Collaborating Authors


Markov Chain


Markov chains are used to model probabilities using information that can be encoded in the current state. Each state has a certain probability of transitioning to each other state, so each time you are in a state and want to transition, a markov chain can predict outcomes based on pre-existing probability data. More technically, information is put into a matrix and a vector - also called a column matrix - and with many iterations, a collection of probability vectors makes up Markov chains. To determine the transition probabilities, you have to "train" your Markov Chain on some input corpus.

Can humans and AI work side by side? A guide to what comes next


In August, Elon Musk announced that he was developing a humanoid robot called "Tesla Bot" -- a prototype of which will supposedly be ready in 2022. The presentation itself was slightly bizarre, both because the bot was represented on stage by a dancing human in a bodysuit, and because Musk has warned for years about the dangers of artificial intelligence. But he was right about one thing: AI and robotics could eventually lead to a future where technology is so advanced that our role, much of our work and even our purpose in life could fundamentally change. As someone who has studied and worked in AI for the better part of four decades, my contention is that this change will likely come faster and go further than many of us anticipate -- even if it's driven more by AI-powered software than dancing robots. The question is how we're going to prepare.

Artificial intelligence in support of the circular economy: ethical considerations and a path forward


The world's current model for economic development is unsustainable. It encourages high levels of resource extraction, consumption, and waste that undermine positive environmental outcomes. Transitioning to a circular economy (CE) model of development has been proposed as a sustainable alternative. Artificial Intelligence (AI) is a crucial enabler for CE. It can aid in designing robust and sustainable products, facilitate new circular business models, and support the wider infrastructures needed to scale circularity.

Engaging with Disengagement


Disengagement is a situation when the vehicle returns to manual control or the driver feels the need to take back the wheel from the AV decision system. I came across this news article a while ago about a man dozing off at the wheel after switching his Tesla to autonomous mode, and being criminally charged soon after because the vehicle was speeding unbeknownst to him. A quick search revealed several such reports on drivers being charged for unlawful practices in semi-autonomous vehicles. This got me thinking: how will traffic laws change as we slowly enter the autonomous vehicle era, and in general, the AI-driven 21st century? Most importantly, this brings up the question of whom to blame when dealing with adverse human-robot interactions. These aren't new questions – only questions to which new perspectives can continually be added until a final course of action is decided. While I actively try to avoid the philosophical and ethical underpinnings of the matter, I will cover the current progress in autonomous vehicle technology, trends and limitations of today's autonomous vehicle policy, and possible directions to better facilitate the transition to autonomous vehicles around the globe. The last decade or so has been a very exciting time in the self-driving vehicle space.

No Ops like 'NoOps' revisited: is the vision a reality yet?


Joe McKendrick is an author and independent analyst who tracks the impact of information technology on management and markets. As an independent analyst, he has authored numerous research reports in partnership with Forbes Insights, IDC, and Unisphere Research, a division of Information Today, Inc. Author's note: Can IT be 99% automated? We've seen the growth of serverless computing and a range of "Ops" approaches to automating software and data pipelines. This is an update to a piece originally published in February 2019, but poses questions that are still being pondered. In a recent AWS customer case study, SGK Inc. -- a provider of packaging and ecommerce solutions -- reports that reduced its IT operating costs using 83% with NoOps and serverless microservices.

There's Now an Algorithm to Help Workers Avoid Losing Their Jobs to an Algorithm


As AI and robotics continue to advance, there are concerns that machines could soon replace humans in a wide range of occupations. Now there's a new way to tell how likely your job is to be taken over by robots or AI, and what job to shift to if you are at risk. Industrial robots have been a fixture on manufacturing lines for decades, but they have generally been dumb and dangerous, incapable of operating outside of highly controlled environments and liable to injure human workers unless safely caged. Advances in AI are starting to change that though, with more nimble and aware robots starting to move from factories and warehouses into storefronts and restaurants. Social distancing requirements due to the Covid-19 pandemic have only accelerated this trend, fueling anxiety that an increasing number of human workers may end up getting displaced by robots.

What is the future of digital art?


What exactly is digital art? This and other queries will be answered in this article. Introduction: Digital Art is a transition from traditional media such as painting on canvas or on paper to creating an image, photo, etc., digitally using a computer monitor. While traditional art is a creative process, digital art is a technology that can be easily manipulated and modified by anyone to create artwork. Digital art can be superimposed on top of traditional artwork in many different ways to make the combination more interesting.

Cities Take the Lead in Setting Rules Around How AI Is Used


Cities are looking at a number of solutions to these problems. Some require disclosure when an AI model is used in decisions, while others mandate audits of algorithms, track where AI causes harm or seek public input before putting new AI systems in place. What would you like to see cities do to make their use of AI more transparent and fair? It will take time for cities and local bureaucracies to build expertise in these areas and figure out how to craft the best regulations, says Joanna Bryson, a professor of ethics and technology at the Hertie School in Berlin. But such efforts could provide a model for other cities, and even nations that are trying to craft standards of their own, she says.

MLops: The Key to Pushing AI into the Mainstream


We are excited to bring Transform 2022 back in-person July 19 and virtually July 20 - 28. Join AI and data leaders for insightful talks and exciting networking opportunities. One of the main roadblocks preventing the enterprise from putting artificial intelligence (AI) into action is the transition from development and training to production environments. To gain real benefits from the technology, this must be done at the speed and scale of today's business environment, which few organizations are capable of doing. This is why the interest in merging AI with devops is gaining steam. Forward-leaning enterprises are trying to blend machine learning (ML) in particular with the traditional devops model, which creates an MLops process that streamlines and automates the way intelligent applications are developed and deployed and then updated on a continual basis to increase the value of its operations over time.

Can we apply creator economy concept to technology with AI and Data?


This article is sponsored by IBM. It is a new concept in which creators can apply passion and creativity to make money, instead of simply relying on likes and views. It focuses on bringing more life and meaning to the traditional media landscape in a way that empowers creative people worldwide to bring out the best in themselves, entirely driven by their passion. According to EMarketer, the creator economy is defined as follow: "We define creators as people or entities that develop original content for digital properties, and who consider creating that content to be either their full-time or parti-time career or livelihood. Of course, there is some overlap between many of these groups; for instance, celebrities can also be creators and vice versa. What's more, few successful influencers today are purely sales-oriented, and many of them are also creators, developing digital or, at times, physical products."