In the very popular show Silicon Valley, one of my favorite characters Jian Yang creates a Deep learning application which accurately predicts if a food item is a hot dog or not, pretty funny stuff, So I thought of using google's open source TensorFlow library to create my very own Hot dog classification program. So without further chit chat let's start classifying some hotdogs. For this project I've used: First we have to set up docker, since I'm using debian it was pretty straight forward. Let's launch that docker instance shall we: Since we're classifying if an article is a hotdog or not, we're going to need 1 folder and 2 subfolders, the main folder is going to be called images and within that folder we will create 2 subfolders named hotdogs and random. Now we need around 100 images of hotdogs in the hotdogs folder and 100 random images of things that aren't hotdogs, I used Fatkun image downloader from chrome extension store for this purpose, but a point to be noted is that TensorFlow only handles JPEG images and using PNG's can run you into a lot of trouble, after you're done populating the directories with images of hotdogs and random things in their respective folders we have to download and retrain the Inception V3 net by google, since we don't have the required time nor resources to train our own CNN.

While Spotify may still be having a difficult time achieving profitability, the company has the money to continue buying essentially whatever it wants, as the financing and fundraising never seems to stop. In 2016 alone, the powerhouse collected $1 billion in debt financing and another half a billion in a convertible note, and that is to say nothing of the untold millions that weren't revealed in fundraising rounds and the actual revenue brought in by the company on its own.

Silicon valley giant Google on Thursday (18 May) at its annual conference announced an Artificial Intelligence (AI) first strategy. Its no longer mobile first it is in AI in mobile now. AI moves into the consumer space with almost all Google's applications that come bundled with Android actively using it. Everyone knows Google through its eponymous search bar, Gmail icon, and Google maps it is part of every netizens life. These software application or even the algorithm is not Google.

In recent years, we've seen a resurgence in AI, or artificial intelligence, and machine learning. Machine learning has led to some amazing results, like being able to analyze medical images and predict diseases on-par with human experts. Google's AlphaGo program was able to beat a world champion in the strategy game go using deep reinforcement learning. Machine learning is even being used to program self driving cars, which is going to change the automotive industry forever. Imagine a world with drastically reduced car accidents, simply by removing the element of human error.

Humans are forgetful; we need calendar reminders, notepads, schedules, and assistants. But the co-creator of Siri, Apple's digital assistant, says artificial intelligence technology could make forgetting an archaic problem of the past. Tom Gruber, the AI guru and Siri co-creator, believes that AI technology could help improve human's shortcomings. During the TED 2017 conference on Tuesday, Gruber said it is inevitable that once artificial intelligence surpasses human intelligence, the technology will be used to enhance human cognition and memory. "What if you could have a memory that was as good as computer memory and is about your life?" Gruber asked the audience, as Recode reports.

To change your world, AI does not need to replace humans -- it just needs to displace you. So stop saying that AI can't replace humans, and start asking, "Can AI displace me?" You Don't Need to Be Totally Replaced by a Sentient AI System to Lose Your Job We are not close enough to general-knowledge artificial intelligence to consider a world where such a system could completely replace a cognitive nonrepetitive (white-collar) worker. And while Hollywood and sensationalist reporting would have you believe otherwise, malevolent AI systems and sentient cyborgs should not be the subject of any serious discussion about job loss. The most probable future is far scarier.

Classification is concerned with building a model that separates data into distinct classes. This model is built by inputting a set of training data for which the classes are pre-labeled in order for the algorithm to learn from. The model is then used by inputting a different dataset for which the classes are withheld, allowing the model to predict their class membership based on what it has learned from the training set. Well-known classification schemes include decision trees and Support Vector Machines, among a whole host of others. As this type of algorithm requires explicit class labeling, classification is a form of supervised learning.

Last week, I spoke at the Swiss Mobile Association. The event was held at one of the oldest cross-functional research institutes Gottlieb Duttweiler Institute just outside Zurich. Prior to being involved in IoT and AI, I worked for many years in Telecoms. I believe that from an innovation standpoint – we are living in a post-mobile world. Today, just as the Web itself, Mobile is a mature industry.

If you have a Google Analytics account, test it out free here. By 2018, Gartner predicts that 20 percent of all business content will be authored by machines. I wanted to find out more about Quill, so I reached out to Narrative Science, the company that makes the solution. Narrative Science helps enterprises use natural language generation to analyze and tell stories from their data. "We hear all the time that content is king--but what's really helping many of our customers is that AI can help automate a lot of high-quality content at scale," Katy De Leon, Narrative Science's VP of marketing, told me via a Skype interview.

Salesforce CEO Marc Benioff isn't just predicting that artificial intelligence will one day help run everyone's companies, he's already using it at Salesforce today. He's got a special, not-yet-released version of Einstein, the company's artificial intelligence tech baked into its products, helping him run his company, he told Wall Street analysts on Thursday during the company's quarterly conference call. He invites this version of Einstein, called Einstein Guidance, to his Monday morning staff meeting, where up to 30 top executives update him on their progress for the quarter. Einstein Guidance is designed to do forecasting and modeling. It's especially useful to make sure that managers aren't trying to snow him.