AntWorks, a global provider of artificial intelligence and intelligent automation solutions powered by fractal science, today announced an exclusive partnership with the SEED Group, a member of The Private Office of Sheikh Saeed bin Ahmed Al Maktoum. The partnership will support expansion of intelligent automation within the Middle East (ME), a region where AI is expected to become a US$320 billion by 2030. The SEED Group establishes groundbreaking companies with a strong presence in the Gulf Cooperation Council (GCC) and will work with AntWorks to offer ethical AI solutions for GCC companies with ANTsteinTM SQUARE, the world's first and only Integrated Automation Platform (IAP), powered by fractal science. AntWorks seek to replicate its success across Asia, the UK and US, where the organisation has automated entire business processes end-to-end for many clients across the BFSI (Banking, Financial Services and Insurance), transportation, logistics and public sector, among others. With successful adoption of AntWorks' IAP solution, businesses will stand to save millions and realise increased performance and efficiency by automating and processing business data, including unstructured data, which will make up 80% of the world's data by 2025.

In the past few years, deep learning has transformed artificial intelligence research and led to impressive performance in various difficult tasks. However, it is still unclear how the brain can perform credit assignment across many areas as efficiently as backpropagation does in deep neural networks. In this paper, we introduce a model that relies on a new role for a neuronal inhibitory machinery, referred to as ghost units. By cancelling the feedback coming from the upper layer when no target signal is provided to the top layer, the ghost units enables the network to backpropagate errors and do efficient credit assignment in deep structures. While considering one-compartment neurons and requiring very few biological assumptions, it is able to approximate the error gradient and achieve good performance on classification tasks. Error backpropagation occurs through the recurrent dynamics of the network and thanks to biologically plausible local learning rules. In particular, it does not require separate feedforward and feedback circuits. Different mechanisms for cancelling the feedback were studied, ranging from complete duplication of the connectivity by long term processes to online replication of the feedback activity. This reduced system combines the essential elements to have a working biologically abstracted analogue of backpropagation with a simple formulation and proofs of the associated results. Therefore, this model is a step towards understanding how learning and memory are implemented in cortical multilayer structures, but it also raises interesting perspectives for neuromorphic hardware.

NEW YORK: Two paintings up for auction in New York highlight a growing interest in artificial intelligence-created works - a technique that could transform how art is made and viewed but is also stirring up passionate debate. The art world was stunned last year when an AI painting sold for $432,500, and auctioneers are keen to further test demand for computer-generated works. "Art is a true reflection of what our society, what our environment responds to," said Max Moore of Sotheby's. "And so it's just a natural continuation of the progression of art," he added. Sotheby's will put two paintings by the French art collective Obvious up for sale on Thursday, including'Le Baron De Belamy'.

Climate change has emerged as the biggest threat to humanity, with devastating consequences such as extreme weather events, climate migration, and a sharp decline in biodiversity. While the brunt of climate action is shouldered by green parties and public activists like the young Greta Thunberg, in recent years many industries have stepped up innovation to try and do their bit. The informatics industry in particular has been flexing its R&D muscle to propose bleeding-edge solutions. A recent paper published by a group of high-profile AI experts and IT professionals explores the potential that can be found "at the nexus of climate change and machine learning". Headed by David Rolnick, a Postdoctoral Research Fellow at the University of Pennsylvania, the paper puts a spotlight on "high-impact opportunities for real-world change" present in such ML fields as artificial intelligence, computer vision, unsupervised learning, and more.

Climate change has emerged as the biggest threat to humanity, with devastating consequences such as extreme weather events, climate migration, and a sharp decline in biodiversity. While the brunt of climate action is shouldered by green parties and public activists like the young Greta Thunberg, in recent years many industries have stepped up innovation to try and do their bit. The informatics industry in particular has been flexing its R&D muscle to propose bleeding-edge solutions. A recent paper published by a group of high-profile AI experts and IT professionals explores the potential that can be found "at the nexus of climate change and machine learning". Headed by David Rolnick, a Postdoctoral Research Fellow at the University of Pennsylvania, the paper puts a spotlight on "high-impact opportunities for real-world change" present in such ML fields as artificial intelligence, computer vision, unsupervised learning, and more.

In any normal year, Cambridge Analytica would have been the biggest story. Facebook alone had a royal flush of scandals, including a huge data breach in September, becoming the subject of multiple class action lawsuits for discrimination, accusations of inciting ethnic cleansing in Myanmar, potential violations of the Fair Housing Act, and hosting masses of fake Russian accounts. Throughout the year, Facebook executives were frequently summoned to testify, with Mark Zuckerberg himself facing the US Senate in April and the European Parliament in May. News broke in March that Google was building AI systems for the Department of Defense's drone surveillance program, Project Maven. The news kicked off an unprecedented wave of tech worker organizing and dissent.

Artificial intelligence (AI) is a megatrend that the industry will continue to talk about for the next 20 years. So said Brian Burke, chief of research at Gartner, who presented the top 10 strategic technology trends for 2019 on day three of the Gartner Symposium/ITxpo in Cape Town this morning. Burke said technology is continuing to advance. It is these advancements that underpin Gartner's "Continuous Next" operating philosophy. "AI is going to underlie pretty much everything that we do in technology." Every year, Gartner puts together a list of what it considers to be the most impactful technology trends for organisations.

In the age of digital transformation, global insurance provider AXA has adopted a decentralised approach to innovation. AXA International and New Markets (AXA INM) takes charge of AXA's operations in emerging and developing markets, covering Eastern European territories, Latin America, the GCC (Gulf Cooperation Council), Africa, India, Singapore, Malaysia and more. "There's a significant amount of Transformation to deliver across the 20-25 entities," says Kuldeep Kaushik, Chief Operating and Transformation Officer at AXA INM. "We have very different maturity levels across the businesses and very different technology landscapes as well. Part of my role is evaluating each of those entities and defining programmes which are specific to their maturity, business strategy, and needs and capabilities."

Machine learning is hard but moving your ML model to your embedded device can be even harder. Here, we'll discuss a few pain points in this process, and some up-front Addressing these issues early in the design process is key to getting your new gadget out the door. Most likely you will develop and train your machine-learning models using one of the big four (Google, Amazon, Microsoft, IBM) service stacks, one of the many MLaaS platforms (C3, BigML, WandB, Databricks, Algorithmia, OpenML, Paperspace, PredictionIO, DeepAI, DataRobot, etc.), or you'll roll your own using some variant of Anaconda/Jupyter and ML frameworks such as Keras, TensorFlow, PyTorch, Caffe, MXNet, Theano, CNTK, Chainer, or Scikit-Learn. How do you get from this set of tools, code and data using many different formats, sources, licenses and execution environments into something that you can execute entirely inside some little box--one that may (or may not) be connected to the internet ever again? The initial code for your model will be written in Python, R, MATLAB, Lua, Java, Scala, C, or C .

With successful adoption of AntWorks' IAP solution, businesses will stand to save millions and realise increased performance and efficiency by automating and processing business data, including unstructured data, which will make up 80% of the world's data by 2025. The partnership will help the GCC become a blueprint for the AI economy in the rest of the Middle East, Turkey and Africa, especially as governments look to diversify and drive revenue from non-oil and gas sectors. "We are deeply honored to partner with The Private Office of Sheikh Saeed bin Ahmed Al Maktoum and SEED Group expanding our reach into the Middle East," said Asheesh Mehra, AntWorks Co-Founder and Group CEO. "We see our partnership with SEED Group as an incredible opportunity to bring AntWorks' leading expertise in artificial intelligence to the GCC - helping the UAE's Ministry of AI realise its 2031 Artificial Intelligence Strategy. This is a market that thrives on innovation and has taken some of the most ambitious steps in the world in adopting the use of AI across government and business as they seek to create new economic, social, and educational opportunities for citizens. We look forward to a powerful and productive relationship that will make straight-through processing a reality across the GCC."