Intelligent Machines and the Future of Recruitment is the conference, organised by Textkernel in honour of its 15th anniversary, that explores the impact of rapidly evolving machine intelligence on the future of people and jobs. Among the speakers are Glen Cathey (Kforce), Behshad Behzadi(Google), Federico Pistono (author), Maarten de Rijke (University of Amsterdam),Martin le Vrang (ESCO), Perry Timms (Media Zoo), Ton Sluiter (USG People),Balazs Paroczay (Randstad Sourceright) and Prof. Dr. Armin Trost (Furtwangen University). "The rise of machine learning, search engines, semantic technologies and the large amounts of available information are changing the labour market," says Jakub Zavrel, CEO of Textkernel. "When I started the company 15 years ago, the use of AI in recruiting was still in its infancy. Companies like us have been making AI and semantic search technology part of the mainstream. What better way to celebrate Textkernel's anniversary than to organise a conference to spark the discussion on how artificial intelligence will evolve and change the way we hire and work."

The future of food looks a lot like advanced animal product substitutes; we've already gone beyond tofurkey to plant-based burgers that "bleed." Down in Santiago, Chile, a five-person startup is using machine learning to figure out how to create its own versions of vegetarian substitutes for animal products. Called the Not Company (or NotCo), the one-year-old company is rolling out its first products -- NotMilk, NotMayo. "All I can tell you is that there are some star ingredients ranging from legumes to flowers," NotCo cofounder Matias Muchnick tells Tech Insider. Machine learning, the programming technique where algorithms learn from data sets, has become the hot new thing in Silicon Valley.

CommerzVentures, the fintech venture capital fund of Commerzbank, has released a white paper highlighting the key technologies which it believes will transform the insurance industry. Aimed at providing insights into their potential uses in the insurance sector, CommerzVentures' 'Emerging Technologies Transforming the 4tn Insurance Industry' paper explores how the insurance chain value will be transformed by technological innovations. Innovations such as artificial intelligence, connected devices, drones, blockchain tech, among others, are enabling new value propositions and distribution methods, the firm says. Effectively cooperating with startups may be the only way for incumbent insurers to fend off potential competitors such as Google, Amazon, Facebook and other non-traditional players, it argues. Generating over US 4 billion in global revenue, insurance is one of the two major sectors within fintech and the largest long-term opportunity, and yet insurtech companies have received 12 times less funding than bankingtech.

Persado is a computerized system that writes natural language to obtain direct marketing goals: to consistently inspire action in any given audience. Our automated machine-learning platform tests millions of words, phrases, and images; collects data; and understands, at scale, consumer reactions to targeted language in calls to action. The engine of the commercial internet is propelled by short, digital marketing messages. Persado is its first qualified driver.

They tell a story, which gives the photos context and additional emotional meaning. A paper published by Microsoft Research describes an image captioning system that mimics humans' unique style of visual storytelling. Companies like Microsoft, Google, and Facebook have spent years teaching computers to label the contents of images, but this new research takes it a step further by teaching a neural-network-based system to infer a story from several images. Someday it could be used to automatically generate descriptions for sets of images, or to bring humanlike language to other applications for artificial intelligence. "Rather than giving bland or vanilla descriptions of what's happening in the images, we put those into a larger narrative context," says Frank Ferraro, a Johns Hopkins University PhD student who coauthored the paper.

Andrew Moore was a professor of computer science and robotics at Carnegie Mellon University for a dozen years when Google hired him away in 2006 to lead some of its efforts around ad targeting and fraud prevention. CMU lured Moore back in 2014, making him the dean of its computer science school. But he still understands well what goes through his colleagues' minds when industry comes calling, and he says the battle to keep them in academia grows fiercer by the year. Earlier today, we talked with Moore about Uber, which famously raided the school's robotics department a year ago, poaching 40 of its researchers and scientists. We also talked about how Moore entices people to stay, and the newest new thing his 2,000-student school is focused on right now.

I recently read an article on robotics by a fellow intern. He cited an example of a flying bird robot developed by Festo Industries' Bionic Learning Network. It is an autonomous ornithopter. While this is certainly an impressive achievement, because they have deciphered the flight of birds, something even more interesting has been going on in the field of machine learning. What is difficult is making them learn how to do things on their own and improve their performance independently.

IBM is expanding its flash storage lineup to power cloud data centers that carry out so-called cognitive computing. The company's newest FlashSystem arrays, introduced Wednesday, combine its fast and relatively affordable FlashCore technology with a scale-out architecture designed to be easy to expand. Cognitive computing, which IBM defines as real-time data analysis for immediate, automated decision-making, is at the heart of much of IBM's current technology push for enterprises and service providers. Its Watson technology is the star of the show but only the most visible part of what the company is doing in this space. An example of cognitive computing is a mobile operator analyzing information about phone call quality to make decisions on the fly about changes in the network, said Andy Walls, an IBM Fellow and CTO for flash systems. Large-scale, real-time computing needs flash, IDC analyst Eric Burgener said.

Machine learning is in the midst a renaissance. Technical advancements in machine learning are enabling a broad assortment of new possibilities for designers to better engage with and understand users. Yet, these technologies also bring new challenges and require new ways of thinking about the design of user interfaces and interactions. Using intuitive analogies and tangible examples, Patrick Hebron offers an introduction to contemporary machine-learning systems and explores how these emerging capabilities will transform the next generation of computing interfaces, such as search engines, intelligent assistants, connected homes, and open-world video games. This webcast is intended for user interface and user experience designers as well as anyone interested in how recent advancements in machine learning can radically enhance software capabilities through natural language processing, image recognition, content personalization, and behavior prediction.

Three weeks ago we reported an amusing anecdote out of China in which robot waiters in a Guangzhou restaurant had been "fired" because whencustomers flocked to the Heweilai Restaurant chain in the southern Chinese city, they found they were not all they are cracked up to be. "A staff member said the robots couldn't effectively handle soup dishes, often malfunctioned, and had to follow a fixed route that sometimes resulted in clashes. A customer also said the robots were unable to do tasks such as topping up water or placing a dish on the table." "The robots weren't able to carry soup or other food steady and they would frequently break down. The boss has decided never to use them again," said one employee. We joked in the summary saying that "for now, it appears, China's minimum wage workers, and it has a few hundred million of those, will not be phased out just yet." According to a report released by the MIT Technology Review, where some saw failure in China's "novelty" worker robots, the Chinese government saw nothing less than the opportunity to perfect what will soon put million of Chinese workers out of a job: an army of worker robots. Because while there is certanly humor to be found in the anecdote about a robot "termination", the Chinese government is keen to change this.