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Adobe Photoshop exclusive: clean up your old photos with just one click!

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Adobe's next downloadable Neural Filter for Photoshop, which is called'Photo Restoration' is about to be announced, and we've been given an exclusive first look. We attended last night's launch party and got a closer look at the Photo Restoration Neural Filter in action – it's designed for processing old photos, and essentially is a fast, AI-powered way to make them look brand new by removing imperfections and grain. And we do mean fast – the Photo Restoration Neural Filter doesn't really do anything that Photoshop couldn't already do, but the difference is simply that it does it in seconds, with just a single click. Taking the grunt work out of image editing, Photo Restorations will turn removing scratches, noise and other imperfections from old photos – a task that could easily take hours – into the work of a moment. This kind of wizardry is par for the course with Neural Filters, and why Photoshop CC ranks so highly in our guide to the best AI photo editing software.


Have You Heard? AI Can Edit Genes Now

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Artificial intelligence does all kinds of things….genomics Genetic engineering has always been a go-to plot twist in sci-fi movies and TV shows. The idea of genetically mutated humans with superior abilities and unique DNAs still has ripple effects on Marvel fans and box offices. But what if we can alter genes in real life? CRISPR gene editing has been doing that since 2012 (no Wolverine or Magneto though). In 2022, this powerful genetic engineering technique is complemented with artificial intelligence.


Editing a GAN's Latent Space With 'Blobs'

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New research from UC Berkeley and Adobe offers a way to directly edit the hyperreal content that can be created by a Generative Adversarial Network (GAN), but which can't usually be controlled, animated, or freely manipulated in a manner long familiar to Photoshop users and CGI practitioners. Titled BlobGAN, the method involves creating a grid of'blobs' – mathematical constructs that map directly to content within the latent space of the GAN. By moving the blobs, you can move the'objects' in a scene representation, in an intuitive manner that's nearer to CGI and CAD methods than many of the current attempts to map and control the GAN's latent space: Scene manipulation with BlobGAN: as the'blobs' are moved by the user, the disposition of latent objects and styles in the GAN are correspondingly altered. For more examples, see the paper's accompanying video, embedded at the end of this article, or at https://www.youtube.com/watch?v KpUv82VsU5k Since blobs correspond to'objects' in the scene mapped out in the GAN's latent space, all the objects are disentangled a priori, making it possible to alter them individually: Objects can be resized, shrunk, cloned, and removed, among other operations. Blobs can be duplicated in the interface, and their corresponding latent representations will also be'copied and pasted'.


How to Build an AI Fashion Designer

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This is a write-up for my old project ClothingGAN. The project generates clothing design with AI using StyleGAN and semantically edits it with attributes such as sleeve, size, dress, jacket, etc. You can also do style transfer as shown in the image above by first generating 2 different clothing designs (output 1) with different seed numbers. Then, it will generate a third design (output 2) that mixes the previous 2 designs. You can then adjust how much style or structure you want it to inherit from the two original designs.


Your Personal Photoshop Expert with AI!

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This new model by Google Research and Tel-Aviv University is incredible. You can see it as a very, very powerful deepfake that can do anything. Take a hundred pictures of any person and you have its persona encoded to fix, edit or create any realistic picture you want. This is both amazing and scary if you ask me, especially when you look at the results. The model simply uses a pertained StyleGAN architecture, which I covered in numerous videos so I won't enter into the detail of this network.


How Has Artificial Intelligence Impacted Video Editing?

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Artificial Intelligence has changed video editing dynamics significantly. It has affected the video editing industry, as with the help of AI, users can now effortlessly create and edit videos. AI technologies are now painless to access, and today anyone can use machine learning software. You will be amazed to know that for video marketing, AI has become one of the essential technologies and the most in-demand tool because of its unique features, such as abilities to react, sense, adapt, and act. With the help of AI technology, you will be able to produce videos using advanced in-house video editors as together, they can create short films within just a couple of minutes. The best thing about them is that you will not have to worry about music or other tools, as it immediately fixes all your editing problems.


Seven technologies to watch in 2022

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From gene editing to protein-structure determination to quantum computing, here are seven technologies that are likely to have an impact on science in the year ahead. Roughly one-tenth of the human genome remained uncharted when genomics researchers Karen Miga at the University of California, Santa Cruz, and Adam Phillippy at the National Human Genome Research Institute in Bethesda, Maryland, launched the Telomere-to-Telomere (T2T) consortium in 2019. Now, that number has dropped to zero. In a preprint published in May last year, the consortium reported the first end-to-end sequence of the human genome, adding nearly 200 million new base pairs to the widely used human consensus genome sequence known as GRCh38, and writing the final chapter of the Human Genome Project1. First released in 2013, GRCh38 has been a valuable tool -- a scaffold on which to map sequencing reads. This is largely because the widely used sequencing technology developed by Illumina, in San Diego, California, produces reads that are accurate, but short.


The top 10 tech trends we should be ready for now

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Bernard Marr* forecasts some of the advances in technology that will affect our lives, both at work and in the home, over the next few months. As a futurist, every year I look ahead and predict the key tech trends that will shape the next few months. There are so many innovations and breakthroughs happening right now, and I can't wait to see how they help to transform business and society in 2022. Let's take a look at my list of key tech trends that everyone should be ready for, starting today. Computing power will continue to explode in 2022.


These 2021 Biotech Breakthroughs Will Shape the Future of Health and Medicine

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With 2021 behind us, we're going down memory lane to highlight biotech innovations that shaped the year--with impact that will likely reverberate for many years to come. Covid-19 dominated the news, but science didn't stand still. CRISPR spun off variations with breathtaking speed, expanding into a hefty toolbox packed with powerhouse gene editors far more efficient, reliable, and safer than their predecessors. CRISPRoff, for example, hijacks epigenetic processes to reversibly turn genes on and off--all without actually snipping or damaging the gene itself. Prime editing, the nip-tuck of DNA editing that only snips--rather than fully cutting--DNA received an upgrade to precisely edit up to 10,000 DNA letters in a variety of cells.


Mixed feelings for artificial intelligence

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Do citizens see the development of artificial intelligence and human enhancement technologies as a possibility for a better society or is it a threat? The Pew Research Centre has made a study in the US comprising 10 260 adults and concludes that people think these technologies "have the potential to remake American society in the coming decades." Pew says that the survey shows Americans see promise in the way artificial intelligence and human enhancement technologies could improve daily life and human abilities. "Yet public views are also defined by the context of how these technologies would be used, what constraints would be in place and who would stand to benefit – or lose – if these advances become widespread." Ambivalence is a theme in the survey data: 45% say they are equally excited and concerned about the increased use of AI programs in daily life, compared with 37% who say they are more concerned than excited and 18% who say they are more excited than concerned.