Nintendo Reports Second Quarter Losses But 3DS Sales Are Up Thanks To'Pokmon GO' At Inbound 2016, HubSpot's co-founders Brian Halligan and Dharmesh Shah entertained 19,000 attendees with their take on the past and future of marketing. Here's what I learned from their keynote presentation and a brief interview. So predicts Halligan, adding "in five years, you will do a lot less navigating through apps and more just asking questions and chatting back and forth with bots… the next thing you know, we like it and it's easier and more efficient than waiting for the sales rep to call you back." Shah notes that businesses started building websites in the 1990s so they can answer customer questions 24/7. "Soon," he says, "they will start building bots. They won't replace the websites, but they will power them. The shortest time between a customer question and the answer will be a bot. It's not human vs. bot, it's human to the bot powered."

Ben Dickson is a software engineer and the founder of TechTalks. As artificial intelligence and machine learning mature and manifest their potential to take on complicated tasks, we've become somewhat expectant that robots can succeed where humans have failed -- namely, in putting aside personal biases when making decisions. But as recent cases have shown, like all disruptive technologies, machine learning introduces its own set of unexpected challenges and sometimes yields results that are wrong, unsavory, offensive and not aligned with the moral and ethical standards of human society. While some of these stories might sound amusing, they do lead us to ponder the implications of a future where robots and artificial intelligence take on more critical responsibilities and will have to be held responsible for the possibly wrong decisions they make. At its core, machine learning uses algorithms to parse data, extract patterns, learn and make predictions and decisions based on the gleaned insights.

When medics apply radiotherapy to a cancer patient, they have to carefully determine which parts of the body should be exposed to radiation in order to kill the tumor while ensuring that as much healthy surrounding tissue as possible is preserved. "Clinicians will remain responsible for deciding radiotherapy treatment plans, but it is hoped that the segmentation process could be reduced from up to four hours to around an hour," explains DeepMind. It's currently drawing on 600,000 medical evidence reports and 1.5 million patient records and clinical trials to help doctors develop better treatment plans for cancer patients. After coming under fire earlier in the year when an app project appeared to provide DeepMind with free access to 1.6 million patients' records, the research outfit recently announced that it was helping to spot the early signs of visual degeneration by sifting through a million eye scans.

Chatbots are on the rise. Startups are building chatbots, platforms, APIs, tools, analytics. Microsoft, Google, Facebook introduce tools and frameworks, and build smart assistants on top of these frameworks. Multiple blogs, magazines, podcasts report on news in this industry, and chatbot developers gather on meetups and conferences. I have been working on chatbot software for a while, and I have been looking on what is going on in the industry. In this article, I will dive into architecture of chatbots.

Deep Learning in Retail & Advertising Summit London The Deep Learning in Retail & Advertising Summit is a multidisciplinary event bringing together data scientists, engineers, CTOs, CEOs & leading retailers to explore the impact of deep learning and AI in the retail and advertising sector. Applications include computer vision for sizing; image analysis for shopping efficiency; and natural language processing for personalised shopping experiences. The Deep Learning in Retail & Advertising Summit is a multidisciplinary event bringing together data scientists, engineers, CTOs, CEOs & leading retailers to explore the impact of deep learning and AI in the retail and advertising sector. Applications include computer vision for sizing; image analysis for shopping efficiency; and natural language processing for personalised shopping experiences.

The idiom "never judge a book by its cover" warns against evaluating something purely by the way it looks. And yet book covers are designed to give readers an idea of the content, to make them want to pick up a book and read it. Good book covers are designed to be judged. And humans are quite good at it. It's relatively straightforward to pick out a cookery book or a biography or a travel guide just by looking at the cover.

Brief Recognition: Elena Grewal leads a team of data scientists responsible for the user's online and offline travel experience at Airbnb. Her team partners with the product team to understand and optimize all parts of the product, using experimentation and machine learning in a wide variety of contexts. Prior to Airbnb, Elena was a doctoral candidate in the Economics of Education program at the Stanford University School of Education. She received a B.A. in Ethics, Politics, and Economics, with distinction, from Yale University, and a Masters degree in Economics at Stanford University. She was also the recipient of the Stanford Interdisciplinary Graduate Fellowship.

DeepMind is the world leader in artificial intelligence research and its application for positive impact. We're on a scientific mission to push the boundaries of AI, developing programs that can learn to solve any complex problem without needing to be taught how. Over time, the insights gleaned from the industries currently taking advantage of AI and improving the technology along the way will make it ever more robust and useful within a growing range of applications. Organizations that can afford to invest heavily in AI. Systems that learn directly from their experience or from more data versus handcrafted heuristic systems so systems where they've been specifically pre-pragramd with a particular solution to a problem Many systems are is they're handcrafted & they're built for one particular purpose in mind what we're interested in mind the idea of generally one system hat out of the box are can do a wide range of tasks What we mean here is that we think that for a true thinking machine to be able to think about & achieve high & tasks they need to be grounded in the sensor motor reality they have to experience the world around them through their senses & ground the Knowledge that they acquire ground in the sensor imotor experience and appose to that logic base system or symbolic systems they are encoded and the problem with those systems is when they intract with the outside world with real events they find it very difficult to map the logic knowledge they have to these real- world messy situations that they find them self.

A new kind of speech synthesiser can translate the movements of your mouth directly into words, without the need for you to use your voicebox.It works by measuring the movements of your mouth and converting them into sounds using an artificial intelligence network Why Mars astronauts risk going BLIND: Scientists finally... Google says its artificial intelligence has taught itself to... Rise of the'cellfie': Parents-to-be can now see pictures of... Why Mars astronauts risk going BLIND: Scientists finally... Google says its artificial intelligence has taught itself to... Rise of the'cellfie': Parents-to-be can now see pictures of... Barron Trump clapping during his father's appearance at RNC Penny for your thoughts: Cute baby laughs at hearing dad say 4p Mob storm police station and lynch suspected paedophile Raging bull destroys car with horns at Spanish festival Bear with us!: Workers rescue bear under concrete pit in Turkey Homeless man has zebra-skin slipcovers & porcelain toilet'Do you know who I am?: 'Angry' cyclist confronts motorist 100 special police agents protect suspected paedophile from mob Girlfriend confronts'cheating boyfriend' at supermarket It was a long and tiresome night for 10-year-old Barron Trump Surprise Castro is dead: Florida grandmother is shocked! 'Do you know who I am?: 'Angry' cyclist confronts motorist Girlfriend confronts'cheating boyfriend' at supermarket Surprise Castro is dead: Florida grandmother is shocked! Trump nemesis Rosie O'Donnell is slammed after speculating... Armed attacker shot dead by cops after mowing down students... Homeless man who turned freeway underpass into a personal... Donald goes to war as Hillary backs recount: Trump accuses... £100 million bed-hopping hypocrite: He claimed he lived on... ISIS fighters target Israel for the first time and are... Thousands of fans BOO Colin Kaepernick in Miami after he... Trump launches furious morning Twitter rant at Hillary,... REVEALED: California supermom was heavily beaten and chained... The Seattle Nike outlet that was completely TRASHED by Black... Skating on thin ice: Wife of Vladimir Putin's spokesman... Outrage as Prince Harry is forced to take part in an... Trump nemesis Rosie O'Donnell is slammed after speculating... Armed attacker shot dead by cops after mowing down students... Homeless man who turned freeway underpass into a personal... Donald goes to war as Hillary backs recount: Trump accuses... ISIS fighters target Israel for the first time and are... Thousands of fans BOO Colin Kaepernick in Miami after he... Trump launches furious morning Twitter rant at Hillary,... REVEALED: California supermom was heavily beaten and chained... The Seattle Nike outlet that was completely TRASHED by Black... Outrage as Prince Harry is forced to take part in an...

Many data set resources have been published on DSC, both big and little data. Some associated with our data science apprenticeship. A list can be found here. Below is a repository published on Github, originally posted here. Quora: Where can I find large datasets open to the public?