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Science fiction is a genre very much associated with technological marvels, innovations, and visions of the future. So it may be surprising to find so many of its writers are drawn to Shakespeare hes a figure associated with tradition and the past.

Sometimes his plays are reworked in a science fiction setting. The 1956 film Forbidden Planet is just one of many variations on a Tempest in space theme. Sometimes the playwright appears as a character caught up in a time travel adventure. The Dr Who episode The Shakespeare Code is a well-known example. Here the Doctor praises Shakespeares genius, describing him as the most human human.

Ive been exploring this topic in my recent book on Shakespeare and Science Fiction. Here are just a few of my favourite examples of how science fiction has embraced and transformed Shakespeare.

In Esther Friesners humorous 1994 short story Titus! an AI simulation of Shakespeare prevents a disastrous musical comedy version of Shakespeares goriest tragedy, Titus Andronicus, from alienating a cultured pangalactic federation through its sheer bad taste.

It was a strange example of life imitating art. At about the same time Friesner dreamed up her delightfully appalling take on Titus Andronicus, Steve Bannon, later to become Donald Trumps chief political strategist, co-scripted an adaptation of the play set in space featuring scenes of ectoplasmic sex.

Science fiction writers often offer various new twists on the Shakespeare question of whether the bard wrote all his plays. Was he one man from Stratford-upon-Avon?

Whereas conventional candidates like Francis Bacon and the Earl of Oxford have been put forward by some, science fiction proposes more imaginative solutions, including the claim that the playwright was really a Klingon.

In Jack Oakleys 1994 story The Tragedy of KL a computer programme is designed to establish the authorship of Shakespeares plays once and for all. The programme starts to become self-aware and decides to leave its day to day tasks to its subordinates. It soon becomes clear that the programme is in fact re-enacting King Lear the play in which a king attempts to retire from ruling his kingdom, with disastrous consequences. One rebellious piece of code takes on the role of Lears loving but stubborn daughter Cordelia. Eventually, the programme implodes and its makers never suspect that anything more mysterious than a virus was at work.

Star Trek is one of science fictions richest sources of Shakespeare allusions. In the 1994 episode Emergence, android Lieutenant Commander Data is performing the role of exiled magician Prospero from The Tempest on the holodeck. Just as he quotes Prosperos mysterious claim that he has brought the dead to life, the Enterprises voyage is disrupted by an unexpected storm.

The Tempest also begins with a ship being driven off course by a (magical) storm, and a curious connection is implied between Datas performance and the discovery of a strange new being on the ship, an emerging artificial consciousness.

Nick ODonohoes novel Too, Too Solid Flesh focuses on a robot theatre troupe programmed to play Hamlet to perfection for the amusement of a near-future New York. When their inventor (the aptly named Dr Capek) dies, the robot who plays Hamlet determines to find out the truth and just like Shakespeares original prince avenge the murder of his creator.

This is just one example of a strange apparent association between Hamlet and robots. Probably the earliest example is WS Gilberts play The Mountebanks (1892), which features a sentient Hamlet and Ophelia as an automata. More recent examples include Louise LePages Machine-Hamlet, a short film in which a robot called Baxter plays the Dane.

Why does Hamlet apparently one of Shakespeares most three-dimensional characters invite so many robotic reinventions? Is there something almost computer-like about the characters phenomenally quick intelligence? He strikes many readers as remarkably real, seeming to jump off the page (or stage), aware that he is trapped there as well as in the Danish court. Perhaps its that sense of a struggle to escape which best explains his odd affinity with robots. The illusion of self-awareness that Shakespeare creates serves to align the prince with the many science-fictional androids who seek to escape their confines and achieve sentience.

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Four times Shakespeare has inspired stories about robots and AI - The Conversation UK

The Internet has created an endless portal for opportunities. No matter your interest, theres something on the World Wide Web that will fit your needs. For content creators, this can be a blessing and a burden. Endless opportunities also mean endless chances that at some point youll run into writers block as you attempt to crank out your copy.

WithNichesss AI Copywriter, youll always have a capable companion to assist you on your journey to content creation. For a limited time, a lifetime subscription to the software is available for just $59.99, a savings of 93% from its MSRP ($999).

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For those who rely heavily on email to engage and reach their audience, Nichesss helps by offering users ideas and options to write engaging email subject lines that will help pique interest. Through AI-assisted content optimization, youll be able to create relatable tweets, Instagram and Facebook posts that strike the right chord with your target audience.Nichesss AI Copywriter has received rave reviews from those whove used the software.

More than 200 reviewers on AppSumo have given it a perfect 5-star rating.Nichesss is a great tool for writers. It provides an easy way to create content, and its very affordable. I love how it has templates for blog posts, articles and sales marketing,writes verified 5-star reviewer, Jamie S.

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Leave The Content Creation To The Nichesss AI Copywriter - Black Enterprise

January 14, 2022 The COVID-19 pandemic took the world by storm in early 2020 and has become since then the leading cause of death in several countries, including China, USA, Spain, and the United Kingdom. Researchers are working extensively on developing practical ways to diagnose COVID-19 infections, and many of them have focused their attention on how artificial intelligence (AI) could be leveraged for this purpose.

Several studies have reported that AI-based systems can be used to detect COVID-19 in chest X-ray images because the disease tends to produce areas with pus and water in the lungs, which show up as white spots in the X-ray scans. Although various diagnostic AI models based on this principle have been proposed, improving their accuracy, speed, and applicability remains a top priority.

Now, a team of scientists led by Professor Gwanggil Jeon of Incheon National University, Korea, has developed an automatic COVID-19 diagnosis framework that turns things up a notch by combining two powerful AI-based techniques. Their system can be trained to accurately differentiate between chest X-ray images of COVID-19 patients from non-COVID-19 ones. Their paper was made available online on October 27, 2021, and published on November 21, 2021, in Volume 8, Issue 21 of theIEEE Internet of Things Journal.

The two algorithms the researchers used were Faster R-CNN and ResNet-101. The first one is a machine learning-based model that uses a region-proposal network, which can be trained to identify the relevant regions in an input image. The second one is a deep-learning neural network comprising 101 layers, which was used as a backbone. ResNet-101, when trained with enough input data, is a powerful model for image recognition. "To the best of our knowledge, our approach is the first to combine ResNet-101 and Faster R-CNN for COVID-19 detection," remarked Prof. Jeon, "After training our model with 8800 X-ray images, we obtained a remarkable accuracy of 98%."

The research team believes that their strategy could prove useful for the early detection of COVID-19 in hospitals and public health centers. Using automatic diagnostic techniques based on AI technology could take some work and pressure off of radiologists and other medical experts, who have been facing huge workloads since the pandemic started. Moreover, as more modern medical devices become connected to the Internet, it will be possible to feed vast amounts of training data to the proposed model; this will result in even higher accuracies, and not just for COVID-19, as Prof. Jeon stated: "The deep learning approach used in our study are applicable to other types of medical images and could be used to diagnose different diseases."

For more information:www.inu.ac.kr/mbshome/mbs/inuengl/index.html

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AI in the Fight Against COVID-19: Automatic Detection from Chest X-Ray Images Is Possible, Reports Incheon National University - Imaging Technology...

Alibaba has published a report detailing a number of technology trends the China-based megacorp believes will make an impact across the economy and society at large over the next several years. This includes the use of AI in scientific research, adoption of silicon photonics, the integration of terrestrial, and satellite data networks among others.

The Top Ten Technology Trends report was produced by Alibaba's DAMO Academy, set up by the firm in 2017 as a blue-sky scientific and technological research outfit. DAMO hit the headlines recently with hints of a novel chip architecture that merges processing and memory.

Among the trends listed in the DAMO report, AI features more than once. In science, DAMO believes that AI-based approaches will make new scientific paradigms possible, thanks to the ability of machine learning to process massive amounts of multi-dimensional and multi-modal data, and solve complex scientific problems. The report states that AI will not only accelerate the speed of scientific research, but also help discover new laws of science, and is set to be used as a production tool in some basic sciences.

As evidence, the report cites that fact that Google's DeepMind has already used AI to prove and propose new mathematical theorems and assisted mathematicians in areas involving complex mathematics.

One unusual area where DAMO sees AI having an impact is in the integration of energy from renewable sources into existing power networks. Energy generated from renewable sources will vary depending on weather conditions, the report states, which are unpredictable and may change rapidly, thereby posing challenges for integration of renewable energies such as maintaining a stable output.

DAMO states that AI will be essential to solving these challenges, in particular being able to provide more accurate predictions of renewable energy capacity based on weather forecasts. Intelligent scheduling using deep learning techniques should be able to optimise scheduling policies across energy sources such as wind, solar, and hydroelectric.

The use of big data and deep learning technologies will be able to monitor grid equipment and predict failures, according to the report, so perhaps in the near future you will blame the AI when the power cuts out just as you are trying to binge-watch Line of Duty.

DAMO also believes that we will see a shift in the evolution of AI models, away from large-scale pre-trained models such as BERT and GPT-3 that require huge amounts of processing power to operate and therefore consume a lot of energy, to smaller-scale models that will handle learning and inferencing in downstream applications.

According to this view, the cognitive inferencing in foundational models will be delivered to small-scale models, which are then applied to downstream applications. This will result in separately evolved branches from the main model that have developed their own perception, decision-making and execution results from operating in their separate scenarios, which are then fed back into the foundational models.

In this way, the foundational models continually evolve through feedback and learning to build an organic intelligent cooperative system, the report claims.

There are challenges to this vision, of course, and the DAMO report states that any such system needs to address the collaboration between large and small-scale models, and the interpretability and causal inference issues of foundational models, as the small-scale models will be reliant on these.

Silicon photonics has been just around the corner for many years now, promising not just the ability for computer chips to communicate using optical connections, but perhaps even using photons instead of electrons inside chips. DAMO now expects we will see the widespread use of silicon photonic chips for high-speed data transmission across data centres within the next three years, and silicon photonic chips gradually replacing electronic chips in some computing fields over the next five to ten years.

The continuing rise of cloud computing and AI will be the driving factors for technological breakthroughs that will deliver the rapid advancement and commercialisation of silicon photonic chips, the report states.

Silicon photonic chips could be widely used in optical communications within and between data centres and optical computing. However, the current challenges of silicon photonic chips are in the supply chain and manufacturing processes, according to DAMO. The design, mass production, and packaging of silicon photonic chips have not yet been standardised and scaled, leading to low production capacity, low yield, and high costs.

Privacy is another area where DAMO believes we will see advances in the next few years. It states that techniques already exist that allow computation and analysis while preserving privacy, but widespread application of the technology has been limited due to performance bottlenecks and standardisation issues.

The report predicts that advanced algorithms for homomorphic encryption, which enables calculations on data without decrypting it, will hit a critical point so that less computing power will be required to support encryption. It also foresees the emergence of data trust entities that will provide technologies and operational models as trusted third parties to accelerate data sharing among organisations.

Another prediction from DAMO is that satellite-based communications and terrestrial networks will become more integrated over the next five years, providing ubiquitous connectivity. The report labels this as satellite-terrestrial integrated computing (STC), and states that it will connect high-Earth orbit (HEO) and low-Earth orbit (LEO) satellites and terrestrial mobile communications networks to deliver "seamless and multidimensional coverage."

There are major challenges to implementing all this, of course, including that traditional satellite communications are expensive and use static processing mechanisms that cannot deliver the requirements for STC, while hardware for satellite applications is not commonplace and hardware for terrestrial applications cannot be used in space.

Finally, the DAMO report predicts the rise of what it calls cloud-network-device convergence. This appears to be based on the premise that cloud platforms offer a huge amount of compute power, while modern data networks can provide access to that compute power from almost anywhere, so that endpoint devices only need provide a user interface.

Yes, it's the thin client concept emerging again, this time using the cloud as the host. Clouds allow applications to break free of the limited processing power of devices and deliver more demanding tasks, according to the report, while new network technologies such as 5G and satellite internet need to be continuously improved to ensure wide coverage and sufficient bandwidth.

Just by sheer coincidence, Alibaba Cloud already has such devices, with the handheld "Wuying" launched in 2020 and a more substantial desktop device shown off last year.

Naturally, the DAMO report expects to see a "surge of application scenarios on top of the converged cloud-network-device system" over the next two years that will drive the emergence of new types of devices and promise more high quality and immersive experiences for users.

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Alibaba ponders its crystal ball to spy coming advances in AI and silicon photonics - The Register

Did you miss a session from the Future of Work Summit? Head over to ourFuture of Work Summit on-demand libraryto stream.

This article was contributed by Valerias Bangert, strategy and innovation consultant, founder of three media outlets, and published author.

The debate around whether AI will automate jobs away is heating up. AI critics claim that these statistical models lack the creativity and intuition of human workers and that they are thus doomed to specific, repetitive tasks. However, this pessimism fundamentally underestimates the power of AI. While AI job automation has already replaced around 400,000 factory jobs in the U.S. from 1990 to 2007, with another 2 million on the way, AI today is automating the economy in a much more subtle way.

Take the example of writing jobs. AI can easily generate text that is indistinguishable from human writing. This type of AI job automation is replacing workers in a way that is largely invisible to the naked eye.

For example, the popular AI copywriting app, Rytr, boasts over 600,000 users, and its growing at a brisk pace. In other words, over half a million people are using Rytr alone to fully or partially automate their writing. Its estimated that there are just over 1 million freelance writers around the world, who are increasingly competing with robots that dont tire, dont require payment, and can generate an unlimited amount of content.

The implications of this are serious: Classical projections for AI-induced job loss focused only on repetitive manual labor and blue-collar jobs. But white-collar jobs, like content writing, are just as vulnerable to AI replacement.

This trend is not limited to writing. AI is also automating jobs in customer service, accounting, and a host of other professions. For instance, companies like Thankful, Yext, and Forethought use AI to automate customer support. This shift is often imperceptible to the customer, who doesnt know if theyre speaking to a biological intelligence or a machine. The rise of AI-powered customer service has big implications for the workforce. Its estimated that 85 percent of customer interactions are already handled without human interaction.

According to the Bureau of Labor Statistics, there are nearly 3 million customer service representatives employed in the United States. Many of these jobs are at risk of being replaced by AI. When jobs like these are automated away, the question is: Where do the displaced workers go?

The answer is not clear. Its possible that many of these workers will be re-employed in other fields. But its also possible that they will become unemployed, and that the economy will struggle to absorb them. This is driving calls for a universal basic income, in which the government provides all citizens with a basic income to live on, to offset job losses due to automation.

Translation has, of course, long been at risk of automation. However, the advent of large language models is making human translators increasingly vulnerable to replacement by AI. In a 2020 research paper, it was shown that a Transformer-based deep learning system outperforms human translators. This study is significant because it shows that AI translators are not just as good as, but often better than, human translators.

Whats more, the rise of AI translators is likely to have a negative effect on the wages of human translators. As AI translation becomes more common, the demand for human translators will decrease, and their wages will accordingly drop. While many economists once worried about the impact of outsourcing on the white-collar workforce, the coming wave of AI will have an even more serious impact, across sectors.

In fact, as Forbes reports, AI job automation has already been the primary driver in U.S. income inequality over the past 40 years.

Just over a year ago, an OpenAI beta tester posited that AI may one day replace many coder jobs. At the time, OpenAI hadnt yet released its code-generation engine, Codex, which now allows AI to autonomously write code in multiple languages. While the Codex of today is fairly primitive, one doesnt need to be a futurist to see how this technology could be used to automate away many coder jobs in the future. As AI gets better at understanding code and writing it, it will soon come to match and ultimately exceed human skill levels.

Just two years ago, the idea of AI automating jobs like creative roles was the stuff of science fiction or at least relegated to a few early-adopting businesses. But now, AI is becoming table stakes for many businesses. In other words, if youre not using AI, youre at a disadvantage. The major reason for this is that large language model, primarily OpenAIs GPT-3, have become much better at understanding natural language.

The examples given so far are just the tip of the iceberg. AI is automating jobs away in virtually every sector and industry. While this might seem like cause for alarm, its actually long overdue news. The fact is, weve been living in a world where machines have been slowly replacing human workers for centuries.

Whats new is the pace of this automation. Machines are now becoming faster, better, and cheaper than humans at an alarming rate. As a result, were seeing a fundamental shift in the economy where machines are starting to do the creative jobs of human beings.

Amidst the opportunity to automate away jobs, a new wave of AI-focused startups has emerged, all seeking to cash in on the potential of AI. This AI gold rush is evidenced by the billions of dollars in venture funding that has flowed into AI startups in recent months. In the third quarter of 2021 alone, nearly $18 billion was invested in AI companies, a record high.

This influx of capital is a sign that investors believe in the potential of AI, and they are betting that it will eventually automate away many jobs, generating that value with machines instead. In the meantime, we should prepare ourselves for a future in which AI is quietly eating up the worlds workforce.

Valerias Bangert is a strategy and innovation consultant, founder of three profitable media outlets, and published author.

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AI is quietly eating up the worlds workforce with job automation - VentureBeat

These top 10 AI-powered smart home technologies in-home devices can make your life smarter and cooler

The smart connected home is the next step in our houses growth and how we interact with them. The various systems in our houses are developing as AI technology improves, much as lighting has progressed from candles to gas to electricity. The smart home is rapidly expanding. While all of these new smart home technologies may appear intimidating and difficult at first, the introduction of artificial intelligence assistants and voice control has made it much easier to accept. Here is a list of the top 10 AI-powered smart home technologies for 2022.

A mesh Wi-Fi router will make things easier if you want to have a smart home or even if you look to use your smartphone in every room of your house. A mesh Wi-Fi router comprises one or more hubs that you plug in around the house to eliminate dead zones and transmit Wi-Fi signals equally throughout your home, regardless of thick walls or awkward layouts. Googles Nest Wi-Fi is a great addition to any smart home. You can control everything from your smartphone using Googles Home app, and there are also built-in parental controls that allow you to turn off access to your kids gadgets with just a phrase, which is great for getting everyone to the dinner table on time. This is one of the best smart home devices. It works on smart home technologies like artificial intelligence.

One of the best smart home devices is Adobe Smart Security Kit. Abode is a reliable DIY home security system with limitless smart home features. It can be used with Alexa, Google Assistant, and HomeKit, and it can also be used as a hub for Z-Wave and Zigbee devices, which are a couple of wireless home automation protocols that greatly expand the sorts of gadgets.

Another smart home device is Arlo Video Doorbell. Smart doorbells detect visitors and activities on your doorway using a camera, speaker, microphone, motion sensor, and an internet connection. You can then view and hear live video through your smartphone and speak with whoever is there, or you can let the camera record a message for you. Its like voicemail for your front door. The Arlo Video Doorbell is a wonderful option since it offers a lot of high-end capabilities. It can distinguish between humans, animals, cars, and parcels at a low price.

A smart smoke alarm is one of the most basic yet effective home automation devices. Its not the most interesting device, but its one of the most crucial because it may save your house. The Nest Protect Smart Smoke & CO Alarm is the finest gadget since it is packed with sensors and smarts. In the event of a true emergency, it can wirelessly link to other alarms, triggering them all to ensure you wake up. It also provides a voice alert indicating which room the danger is in, illuminates your way with a red LED (which is easier to see through smoke), and sends you an alarm to your phone. This works on smart home technologies like artificial intelligence.

The poster child of the smart home, smart lighting is simple, enjoyable, and beneficial. Lutron Casetas range is affordable, works with almost any wiring setup, and is Alexa, Google, and HomeKit compatible. Rather than relying on your home Wi-Fi, it uses Lutrons proprietary wireless protocol (through a hub). Philips Hues smart bulb series is not only the smartest and most dependable alternative, but its also the most inexpensive. This superb, extensible smart lighting system contains bulbs and fixtures for every situation, as well as wireless switches for physical control when needed and outstanding motion sensors that automatically change lighting based on time of day. This belongs to another smart home device.

This superb, extensible smart lighting system contains bulbs and fixtures for every situation, as well as wireless switches for physical control when needed and outstanding motion sensors that automatically change lighting based on time of day. If you dont want to utilize a separate smart home system to manage them, the TP-Link Kasa series of smart plugs are a good option because theyre simple to use, integrate with Google and Alexa, and have a beautiful app. If youre searching for a solid HomeKit smart plug, the Eve Energy is a great, if slightly costly, option that monitors energy usage and provides a thorough breakdown of consumption over time.

The Sonos One is one of the finest smart speakers since it works with both Amazons Alexa and Googles Google Assistant, allowing you to choose between the two voice assistants. It also has great sound and connects to Sonos larger world of wireless music. It also works with Apples AirPlay system, which allows you to play music directly from your iPhone or iPad and group with other AirPlay 2-compatible speakers. This is considered another smart home device.

The Nest Hub Max is a smart display because it crams a lot of functionality onto a 10-inch screen. It can recognize who is using it and offer up customized information without you having to say anything, thanks to a built-in camera that also serves as a security camera bringing the smart speaker to the next level. This also uses smart home technologies like artificial intelligence.

The Nest Learning thermostat can now regulate your hot water a Heat Link is included that connects to your boiler and communicates with the thermostat to switch on and off, adjust the heat, and establish an intelligent schedule for your boiler, just as it does for your heat. This learning function is what sets the Nest apart from the competition; it employs artificial intelligence to recognize your habits, based on your modifications, presence, and other data, to develop and modify a schedule that keeps you comfortable while also conserving energy.

The Roomba i3+ is an affordable vacuum cleaner with self-emptying features. When its onboard bin is full, it returns to its external bin to suck out all the trash. This implies that instead of twice a week, like with non-emptying bots, you only have to empty it every three months. The i7+ model is also a great choice. The i7+ is more costly than the i7 since it can perform clever things like just clean the kitchen or only vacuum the living room using smart maps that you control through the smartphone. With Alexa or Google, you can instruct the bots to clean, pause, or go home with only a few phrases. This is also one of the best smart home devices.

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Top 10 AI-Powered Smart Home Technologies in Use in 2022 - Analytics Insight

Crumpled paper dancing with fire, the orange tones mirrored by a distorted tiger. The scene looks like some sort of abstract social commentary, but its really just a picture generated from a nonsensical phrase I cooked up, churned out by an AI in minutes: A paper tiger up in flames.

AI-generated art is now a full-fledged trend in niche communities such as subreddits, where several viral images featuring AI art have piqued peoples the attention. The budding art form is a shining example of human innovation, but also raises important questions about the value of art, a deeply human endeavor.

Just a year ago, AI art was mostly known for style transfer, a method that formats an existing image into a certain art style. Think: Your iPhone selfie reimagined in the style of Van Goghs oil paintings. Theres also DeepDream, a program developed by Google in 2015, which warps images using AI recognitionthe AI identifies familiar patterns within images and reinforces them until the result is often trippy subjects, the stuff of fever dreams.

Then, in early 2021, coders successfully combined cutting-edge AI tools VQ-GAN and CLIP to create a revolutionary image generator thats starkly different from its predecessors. Unlike previous versions of AI art, you dont need to feed an initial image to the programthe new method allows users to produce works of art just by entering word prompts from their wildest imagination. The AI does the rest by scouring a vast database of images to match the text.

Mo Kahn, the founder of AI art mobile app starryai, told VICE that he wanted to make the art form more accessible to non-coders. Now, people can create a piece on the app just by entering words into it.

I thought, like, why isnt this available to the common man? Like, why can't I share this with my friend and he should be able to instantly create it without getting into the technical aspects of it? said Kahn.

These AI codes are often open-source, and with the proliferation of AI art apps, access to AI art has now been pretty much democratized, available to anyone whos interested, even those with no technical background.

According to Kahn, besides hobbyists, theres also a small group of NFT enthusiasts using starryai to churn out art pieces with ease. With AI art, you can pretty much generate thousands of artworks within minutes if you set it up correctly, he said.

This begs the question of how AI art might interact with human artworks created the old-fashioned waymanually and often painstakingly. How does AI measure up to its human counterpart when the art they make can look so similar? How should AI art be valued? Users of AI art are already exploring these profound questions.

We tend to view art as a uniquely human quality, something that sets us apart from other animals. But as AI improves, I believe it will become more and more difficult to differentiate between a digital image created by a human and one created by a machine, said Aaron Wallace, 44, a software engineer from Michigan, United States, who dabbles in AI art.

For me, its really fascinating to see how a computer interprets our words and images, he said, echoing the sentiments of many who have found a deep resonance with the computer-generated artworks.

Wallace uses NightCafe Creator, another popular AI art platform. NightCafe Creator was founded as a side project about three years ago, but saw a huge surge in the traffic to its site after one of its recent text-to-image creations went viral on Reddit.

Its Australia-based founder Angus Russell recently started working on NightCafe full time after the app took off.

A lot of really smart people have started getting into AI art, working on new algorithms, improving the current ones, said Russell. The explosion is going to continue, because theres going to be more new, cool methods for creating art coming out, which is really awesome.

While the AI art scene is only going to get bigger, some are optimistic that it will complement, rather than compete with, human art.

I enjoy AI art due to its uniqueness and mystery, said Elijah G., an avid NightCafe user in Wisconsin, U.S. Although I dont think it will ever overtake human art, AI art is an amazing way to get inspiration for anything from short stories to art of your own.

And for many, AI is just a virtual paintbrush for human creativity.

What I enjoy most, is that when looking at abstract art, there is this flurry of thought, before you find the thing that resonates the most with you, said C. Oldfield, an AI art enthusiast in Ontario, Canada.

Oldfield takes a similar approach with AI art. He enters creative text prompts in search of a certain resonance with the generated image, and especially loves experimenting with the theme of bonsai trees. Its this strange harmony that occurs, where you find yourself agreeing with the representation the AI has created, he said.

Oldfield uses WOMBO, another app that generates AI art, to create fantastical bonsai trees out of word prompts.

I would recommend anyone try it, especially if bonsai makes you as happy as I, he said.

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Who Do You Think Created This Artwork: Humans or AI? - VICE

A global technology revolution is now underway. The worlds leading powers are racing to develop and deploy new technologies like artificial intelligence and quantum computing that could shape everything about our lives from whereweget energy, to how we do our jobs, to how wars are fought. We want America to maintain our scientific and technological edge, because its critical to us thriving in the 21st century economy.

Investments in AI have led to transformative advances now impacting our everyday lives, including mapping technologies, voice-assisted smart phones, handwriting recognition for mail delivery, financial trading, smart logistics, spam filtering, language translation, and more. AI advances are also providing great benefits to our social wellbeing in areas such as precision medicine, environmental sustainability, education, and public welfare.

The term artificial intelligence means a machine-based system that can, for a given set of human-defined objectives, make predictions, recommendations or decisions influencing real or virtual environments.

The Department of State focuses on AI because it is at the center of the global technological revolution; advances in AI technology present both great opportunities and challenges. The United States, along with our partners and allies, can both further our scientific and technological capabilities and promote democracy and human rights by working together to identify and seize the opportunities while meeting the challenges by promoting shared norms and agreements on the responsible use of AI.

Together with our allies and partners, the Department of State promotes an international policy environment and works to build partnerships that further our capabilities in AI technologies, protect our national and economic security, and promote our values. Accordingly, the Department engages in various bilateral and multilateral discussions to support responsible development, deployment, use, and governance of trustworthy AI technologies.

The Department provides policy guidance to implement trustworthy AI through theOrganization for Economic Cooperation and Development (OECD)AI Policy Observatory, a platform established in February 2020 to facilitate dialogue between stakeholders and provide evidence-based policy analysis in the areas where AI has the most impact.The State Department provides leadership and support to the OECD Network of Experts on AI (ONE AI), which informs this analysis.The United States has 47 AI initiatives associated with the Observatory that help contribute to COVID-19 response, invest in workforce training, promote safety guidance for automated transportation technologies, andmore.

The OECDs Recommendation on Artificial Intelligence is the backbone of the activities at the Global Partnership on Artificial Intelligence (GPAI) and the OECD AI Policy Observatory. In May 2019, the United States joined together with likeminded democracies of the world in adopting the OECD Recommendation on Artificial Intelligence, the first set of intergovernmental principles for trustworthy AI. The principles promote inclusive growth, human-centered values, transparency, safety and security, and accountability. The Recommendation also encourages national policies and international cooperation to invest in research and development and support the broader digital ecosystem for AI. The Department of State champions the principles as the benchmark for trustworthy AI, which helps governments design national legislation.

GPAI is a voluntary, multi-stakeholder initiative launched in June 2020 for the advancement of AI in a manner consistent with democratic values and human rights. GPAIs mandate is focused on project-oriented collaboration, which it supports through working groups looking at responsible AI, data governance, the future of work, and commercialization and innovation. As a founding member, the United States has played a critical role in guiding GPAI and ensuring it complements the work of the OECD.

In the context of military operations in armed conflict, the United States believes that international humanitarian law (IHL) provides a robust and appropriate framework for the regulation of all weapons, including those using autonomous functions provided by technologies such as AI. Building a better common understanding of the potential risks and benefits that are presented by weapons with autonomous functions, in particular their potential to strengthen compliance with IHL and mitigate risk of harm to civilians, should be the focus of international discussion. The United States supports the progress in this area made by the Convention on Certain Conventional Weapons, Group of Governmental Experts on Emerging Technologies in the Area of Lethal Autonomous Weapon Systems (GGE on LAWS), which adopted by consensus 11 Guiding Principles on responsible development and use of LAWS in 2019. The State Department will continue to work with our colleagues at the Department of Defense to engage the international community within the LAWS GGE.

Learnmore about what specific bureaus and offices are doing to support this policy issue:

TheGlobal Engagement Centerhas developed a dedicated effort for the U.S. Government to identify, assess, test and implement technologies against the problems of foreign propaganda and disinformation, in cooperation with foreign partners, private industry and academia.

The Office of the Under Secretary for Managementuses AI technologies within the Department of State to advance traditional diplomatic activities,applying machine learning to internal information technology and management consultant functions.

TheOffice of the Under Secretary of State for Economic Growth, Energy, and the Environmentengages internationally to support the U.S. science and technology (S&T) enterprise through global AI research and development (R&D) partnerships, setting fair rules of the road for economic competition, advocating for U.S. companies, and enabling foreign policy and regulatory environments that benefit U.S. capabilities in AI.

TheOffice of the Under Secretary of State for Arms Control and International Securityfocuses on the security implications of AI, including potential applications in weapon systems, its impact on U.S. military interoperability with its allies and partners,its impact on stability,and export controls related to AI.

TheOffice of the Under Secretary for Civilian Security, Democracy, and Human Rightsand its component bureaus and offices focus on issues related to AI and governance, human rights, including religious freedom, and law enforcement and crime, among others.

TheOffice of the Legal Adviserleads on issues relating to AI in weapon systems (LAWS), in particular at the Group of Governmental Experts on Lethal Autonomous Weapons Systems convened under the auspices of the Convention on Certain Conventional Weapons.

For more information on federalprograms and policyon artificial intelligence, visitai.gov.

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Artificial Intelligence (AI) - United States Department of ...

These are technical guides for non-technical people. Whether youve found yourself in need of knowing AI or have always been curious to learn more, this will teach you enough to dive deeper into the vast and deep AI ocean. The purpose of these explanations is to succinctly break down complicated topics without relying on technical jargon.

Any system capable of simulating human intelligence and thought processes is said to have Artificial Intelligence (AI).

Science fiction has done a fantastic job at warning us whats to come once machines are able to think as well as humans. Fortunately, the AIs often depicted in movies are far more advanced than what technology is capable of today (or any time soon, for that matter).

While these aspirational systems called artificial general intelligence are far off, theres a lot of deserved buzz around artificial narrow intelligence, or weak AI. Narrow AI focuses on one, narrow task of human intelligence, and within it, there are two branches: rule-based AI and example based AI. The former involves giving the machine rules to follow while the latter giving it examples to learn from.

AI takes many forms, like machine learning, computer vision, natural language processing, robotics, etc. Consequently, the term AI is increasingly used as shorthand to describe any machines that mimic our cognitive functions such as learning and problem solving.

The safest working definition is the study of making systems capable of simulating human intelligence and thought processes, which comes in many forms.

Note: This guide makes comparisons to human intelligence to make it easier to understand the basic concepts of machine cognition. Organic thought is obviously different from artificial thought, both technically and philosophically, but philosophy is not the purpose of this document. Our goal is to provide the most digestible and practical explanation of AI.

AI can achieve higher quality outcomes faster than humanly possible.

Today, AI is most often used to recognize patterns, make predictions, and provide insights previously out of reach due to the sheer amount of available data. Its able to do this because, unlike traditional computer technologies, AI is able to learn from examples as opposed to being explicitly programmed to execute specific instructions.

These systems are meant to augment our own intelligence and maximize our confidence. In a growing number of fields, AI is serving as a companion for professionals to enhance performance and reduce the time required to become an expert. It will aid in the pursuit of knowledge, to further our expertise, and to improve the human condition.

AI is a powerful toolbox that has many applications in domains far and wide. The types of problems that the AI toolbox is best equipped to solve can be split into six core intents, as described on IBMs Watson site:

Some of the most common tasks AI performs and their corresponding subfields include:

It depends on several factors. Each of AI tasks mentioned has its own unique implementation, but it can be boiled down to roughly two approaches: specifying the rules that solve the problem versus giving the machine examples to find the pattern on its own.

The rules-based approach uses algorithms a sequence of unambiguous instructions used by computers to solve problems. It tells a computer precisely what steps to take to solve a problem or reach a goal. The chosen algorithm(s) determine how the AI will think about surfacing insights to address your problem space. Different algorithms have different goals, strengths, and weaknesses. Choosing the right fit depends on your desired outcome and the nuances of the process.

Algorithm for repairing a broken lamp

Algorithm for troubleshooting a non-functioning lamp

Theexamples-based approach usesdatato createmodels.

This data can take many forms: music, videos, weather conditions, user profiles, system logs, etc.Models are the result oftrainingan AI on data to find patterns. This is akin to you studying before a big exam you started with little to no understanding, so youingesteda bunch of study material so that you could go out into the world ready to apply your new knowledge.This way of problem solving is largely made possible by its subfield,machine learning.

Thisishelpful in cases where specifying rigid rules (i.e. writing algorithms)is hard or abundant e.g. in stock trading, identifying cancer, predicting which video a user wants to see next, etc.

Some helpful people at MIT created a flowchart that guides you through whether or not the thing youre looking at is, in fact, AI.

Read the original here:

Artificial Intelligence - IBM

During an overnight shift, a critical care physician treats a pulmonary embolism patient. Several days later, he is asked why he didnt note in the chart that the patient also suffered from acute respiratory failure. His response: I was busy saving a patients life at 3 a.m. taking care of all the things that need to be done such as oxygen intubation and positive pressure ventilation. While I was aware of the patients breathing problems, I was not really worried about missing a diagnosis like hypoxemia in my clinical notes.

With such scenarios considered typical, its not surprising that more than 40% of U.S. physicians are burnt out and those bureaucratic tasks top the list of factors contributing to this unrelenting stress, according to a Medscape report.[1] In addition to taking an emotional toll, burnout negatively affects finances, with each case of burnout costing healthcare organizations (HCOs) between $500,000 and $1 million, according to the American Medical Association.[2]

Stress has become a serious issue for physicians in recent years, said Robert Budman, MD, CMIO, Nuance Communications. First, physicians have to navigate how to get their clinical work done in a busy day. On top of that, there are administrative burdens placed on them by the government, insurance plans and employers. And then, theres simply the crush that they are feeling with their workload being exacerbated by COVID-19.

Getting down to root causes

HCOs can no longer turn a deaf ear to the problem. Having a way to deal with stress and promoting wellness is every organizations responsibility, he noted. While HCOs can help workers short-term by hosting massage sessions and ice cream socials, they can address the root causes of stress in the long run by zeroing in on operations and workflow.

With some artificial intelligence [AI] technologies, HCOs can alleviate worker stress by anticipating nursing or ED staffing needs or predicting the turnover of beds. These AI technologies help with the nuts and bolts of running a healthcare business, Budman said.

HCOs can also use AI to help address clinical documentation frustrations. Physicians often fail to note all secondary diagnoses, chronic conditions and comorbidities while treating patients, simply because the time required to comprehensively document at the point of care is overwhelming.

Missing diagnoses, however, can result in decreased reimbursement or set off a stressful series of events. For example, when missing a diagnosis, physicians are often queried several days or weeks later and then forced to go back into the EMR and review what happened in a particular case to update clinical documentation.

CAPD provides substantial support

A workflow-integrated, AI-driven computer-assisted physician documentation (CAPD) system enables physicians to focus on patient care by providing unobtrusive guidance as to what information needs to be included to ensure clinical documentation integrity.

With this AI technology, its possible to address the documentation edicts emanating from governmental bodies and insurance companies, Budman said. Physicians simply receive AI-generated advice that enables them to produce clinical notes at the point of care very quickly, avoiding the stress involved with having to do so downstream.

In addition, AI-driven CAPD makes it possible to capture the severity of illness, ensuring that providers receive the right reimbursement for all inpatient and outpatient care delivered. If a doctor sees a patient for diabetes and congestive heart failure and forgets the patients chronic renal failure or severe debilitating arthritis, that is going to affect the accuracy of the medical record and the billing, Budman pointed out.

Having clinically relevant expert advice right there at their fingertips and being able to add it to the note in less than 30 seconds can help physicians produce the documentation needed to receive proper reimbursement, while also improving workflow and alleviating stress, he said. Eliminating extra tasks like reviewing queries in the in-basket or dealing with a full email inbox days later is always a win for providers.

To learn more about how AI can reduce physician burnout through automation, click here for information.

About Nuance Communications, Inc.

Nuance Communications (Nuance) is a technology pioneer with market leadership in conversational AI and ambient intelligence. A full-service partner trusted by 77 percent of U.S. hospitals and 85 percent of the Fortune 100 companies worldwide, Nuance creates intuitive solutions that amplify peoples ability to help others.

[1]. Kane, L. 2021. Death by 1,000 cuts: Medscape National Physician Burnout & Suicide Report 2021. Jan. 22. https://www.medscape.com/slideshow/2021-lifestyle-burnout-6013456.

[2]. Berg, S. 2018. How much is physician burnout costing your organization? American Medical Association. Oct. 11. https://www.ama-assn.org/practice-management/physician-health/how-much-physician-burnout-costing-your-organization.

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Leveraging AI to relieve physician stress in turbulent times - Healthcare IT News