Sorites de produit, innovation, start-up

Machine learning platforms are not the wave of the future. It’s happening now. Developers need to know how and when to harness their power. Working within the ML landscape while using the right tools like Filestack can make it easier for developers to create a productive algorithm that taps into its power. The following machine learning platforms and tools — listed in no certain order — are available now as resources to seamlessly integrate the power of ML into daily tasks.

1. H2O

H2O was designed for the Python, R, and Java programming languages by H2O.ai. By using these familiar languages, this open source software makes it easy for developers to apply both predictive analytics and machine learning to a variety of situations. Available on Mac, Windows, and Linux operating systems, H2O provides developers with the tools they need to analyze data sets in the Apache Hadoop file systems as well as those in the cloud.


Source de l’article sur DZONE

In 2017, there were reports on how the world’s leading robotics and artificial intelligence pioneers called on the United Nations to ban the development and use of killer robots and weapons such as drones, tanks, and automated machine guns. A group of 116 specialists from across 26 countries led by Tesla’s Elon Musk and Alphabet’s Mustafa Suleyman had called a ban on autonomous weapons. This proves that even the big guns in automation are worried about robots running amok in the war field!

Almost a year back, even Facebook had abandoned an experiment after two artificially intelligent programs started interacting with each other in a strange language only they understood. Ensuring a stringent surveillance and monitoring plan is one of the key focus areas for any Artificial Intelligence (AI) related activity or applications. All these inventions closely impact our regular routine and peaceful coexistence. Hence, if anything goes wrong, it can probably endanger lives or our well-being in some way. Cybersecurity is as well a perspective to look at the ongoing boom around AI. What you need is a robust Quality Assurance and Testing plan!


Source de l’article sur DZONE

Reading the news every day will subject the reader to a deluge of hype around artificial intelligence. Depending on the perspective taken by the writer, the technology will often either be about to revolutionize things for the better, or, more probably, for the worse. However, we should be under no illusion that it will revolutionize things.

With such a barrage of hype, it’s easy to fall into the trap of thinking that our organizations are already being disrupted on an unprecedented scale by AI-based technologies. That the future so giddily predicted is already here.


Source de l’article sur DZONE

Unless you’ve been hiding under a rock, you’ve probably heard of the Cambridge Analytica Scandal and Mark Zuckerberg’s statements about the worldwide changes Facebook is making in response to European Union’s General Data Protection Regulation (GDPR). If your business is not yet in Europe, you may be taken aback by the statement from U.S. Senator Brian Schatz that "all tech platforms ought to adopt the EU approach to (data protection)." This, despite the fact that 45% of U.S. citizens think that there is already "too much" government regulation of business and industry.

So yes, GDPR is a big deal indeed. When it became the law in European Union on May 25, 2018, it improved data protection for EU citizens dealing with companies not only in Europe but all around the world. In other words, whether your company is based in EU or not, as long as you have EU citizens as customers or users and you process their data, GDPR is very much relevant for your business.


Source de l’article sur DZONE


While you may think sci-fi and imagination when you hear about AI, the future of Artificial Intelligence in dentistry is very, very real.

Some of us remember Will Robinson’s loyal robotic pal in the “Lost in Space” series of the 1960s. Others will trace the sci-fi vision of intelligent autonomous machines to the day Skynet became self-aware and turned on humanity in the “Terminator” films.

The term artificial intelligence (AI) and the official pursuit of intelligent machines in the scientific community actually dates to a 1956 conference of researchers from Dartmouth and IBM.


Source de l’article sur DZONE

Creating a chatbot that can understand and use a language other than English can be an ambitious task. Chatbots are still in their early days and even though there are many NLP libraries available, most of them support only the English language. From stopwords and POS taggers to pretrained word2vec models, it can be time-consuming to work on an NLP problem in a different language.

We at SmartCat tried a bit of a different approach in creating a bot that uses the Serbian language. Using a large dataset of unlabeled sentences written in Serbian and performing ML methods, we were able to create a chatbot that resulted in a very decent performance. It was able to return an expected response 9/10 times. Interested in how we did it? Keep on reading.


Source de l’article sur DZONE

Conçu par l’université du Michigan, ce micro ordinateur qui mesure à peine 0,3mm de côté pourrait loger dans l’extrémité d’un grain de riz.
Source de l’article sur ZDNet

A chatbot is a text-based program empowered by Artificial Intelligence (AI) and Natural Learning Processes (NLP). A user generally interacts with the chatbot over a platform through a communication channel connected to a network. In other words, chatbots are bots that live in chat platforms. There are numerous kinds of bots present globally, and they all can perform various tasks. The most common type of bot is the one offering customer services. So, according to a survey by Gartner, it is predicted that by 2020, an average person will converse with chatbots more than their spouse. Various new methods of customer engagement and development of enterprises have been created by conversational artificial intelligence. The AI enabled conversational bots have the potential of working 24/7, unlike human beings. With the of help this feature, enterprises have significantly reduced their response time and streamlined tasks in order to achieve the targets, which ultimately helped them retain their customers.

Bots also help businesses perform the same set of tasks multiple times in a cost-effective manner. The above mentioned are the primary reasons why chatbots are actively harnessed in different industry fields like banking sectors and on e-commerce sites. Undoubtedly, chatbots provide a lot of advantages like bots are available 24/7 and act as a dedicated resource that offer customers the services they actually need. Chatbots are known for enhancing brand value by providing instant customer service.


Source de l’article sur DZONE

This article is a continuation of Part 1. You can find the first part here.

Mid-Stage: Implement Existing Analytics Workflows

It is likely that when you begin your AIOps journey, you will already have certain analytics in place. I do not mean the analytics that are embedded in your IT tools. I mean offline, mostly manual analytics, that you do regularly, irregularly, or periodically to identify areas for process improvement, reduce costs, improve performance, etc.


Source de l’article sur DZONE

On Monday, June 18 in an IBM office in a San Francisco, California, IBM demonstrated an AI-based system that purports to hold its own in a debate with a human being. They named the system (wait for it) IBM Debater. For the human opponent, they picked a proven, skilled debater: Noa Ovadia, a college senior who won a debating championship in 2016. 

[Me stepping on a soapbox…feel free to skip]


Source de l’article sur DZONE