males, known as'sugar daddies', and younger females ('sugar babies'), although there are'sugar mummies' too. Examples of sugar dating apps include My Sugar Daddy, Spoil, SDM, Elite Millionaire Singles and Seeking Arrangement. According to one young user, sugar daddy apps have earnt them a whopping £18,000 a month – enough to pay for their university degree.

For newbies who are just starting to learn to code or those who would like to get started, this can be a little intimidating! There are many programming languages and it can be difficult to choose which one is right for you. If you are new to programming, you need to learn a new language or a new structure. As a beginner to a programming language, make sure you remain stable in both learning and programming. However, choosing the best of hundreds of programming languages can be daunting and confusing.

When solving machine learning problems, simply training a model based on a problem-specific training machine learning algorithm does not guarantee either that the resulting model fully captures the underlying concept hidden in the training data or that the optimum parameter values were chosen for model training. Failing to test a model's performance means an underperforming model could be deployed on the production system, resulting in incorrect predictions. Choosing one model from the many available options based on intuition alone is risky. By generating different metrics, the efficacy of the model can be assessed. Use of these metrics reveals how well the model fits the data on which it was trained.

"UC Berkeley is a leader in AI, machine learning and optimization," said Atamturk. "We are delighted to join forces with interdisciplinary research …

We introduce mTVR, a large-scale multilingual video moment retrieval dataset, containing 218K English and Chinese queries from 21.8K TV show video clips. The dataset is collected by extending the popular TVR dataset (in English) with paired Chinese queries and subtitles. Compared to existing moment retrieval datasets, mTVR is multilingual, larger, and comes with diverse annotations. We further propose mXML, a multilingual moment retrieval model that learns and operates on data from both languages, via encoder parameter sharing and language neighborhood constraints. We demonstrate the effectiveness of mXML on the newly collected MTVR dataset, where mXML outperforms strong monolingual baselines while using fewer parameters. In addition, we also provide detailed dataset analyses and model ablations. Data and code are publicly available at https://github.com/jayleicn/mTVRetrieval

What's New: Intel in collaboration with the Central Board of Secondary Education (CBSE), Ministry of Education today announced the launch of the AI For All initiative with the purpose of creating a basic understanding of artificial intelligence (AI) for everyone in India. Based on Intel's AI For Citizens program, AI For All is a 4-hour, self-paced learning program that demystifies AI in an inclusive manner. It is as applicable to a student, a stay-at-home parent as it is to a professional in any field or even a senior citizen. The program aims to introduce AI to 1 million citizens in its first year. "AI has the power to drive faster economic growth, address population-scale challenges and benefit the lives and livelihoods of people. The AI For All initiative based on Intel's AI For Citizens program aims to make India AI-ready by building awareness and appreciation of AI among everyone. The program further strengthens Intel's commitment to collaborating with the Government of India to reach the full potential of AI and further the vision of a digitally-empowered India."

Machine learning, a form of artificial intelligence, vastly speeds up computational tasks and enables new technology in areas as broad as speech and image recognition, self-driving cars, stock market trading and medical diagnosis. Before going to work on a given task, machine learning algorithms typically need to be trained on pre-existing data so they can learn to make fast and accurate predictions about future scenarios on their own. But what if the job is a completely new one, with no data available for training? Now, researchers at the Department of Energy's SLAC National Accelerator Laboratory have demonstrated that they can use machine learning to optimize the performance of particle accelerators by teaching the algorithms the basic physics principles behind accelerator operations--no prior data needed. "Injecting physics into machine learning is a really hot topic in many research areas--in materials science, environmental science, battery research, particle physics and more," said Adi Hanuka, a former SLAC research associate who led a study published in Physical Review Accelerator and Beams.

Prime Minister Narendra Modi launched'AI For All' initiative at the first anniversary of National Education Policy (NEP) 2020. 'AI for All' is an online course aimed at offering a basic understanding of artificial intelligence (AI) for every citizen in the country. Under the programme, the government aims to train 1 million citizens in its first year. This is one of the largest AI public awareness programmes across the globe. To ensure the course reaches a wider range of people, it will be available in 11 different vernacular languages.

AlphaFold 2 paper and code is finally released. This post aims to inspire new generations of Machine Learning (ML) engineers to focus on foundational biological problems.

Earlier this week the Australian Research Council (ARC) awarded Monash University $4.8 million in funding to develop a new training centre for optimal ageing. The centre will focus on developing emerging technologies including artificial intelligence, digital health apps, and sensors to improve and maintain overall quality of life among the elderly. Students and academics from engineering, health, data and information technology faculties will work in partnership with industry partners and community organisations. "Our approach is to shift from a reactive to a proactive model of ageing, from the diagnosis and treatment of isolated diseases of ageing to a more complete, preventative and consumer-empowered system," said training centre director, associate professor Yen Ying Lim. Digital innovation has been recognised as a leading solution to address the needs of the growing ageing population.