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"Oh, I just listen to bird sounds a lot and then try to emulate the kinds of things they do. Synthesizers are quite good at that because some of the new software has what's called physical modeling. This enables you to construct a physical model of something and then stretch the parameters. You can create a piano with 32-foot strings, for instance, or a piano made of glass. It's a very interesting way to try to study the world, to try to model it. In the natural world there are discrete entities like clarinets, saxophones, drums. With physical modeling, you can make hybrids like a drummy piano or a saxophone-y violin. There's a continuum, most of which has never been explored."

"TikTok's algorithm is famously effective, yet hard to study. As part of the Guardian's special series on the platform's explosive rise, we tested how the algorithm treats different users. We wondered what would happen if three people - with varying ages, backgrounds, and familiarity with the platform - created new accounts and recorded what they saw."

""Even though mobile phones are intertwined with our lives, they do not belong in the classroom," education minister Robbert Dijkgraaf said. "Students need to be able to concentrate and need to be given the opportunity to study well. Mobile phones are a disturbance, scientific research shows. We need to protect students against this.""

"Curtin University internet studies professor Tama Leaver posted about some of his tests with Emu's sticker generation to X, formerly known as Twitter. Leaver found, for example, that the AI will block a phrase like "child with gun" and display a warning message about how the prompt doesn't follow Meta's Community Guidelines. Emu will, however, generate stickers with the similar, more niche prompt "child with grenade." It not only creates stickers of kids holding the weapon but also produces stickers of children holding guns."

"In fact, generating an image using a powerful AI model takes as much energy as fully charging your smartphone, according to a new study by researchers at the AI startup Hugging Face and Carnegie Mellon University. However, they found that using an AI model to generate text is significantly less energy-intensive. Creating text 1,000 times only uses as much energy as 16% of a full smartphone charge. "

"Students on online courses report insufficient interaction and familiarity with their instructors and a lack of motivation. Feedback in one study included: "I want a real teacher", "I prefer a course taught by a human" and "There is no instructor personality interjected into the course". So, how do instructors overcome this perception and ensure students view them as "present" in online courses? "

"No prominent developer of AI foundation models - a list including companies like OpenAI and Meta - is releasing sufficient information about their potential impact on society, determines a new report from Stanford HAI (Human-Centered Artificial Intelligence). Today, Stanford HAI released its Foundation Model Transparency Index, which tracked whether creators of the 10 most popular AI models disclose information about their work and how people use their systems. Among the models it tested, Meta's Llama 2 scored the highest, followed by BloomZ and then OpenAI's GPT-4. But none of them, it turned out, got particularly high marks."

"Wikipedia lives and dies by its references, the links to sources that back up information in the online encyclopaedia. But sometimes, those references are flawed - pointing to broken websites, erroneous information or non-reputable sources. A study published on 19 October in Nature Machine Intelligence1 suggests that artificial intelligence (AI) can help to clean up inaccurate or incomplete reference lists in Wikipedia entries, improving their quality and reliability."

"Researchers involved in a recent study trained an artificial intelligence (AI) model to diagnose type 2 diabetes in patients after six to 10 seconds of listening to their voice. Canadian medical researchers trained the machine-learning AI to recognise 14 vocal differences in the voice of someone with type 2 diabetes compared to someone without diabetes. The auditory features that the AI focussed on included slight changes in pitch and intensity, which human ears cannot distinguish. This was then paired with basic health data gathered by the researchers, such as age, sex, height and weight. Researchers believe that the AI model will drastically lower the cost for people with diabetes to be diagnosed."

"Could it be the phones? Absolutely! To be clear: the idea that phones are causing distraction both inside and outside of school hours, and this contributes to declining test scores, seems totally plausible to me-and preliminary cross-sectional data from the PISA report indicates the same. Might it be a good idea to keep phones out of the classroom? Definitely! But, as often happens when an excerpt of a larger study makes the rounds online, some nuance is missing. Let's talk about what the data actually show. "

""The face jumped out at me as being fake," said DiResta, a veteran researcher who has studied Russian disinformation campaigns and anti-vaccine conspiracies. To her trained eye, these anomalies were red flags that Ramsey's photo had likely been created by artificial intelligence."

"Facebook failed to label 80% of articles on its platform promoting a fast-spreading conspiracy theory that the US is funding the use of bioweapons in Ukraine, according to a study released Friday by the Center for Countering Digital Hate (CCDH)."

"What is in doubt is who will benefit from the boost to productivity. What if all the gains are seized by a handful of tech giants? What if history fails to repeat itself, and AI destroys more jobs than it creates? What if AI does lead to a net increase in employment, but the new jobs are less well-paid than the old ones? Put simply, what if it is different this time? That may well be the case. Much of the debate around the impact of AI is based on conjecture. There have been studies galore that have sought to estimate the number of jobs that will be affected - potentially running into the hundreds of millions globally - but nobody knows for sure. That said, certain conclusions can be drawn with a reasonable degree of confidence."

"A collaboration between Oxford University, The Education University of Hong Kong, Reading University and Durham University has found "no evidence to suggest abstaining from social media has a positive effect on an individual's well-being." The researchers noted that this contrasts popular beliefs about the benefits of digital detoxes. Moreover, this international study found that those who took a break from social media didn't replace online socializing with face-to-face, voice, or email interactions, as the researchers had expected. Taking a break from social media therefore led to reduced overall interaction and loneliness as social media was not replaced with forms of socializing."

"n a statement on his website, Eldagsen, who studied photography and visual arts at the Art Academy of Mainz, conceptual art and intermedia at the Academy of Fine Arts in Prague, and fine art at the Sarojini Naidu School of Arts and Communication in Hyderabad, said he "applied as a cheeky monkey" to find out if competitions would be prepared for AI images to enter. "They are not," he added. "We, the photo world, need an open discussion," said Eldagsen. "A discussion about what we want to consider photography and what not. Is the umbrella of photography large enough to invite AI images to enter - or would this be a mistake?"

"Their findings show that currently, only about 23 percent of wages paid for tasks involving vision are economically viable for AI automation. In other words, it's only economically sensible to replace human labor with AI in about one-fourth of the jobs where vision is a key component of the work. "

"However, this relationship between social media use and political polarization seems to depend a lot on duration of exposure and does not appear in all the samples surveyed. Thus, recent studies exploring the effects of stopping Facebook and Instagram use failed to observe that social media noticeably polarize users' political opinions. Let us always remember that narratives pointing to threats on society enjoy a considerable competitive advantage on the market of ideas and conversations, due to their attractiveness to our minds. One should thus approach the question of the relationship between social media, and political hostility and polarisation, by avoiding the symmetrical pitfalls of naive optimism and collective panic."

"Cancer diagnosis and management depend upon the extraction of complex information from microscopy images by pathologists, which requires time-consuming expert interpretation prone to human bias. Supervised deep learning approaches have proven powerful, but are inherently limited by the cost and quality of annotations used for training. Therefore, we present Histomorphological Phenotype Learning, a self-supervised methodology requiring no labels and operating via the automatic discovery of discriminatory features in image tiles. Tiles are grouped into morphologically similar clusters which constitute an atlas of histomorphological phenotypes (HP-Atlas), revealing trajectories from benign to malignant tissue via inflammatory and reactive phenotypes. These clusters have distinct features which can be identified using orthogonal methods, linking histologic, molecular and clinical phenotypes. Applied to lung cancer, we show that they align closely with patient survival, with histopathologically recognised tumor types and growth patterns, and with transcriptomic measures of immunophenotype. These properties are maintained in a multi-cancer study."

"Exposure to false and inflammatory content is remarkably low, with just 1% of Twitter users accounting for 80% of exposure to dubious websites during the 2016 U.S. election. This is heavily concentrated among a small fringe of users actively seeking it out. Examples: 6.3% of YouTube users were responsible for 79.8% of exposure to extremist channels from July to December 2020, 85% of vaccine-sceptical content was consumed by less than 1% of US citizens in the 2016-2019 period. Conventional wisdom blames platform algorithms for spreading misinformation. However, evidence suggests user preferences play an outsized role. For instance, a mere 0.04% of YouTube's algorithmic recommendations directed users to extremist content. It's tempting to draw a straight line between social media usage and societal ills. But studies rigorously designed to untangle cause and effect often come up short. "