Despite the hype, there is a lot of work to be done before we can build conversational software. These are some notes about what interesting conversational software would look like, and what techniques we'll need to build it. It may be obvious, but I feel we have to point out that the giddy excitement around bots stems from being happy that there is something new to build/invest in/write medium posts about, and not from exciting new technology. For VCs, new platforms mean new opportunities to bundle and unbundle services, and new battlegrounds for the big players (likely leading to acquisitions). So even without real technological breakthroughs, there is at least some money to be made investing in bot startups.

Norwegian authorities have violated mass killer Anders Behring Breivik's human rights by holding him in solitary confinement in a three-cell complex where he can play video games, watch TV and exercise, a court in Oslo ruled Wednesday. In a written decision, the Oslo district court said Breivik's solitary confinement for killing 77 people in 2011 bomb-and-gun massacres breached the European Convention on Human Rights' ban on inhuman treatment. "The prohibition of inhuman and degrading treatment represents a fundamental value in a democratic society," the court said. "This applies no matter what -- also in the treatment of terrorists and killers." The court ordered the government to pay Breivik's legal costs of 331,000 kroner, about 41,000.

This paper investigates the problem of cross-lingual transfer parsing, aiming at inducing dependency parsers for low-resource languages while using only training data from a resource-rich language (e.g., English). Existing model transfer approaches typically don't include lexical features, which are not transferable across languages. In this paper, we bridge the lexical feature gap by using distributed feature representations and their composition. We provide two algorithms for inducing cross-lingual distributed representations of words, which map vocabularies from two different languages into a common vector space. Consequently, both lexical features and non-lexical features can be used in our model for cross-lingual transfer. Furthermore, our framework is flexible enough to incorporate additional useful features such as cross-lingual word clusters. Our combined contributions achieve an average relative error reduction of 10.9% in labeled attachment score as compared with the delexicalized parser, trained on English universal treebank and transferred to three other languages. It also significantly outperforms state-of-the-art delexicalized models augmented with projected cluster features on identical data. Finally, we demonstrate that our models can be further boosted with minimal supervision (e.g., 100 annotated sentences) from target languages, which is of great significance for practical usage.

We study high-dimensional distribution learning in an agnostic setting where an adversary is allowed to arbitrarily corrupt an $\varepsilon$-fraction of the samples. Such questions have a rich history spanning statistics, machine learning and theoretical computer science. Even in the most basic settings, the only known approaches are either computationally inefficient or lose dimension-dependent factors in their error guarantees. This raises the following question:Is high-dimensional agnostic distribution learning even possible, algorithmically? In this work, we obtain the first computationally efficient algorithms with dimension-independent error guarantees for agnostically learning several fundamental classes of high-dimensional distributions: (1) a single Gaussian, (2) a product distribution on the hypercube, (3) mixtures of two product distributions (under a natural balancedness condition), and (4) mixtures of spherical Gaussians. Our algorithms achieve error that is independent of the dimension, and in many cases scales nearly-linearly with the fraction of adversarially corrupted samples. Moreover, we develop a general recipe for detecting and correcting corruptions in high-dimensions, that may be applicable to many other problems.

It's almost a given that you'll ride in an autonomous car at some point in your life, and when you do, the AI controlling it just might have honed its skills playing Minecraft. It sounds crazy, but open-world games like Minecraft are a fantastic tool for teaching learning algorithms--which power the next generation of advanced artificial intelligence--how to understand and navigate three-dimensional spaces. Achieving that is a major stepping stone toward creating AI that can interact with the real world in complex ways. It's easy to consider videogames mindless escapism, but because they generate such vast amounts of information--think of the expansive world players create in Minecraft--they are exceptionally well suited to teaching an AI how to perceive the world and interact with it. "It's hard for a human to teach AI," says Xerox researcher Adrian Gaidon, because they are "worse than the worst toddlers in the world--you have to explain everything."

A pair of super-rich American technology gurus are planning to undergo surgery to install experimental implants directly into their brains. The two men are currently trying to find a doctor willing to perform this untested and highly risky procedure, The Mirror has learned. If they survive the operation, the men hope to be able to directly communicate with the primitive forms of artificial intelligence currently being developed in labs across the world. But critics and conspiracy theorists fear these pioneering implants are the first step towards creating a society where every human is plugged into "the matrix". Zoltan Istvan, a U.S. Presidential candidate, personally knows both of these would-be bionic men.

A new public data set for self-driving cars shows that even a straightforward city commute may push automated driving to the limit. It also highlights how sharing data could help self-driving cars hit the roads far sooner. Researchers from Oxford University released the detailed data set, which highlights some of the most challenging issues that self-driving cars will face. The data consists of thousands of hours of data from the same 10-kilometer stretch of road over the course of a year. And it shows how weather, lighting, and even the features of roads themselves can vary wildly in a relatively short period of time.

This post is based on a presentation I shared at Ignite DFW on April 15, 2016. It was absolutely an amazing experience! Thank you to everyone who organized it, participated as a speaker, and showed up to enjoy the amazing topics we shared as Dallas-Fort Worth community. Ignite is a night of presentations on a variety of inspired topics -- with a twist. Each presentation has 20 slides that automatically advance after 15 seconds.

As a reminder, all participants' lines will be in the listen-only mode. There will be an opportunity for you to ask questions after the presentation concludes. I would now like to hand the conference over to Mr. Aravind Viswanathan. Thank you and over to you, sir. We will begin the call with business highlights and overview by Abid, the Chief Executive Officer and Member of the Board, followed by the financial overview by our CFO, Jatin Dalal. Afterwards, the operator will open the bridge for Q&A with our management team. Before Abid starts, let me draw your attention to the fact that during this call, we may make certain forward-looking statements within the meaning of Private Securities Litigation Reform Act 1995. These statements are based on management's current expectations and are associated with uncertainties and risks, which may cause the actual results to differ materially from those expected. The uncertainties and risk factors are being explained in our detailed filings with the SEC. Wipro does not undertake any obligation to update the forward-looking statements to reflect events and circumstances after the date of filing thereof. The conference call will be archived and the transcript will be available on our website. Ladies and gentlemen, let me now hand it over to Mr. Abid. Today is the first opportunity for me to interact with all of you since I've taken over as the Chief Executive Officer of Wipro, and it's a special moment for me. While I will speak about the performance of our full quarter and the full fiscal year, I thought I will take this opportunity to begin by speaking about our ambition, our strategy and how we are going to execute this strategy. Since I got announced within two days, I was able to define and announce my structure and I had already preselected my leadership team which I announced on 6th of January, effective February 1. Over the past 80 days after I have taken over as CEO, I've had the opportunity to go around the globe and meet about 70 of our top 100 clients. And both with my leadership team and with the customers, I've had the opportunity to validate the strategy that we have been working on and this gives me a high level of confidence on the relevance of our overall strategy. Our ambition is to double our revenues to 15 billion by fiscal 2020 with a 23% operating margin.

These days, writing is typing. And it looks as if the layout of QWERTY keyboards is influencing the way we feel about certain words. Our relationship with the written word has changed in the last few years. We read words differently on a screen to how we read them on paper, for example. And using keyboards – both on phones and computers – has given rise to txtspk and popular acronyms such as "OMG" and "ROFL".