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#artificialintelligence

Artificial intelligence is an oxymoron (Technology quarterly, June 13th).


Does the Human Touch + AI = The Future of Work?

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AI and machine learning have infiltrated almost every industry and impacted businesses in many positive ways, but my belief is that machines will never …


Artificial neural networks are more similar to the brain than they get credit for

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This article is part of our reviews of AI research papers, a series of posts that explore the latest findings in artificial intelligence. Consider the animal in the following image. If you recognize it, a quick series of neuron activations in your brain will link its image to its name and other information you know about it (habitat, size, diet, lifespan, etc…). But if like me, you've never seen this animal before, your mind is now racing through your repertoire of animal species, comparing tails, ears, paws, noses, snouts, and everything else to determine which bucket this odd creature belongs to. Your biological neural network is reprocessing your past experience to deal with a novel situation. Our brains, honed through millions of years of evolution, are very efficient processing machines, sorting out the ton of information we receive through our sensory inputs, associating known items with their respective categories.


Recyclers turn to AI robots after waste import bans

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When China restricted the importation of recyclable waste products in 2018, many western companies turned to robotic technologies to strengthen their processing capabilities. "The ban exposed how vulnerable the current infrastructure for recycling is," says Chris Wirth, vice-president of marketing and business development for AMP Robotics, a Denver-based industrial recycling artificial intelligence company. To recycle in a cost-effective, comprehensive and safe way, goods must be broken down into their constituent commodities to be sold on, in a process that has been likened to "unscrambling an egg". Roboticists think that computer vision, neural networks and modular robotics can enable a more intelligent, flexible approach to recycling. AI-enabled robotics can identify items based on visual cues such as logos, colour, shape and texture, sorting them and taking them apart.


Top 11 Machine Learning Frameworks You Need to Know! - Simpliv Blog

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With changing technology landscape, software Engineering has come a long way, thanks to the evolving intelligent systems. Machine Learning and Deep Learning Technologies have created avenues to execute tasks efficiently and more intelligently. In this entire transformations, Machine learning and Deep Learning frameworks have played a huge role allowing innovation to take the centre stage. So much is said about Machine Learning and the multifaceted benefits it offers. But it is actually difficult to comprehend the advantages unless the fundamentals are laid out clearly.


Smarter Chatbots and Virtual Agents for your Contact Center VoiceFoundry

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Conversational AI, Virtual Assistance and the use of Bots are on the rise today. The terminology can be confusing and so it is important to understand the differences in order to determine what is best for your customers. Understanding how customers interact with your business and their preferences for engagement are a must. Businesses are looking for ways to deliver a better conversational approach to meets their customer's needs in this day of fast-paced communication and right-now resolution. Many businesses are increasingly looking to incorporate sophisticated bot communications, which is why VoiceFoundry offers a full suite of services that leverage the power of Amazon solutions like Amazon Connect, Lex, Polly and more in order to deliver a complete experience.


Mihnea Birisan Joins Steampunk to Lead Its Data Exploitation Capability Practice

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Mihnea's professional expertise lies in machine learning, data mining, and data optimization. Prior to joining Steampunk, he spent 4 years as the Analytics and Modeling Senior Manager at Accenture Federal, responsible for leading data science and engineering teams across multiple DHS accounts and projects. Prior to Accenture Federal, Mihnea worked for Agilex Technologies as a Technical Manager where he led a team of highly-trained quantitative modelers creating, evaluating, and deploying statistical models in support of client missions. Data strategy, architecture, big data, data security, data processing, machine learning and artificial intelligence are just a few of the technology areas the practice will cover. Mihnea's analytical passion started early when he attended the Thomas Jefferson High School for Science and Technology.


Deep Learning: Big Data Intelligence

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Big Data Intelligence: A machine learning approach inspired by the human brain, Deep Learning is taking many industries by storm. Empowered by the latest generation of commodity computing, Deep Learning begins to derive significant value from Big Data. It has already radically improved the computer's ability to recognize speech and identify objects in images, two fundamental hallmarks of human intelligence.


A neural network generated a bunch of mutated-looking new animals

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You probably remember the neural network that generates photos of people who don't actually exist. You might even remember the one that spits out photos of nonexistent cats, or the one that whips up fake résumés, or the one that dreams up listings for imaginary rental properties. Now, a programmer named Aldo Cortesi has created an even stranger algorithm -- one that draws silhouettes for nonexistent animals, some of which look plausible and others which look like nothing you've ever seen before. In a post about the project, Cortesi wrote that he was indeed inspired by algorithms that generate human likenesses. "Looking at these images, it seems like the neural net would have to learn a vast number of things to be able to do what these networks were doing. Some of this seems relatively simple and factual -- say, that eye colours should match," he wrote.


NAIC's Artificial Intelligence Working Group Adopts Principles for AI

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On June 30, the National Association of Insurance Commissioners' (NAIC) Artificial Intelligence Working Group approved principles that call on insurers and others using artificial intelligence (AI) to take proactive steps to avoid proxy discrimination against protected classes. In the run-up to the vote, Commissioner Jon Godfread (Chair – ND) delivered a passionate statement indicating that the nation's insurance regulators are committed to addressing discriminatory practices while preserving the industry's ability to engage in appropriate underwriting. After extensive discussion, 15 of the states participating in the call voted in favor of the principles, and one abstained. The AI principles will be considered by the NAIC's Innovation and Technology Task Force on July 23 and, if approved, by the full NAIC membership during the virtual summer national meeting. While the principles will not have the effect of law, they are expected to serve as a road map for future regulatory workstreams.