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Category: business – Page 126

IBM has just announced a partnership with the Government of Quebec to create the Quebec-IBM Discovery Accelerator in Bromont, Quebec. The accelerator will focus on using quantum computing, Artificial Intelligence (AI), and High-Performance Computing (HPC) to develop new projects, business/scientific/academia collaborations, and skills-building initiatives in research areas including energy, life sciences (genomics and drug discovery), new materials development, and sustainability. This is the fourth such center that IBM has announced. The three previously announced partnerships are with Cleveland Clinic, the University of Illinois Urbana-Champaign, and the UK’s Science and Technology Facilities Council Hartree Centre. IBM’s formal mission statement for these Discovery Accelerators is: “Accelerate scientific discovery and societal impact with a convergence of AI, quantum, and hybrid cloud in a community of discovery with research, academic, industry, startup, and government organizations working together.” IBM’s formal mission statement for these Discovery Accelerators is:

“Accelerate scientific discovery and societal impact with a convergence of AI, quantum, and hybrid cloud in a community of discovery with research, academic, industry, startup, and government organizations working together.”

In addition, the company has developed individual mission statements for each of the four Discovery Accelerators:

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The endless parade of bad news for Israeli malware merchant NSO Group continues. While it appears someone might be willing to bail out the beleaguered company, it still has to do business as the poster boy for the furtherance of human rights violations around the world. That the Israeli government may have played a significant part in NSO’s sales to known human rights violators may ultimately be mitigating, but for now, NSO is stuck playing defense with each passing news cycle.

Late last month, the New York Times revealed some very interesting things about NSO Group. First, it revealed the company was able to undo its built-in ban on searching US phone numbers… provided it was asked to by a US government agency. The FBI took NSO’s powerful Pegasus malware for a spin in 2019, but under an assumed name: Phantom. With the permission of NSO and the Israeli government, the malware was able to target US numbers, albeit ones linked to dummy phones purchased by the FBI.

The report noted the FBI liked what it saw, but found the zero-click exploit provided by NSO’s bespoke “Phantom” (Pegasus, but able to target US numbers) might pose constitutional problems the agency couldn’t surmount. So, it walked away from NSO. But not before running some attack attempts through US servers — something that was inadvertently exposed by Facebook and WhatsApp in their lawsuit against NSO over the targeting of WhatsApp users. An exhibit declared NSO was using US servers to deliver malware, something that suggested NSO didn’t care about its self-imposed restrictions on US targeting. In reality, it was the FBI and NSO running some tests on local applications of zero-click malware that happened to be caught by Facebook techies.

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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.

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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).

Sandoz is a division of the Novartis Group and a global leader in generic pharmaceuticals and biosimilars and was established in 2003, when Novartis united all of its generics businesses under the name Sandoz – a single global brand with a long history. Since then, Sandoz has grown into a leading global generics business with annual sales of approximately US$10 billion.

In her current role, Keren leads Sandoz’ largest commercial and country organization – the United States – which is responsible for over 35% of Sandoz global revenue. She also oversees Sandoz commercial operations in Canada. In addition to serving on the Novartis Country Leadership Team, Keren is a member of the Global Sandoz Executive Committee.

Prior to joining Sandoz, Keren served as Global Head of M&A at Novartis International AG. Her early career began at Teva Pharmaceutical Industries where she steadily advanced in leadership roles to Senior VP, Global Business Development and Alliance Management.

Continue reading “Keren Haruvi — President, Sandoz US, Head Of North America — Global Generic Medicine Access For All” | >

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.

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Continue reading “This Huge Bet on Blockchain Could Change A 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.

Full Story:

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.

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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.

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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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