DEVELOPMENT


What are the Drivers of Artificial Intelligence Industry, China vs. U.S.?

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Capital investment: Based on existing data, U.S. – based AI companies have raised a total of 97.8 billion RMB (50.1% of global AI investment) compared to China-based companies that have raised 63.5 billion RMB (33.2% of global AI investment) Human capital: China has 39,200 AI specialists compared to the U.S.' 78,700. Training and retaining talent has become a critical impediment to the development of China's AI industry. Number of investment firms: The U.S. has three times the number of AI investment firms as China does. Capital investment: Based on existing data, U.S. – based AI companies have raised a total of 97.8 billion RMB (50.1% of global AI investment) compared to China-based companies that have raised 63.5 billion RMB (33.2% of global AI investment) Human capital: China has 39,200 AI specialists compared to the U.S.' 78,700.


Machine Learning Lends a Hand for Automated Software Testing - The New Stack

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Now, a set of artificial intelligence-powered options like Microsoft's Security Risk Detection service and Diffblue's security scanner and test generation tools aim to make these techniques easier, faster and accessible to more developers. Microsoft Security Risk Detection (previously known as Project Springfield) takes a slightly different approach. The AI in Springfield combines two techniques; time travel debugging and constraint solving. Molnar is the researcher running the team behind Springfield; previously he helped apply the same techniques to products like Windows and Microsoft Office, finding a third of the security bugs discovered by fuzzing in the Windows 7 client.


How to make robots we can trust

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For example, what (inter)national laws should be enacted to regulate autonomous system development and deployment? For some domains the system's decision making process should take into account relevant human values. These may include privacy, human autonomy and safety. Similarly, developing software that can take into account human values requires philosophy and sociology.


Deep learning must happen at the edge, too - SiliconANGLE

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We've written about a number of them at Wikibon: machine learning systems that extend the useful life of ERP systems in the grocery business; digital twin software that can dramatically improve automation in complex operations; and rapidly evolving technologies for accelerating productivity in information technology operations management, or ITOM, without which advances in other digital business domains would be impossible. That got the Wikibon research team thinking: Where will deep learning processing take place? Moreover, the rapid advances in hardware technologies that are powering the development of the cloud are also reshaping computing possibilities at the edge, in local machines and human-friendly, mobile devices. Action item: Business leaders must explore the new generation of artificial intelligence technologies, which will have profound product, operations and customer experience implications in all industries.


Flipboard on Flipboard

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An attempt will be made to find how to make machines use language, form abstractions and concepts, solve kinds of problems now reserved for humans, and improve themselves." They left out the most important part of building intelligent machines, the intelligence … before we attempt to build intelligent machines we have to first understand how the brain things, and there is nothing artificial about that." If intelligence was a cake, unsupervised learning would be the cake, supervised learning would be the icing on the cake, and reinforcement learning would be the cherry on the cake. We need to solve the unsupervised learning problem before we can even think of getting to true AI."


Going Back To School

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"Very few institutes in India like ISB and IIM-B are offering courses in innovation, while courses in specialisation in data management and data analytics etc are being offered by many premier institutes such as IIM-Ranchi and IIM-Bangalore," points out Mohan Tiwari, CEO and co-founder of Students' Destination. Taking teaching out of the classroom, Enactus India encourages experiential learning through students' interaction with communities. "This is driving a large number of working professionals to take up management programmes in various specialised domains. In addition, the IIM-Calcutta offers innovative management development programmes to meet the needs of the industry.


AI will redefine the role of manager

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At present, managers spend 54 percent of their time on administrative tasks like scheduling and logistics coordination. We know that AI will change the way many different departments work, so team members will need to adapt through tech training and rethinking the ways they can contribute to the company. Managers can bring empathy and context to the picture to decide the best course for the company's long-term goals, which aligns with Deloitte's prediction that problem-solving, social skills, creativity, and emotional intelligence will serve as vital complements to increased technical skills. With AI's assistance, for example, managers can overhaul outdated workflows, implement more dynamic project management strategies, and use customer data to brainstorm truly disruptive ideas.


Why AI success depends on IT picking the low-hanging fruit

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Speaking to Computer Weekly about the results of the study, Capgemini global CTO Ron Tolido said: "In the short and mid-term, the benefits of AI are based on using off-the-shelf products to apply AI for a specific purpose, then training the AI to make it work." One example cited in the report is investment bank JP Morgan, whose lawyers spend thousands of hours studying financial deals. Among the areas Tolida expects to benefit from AI augmentation are customer service and the EU's General Data Protection Regulation (GDPR). "At Capgemini, we use AI for service management, cyber security, development and testing," he added.


Why AI success depends on IT picking the low-hanging fruit

#artificialintelligence

Speaking to Computer Weekly about the results of the study, Capgemini global CTO Ron Tolido said: "In the short and mid-term, the benefits of AI are based on using off-the-shelf products to apply AI for a specific purpose, then training the AI to make it work." One example cited in the report is investment bank JP Morgan, whose lawyers spend thousands of hours studying financial deals. Among the areas Tolida expects to benefit from AI augmentation are customer service and the EU's General Data Protection Regulation (GDPR). "At Capgemini, we use AI for service management, cyber security, development and testing," he added.


How far are we from The Singularity?

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In the case of computer science, or artificial intelligence, a singularity is a point when we would achieve human intelligence (or even better, super intelligence) on computers. Bill Gates put it very nicely when he said the human brain is an extremely slow computer, running a very beautiful algorithm – the ability to question things, and possessing sentience itself. It will soon be possible to run our very beautiful algorithm on extremely fast computers made of silicon. When a breakthrough happens, we would be able to crack the rest to achieve human or rather human intelligence on computers.