developer


r/MachineLearning - [D] Keras vs PyTorch

#artificialintelligence

Ok, I can give you some answers based on my experiences as software engineer (over 10 years). I deal also a lot with open-source and I'm the author of dozens of open-source libraries with thousands of stars and millions of installations as well, so I know both sides (author and user) in both private and commercial applications pretty well. Also, many people ask me the question why we use at aetros.com Let's define some properties that define whether a library X is good or not: Let me explain in detail each point. When you use libraries, no matter if open-source or commercial, and you want to continue to develop an application using that library, it's very important that there are no hidden changes and your application doesn't break when you update the library (to get wanted features or bugfixes).


r/MachineLearning - [D] Keras vs PyTorch

#artificialintelligence

Ok, I can give you some answers based on my experiences as software engineer (over 10 years). I deal also a lot with open-source and I'm the author of dozens of open-source libraries with thousands of stars and millions of installations as well, so I know both sides (author and user) in both private and commercial applications pretty well. Also, many people ask me the question why we use at aetros.com Let's define some properties that define whether a library X is good or not: Let me explain in detail each point. When you use libraries, no matter if open-source or commercial, and you want to continue to develop an application using that library, it's very important that there are no hidden changes and your application doesn't break when you update the library (to get wanted features or bugfixes).


How the AI cloud could produce the richest companies ever

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For years, Swami Sivasubramanian's wife has wanted to get a look at the bears that come out of the woods on summer nights to plunder the trash cans at their suburban Seattle home. So over the Christmas break, Sivasubramanian, the head of Amazon's AI division, began rigging up a system to let her do just that. So far he has designed a computer model that can train itself to identify bears--and ignore raccoons, dogs, and late-night joggers. He did it using an Amazon cloud service called SageMaker, a machine-learning product designed for app developers who know nothing about machine learning. Next, he'll install Amazon's new DeepLens wireless video camera on his garage.


'Stardew Valley' multiplayer arrives on PC, Mac and Linux August 1st

Engadget

We've been waiting on Stardew Valley multiplayer for awhile now, and now we finally have a release date. According to the developer's Twitter account, it will arrive on PC, Mac and Linux on August 1st. There's also a new trailer to enjoy. Eric Barone, the solo game developer of Stardew Valley, answered some questions in the replies to this original tweet, so feel free to take a look if you have additional concerns. There is currently no date for the Nintendo Switch or other console multiplayer versions, though they are in the works.


Huawei now wants developers to exploit its artificial intelligence capabilities

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After having tested the waters with artificial intelligence in its top-end devices, Huawei will now open up its platform for developers to exploit it to the fullest. "Developers need to understand how AI works so they can build those capabilities into their apps. For us, the biggest challenge is natural interaction, and direct service access, when it comes to AI," Huawei's director of AI James Lu told indianexpress.com The telecom giant and smartphone manufacturer plans to hold a global developer conference on the lines of Apple's WWDC soon and hopes to rope in more developers, who will use the company's Application Programming Interface (APIs) in their apps. However, this seems to the natural progression of what has been a clear focus on AI for Huawei.


Why Should You Integrate Machine Learning Into Your Mobile App?

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Machine Learning Apps are fast invading into our everyday lives as the technology is progressing towards delivering smarter mobile-centric solutions. Embedding mobile apps with Machine Learning, a promising segment of AI, is spelling out a lot of advantages for the adopting companies to stand out amidst the clutter and rake in sizeable profits. Many organizations are investing heavily in Machine Learning to reap its benefits. Based on a prediction, Machine Learning as a service market will touch $5,537 million by 2023 while growing at a CAGR of 39 per cent from 2017-2023. Machine Learning Applications refer to a set of apps with Artificial Intelligence mechanisms that are designed to create a universal approach throughout the web to solve similar problems.


AI solutions required for fast-paced application development?

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According to Gartner, "to keep pace with the demands of digital transformation initiatives, application development teams will augment their efforts with AI "co-developers" to streamline programming efforts". Gartner predicts that "by 2022, at least 40% of new application development projects will have virtual AI co-developers on their team." Mendix is a digital transformation enabler platform that helps businesses to build web and mobile applications without the need to code – what's called low-code development. The company has recently launched Mendix Assist, which uses machine learning and AI analysis of over 5 million application logic flows to deliver 90% accuracy on next-step suggestions and reduce the cost of development defects by 10x. The platform allows people from across the business with no coding skills to collaborate, build and continuously improve apps at speed and scale.


Pentagon makes massive new AI push for tanks, ships, weapons, drones and networks

FOX News

The Pentagon is making a massive push to accelerate the application of artificial intelligence to ships, tanks, aircraft, drones, weapons and large networks as part of a sweeping strategy to more quickly harness and integrate the latest innovations. Many forms of AI are already well-underway with U.S. military combat systems, yet new technologies and applications are emerging so quickly that Deputy Secretary of Defense Patrick Shanahan has directed the immediate creation of a new Joint Artificial Intelligence Center. "The Deputy Secretary of Defense directed the DoD Chief Information Officer to standup the Joint Artificial Intelligence Center in order to enable teams across DoD to swiftly deliver new AI-enabled capabilities and effectively experiment with new operating concepts in support of DoD's military missions and business functions." DoD spokeswoman Heather Babb told Warrior Maven. Pentagon officials intend for the new effort to connect otherwise disparate AI developments across the services.


Video: R for AI, and the Not Hotdog workshop

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Earlier this year at the QCon.ai I also presented an interactive workshop, using R and the Microsoft Cognitive Services APIs, to automatically generate captions for images, and to create a tool to recognize images of hotdogs. Video from both the presentation, and the workshop (which starts at the 10:00 mark), is now available to view the QCon.ai You can find the slides for the presentation here. The R code for the "Not Hotdog" workshop is available as an Azure Notebook which you can clone and use to follow along with the workshop.


Machine Learning Explored at Amazon Conference PYMNTS.com

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Machine learning was one of the main subjects on Tuesday (July 17) during the Amazon AWS Summit in New York City, as the eCommerce operator rolled out new cloud-based features related to commerce and payments. The announcements from Amazon Web Services (AWS) come at a time when machine learning and AI are receiving increased focus in the payments and commerce industries, with executives and researchers developing technologies that can operate outside the limitations of human bias and intuition. In fact, an upcoming PYMNTS webinar with Karen Webster and Sunil Madhu, founder of identity verification and fraud prevention services provider Socure, will include discussion about how a robust AI robot could leverage the full power of machine learning paired with massive data sets, drawing in data from online, offline and social sources. In New York on Tuesday, AWS said it had built machine learning and AI improvements into its cloud computing services designed for enterprises. Two of the improvements are meant to speed up the AWS SageMaker service, which customers can use to test and deploy custom AI algorithms.