In less than a year, the American grocery store has gone from an age-old, in-person shopping institution to a destination at the forefront of a technological transformation. Grocery giant Kroger, for instance, covered 98 percent of households in its delivery areas in 2020 by investing in a large digital and delivery presence. Furthermore, according to a recent global study, over 50 percent of respondents are not planning to re-integrate in-store shopping into their routine for "a long time"--underlining the need for innovative solutions. As the world traverses a slow path to recovery amid COVID-19, how we purchase food and staple goods may never look quite the same, thanks to new technologies and consumer habits. Though automats and self-service technologies have existed since the 1930s, the first proper self-checkout platform was introduced in 1992 by Dr.

Data science is one of the most buzzed about fields right now, and data scientists are in extreme demand. And with good reason -- data scientists are doing everything from creating self-driving cars to automatically captioning images. Given all the interesting applications, it makes sense that data science is a very sought-after career. Data science is applied in many field, including in developing self-driving cars. If you're reading this post, I'm assuming that you'd like to learn how to become a data scientist.

We have recently shared introductory courses from Amazon's recently-launched Machine Learning University initiative, courses focusing on both computer vision (CV) and natural language processing (NLP). These courses assume no previous knowledge of the topics, and are based on short video lectures and corresponding Python notebooks. But what if you are not interested in the specialized paths of either CV or NLP? What if you would like to gain an understanding of applying machine learning to more traditional datasets? If this remark resembles you, Accelerated Tabular Data from Amazon's Machine Learning University might be a good place to start.

TV has reached its maximum capacity of quirky afterlifes. The Good Place set this recent wave in motion on NBC with its vision of Hell as a metaphysical bureaucracy plastering a cheery expression over its endless labyrinth of paperwork and intra-departmental conflicts. TBS's Miracle Workers cranked the whimsy up a notch for the romcom angle, as two low-level angels invisibly nudged a pair of shy mortals together. Amazon's Forever went the existential route, confronting a married couple stuck in a rut with the horror of continuing all their daily drudgeries after death in a suburb identical to their own. In each case, the series generated comedy by offering a banal solution to the grand mystery of what happens after we shuffle off this mortal coil.

You don't need to be a rocket scientist to understand AI and its impact, but you should develop foundational knowledge about AI in order to help you vet new opportunities. To get started, check out this glossary to find simple definitions of common AI terms. When it's time to start thinking about AI-based projects, you can use use-cases to see what's already been done with the technology. To find the right use cases, you'll need to evaluate all the tasks you do in a day, then assess which ones are valuable to automate with AI. There are plenty of AI technologies you can start getting your hands dirty with, starting today, and experimentation is one of the best ways to develop your knowledge.

An AI vision company is launching a wearable camera for tracking your relationships. If that sounds creepy… well, it sort of is. And if it sounds useful, it might be that, too. It's a device that seems almost custom-built to tap into our fears about how technology will change relationships. And it almost certainly won't be the last of its kind.

Science fiction is where artificial intelligence goes to suffer. In nearly every robot-adjacent story, artificial lifeforms succeed in achieving sentience only to realize that they are abjectly, unendingly oppressed. That realization kicks off an array of terrible events: suicide, submission, or rebellion leading, most often, to death. But these dire possibilities of are limited only by the humans imagining them. Our robots, androids, and AIs should have more options than ending themselves or ending us.

The past 10 years have given us some truly innovative technology; now, healthcare providers are beginning to figure out the best ways to use it. They would do well to follow other industries by listening to consumers – in this case, patients – to determine the best way to incorporate this technology into their workflows. In this guest post, Vinay Seth Mohta, a managing director at an artificial intelligence engineering services firm, offers three patient-focused AI applications that might be a good place for healthcare executives to start. Accenture's "2018 Consumer Survey on Digital Health" found that three-quarters of the patients surveyed use technology to manage their own health. In addition, patients said they were eager to incorporate a new kind of technology into their health care: artificial intelligence.

I have been asked by quite a few people on how to start Machine Learning and Deep Learning. Here, I have curated a list of resources which I used and the path I took when I first learnt Machine Learning. I will keep on updating this article as I find more helpful resources. This will teach you the ropes of Machine Learning and will brush up your Linear Algebra skill a little bit. Make sure you do all the assignments and after you have completed the course, you will get a hold of Machine Learning concepts such as; Linear Regression, Logistics Regression, SVM, Neural Networks and K-means clustering.

This week's IRL focuses on two shows that don't appear to have much in common. But now Westworld viewers may be able to find a new appreciation for The Good Place, at least until season 3 rolls around. The Good Place is a Good Show. This much most people have already heard. It has a unique concept and a clever plot driven by some insane and insanely endearing characters.