Artificial intelligence (AI), robotics and automation are possibly the most fascinating topics for those dealing with technology (and sourcing) matters. They raise a lot of interesting questions and scenarios. Even the few official legal documents about these subjects refer to Mary Shelley's Frankenstein, Pygmalion, Prague's Golem – and the more obvious Asimov's Three Laws of Robotics (see the EU Parliament Draft Report with recommendations to the Commission on Civil Law Rules on Robotics). But this is not only about philosophy and futuristic settings. There is already no doubt that robots, androids and all other forms of artificial intelligence are already playing a fundamental role in the new Internet of Things (IoT) "smart" industrial revolution, which will affect most if not all industrial sectors and countries.

How do children learn language? Could we use robots to model children language acquisition? This question is linked to a more general issue: how does the brain associate sequences of symbols to internal symbolic or sub-symbolic representations? I will present a Recurrent Neural Network (RNN), namely an Echo State Network (ESN) or Reservoir, that performs sentence comprehension and can be used for Human-Robot Interaction. The RNN is trained to map sentence structures to meanings (i.e. This model has interesting capabilities, for instance it can learn to "understand" French and English at the same time.

This is a TensorFlow implementation of the WaveNet generative neural network architecture for audio generation. The WaveNet architecture directly generates a raw audio waveform, and shows excellent results in TTS and general audio generation (see the DeepMind blog post and paper for examples). The network is a model of the conditional probability to generate the next sample in the audio waveform, given all previous samples and possibly additional parameters. It is constructed from a stack of causal dilated layers, each of which is a dilated convolution (convolution with holes), which only accesses the current and past audio samples. The network is implemented in the file wavenet.py.

The cashiers' demands were simple: management must remove the tracking software they had installed in the checkout terminals, or the cashiers would refuse to return to work. The technology that tracked their every movement – their speed, efficiency, etc – had been installed without their knowledge, they asserted, and was an invasion of privacy. While this seems like something one might see today, this happened nearly 40 years ago at the biggest supermarket chain in Denmark. It is easy to see these cashiers as luddites, anti-progress and anti-technology, but like the original luddites they had valid concerns about the way that new technologies are used by employers. New technologies can not only lead to jobs lost through automation, but can also change the nature of work itself in detrimental ways.

A new movie that depicts AI making problems for humanity was released this week. While it's certainly not the first such movie--Hollywood has been profiting off of our reservations about AI for decades--this was the first movie to have a trailer created by AI. In keeping with the theme of the film in which a corporate risk management consultant must make the difficult decision of whether or not to kill an artificially intelligent being, IBM decided that they would consult their deep learning machine, Watson, to create the perfect trailer for the film. Machine learning is a branch of artificial intelligence in which machines are programmed to analyze massive amounts of input to search for patterns. To teach Watson to create a trailer for a horror movie, IBM had it "watch" 100 classic horror movies so it could understand what horror is, and what components in a film triggers a fear response in humans.

Natural language generation, a field in artificial intelligence which automatically turns facts and statistics into coherent English and other languages, offers important advantages for finance and accounting, according to Robert Dale, a longtime expert in the technology. Gain a deeper understanding of how your business can benefit from IT and finance working cooperatively towards a unified goal. This email address is already registered. By submitting my Email address I confirm that I have read and accepted the Terms of Use and Declaration of Consent. By submitting your email address, you agree to receive emails regarding relevant topic offers from TechTarget and its partners.

The Times Bayer bets the farm in 66 billion Monsanto deal: An American pioneer of genetically modified seeds has struck a 66 billion takeover deal with Bayer, the German chemicals giant, in the latest round of megadeal consolidations in agricultural production. Lawyers set to pass M&A paperwork to machines: Luminance, a start-up backed by Mike Lynch, the British technology investor, is aiming to reduce the time taken on due diligence that accompanies multimillion-pound M&A deals from weeks to days or even hours using a new form of artificial intelligence. Public sector job numbers plunge to record low: Employment in the public sector has fallen to a record low as private sector jobs surge ahead despite Brexit, official figures have shown. Mortgage lending falls in wake of Brexit vote: The number of mortgages advanced for house purchases fell in the first month after Britain's decision to leave the European Union. Miner in'bribery scandal' intends to quit AIM: An Africa-focused mining company that has been caught up in a bribery scandal is planning to delist its shares.

The techniques Microsoft Research used to achieve a new world-best error rate will eventually enhance the Cortana Windows 10 personal assistant. Microsoft claims to have achieved the world's lowest error rate for speech recognition, as the company jostles with Amazon, Apple, Google, and IBM to develop products that understand speech as well as humans can. According to Microsoft, its speech scientists at Microsoft Research have achieved a word error rate (WER) of just 6.3 percent under an industry-standard evaluation, using techniques that will eventually enhance Cortana. The previous lowest error rate was 6.9 percent, achieved by IBM's Watson team, which beat their own record of eight percent set last year. Both Microsoft and IBM presented papers detailing their work on speech recognition at the Interspeech conference in San Francisco this week, where papers were also presented by Google's speech researchers.

Is your firm prepared to welcome in an era of legal practice using artificial intelligence (AI)? Where is this technology headed and why must law firm leaders fully understand how cognitive computing works in order to benefit from it? With the vast amounts of structured and unstructured data firms have to deal with, there is increasing pressure from nimble technologies and clients to attract AI and cognitive technologies. Understanding the market implications of digital business information and trends is now key to attaining the best possible performance, revenue gains and cost savings. Berwin Leighton Paisner was one of the first firms to embrace AI in the UK, developing its'contract robot' which promised to complete work in seconds that would have otherwise taken a team of paralegals months to do.

Gun lovers now have a dating website dedicated to them. Concealed Carry Match allows its users to meet other members who have similar views on Second Amendment rights. The development is potentially controversial, considering the anti-gun rhetoric that has been doing the rounds following the spate of shootings in the United States in the recent past. Working on a similar platform as other niche dating sites, Traverse City, Michigan-based ConcealedCarryMatch.com offers a paid membership, ranging from 10 weekly to 150 for a year. The site launched last month and reportedly registered opening-day traffic of 10,000 interested visitors, signaling at an increased intensification of the debate on gun control ahead of the presidential election in November.