Digital Transformation moved at a relatively slow pace for the past ten years, mainly focusing on improving products, employee experience and processes. But then, after COVID – 19 hit, IT decision-makers were forced to prioritize their IT initiatives in order to increase digital investments. According to IDC, over the next four years, worldwide Digital Transformation technology investment is set to reach at least $7.4 trillion and will be the first time that DX will account for the majority of IT spending – predicted to be a huge 53% of budgets. Digital transformation is a set of methodologies and tools which are used by modern companies to optimize their operational activities, such as increasing their reach power, providing differentiated service and increasing performance. However, digital transformation is not just a new department in the firm, but it is definitely a game-changer in technology's role in the corporate environment. That's why it is increasingly being seen as the 4th Industrial Revolution. "Think of digital transformation less as a technology project to be finished than as a state of perpetual agility, always ready to evolve for whatever customers want next, and you'll be pointed down the right path."-

Science fiction is a genre very much associated with technological marvels, innovations, and visions of the future. So it may be surprising to find so many of its writers are drawn to Shakespeare – he's a figure associated with tradition and the past. Sometimes his plays are reworked in a science fiction setting. The 1956 film Forbidden Planet is just one of many variations on a "Tempest in space" theme. Sometimes the playwright appears as a character caught up in a time travel adventure.

The award-winning picture of Munzir El Nezzel playfully lifting Mustafa, his son who was born without limbs, has given the family a shot at a new life after becoming a poignant symbol of the plight of war-torn Syria. The shocking yet tender picture taken by Turkish photographer Mehmet Aslan, titled Hardship of Life, captured an intimate moment of affection between a father and son whose bodies have been maimed by the brutal conflict. Six-year-old Mustafa was born with a congenital disorder caused by medications his mother took while pregnant after being sickened by nerve gas. His 35-year-old father had his leg amputated following a bomb attack in Syria. After being declared photo of the year at the Siena International Photo Awards (SIPA) last year and making headlines in Italy, it sparked crowdfunding efforts that raised about 100,000 euros ($114,000) to provide both father and son with prosthetic limbs.

A Wild Snark comforts Alice is a piece of digital artwork by Wild Snark which was uploaded on January 21st, 2022. The digital art may be purchased as wall art, home decor, apparel, phone cases, greeting cards, and more. All products are produced on-demand and shipped worldwide within 2 - 3 business days.

The facial expressions in the acquired 3D images were distinguished through machine learning with an average of 85% accuracy – a statistically …

… an AI/Machine Learning (ML) platform designed to address the needs of … gap between the quantum computing and machine learning communities.

Image categorization may be quickly prototyped or shown.

When artificial intelligence is predicting changes even a small change of course can have major impacts.

With the help of artificial intelligence, this process can be automated and sped up significantly.

Language models (LMs) have introduced a major paradigm shift in Natural Language Processing (NLP) modeling where large pre-trained LMs became integral to most of the NLP tasks. The LMs are intelligent enough to find useful and relevant representations of the language without any supervision. Perhaps, these models are used to fine-tune typical NLP tasks with significantly high accuracy as compared to the traditional approaches. Conversely, the training of these models requires a massively large corpus that is a good representation of the language. English LMs generally perform better than their other language counterparts, due to the availability of massive English corpora. This work elaborates on the design and development of a large Arabic corpus. It consists of over 500 GB of Arabic cleaned text targeted at improving cross-domain knowledge and downstream generalization capability of large-scale language models. Moreover, the corpus is utilized in the training of a large Arabic LM. In order to evaluate the effectiveness of the LM, a number of typical NLP tasks are fine-tuned. The tasks demonstrate a significant boost from 4.5 to 8.5% when compared to tasks fine-tuned on multi-lingual BERT (mBERT). To the best of my knowledge, this is currently the largest clean and diverse Arabic corpus ever collected.