Internet


Harri Valpola dreams of an internet of beautiful AI minds

@machinelearnbot

Valpola, 44, is founder of The Curious AI Company, a 20-person artificial intelligence startup based in Helsinki, which has just raised $3.67 million in funding – small change compared to many tech funding rounds, but an impressive sum for a company that has no products and is only interested in research. Wanting to put his theories into practice, Valpola co-founded ZenRobotics, a startup building brains for intelligent robots. At this year's Conference on Neural Information Processing Systems (the leading conference in AI, better known as NIPS), he is going to present a cousin of the ladder network, punningly entitled Mean Teacher. "I've met Harri a few times, and we have similar views on AI and deep learning," says Murray Shanahan, professor of cognitive robotics at Imperial College London.


Machine Learning Part I: The Terminator Meets the Internet of Things

#artificialintelligence

The internet of things (IoT), machine-learning, deep learning, and artificial intelligence (AI) are concepts you've probably heard or read about, but chances are you may not fully understand their differences and the impact they can have on your business. This blog series will help breakdown how your data is handled, starting at the beginning with how the IoT has revolutionized how we interact with technology, all the way through to AI (Artificial Intelligence), into our ever-evolving future. In its most simple form, the Internet of Things (IoT) is an internal network of devices that communicate, share, and interpret exchanged data. We will uncover the next step of the process – IoT data collection – in the next blog post in this series.


Machine Learning Part I: The Terminator Meets the Internet of Things

#artificialintelligence

The internet of things (IoT), machine-learning, deep learning, and artificial intelligence (AI) are concepts you've probably heard or read about, but chances are you may not fully understand their differences and the impact they can have on your business. This blog series will help breakdown how your data is handled, starting at the beginning with how the IoT has revolutionized how we interact with technology, all the way through to AI (Artificial Intelligence), into our ever-evolving our future. In its most simple form, the Internet of Things (IoT) is an internal network of devices that communicate, share, and interpret exchanged data. We will uncover the next step of the process – IoT data collection – in the next blog post in this series.


Beginners Guide to Machine Learning, Artificial Intelligence, Internet of Things (IoT), NLP, Deep Learning, Big Data Analytics and Blockchain

@machinelearnbot

The new technologies like Machine Learning, Internet of Things, Deep Learning, NLP, Artificial Intelligence, Cloud, Big data and Predictive analytics are having a massive impact in India. This post is a Beginners Guide to Machine Learning, Artificial Intelligence, Internet of Things (IoT), Natural Language Processing (NLP), Deep Learning, Big Data Analytics and Blockchain. While big data is all about data, patterns (or trends) insights & impacts, internet of things is about data, devices, and connectivity. The Internet of things (IoT) is the inter-networking of physical devices (also termed as connected devices or smart devices), vehicles, buildings and other objects (which could be smart wearable, diagnostic device, kitchen appliances etc.)


Is Fashion Ready for the AI Revolution?

#artificialintelligence

In the last few years, a trifecta of cheap, ubiquitous, powerful computing; big data; and the development of deep learning have triggered a revolution in artificial intelligence. The computing devices that now fill our everyday lives generate large data sets, which "deep learning" algorithms analyse to find trends, make predictions and perform specific tasks, such as identifying specific objects in an image. Edited let this loose on a bank of data on 60 million fashion products, collected from retailers and brands in over 30 countries, in over 35 languages: the result is a searchable database of organised, structured information on each of these products. Thread, an online personal styling service, combines human stylists with machine learning algorithms.


Can Machine Learning Turn Big Data into No Big Deal?

#artificialintelligence

Is machine learning (ML) or artificial intelligence (AI) the key? Companies have worked on many ways to offer plug-and-play sensor packages to collect information, with multiple options to send it where ever it needs to go. To reap the benefits of a higher-performing data network such as IIoT, ML, or Big Data, an interdisciplinary communication network is essential. "OT professionals are focused on keeping manufacturing, plant, and physical equipment in operation for extended periods of time, while IT professionals focus on keeping data flowing and accessible to all facets of an organization," says Dariol.


IoT as a Metaphor

@machinelearnbot

Beyond the network of sensors & devices and base IT technologies partially listed in the last paragraph, what is unique and new in IOT is Data Science applications –Data Science applied with the focus on information extraction, insights generation and prescriptive decisions. When IoT is defined as "(Network of Sensors & Devices) IT (Engineering Data Science)", it seems to pervade ALL industries from my vantage point! I have partitioned applied Data Science into three: Industry, Business & Social Data Science. Specialization for each vertical notwithstanding, the three "types" of Data Science are best seen as a unified whole, which we are calling "Engineering Data Science or EDS".


Loan Underwriting Gets Artificial Intelligence Upgrade

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However, fintech startups are working to upend the traditional underwriting process with an injection of machine learning technology. Datanomers, a New Jersey-based fintech startup, has developed a "financial risk profiler" that trawls the web for unstructured non-financial data on loan applicants, indexes the information and generates a report for the underwriter. Datanomers' Risk Profiler collects billions of data points available on the web about small businesses to create a credit profile for borrowers. So rather than digging through pages upon pages of a small business owner's reviews via Yelp Inc (NYSE: YELP) and Angie's List Inc (NASDAQ: ANGI) for signs of unsound business practices, an underwriter can simply enter the proprietor's name into a Google (parent company, Alphabet Inc (NASDAQ: GOOG) (NASDAQ: GOOGL))-like interface that will produce a PDF report of the prospective borrower's creditworthiness.


Futurist David Brin: Get ready for the 'first robotic empathy crisis'

#artificialintelligence

"Within three to five years we will have entities either in the physical world or online who demand human empathy, who claim to be fully intelligent, and claim to be enslaved beings, enslaved artificial intelligences, and who sob and demand their rights." Thousands upon thousands of protesters will be in the streets demanding rights for AI, Brin predicts, and those who aren't immediately convinced will be analyzed. "If they fool 40 percent of people but 60 percent of people aren't fooled, all they have to do is use the data on those 60 percent of people and their reactions to find out why they weren't fooled. Earlier this week influence marketing company Onanalytica called Brin the top influencer in artificial intelligence so far this year.


The world's best Go player lost to Google's artificial intelligence

USATODAY

Go champion'speechless' after 2nd loss to machine Internet users outside China could watch this week's games live but Chinese censors blocked most mainland web users from seeing the Google site carrying the feed. Google says 60 million people in China watched online when AlphaGo played South Korea's go champion in March 2016. Chinese Go player Ke Jie reacts as he plays a match against Google's artificial intelligence program, AlphaGo, during the Future of Go Summit in Wuzhen in eastern China's Zhejiang Province. On Thursday, AlphaGo "thought that Ke Jie played perfectly" for the first 50 moves, Hassabis said at a news conference.