The use of AI in public spaces continually raises concerns about privacy and the protection of sensitive data. An example is the deployment of detection and recognition methods on humans, where images are provided by surveillance cameras. This results in the acquisition of great amounts of sensitive data, since the capture and transmission of images taken by such cameras happens unaltered, for them to be received by a server on the network. However, many applications do not explicitly require the identity of a given person in a scene; An anonymized representation containing information of the person's position while preserving the context of them in the scene suffices. We show how using a customized loss function on region of interests (ROI) can achieve sufficient anonymization such that human faces become unrecognizable while persons are kept detectable, by training an end-to-end optimized autoencoder for learned image compression that utilizes the flexibility of the learned analysis and reconstruction transforms for the task of mutating parts of the compression result. This approach enables compression and anonymization in one step on the capture device, instead of transmitting sensitive, nonanonymized data over the network. Additionally, we evaluate how this anonymization impacts the average precision of pre-trained foundation models on detecting faces (MTCNN) and humans (YOLOv8) in comparison to non-ANN based methods, while considering compression rate and latency.

The Nvidia GeForce RTX 4080's slow-paced announcement and eventual launch has been… a fascinating road. From its mis-named little brother getting "unlaunched" to the RTX 4080 Founders Edition being the same size as the massive RTX 4090 for some reason, to the melting 12VHPWR power connectors--which are still on this card, yes. Nvidia has quite the PR battle with the $1,200 GeForce RTX 4080, but if you ignore all the noise, does this new card deliver the goods for content creators? Thankfully, performance-wise it does mostly live up to the hype; I just find myself wishing we had higher VRAM capacities on such expensive graphics cards. This review is focused on work, instead of play, similar to my recent RTX 4090 content creation analysis.

When the Nvidia GeForce RTX 4090 was announced with an eye-watering $1,600 price tag, memes spread like wildfire. While $1,600 is a little too much for most gamers to spend on a single component (most PC build budgets I see are less than that for the whole PC). I couldn't help but be intrigued at the potential performance improvements for my work--you know, the 3D and AI-accelerated tasks I spend most of my day doing as part of managing the EposVox YouTube channel, instead of gaming. Spoiler alert: The GeForce RTX 4090's content creation performance is magical. In quite a few cases, the typically nonsense "2X performance increase" is actually true.

In recent years, video compression techniques have been significantly challenged by the rapidly increased demands associated with high quality and immersive video content. Among various compression tools, post-processing can be applied on reconstructed video content to mitigate visible compression artefacts and to enhance overall perceptual quality. Inspired by advances in deep learning, we propose a new CNN-based post-processing approach, which has been integrated with two state-of-the-art coding standards, VVC and AV1. The results show consistent coding gains on all tested sequences at various spatial resolutions, with average bit rate savings of 4.0% and 5.8% against original VVC and AV1 respectively (based on the assessment of PSNR). This network has also been trained with perceptually inspired loss functions, which have further improved reconstruction quality based on perceptual quality assessment (VMAF), with average coding gains of 13.9% over VVC and 10.5% against AV1.

Internet-connected robots that can stream audio and video are increasingly helping housebound sick children and elderly people keep in touch with teachers, family and friends, combating the scourge of isolation and loneliness. Zoe Johnson, 16, hasn't been to school since she was 12. She went to the doctor in 2014 "with a bit of a sore throat", and "somehow that became A&E [accident and emergency]," says her mother, Rachel Johnson. The doctors diagnosed myalgic encephalomyelitis, ME for short, also known as Chronic Fatigue Syndrome - a debilitating illness affecting the nervous and immune systems. Zoe missed a lot of school but was able to continue with her studies with the help of an online tutor.

As a rule of thumb, the best ideas are the simplest. That's easy to forget in an age of rapid technological innovation, when the tendency is to be led by capability rather than need. For as Karen Dolva, co-founder of the Norwegian startup No Isolation, says: "There are a lot of engineers who don't want to make something useful – they want to make something cool." Dolva, a 26-year-old who studied computer science and interaction design at Oslo University, is not one of them. She and her two co-founders – Marius Aabel and Matias Doyle – are all about utility.