Global banks that have a large mortgage business are facing pressure internally and externally to upgrade their operating model to save money, decrease processing times and enhance the customer experience – today it can take more than 60 days to complete a mortgage transaction. The pressure is particularly strong with FinTechs like US online lender Rocket Mortgage and UK digital mortgage broker Trussle creating a completely digital experience for prospective home buyers. Banks, therefore, are exploring everything from mature technologies like Optical Character Recognition (OCR) to more leading edge and high-tech solutions based on blockchain and artificial intelligence. While some of these solutions could dramatically impact day-to-day business for lenders and their brokers and customers, blockchain has the potential to completely transform the entire mortgage financing industry. The financial services industry is all about trust – whether relationship based, reputational, authoritative (legal) or transactional – banking today is built on trust.

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Chinese tech giant Baidu's text-to-speech system, Deep Voice, is making a lot of progress toward sounding more human. The latest news about the tech are audio samples showcasing its ability to accurately portray differences in regional accents. The company says that the new version, aptly named Deep Voice 2, has been able to "learn from hundreds of unique voices from less than a half an hour of data per speaker, while achieving high audio quality." That's compared to the 20 hours hours of training it took to get similar results from the previous iteration, for a single voice, further pushing its efficiency past Google's WaveNet in a few months time. Baidu says that unlike previous text-to-speech systems, Deep Voice 2 finds shared qualities between the training voices entirely on its own, and without any previous guidance.

TL;DR Baidu's TTS system now supports multi-speaker conditioning, and can learn new speakers with very little data (a la LyreBird). I'm really excited about the recent influx of neural-net TTS systems, but all of the them seem to be too slow for real time dialog, or not publicly available, or both. Hoping that one of them gets a high quality open-source implementation soon!

Next time you hear a voice generated by Baidu's Deep Voice 2, you might not be able to tell whether it's human. Baidu, the Beijing-based juggernaut that commands 80 percent of the Chinese internet search market, is investing heavily in artificial intelligence. In 2013, it opened the Institute of Deep Learning, an R&D center focused on machine learning. And in May, it took the wraps off the newest version of Deep Voice, its AI-powered text-to-speech engine. Deep Voice 2, which follows on the heels of Deep Voice's public debut earlier this year, can produce real-time speech that's nearly indistinguishable from a human voice.

A version of this post originally appeared on Tedium, a twice-weekly newsletter that hunts for the end of the long tail. We live in a world where facial recognition has become so sophisticated that we're being forced to ask very serious ethical questions about it. In China, it's being used to detect toilet paper theft. But I want to take a step back from the big hairy ethical questions and consider how we started on this road--with typography. Optical character recognition, or OCR, is a technology that came up with computing in general.

The bar for what counts as artificial intelligence is continually rising. Technologies should lose their AI status when they become routine (optical character recognition is no longer recognized as an example of AI for this reason). However, for marketers it's tempting to go in the opposite direction and rebrand all kinds of routine technologies as AI in order to make them sound more exciting and newsworthy. AI was a key theme at this year's Mobile World Congress. One AI-themed announcement was "aia", from telecoms IT giant Amdocs, which claims to enable the "self-driving telco".

In this survey, we conduct an investigation on the robustness of several features and classifiers in automatic authorship attribution. Our corpus consists in 25 different documents written by 5 different American philosophers in English. The different documents pass throw a digital conversion into grey-scaled images and several levels of noise are added to corrupt those image documents. The noise consists in a “Salt & Pepper” type, which is randomly added on the surface of the images with the following noise levels: 0%, 1%, 2%, 3%, 4%, 5%, 6% and 7%. Thus, each image goes throw an OCR program (Optical Character Recognition) to extract the text from the image. Then, the obtained text document is kept to be used during the experiments of authorship attribution. Several features and classifiers are employed and evaluated with regards to the classification performances. Results are quite interesting and show that the most robust feature in au-thorship attribution is the character-tetragram, which provides a score of 100% even at a noise level of 7%.

Palo Alto – April 26, 2017: Infosys (NYSE: INFY), a global leader in consulting, technology, outsourcing and next-generation services, today announced the launch of Infosys Nia, the next-generation Artificial Intelligence Platform building on the success of the Company's first-generation AI platform, Infosys Mana, and its Robotic Process Automation (RPA) solution, AssistEdge. Together, both these products have amassed 50 clients and 150 engagements across all industry sectors, within a year of operations. Infosys Nia converges the big data/analytics, machine learning, knowledge management, and cognitive automation capabilities of Mana; end-to-end RPA capabilities of AssistEdge; advanced, high-performance and scalable machine learning capabilities of Skytree; and optical character recognition (OCR), natural language processing (NLP) capabilities and infrastructure management services. As a unified, flexible, and modular platform, Infosys Nia enables a wide set of industry and function-specific solutions and allows customers to build custom experiences to suit their business needs. Infosys' first-generation AI platform was about IT, simplification, efficiency and cost.

IT services provider Infosys on Thursday announced the launch of Infosys Nia, the next-generation Artificial Intelligence (AI) platform building on the success of the Company's first-generation AI platform, Infosys Mana, and its Robotic Process Automation (RPA) solution, AssistEdge. The new platform converges the big data/analytics, machine learning, knowledge management, and cognitive automation capabilities of Mana; end-to-end RPA capabilities of AssistEdge; advanced, high-performance and scalable machine learning capabilities of Skytree; and optical character recognition (OCR), natural language processing (NLP) capabilities and infrastructure management services. "We have seen tremendous adoption, and indeed, a massive embrace of Mana by our clients, particularly in leveraging Mana to improve service delivery and drive efficiencies and cost performance through automation. But we could clearly see that there was much more potential, an unlimited potential, in bringing AI to our clients' most sophisticated and complex business problems, as they work toward a vision of bringing technology to every aspect of their businesses," said Dr. Vishal Sikka, Chief Executive Officer, Infosys. "Nia, the next generation of our AI platform now takes our purposeful approach to AI, one in which technology serves to amplify people and empowers them to work in new ways, to new heights. When we bring this together with our unmatched ability to educate and train in AI techniques and emerging technologies, we now have the platform, the services and the skills, to deliver new unprecedented value to our clients," he added.