Imagine a world where plastic materials would never go to waste. Agilyx Corporation ("Agilyx"), the leader in chemical recycling of post-use plastics back into plastics chemicals and low carbon fuels, today announced a dynamic collaboration in artificial intelligence (AI) technology with the General Electric Company through its Licensing business unit that would bring the world closer than ever to making this green dream possible. Combining Agilyx's deep domain experience in chemical recycling with GE's vast experience in the application of Industrial AI, the two companies are aiming to increase the chemical recyclability of all post-use plastics from the current 10% to over 95%. This announcement is the result of a year-long, successful effort to assess GE's advanced modeling technology developed by GE Research, and its applicability to the database of chemical conversions of post-use plastics that Agilyx has amassed over the last 15 years. Together, the companies can greatly improve recycling rates by deploying an innovative set of artificial intelligence ("AI") technologies, including machine learning ("ML"), predictive modeling ("PM") and optimization tools, in combination with other supply chain innovations in partnership with a growing number of diverse leaders in the waste and recycling, petrochemical, consumer goods products and retail industries.

Many a middle school science teacher has dripped a few drops of potassium iodide into hydrogen peroxide and watched the delight of their students as a volcano of foam erupted from the container. This experiment is often the way young people first learn about catalysts as something that that can induce a chemical reaction. But catalysts can make more than foam. As those young people grow into young scientists, they learn that catalysis--the acceleration of a chemical reaction by a catalyst--is a key process in the creation of just about everything. From the plastics that make up our medical equipment, to the gasoline in our cars, to the paint that colors our homes--none of these could exist without catalysts.

The Anglo-Saxon vessel found in the Sutton Hoo burial mound in Suffolk 80 years ago will sail again as experts look to rebuild the ship from digital 3D models. Dated back to the early 7th century, the 90 foot (27 metre) -long vessel is oft dubbed a'ghost ship' thanks to its manner of preservation. In the mound -- thought the resting place of King Rædwald -- only the impression of the ship and its iron rivets remained, the timber having long rotted away. Nevertheless, a team of archaeologists and shipbuilders have succeeded in creating a three-dimensional digital mock-up of the vessel to allow it to be reconstructed. Expert hope that recreating a full-size, fully-operational version of the ship will help shine light on how the Anglo-Saxons began England's tradition of seafaring.

Farmers may soon have an alternative to spraying their fields with chemicals, as Small Robot Company and RootWave, two UK-based agritech startups, today announced a partnership to develop a high-precision robot that can kill weeds with a zap of electricity. Small Robot has already developed a series of small, agricultural robots, called Tom, Dick and Harry, which can automate some of the routine tasks of farming. Tom, a scouting robot similar to the Mars Rover, for example, uses computer vision to map the weeds in a field, covering about 20 hectares a day. Dick, a weeding robot, can already remove unwanted plants with either a micro-dose of pesticide or by physically crushing them, but the next stage will be to combine this with technology from RootWave, which destroys weeds by with an electric current, essentially boiling them from the inside out. "Farmers are really desperate for an alternative to the chemical control of weeds," says Sam Watson Jones, the chief executive of Small Robot Company.

I'm trying to explain to Arthur I. Miller why artworks generated by computers don't quite do it for me. The works aren't a portal into another person's mind, where you can wander in a warren of intention, emotion, and perception, feeling life being shaped into form. What's more, it often seems, people just ain't no good, so it's transcendent to be reminded they can be. Art is one of the few human creations that can do that. No matter how engaging the songs or poems that a computer generates may be, they ultimately feel empty. They lack the electricity of the human body, the hum of human consciousness, the connection with another person.

On a warm day in April 2013, I was sitting in a friend's kitchen in Paris, trying to engineer serendipity. I was trying to get my computer to write music on its own. I wanted to be able to turn it on and have it spit out not just any goofy little algorithmic tune but beautiful, compelling, mysterious music; something I'd be proud to have written myself. The kitchen window was open, and as I listened to the sounds of children playing in the courtyard below, I thought about how the melodies of their voices made serendipitous counterpoint with the songs of nearby birds and the intermittent drone of traffic on the rue d'Alésia. In response to these daydreams, I was making a few tweaks to my software--a chaotic, seat-of-the-pants affair that betrayed my intuitive, self-taught approach to programming--when I saw that Bill Seaman had just uploaded a new batch of audio files to our shared Dropbox folder. I had been collaborating with Bill, a media artist, on various aspects of computational creativity over the past few years. I loaded Bill's folder of sound files along with some of my own into the software and set it rolling. I was thrilled and astonished.

Ross Goodwin has had an extraordinary career. After playing about with computers as a child, he studied economics, then became a speech writer for President Obama, writing presidential proclamations, then took a variety of freelance writing jobs. One of these involved churning out business letters--he calls it freelance ghostwriting. The letters were all pretty much the same, so he figured out an algorithm that would generate form letters, using a few samples as a database. The algorithm jumbled up paragraphs and lines following certain templates, then reassembled them to produce business letters, similar but each varying in style, saving him the job of starting anew each time. He thought he was on to something new but soon found out that this was a well-explored area.

Just behind us, a giant industrial magnet powered up with warning signs dotted about its perimeter so we wouldn't scramble our phones. Before long, John Durrell, a specialist in superconductor engineering (who took apart more machines as a teenager than he can remember), arrived with a set of tools in his hands and a glint in his eye.

Robots, we are told, are going to take over the world, taking away most jobs as we know them. And yes, it is true that automation will make some jobs disappear. AI is also now intelligent enough that we will probably see a greater range of jobs change than we have ever seen before. This is likely to include some professional jobs that have always been "safe" from automation in the past. We are already seeing the beginning of this with online financial advice, translators, drivers, etc. However, the reality is that the job market is constantly changing.

The steel industry has great impacts on the economy and the environment of both developed and underdeveloped countries. The importance of this industry and these impacts have led many researchers to investigate the relationship between a country's steel consumption and its economic activity resulting in the so-called intensity of use model. This paper investigates the validity of the intensity of use model for the case of Iran's steel consumption and extends this hypothesis by using the indexes of economic activity to model the steel consumption. We use the proposed model to train support vector machines and predict the future values for Iran's steel consumption. The paper provides detailed correlation tests for the factors used in the model to check for their relationships with the steel consumption. The results indicate that Iran's steel consumption is strongly correlated with its economic activity following the same pattern as the economy has been in the last four decades.