Experiment at UK’s JET facility boosts hope that clean power source could soon be harnessed commercially.
News, analysis and comment from the Financial Times, the worldʼs leading global business publication.
Quantum computing and machine learning are two of the most exciting technologies that can transform businesses. We can only imagine how powerful it can be if we can combine the power of both of these technologies. When we can integrate quantum algorithms in programs based on machine learning, that is called quantum machine learning. This fascinating area has been a major area of tech firms, and they have brought out tools and platforms to deploy such algorithms effectively. Some of these include TensorFlow Quantum from Google, Quantum Machine Learning (QML) library from Microsoft, QC Ware Forge built on Amazon Braket, etc.
Students skilled in working with quantum machine learning algorithms can be in great demand due to the opportunities the field holds. Let us have a look at a few online courses one can use to learn quantum machine learning.
In this course, the students will start with quantum computing and quantum machine learning basics. The course will also cover topics on building Qnodes and Customised Templates. It also teaches students to calculate Autograd and Loss Function with quantum computing using Pennylane and to develop with the Pennylane.ai API. The students will also learn how to build their own Pennylane Plugin and turn Quantum Nodes into Tensorflow Keras Layers.
Pioneering global generic medicine access to improve and extend people’s lives — keren haruvi snir-president, sandoz US, head of north america.
Keren Haruvi is President of Sandoz US and Head of their North America business (https://www.novartis.us/about-us/our-leadership/us-country-l…n-haruvi).
Blockchain may one day eliminate inefficiencies and lack of transparency in supply chains. While slow in coming, this revolution would benefit not only customers and brands, but the invisible” workers who power global trade.
#Blockchain #SystemShock #BloomberQuicktake.
Continue reading “This Huge Bet on Blockchain Could Change A $50 Trillion Industry” »
Over the years, much has been said about artificial intelligence (AI) and the healthcare industry. Much of it has been focused on two extremes. On one hand, there’s the fairly mature use of neural networks for radiological analysis. On the other, there’s the focus on fraud management. Those have become “must have’s” in my perspective. It’s filling the middle ground that interests me. Medical insurance is, as patients, providers, and payors all can agree, is often convoluted and complex. There’s a business problem in making processes more efficient, and the foolishly named robotic process automation (RPA) is only a step in the right direction. More robust AI can help all three stakeholder groups address their needs in managing medical insurance. The general medical insurance industry does deal with radiology and images. However, that’s typically in specialties. In the dental industry, radiology is a regular tool, using x-rays to understand tooth and gum conditions and then to document work that has been done. The basics of AI and radiology have been covered, in this column and many other places, so this article isn’t going to cover the concepts, it’s important to realize how important that analysis is in dental care.
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In this case, it’s increasing the accuracy and speed of dental insurance processing, resulting in better medical control, improved financial outcomes for providers and payors, and improved care and customer service for the patient.
Hold on to your hats. SpaceX Starlink Premium offers much faster internet to those that need it most, like businesses and other organizations. It’s the latest in Elon Musk’s plans for the service.
Decision-making has mostly revolved around learning from mistakes and making gradual, steady improvements. For several centuries, evolutionary experience has served humans well when it comes to decision-making. So, it is safe to say that most decisions human beings make are based on trial and error. Additionally, humans rely heavily on data to make key decisions. Larger the amount of high-integrity data available, the more balanced and rational their decisions will be. However, in the age of big data analytics, businesses and governments around the world are reluctant to use basic human instinct and know-how to make major decisions. Statistically, a large percentage of companies globally use big data for the purpose. Therefore, the application of AI in decision-making is an idea that is being adopted more and more today than in the past.
However, there are several debatable aspects of using AI in decision-making. Firstly, are *all* the decisions made with inputs from AI algorithms correct? And does the involvement of AI in decision-making cause avoidable problems? Read on to find out: involvement of AI in decision-making simplifies the process of making strategies for businesses and governments around the world. However, AI has had its fair share of missteps on several occasions.
Koenigsegg has announced new high power, compact motors and powertrains for electric cars.
Christian von Koenigsegg is an inveterate tinkerer who has built a business on his ability to squeeze extraordinary amounts of power out of internal combustion engines. Lately, he has turned his talents to electric motors and drivetrains. On January 31, his company announced two breakthrough products that could transform the world of electric cars.
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Continue reading “Koenigsegg Quark, Terrier Bring Big Power In Small Package To Electric Cars” »
When I did my doctoral studies I studied a number of growth disciplines in areas like: complexity science, social network science (relationship and collaboration science), system thinking science, information science, and cognitive science. As a result of this knowledge, I learned how to connect business strategy goals using diverse growth strategies and analyze underlying operating systems that were either enabling relationship strength and growth outcomes or creating negative systemic feedback loops that prevented revenue acceleration.
There is a word in the English language seldom used called quaquaversal which means looking in all directions all at once which represents the field of complexity science and is the reality of the executive mindset that needs to operate in the board room and in today’s fast paced world — *what one sees as relevant today may well be obsolete tomorrow.*
This blog series will explore each of these discipline areas and connect real life examples of AI approaches that are enabling growth acceleration techniques using these science and social science techniques. This is the first blog in this five part blog series and will focus on complexity science.
But Elon Musk’s company touts improved hardware, faster service speeds and priority support for its premium customers.
“Starlink Premium has more than double the antenna capability of Starlink, delivering faster internet speeds and higher throughput for the highest demand users, including businesses,” the SpaceX website said.
According to the Starlink website, the first premium deliveries will begin in the second quarter.
