Artificial intelligence guru Robert Dale explains the benefits and shortcomings of natural language generation technology and advocates for disclosure of use of the software. 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. He is also co-author, with Arria's chief scientist Ehud Reiter, of the textbook, Building Natural Language Generation Systems, first published in 2000 and then again in 2006. We can build pretty sophisticated systems that can produce pretty sophisticated narratives, but we still cannot do that with quite the nuance of a human author.

Artificial intelligence guru Robert Dale explains the benefits and shortcomings of natural language generation technology and advocates for disclosure of use of the software. 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. Since 2012, Dale has been CTO and chief strategy scientist at Arria NLG, based in London, and one of the first companies to offer automatic text generation. He is also co-author, with Arria's chief scientist Ehud Reiter, of the textbook, Building Natural Language Generation Systems, first published in 2000 and then again in 2006. In an interview with SearchFinancialApplications, Dale discussed NLG, its benefits for the office of the CFO and the future of artificial intelligence (AI).

As a longtime health care professional, it is hard to imagine a more exciting time in health care. The innovation and pace of change is breathtaking. Before our eyes, our health care system is being deconstructed. As it is reconstructed, aided by technology, the focus of care is shifting from the provider to the person. We have seen this evolution in the financial services sector, the transportation sector, etc. Technology has finally come to health care.

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.

The Microsoft Band is part of a new project to help with the management of epilepsy. A project using wearable devices and machine learning could help people with epilepsy to monitor their condition better. The initiative, called myCareCentric, combines wearable technologies, shared care records, machine learning, and data analysis tools. It collects information from the wearables, along with smartphones and portals, and integrates it with a patient's clinical record. UK citizens should be able to provide their own data to their personal health records in the next two years.

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.