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"Google is using romance novels to teach its artificial intelligence (AI) system to better understand how people communicate. Researchers at Google Brain, the company's AI-focused deep learning project, presented a paper earlier this month that detailed techniques they used to teach its AI to write fiction - and the results were unexpectedly haunting."

"The company has called for Australian policymakers to promote "copyright systems that enable appropriate and fair use of copyrighted content to enable the training of AI models in Australia on a broad and diverse range of data, while supporting workable opt-outs for entities that prefer their data not to be trained in using AI systems". The call for a fair use exception for AI systems is a view the company has expressed to the Australian government in the past, but the notion of an opt-out option for publishers is a new argument from Google."

"The camera never lies. Except, of course, it does - and seemingly more often with each passing day. In the age of the smartphone, digital edits on the fly to improve photos have become commonplace, from boosting colours to tweaking light levels. Now, a new breed of smartphone tools powered by artificial intelligence (AI) are adding to the debate about what it means to photograph reality. Google's latest smartphones released last week, the Pixel 8 and Pixel 8 Pro, go a step further than devices from other companies. They are using AI to help alter people's expressions in photographs. It's an experience we've all had: one person in a group shot looks away from the camera or fails to smile. Google's phones can now look through your photos to mix and match from past expressions, using machine learning to put a smile from a different photo of them into the picture. Google calls it Best Take. "

"Green Light uses machine learning systems to comb through Maps data to calculate the amount of traffic congestion present at a given light, as well as the average wait times of vehicles stopped there. That information is then used to train AI models that can autonomously optimize the traffic timing at that intersection, reducing idle times as well as the amount of braking and accelerating vehicles have to do there. It's all part of Google's goal to help its partners collectively reduce their carbon emissions by a gigaton by 2030."

"Eck said machine learning, a powerful form of AI, will be integrated into how humans communicate with each other. He raised the idea of "assistive writing" in the future with Google Docs, the company's online word processing software. This may be based on Google's upcoming Smart Compose technology that suggests words and phrases based on what's being typed. Teachers used to worry about whether students used Wikipedia for their homework. Now they may wonder what part of the work the students wrote themselves, Eck said."

"In a paper titled "Towards Causal Representation Learning," researchers at the Max Planck Institute for Intelligent Systems, the Montreal Institute for Learning Algorithms (Mila), and Google Research discuss the challenges arising from the lack of causal representations in machine learning models and provide directions for creating artificial intelligence systems that can learn causal representations."

"Over the Bridge hopes the project emphasizes exactly how much work goes into creating AI music. "There's an inordinate amount of human hands at the beginning, middle and end to create something like this," explained Michael Scriven, a rep for Lemmon Entertainment whose CEO is on Over the Bridge's board of directors. Scriven added, "A lot of people may think [AI] is going to replace musicians at some point, but at this point, the number of humans that are required just to get to a point where a song is listenable is actually quite significant.""

"Google has pledged to continue developing advanced programs using machine learning to combat the rise of extremist content, after it found that it was both faster and more accurate than humans in scrubbing illicit content from YouTube."

"It is also self-improving. The 10-year-old grading software leverages deep learning algorithms to "compare notes" with human teachers' scores, suggestions, and comments. An engineer involved in the project compared its capabilities to those of AlphaGo, the record-breaking AI Go player developed by Google subsidiary DeepMind."

"Unskilled manual laborers have felt the pressure of automation for a long time - but, increasingly, they're not alone. The last few years have been a bonanza of advances in artificial intelligence. As our software gets smarter, it can tackle harder problems, which means white-collar and pink-collar workers are at risk as well. Here are eight jobs expected to be automated (partially or entirely) in the coming decades. Call Center Employees call-center Telemarketing used to happen in a crowded call center, with a group of representatives cold-calling hundreds of prospects every day. Of those, maybe a few dozen could be persuaded to buy the product in question. Today, the idea is largely the same, but the methods are far more efficient. Many of today's telemarketers are not human. In some cases, as you've probably experienced, there's nothing but a recording on the other end of the line. It may prompt you to "press '1' for more information," but nothing you say has any impact on the call - and, usually, that's clear to you. But in other cases, you may get a sales call and have no idea that you're actually speaking to a computer. Everything you say gets an appropriate response - the voice may even laugh. How is that possible? Well, in some cases, there is a human being on the other side, and they're just pressing buttons on a keyboard to walk you through a pre-recorded but highly interactive marketing pitch. It's a more practical version of those funny soundboards that used to be all the rage for prank calls. Using soundboard-assisted calling - regardless of what it says about the state of human interaction - has the potential to make individual call center employees far more productive: in some cases, a single worker will run two or even three calls at the same time. In the not too distant future, computers will be able to man the phones by themselves. At the intersection of big data, artificial intelligence, and advanced

"It is one of the first programs to combine an external memory with an approach called deep-learning, in which the program learns how to do tasks independently rather than being pre-programmed with a set of rules by a human."

"That is why we must demand transparency here, especially in the case of technology that uses human-like interfaces such as language. For any automated system, we need to know what it was trained to do, what training data was used, who chose that data and for what purpose. In the words of AI researchers Timnit Gebru and Margaret Mitchell, mimicking human behaviour is a "bright line" - a clear boundary not to be crossed - in computer software development. We treat interactions with things we perceive as human or human-like differently. With systems such as LaMDA we see their potential perils and the urgent need to design systems in ways that don't abuse our empathy or trust."

""Each time we build new ways of doing something close to human level, it allows us to automate or augment human labor," said Jeremy Howard, founder of Fast.ai, an independent lab based in San Francisco that is among those at the forefront of this research. "This can make life easier for a lawyer or a paralegal. But it can also help with medicine." It may even lead to technology that can - finally - carry on a decent conversation. But there is a downside: On social media services like Twitter, this new research could also lead to more convincing bots designed to fool us into thinking they are human, Howard said."

""We'd have to show them 100,000 penny-farthings and tell them it's a bike," Giannandrea says. Then-looking on the bright side-he adds that "once they'd seen 100,000, they'd probably be better at identifying them than humans are.""

""AI can pick up missed cues and suggest nudges to bridge the gap in emotional intelligence and communication styles. It can identify optimal ways to discuss common problems and alleviate common misunderstandings based on these different priorities and ways of viewing the world. We could be looking at a different gender dynamics in a decade.""

"The development of autonomous military systems - dubbed "killer robots" by campaigners opposed to them - is deeply contentious. Earlier this year, Google withdrew from the Pentagon's Project Maven, which uses machine learning to analyse video feeds from drones, after ethical objections from the tech giant's staff. The government insists it "does not possess fully autonomous weapons and has no intention of developing them". But, since 2015, the UK has declined to support proposals put forward at the UN to ban them. Now, using government data, Freedom of Information requests and open-source information, a year-long investigation reveals that the MoD and defence contractors are funding dozens of artificial intelligence programmes for use in conflict."

"The models work by dividing maps into what Google calls "supersegments" "

"YouTube will rely more on machine learning and less on human reviewers during the coronavirus outbreak. Normally, algorithms detect potentially harmful content and send it to human reviewers for assessment. But these are not normal times, and in an effort to reduce the need for employees and contractors to come into an office, YouTube will allow its automated system to remove some content without human review."

"Researchers from MIT and Google recently showed off a machine learning algorithm capable of automatically retouching photos just like a professional photographer. Snap a photo and the neural network identifies exactly how to make it look better-increase contrast a smidge, tone down brightness, whatever-and apply the changes in less than 20 milliseconds."

"The arcane nature of "protein folding", a mind-boggling form of molecular origami, is rarely discussed outside scientific circles, but it is a problem of profound importance. The machinery of biology is built from proteins and it a protein's shape defines its function. Understand how proteins fold up and researchers could usher in a new era of scientific and medical progress."