Information Technology


Harvard's robot arm can grab squishy sea animals without hurting them

Engadget

As you might imagine, you can't just grab extra-soft sea creatures like jellyfish or octopuses when you want to study them. Not if you want them to remain intact, anyway. Thankfully, researchers at Harvard's Wyss Institute have a far more delicate solution. They've created a robot arm (the RAD sampler) whose petal-like fingers can quickly form a ball shape around an animal, capturing it without risking any harm. It's simpler than it looks -- it uses just a single motor to drive the entire jointed structure, so it's easy to control and easier still to repair if something breaks.


IoT and AI to fundamentally change the way we live and work: CSG

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CSG, a business support solutions (BSS) provider said that telecom carriers are increasingly leveraging the cloud to bring down the recurring operational costs, and with India's top service provider Bharti Airtel as one of the telcos to deploy revenue management platform, the US-headquartered company feels that the IoT and AI would fundamentally the change the way we live, work and play. How have you been supporting businesses to digitally transform? Almost every industry is faced with digital disruption and the need to transform to survive and thrive. Among our primary client base of communications service providers, digital transformation encompasses every aspect of their business, from rolling out new 5G networks to launching new services designed to attract consumers on-the-go. CSG supports the digital transformation of companies in ways such as investments in our solution portfolio that enable our customers to meet these increased demands, and through the deep expertise of our people across digital strategy, processes, and technology domains.


r/MachineLearning - [D] Keras vs PyTorch

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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).


CDOs step out of comfort zones as data monetization efforts increase - SiliconANGLE

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Monetizing data assets is enticing for businesses sitting on lakes of information about consumer likes, dislikes, wants and needs. The spotlight is on the benefits of artificial intelligence and machine learning to parse through it all, but this big data is personal data, and Wild-West attitudes to collection and analysis methods can have serious consequences in the modern business world. "Business leaders don't necessarily know how [AI models] work or what can go wrong with them," said Cortnie Abercrombie (pictured, left), founder and chief executive officer of the non-profit AITruth.org. "Data scientists are just trying to fulfill the challenge at hand, and they get really swept up in it to the point where data is getting bartered back and forth without any real governance or policies in place." So what are companies supposed to do? "What I'm advising executives, the board, and my clients is that we need to step back and think bigger about this, think about it not just as GDPR -- the European scope -- it's global data privacy," said Carl Gerber (pictured, right), managing partner at Global Data Analytics Leaders LLC.


Landbot gets $2.2M for its on-message 'anti-AI' chatbot

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Who needs AI to have a good conversation? Spanish startup Landbot has bagged a $2.2 million seed round for a'dumb' chatbot that doesn't use AI at all but offers something closer to an old school'choose your adventure' interaction by using a conversational choice interface to engage potential customers when they land on a website. The rampant popularity of consumer messaging apps has long been influencing product development decisions, and plenty of fusty business tools have been consumerized in recent years, including by having messaging-style interfaces applied to simplify all kinds of digital interactions. In the case of Landbot, the team is deploying a familiar rich texting interface as a website navigation tool -- meaning site visitors aren't left to figure out where to click to find stuff on their own. Instead they're pro-actively met with an interactive, adaptive messaging thread that uses conversational choice prompts to get them the information they need.


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.


'Machine learning, AI top professionals' reskilling list'

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Artificial intelligence (AI) and machine learning (ML) are the most widely chosen domains for reskilling among working tech professionals in India, according to the findings of education technology company Simplilearn. The firm's'Career Impact Survey 2018' which was aimed at analyzing the impact of professional certifications and reskilling among working professionals revealed that AI and ML domains were chosen by 25% of respondents. This was followed by big data and data science domains chosen by 20% of the participants. Other new age categories such as'digital marketing, cloud computing, cybersecurity, DevOps and Agile and Scrum' together saw 55% uptake in reskilling among professionals. The certification courses helped 31% of professionals to enhance their performance, gain manager and peer appreciation, according to the survey.


Fear not humans: Artificial intelligence to create millions of jobs, predicts PwC

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The research found that while AI could displace roughly seven million jobs in the country, it could also create 7.2 million roles, resulting in a modest net boost of around 200,000 jobs. It has also estimated that about 20 percent of jobs would be automated over the next 20 years and no sector would be unaffected. Technologies such as robotics, drones and driverless vehicles would replace human workers in some areas, but also create many additional jobs as productivity and real incomes rise and new and better products are developed. In the health and social work sector the number of people employed could rise by almost one million, while jobs in manufacturing could fall by roughly 25 percent, a net loss of almost 700,000 roles. "Major new technologies, from steam engines to computers, displace some existing jobs but also generate large productivity gains," PwC's Chief Economist John Hawksworth said in a press release.