The Cupertino, Calif., company said a new M4 chipset used in its Pro models contains a more powerful "neural engine" to drive features in third-party apps and its own software that rely on AI and machine learning. These engines have been part of Apple's chips since 2017 but have grown considerably more powerful since then, the company said. Tim Millet, the company's vice president of platform architecture, claimed the M4's neural engine is capable of performing 38 trillion operations per second, more than doubling operations per second compared with the base-level M3 chipset found in the company's MacBook Air, MacBook Pro and iMac.

Countries looking to fully utilize artificial intelligence (AI)'s potential and capabilities will need to look for upgrades to data storage and processing, turning to either blockchains or quantum computing for the way forward, experts told Fox News Digital. "You're going to have massive data storage issues and issues for computation when you get into pattern recognition," Christopher Alexander, chief analytics officer of Pioneer Development Group, told Fox News Digital. The race to develop and implement AI systems cannot occur without proper infrastructure, according to TS2 Space, a Polish internet service provider for the U.S. Army in areas like Iraq and Afghanistan. In a blog post on the company website, TS2 Space highlighted the challenges AI infrastructure faces, including "the sheer volume of data" and "the complexity of AI algorithms and models." "Developing and deploying AI applications require a deep understanding of the underlying algorithms and models, as well as the ability to fine-tune them for specific use cases," the company wrote.

Imagine that data could be shared seamlessly with partners, governments, and other organisations, without breaking any data protection law, to facilitate innovation. How will it be possible to use closely guarded customer data while still maintaining the highest privacy and safety standards? Is it possible to monetise data without compromising the sensitivity of the information (or data)? The following write-up spills it all. Data is the fuel for the rapidly progressing Artificial Intelligence (AI) industry -as it is for almost all other industries.

Artificial Intelligence and Machine Learning are two disruptive technologies that are changing business, education, healthcare and finance in productive ways. Reports of the International Data Corporation (IDC) survey say that companies are already spending more on AI. Over half of the businesses have adopted AI in one form or other. To implement such powerful technologies and empower your business, these are the basic requirements. In order to be proactive in implementing these advanced technologies, we have to identify commonalities throughout the business.

On August 15, India's Independence Day, it's customary to sing Jana Gana Mana: the Indian national anthem, originally composed by the poet Rabindranath Tagore and adopted as the anthem after India gained full independence. This year, together with Prasar Bharati and Virtual Bharat, we offered Indians a new take on the familiar with Sounds of India, an AI-powered web app. Using the app, you sing Jana Gana Mana into your phone, karaoke-style, and it transforms your voice into one of three traditional Indian instruments. The day culminated in a rendition of the national anthem, combining many of the voices that Indians submitted through the app. The Sounds of India experiment was made possible by machine learning models built with Google's TensorFlow platform to convert sounds into musical instruments (in this case, the Bansuri, the Shehnai, and the Sarangi).

Canadian Prime Minister Justin Trudeau says Canada is "investing massively in AI," building on decades of research by Canadian computer scientists who helped provide the "modern underpinnings" advancing the field of artificial intelligence.