Microsoft has pledged to clamp down on access to AI tools designed to predict emotions, gender, and age from images, and will restrict the usage of its facial recognition and generative audio models in Azure. The Windows giant made the promise on Tuesday while also sharing its so-called Responsible AI Standard, a document [PDF] in which the US corporation vowed to minimize any harm inflicted by its machine-learning software. This pledge included assurances that the biz will assess the impact of its technologies, document models' data and capabilities, and enforce stricter use guidelines. This is needed because – and let's just check the notes here – there are apparently not enough laws yet regulating machine-learning technology use. Thus, in the absence of this legislation, Microsoft will just have to force itself to do the right thing.
News that Alphabet Inc.'s Google sidelined an engineer who claimed its artificial intelligence system had become sentient after he'd had several months of conversations with it prompted plenty of skepticism from AI scientists. Many have said, via postings on Twitter, that senior software engineer Blake Lemoine projected his own humanity onto Google's chatbot generator LaMDA. Whether they're right, or Lemoine is right, is a matter for debate -- which should be allowed to continue without Alphabet stepping in to decide the matter.
A robotic arm with an attached microphone has learned how to locate noisy objects tossed into a bag, grabbing a set of keys by listening for the telltale clinking sound and picking out a crinkly bag of crisps sight unseen. "That environment is basically like you reach down, you don't know where the keys are, but then once you hear the sound of the keys you can kind of localise it," says Maximilian Du …
As a chemistry PhD student, Dmytro Kolodieznyi was used to running experiments. But in early 2018, his research advisers asked him to take part in one run by robots instead. They wanted Kolodieznyi, who was developing intracellular fluorescent probes at Carnegie Mellon University in Pittsburgh, Pennsylvania, to spend a month attempting to recreate his research at Emerald Cloud Lab (ECL). The biotechnology company in South San Francisco, California, enables scientists to perform wet-laboratory experiments remotely in an automated research environment known as a cloud lab. If the trial went well, it would help pave the way to the wider use of cloud labs at the university.
Teslas with partially automated driving systems are a step closer to being recalled after the U.S. elevated its investigation into a series of collisions with parked emergency vehicles or trucks with warning signs. The National Highway Traffic Safety Administration said Thursday that it is upgrading the Tesla probe to an engineering analysis, another sign of increased scrutiny of the electric vehicle maker and automated systems that perform at least some driving tasks. Documents posted Thursday by the agency raise some serious issues about Tesla's Autopilot system. The agency found that it's being used in areas where its capabilities are limited, and that many drivers aren't taking action to avoid crashes despite warnings from the vehicle. The probe now covers 830,000 vehicles, almost everything that the Austin, Texas, carmaker has sold in the U.S. since the start of the 2014 model year.
New legislation is expected to open the door to the use of facial recognition within a range of surveillance technologies in Ireland, including CCTV cameras and police body cams, automatic number plate recognition (ANPR or LPR in the U.S.), according to reports by the Irish Times. Backlash to the facial recognition element has been significant from civil society and academics. They find the move premature given the current stage of the EU AI Act and call for a moratorium on facial recognition technology. An amendment to the Garda Síochána (Digital Recording) Bill (Garda Síochána being the National Police), expected in the autumn after further scrutiny by government, will clarify the law in light of national and European Union legislation such as GDPR for these technologies to be used with face biometrics. It could be enacted by the end of the year.
As worker shortages are felt across the hospitality sector, the owners of the Bella Italia chain are turning to robots to provide table service to customers. Big Table Group, which also owns Café Rouge and Las Iguanas, is testing out the robot at its Bella Italia restaurant in Center Parcs Whinfell Forest in Cumbria, in the first such trial by a big restaurant chain. The BellaBot, made by Chinese company Pudu, can carry up to 40kg on four trays and deliver and retrieve plates from tables with help from humans who load and unload its "body". Eric Guo, the chief executive of Spark which distributes Pudu robots in the UK, said there were 60 working across 20 British businesses and he expected more orders in the year ahead. Most are operating in restaurants, but hotels, supermarkets, care homes, snooker clubs and bowling alleys are also experimenting with the technology.
US regulators expanded a probe into Tesla's "Autopilot" system, moving the investigation closer to a potential recall of a controversial feature in Elon Musk's electric vehicles. The National Highway Traffic Safety Administration is investigating whether "Autopilot and associated Tesla systems may exacerbate human factors or behavioral safety risks by undermining the effectiveness of the driver's supervision," according to a summary statement. The agency now considers the probe an "engineering analysis" -- which in NHTSA parlance upgrades the status from a "preliminary evaluation" -- to determine "whether a safety recall should be initiated or the investigation should be closed." Tesla did not immediately respond to a request for comment. NHTSA opened the probe in August 2021 after identifying 11 crashes involving a first responder vehicle and a Tesla in which Autopilot or Traffic Aware Cruise Control was engaged, and five additional cases were later found that fit into this group.
With the intensification of ecosystem damage, birds have become the symbolic species of the ecosystem. Ornithology with interdisciplinary technical research plays a great significance for protecting birds and evaluating ecosystem quality. Deep learning shows great progress for birdsongs recognition. However, as the number of network layers increases in traditional CNN, semantic information gradually becomes richer and detailed information disappears. Secondly, the global information carried by the entire input may be lost in convolution, pooling, or other operations, and these problems will weaken the performance of classification. In order to solve such problems, based on the feature spectrogram from the wavelet transform for the birdsongs, this paper explored the multi-scale convolution neural network (MSCNN) and proposed an ensemble multi-scale convolution neural network (EMSCNN) classification framework. The experiments compared the MSCNN and EMSCNN models with other CNN models including LeNet, VGG16, ResNet101, MobileNetV2, EfficientNetB7, Darknet53 and SPP-net. The results showed that the MSCNN model achieved an accuracy of 89.61%, and EMSCNN achieved an accuracy of 91.49%. In the experiments on the recognition of 30 species of birds, our models effectively improved the classification effect with high stability and efficiency, indicating that the models have better generalization ability and are suitable for birdsongs species recognition. It provides methodological and technical scheme reference for bird classification research.