Trained neural networks at Microsoft are now as good at recognizing the human voice as humans are, researchers announced today. In a report released Monday, researchers pitted Microsoft's NIST 2000 automated system against professional transcriptionists and found for the first time a higher error rate among humans than computers. "This marks the first time that human parity has been reported for conversational speech," said the report published Monday. Better speech recognition could impact a range of Microsoft products in the future. "The milestone will have broad implications for consumer and business products that can be significantly augmented by speech recognition. That includes consumer entertainment devices like the Xbox, accessibility tools such as instant speech-to-text transcription, and personal digital assistants such as Cortana," Microsoft said in a blog post published today about the achievement.

As an example of how the above mentioned will help businesses, one project I have been working on implements these capabilities with an E-Commerce system, to provide not an E-Commerce store with a chatbot, but an Artificially Intelligent E-Commerce store. I have teamed up with API.AI, recently acquired by Google, to integrate their state of the art natural linguistics platform to enhance the user experience. From a visitors point of view, they can navigate the store, speak to the A.I to identify products or services they are interested in, manage their cart and account, all by simply interacting with the A.I via speech or text. From a business owners point of view, their A.I comes pre trained with the capabilities of seamlessly learning the products added to the store, and how to interact with the front end allowing them to assist site visitors. Through the GUI businesses can train their A.I exactly how they want, allowing them to mold their A.I in a way that best fits the image of their business.

Donald Trump is stepping on Veep's toes. The satirical TV show was forced to pull a joke planned for an upcoming episode after Trump's comments about grabbing women "by the pussy" came out in a tape from 2005. "We had a scene where a minor character gets picked up on a DUI and he's being a little mouthy to a female police officer and we sort of had a run using [the P-word]," Veep showrunner David Mandel told the Los Angeles Times. "It was pretty funny and they basically threw it in the garbage. While in this instance life got ahead of art, Mandel said there have been other moments that played out on Veep and then were later repeated on the real-life campaign trail. "In some ways, we're ahead of the election," Mandel said. "We had a story line last season where there were running jokes about the pronunciation of Nevada.

Microsoft Artificial Intelligence and Research group has claimed in a paper published this week that its speech recognition system can now understand human conversations, marking the first time "human parity" has been reported for conversational speech. According to Network World, Microsoft's researchers are now working on ways to make sure that speech recognition works well in more real-life settings. "The error rate of professional transcriptionists is 5.9% for the Switchboard portion of the data, in which newly acquainted pairs of people discuss an assigned topic, and 11.3% for the CallHome portion where friends and family members have open-ended conversations. In both cases, our automated system establishes a new state-of-the-art, and edges past the human benchmark. This marks the first time that human parity has been reported for conversational speech".

For the vast majority of organizations, customers should be the number one priority. Without their support, revenue streams dry up and businesses quickly fail. For small businesses that have a face-to-face relationship with their clients keeping them happy is straightforward, but in larger organizations ensuring that the relationship between business and customer is as positive as it can be is not always easy. Imagine being in charge of a global, multi-national company with thousands of customers in disparate locations. Each of these customers has their own specific needs and businesses can't afford to treat them all as a single homogeneous entity.

For anyone who has yet to experience Virtual Reality, I implore you, seek out a VR experience of some description. Whether Goggle Cardboard or Oculus Rift, it will likely be mind blowing. Why else would everyone who's anyone be talking about it being the future? When it comes to quality VR becoming an actual living room reality, though, there are many questions. Will there ever be a reason to?

Today with the growth of the internet of things there is a surge in usage of fast internet, smartphones, portable devices, smart TV, smart wearable and connected cars among retail consumers. This indicates the rise of connected consumers. This has made the huge impact in the retail landscape and the retail experience is evolving from multi-channel to Omni-channel. The connected consumer requires connected retail. Omni-channel retailing means establishing a presence on many channels and platforms (i.e. Physical stores remain the foundation of retailing, evidenced by the fact that - in the internet era, 90% of retail sales still take place in physical stores. According to eMarketer, the total retail sales in the US topped 4.53 trillion in 2013, of this brick-and-mortar sales still command a vast majority of the retail market nearly 4.27 trillion. According to A.T. Kearney, 95 percent of all retail sales are captured by retailers with a brick-and-mortar presence in total retail. Two-thirds of consumers who purchase online use the store before or after the transaction. The role of the brick & mortar store is changing, NOT going away. Stores remain at the heart of retailers' relationships with consumers, even in today's "Omni Channel" world where online and physical sales appear to rule. According to a report, When it comes to product trial and tests, respondents indicate a clear preference for physical stores. Despite the growing popularity of e-commerce and digital retailing are capturing headlines in news media and inspiring spirited debates (blah, blah..) retailers plan how best to invest for future success, including a plan to build an another planet. The e-commerce retail market share is only 263 billion. It is only 5.8% of the market share. Small basket, single channel, ineffective delivery, can't see, can't feel or try made it as a hard business model. Is pure play e-commerce is an unprofitable business model? Investment on e-commerce is "river of no returns"? Are we nearing the end of the e-commerce bubble? Is M-commerce the future of retail? Drop out, make an app, go viral and make money?

PyData Chicago 2016 This tutorial provides you with a comprehensive introduction to machine learning in Python using the popular scikit-learn library. We will learn how to tackle common problems in predictive modeling and clustering analysis that can be used in real-world problems, in business and in research applications. And we will implement certain algorithms as scratch as well, to internalize the inner workings This tutorial will teach you the basics of scikit-learn. We will learn how to leverage powerful algorithms from the two main domains of machine learning: supervised and unsupervised learning. In this talk, I will give you a brief overview of the basic concepts of classification and regression analysis, how to build powerful predictive models from labeled data.

Quantum physics has some spooky, anti-intuitive effects, but it could also be essential to how actual intuition works, at least in regards to artificial intelligence. In a new study, researcher Vedran Dunjko and co-authors applied a quantum analysis to a field within artificial intelligence called reinforcement learning, which deals with how to program a machine to make appropriate choices to maximize a cumulative reward. The field is surprisingly complex and must take into account everything from game theory to information theory. Dunjko and his team found that quantum effects, when applied to reinforcement learning in artificial intelligence systems, could provide quadratic improvements in learning efficiency, reports Phys.org . Exponential improvements might even be possible over short-term performance tasks.

Speech recognition software isn't perfect, but it is a little closer to human this week, as a Microsoft Artificial Intelligence and Research team reached a major milestone in speech-to-text development: The system reached a historically low word error rate of 5.9 percent, equal to the accuracy of a professional (human) transcriptionist. The system can discern words as clearly and accurately as two people having a conversation might understand one another. By combining Microsoft's open-source Computational Network Toolkit, and being a little bit over-obsessed with this project, the team was able to beat its goal of human parity by years in just months, according to Microsoft's blog. They hit the parity milestone around 3:30 a.m., when Xuedong Huang, the company's chief speech scientist, woke up to the breakthrough. It's a difference you'll likely notice when you're talking to an AI assistant in the near future says Huang, as speech recognition becomes a mainstream user interface.