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7 Real-Life Use Cases for Google DeepMind's Machine Learning Systems

#artificialintelligence

Tom studied English Literature and History at Sussex University before gaining a Masters in Newspaper Journalism from City University.


Who Made the News? Text Analysis using R, in 7 steps

@machinelearnbot

The dataset used for the analysis was obtained from Kaggle Datasets, and is attributed to UCI Machine Learning. The raw tabular data includes information about news category (business, science and technology, entertainment, etc.) R language has some useful packages for text pre-processing and natural language processing. I prefer fread() over read.csv() For the scope of this program, we limit ourselves to only the headline text and publisher name. We use a "for loop" to filter and a custom function aggregate the headline texts for each publisher.


3 Ways Artificial Intelligence Will Change Publishing

#artificialintelligence

Change is happening all around us, and one of the biggest drivers of change in the digital world is artificial intelligence (AI). We can't listen to a tech CEO keynote without stumbling on how they are using AI for a variety of products or innovations. Smart publishers are also beginning to embrace AI. They are weaving it into the core of their business -- to inform and improve content, advertising and product. The benefit of AI to readers is that it can be both interactive and anticipatory.


Microsoft Will Ride Artificial Intelligence, Cloud Computing To Higher Share Price, Morgan Stanley Says - BI News - Business Intelligence

#artificialintelligence

It's not just Amazon that will make money from cloud computing and artificial intelligence, according to Wall Street. Morgan Stanley believes Microsoft's Azure business will thrive riding the same hot technology trends. The firm reiterated its overweight rating on Microsoft shares, predicting the company will report profits ahead of expectations next year due to cloud computing demand.


How to leverage Big Data and Artificial Intelligence for your marketing campaigns Blog Buzzoole

#artificialintelligence

The marketing industry is rapidly evolving. It's at a new phase where Big Data and AI (Artificial Intelligence) are driving strategy development and decision making. Because conventional analytics scale at a gradual pace, marketers are beginning to utilise AI to analyse the large volume of unstructured data to improve marketing research, forecasting accuracy and campaign experiences. A research of CMOs from the US, UK, and China from companies with more than $500 million in revenue revealed that around two thirds of these think Artificial Intelligence will play a significant role in their future marketing operations. But only a third claimed to have good knowledge of how it is actually implemented.


Energy-Based Sequence GANs for Recommendation and Their Connection to Imitation Learning

arXiv.org Machine Learning

Recommender systems aim to find an accurate and efficient mapping from historic data of user-preferred items to a new item that is to be liked by a user. Towards this goal, energy-based sequence generative adversarial nets (EB-SeqGANs) are adopted for recommendation by learning a generative model for the time series of user-preferred items. By recasting the energy function as the feature function, the proposed EB-SeqGANs is interpreted as an instance of maximum-entropy imitation learning.


Apple just got deeper into AR with purchase of eye-tracking tech firm

USATODAY - Tech Top Stories

The iPhone 7 and 7 Plus were released on Sept. 16, 2016. The iPhone 7 models featured new hardware updates and an updated 12 megapixel rear-facing camera. Notably, Apple removed the 3.5 mm headphone jack in the 7 and 7 Plus models. SAN FRANCISCO -- Apple wants to make AR a reality. Three weeks after it unveiled ARKit, a new augmented reality developer kit that would help Apple app developers integrate this technology that overlays digital images on the physical world, and Apple CEO Tim Cook singed its praises, the company has acquired SensoMotoric Instruments, a German developer of eye-tracking movement technology.


How HBO's Silicon Valley built "Not Hotdog" with mobile TensorFlow, Keras & React Native

@machinelearnbot

Have you ever found yourself reading Hacker News, thinking "they raised a 10M series A for that? I could build it in one weekend!" This app probably feels a lot like that, and the initial prototype was indeed built in a single weekend using Google Cloud Platform's Vision API, and React Native. But the final app we ended up releasing on the app store required months of additional (part-time) work, to deliver meaningful improvements that would be difficult for an outsider to appreciate. We spent weeks optimizing overall accuracy, training time, inference time, iterating on our setup & tooling so we could have a faster development iterations, and spent a whole weekend optimizing the user experience around iOS & Android permissions (don't even get me started on that one).


Google Home now supports up to six users in the UK

Engadget

Good news, Google Home owners: your smart speaker is now ready to get to know your family. The search giant has confirmed that UK Homes now support up to six users, allowing members of your household to train Google's Assistant to recognize their voices. It also means that their music playlists, schedules and appointments can be synced, ensuring everyone gets more use out of the tiny white speaker. The feature is actually pretty easy to set up. Simply make sure that you have the latest version of the Google Home app on your smartphone (iOS or Android) and then find the card that says "multi-user is available."


AI, Machine Learning and Sentiment Analysis Applied to Finance – Millennium Hotel London Mayfair

#artificialintelligence

Artificial Intelligence, Machine Learning and Sentiment Analysis are changing the way in which numerous client services are offered. In particular, Financial Organisations are creating and leveraging such innovation in the domain of wealth management. This trend is now being taken on board by multiple innovators: academia, start-ups, technology companies and financial market participants. AI and Machine Learning have emerged as a central aspect of analytics which is applied to multiple domains. AI and Machine Learning, Pattern classifiers and natural language processing (NLP) underpin Sentiment Analysis (SA); SA is a technology that makes rapid assessment of the sentiments expressed in news releases as well as other media sources such as Twitter and blogs.