Yapay Zeka Destekli Bilgisayar Programları

Yapay Zeka Destekli Bilgisayar Programları 🤖💻 Yapay zeka (YZ) teknolojisi, bilgisayar programlarını daha akıllı ve kullanıcı dostu hale getiriyor. Hem iş dünyasında hem de günlük kullanımda verimliliği artıran bu programlar, karmaşık işlemleri kolaylaştırıyor. İşte yapay zeka destekli en popüler bilgisayar programları: 1. ChatGPT 🟪 Metin üretimi, yazılı içerik oluşturma ve sorulara yanıt verme konusunda güçlü

PDFs per ML taggen lassen – Adobe hat dafür eine durch maschinelles Lernen gestützte API angekündigt: „Adobe PDF Accessibility Auto-Tag API“.
Getaggtes PDF ist notwendig, um den barrierefreien Zugang zu den Inhalten von PDF-Dateien zu ermöglichen. Dies nachträglich händisch durchzuführen, ist mühsam.
Anwender, die eine Adobe-ID haben, können die Funktion testen. Als Download erhält man ein PDF/UA und eine Log-Datei.

#PDF #Tagging #Accessibility #AdobeSensei #ML #KI

https://acrobatservices.adobe.com/dc-accessibility-playground/main.html#

PDF Accessibility Auto-Tag API

Account Sharing: Adobe serviert Netflix die Lösung

Netflix möchte effektiv gegen Account-Sharing vorgehen, ohne Bestandskunden in die Flucht zu schlagen. Adobe bietet nun eine Lösung dafür.

Tarnkappe.info
Adobe After Effects is now (finally) native to Apple M1 and Photoshop gets Panasonic GH6 support

If you’re an Apple Silicon user that uses Adobe After Effects, you’ve probably Googled “when the hell will After Effects get M1 support?” at least a handful of times over the last couple of years. Even before writing this post, I did a quick search and found a bunch of Reddit and social media posts […]

DIY Photography

Adobe ‘Project In-Between’ Animates Still Photos Using AI

Every year as part of MAX, Adobe shares looks at technology that might make its way into future releases called "Sneaks." Project In-Between is one Such sneak, and can animate still photos by using Adobe's Sensei Artificial Intelligence (AI).

Adobe says that because cameras are capable of capturing so many photos in succession thanks to enhanced framerates and faster processors, many photographers will end up with multiple photos of the same scene as they attempt to capture just the right moment. Usually, all but the "perfect" photo in a sequence will be used, but Adobe decided that more could be done with those other images instead of throwing them out or leaving them on a hard drive to never be seen again.

Billed as a new way to "cherish" memories, Project In-Between is capable of taking two or more photos in a sequence and generating what the company calls an "animated bridge" between them. The result adds motion to photos that would otherwise be motionless.

The company says that the technology can work with as few as two photos but is also able to leverage short video clips to produce what it calls "silky smooth slow-motion footage" that can be watched over and over again.

These "living photos" are similar to other artificial intelligence-based animations that have come up in recent years but is among the first to draw animations together using multiple images in a sequence rather than adding animation to a single photo that may or may not have been part of the original capture. Adding moving lips to a still photo is one thing, but bringing a set of stills to life like they actually occurred is another.

Project In-Between is one of several Sneaks that the company showed off this morning during a live presentation. Another that may interest photographers is called Project Shadow Drop, which allows for more realistic shadow rendering by using 2D light positioning of the source and the horizon to automatically generate shadows in 2D vectors, 2D animations, or photos.

These two Sneaks join seven others, all of which can be viewed in greater detail on Adobe's blog.

#news #software #technology #adobe #adobemax #adobesensei #adobesneaks #ai #animation #artificialintelligence #projectinbetween

Adobe 'Project In-Between' Animates Still Photos Using AI

Making better use of multiple frames from a photo sequence.

Making Visual Search Smarter: How AI Understands Creative Intent

Most visual creations start with a search—for images, colors, fonts, and inspiration -- but search has always felt disconnected from the creative process. It can be tedious and time-consuming to translate brilliant, imaginative ideas into words.

Search terms rarely convey the aesthetics and emotions at the heart of a creative idea – which can make image search become a mind-numbing task when it should be inspiring. However, artificial intelligence (AI) and machine learning technology can fundamentally change the nature of search and help make creative visions a reality.

What AI-Powered Search Can Do, and What It Means For Creativity

With deep learning, search algorithms can be trained to better understand images to recognize objects—like cars, cats, humans, or even the Eiffel Tower—as well as colors, composition, style, and mood. Then, it can be broken down so people can search for any of these aspects, or combine search terms and components from multiple images. The result is a search that doesn’t just find something similar to a keyword or image—it finds something similar to the exact elements that are most meaningful to the searcher. Ultimately, search captures nuance and creative intent.

Search results showing images based on a “sunset” query that also includes a specific color palette

Here’s an example of how it works. Imagine you’ve just done a keyword search for an image of a gazelle. You have a trove of interesting gazelle photos, but none of them is quite right.

To hone in on what you need, you choose an image that’s close. Then, you can use image similarity search to find gazelle photos with similar colors, content, and composition to your original. You find the perfect lone gazelle, looking to the right, with a warm color palette.

But what if gazelles aren’t the only piece of your puzzle? You might also need a German shepherd in the same pose and location, so you change your keyword, but keep the composition constraints, which quickly takes you to images of a German shepherd that look remarkably like your gazelle -- your dog is front and center, looking right with warm colors.

“Find similar” image search results for a ‘German shepherd’ query based on an image of a gazelle looking to the right

As you can see, the combination of keywords with visual search for subtle aspects of an image allows the search engine to understand the nuances of your aesthetic and creative vision—far beyond what it could ever do with keywords alone.

Now, imagine that you want an image with a particular kind of object. Maybe you have a photo of a tent in the woods, but you want the tent further to the left, and out of the woods. You can click the tent, an object that machine learning technology can recognize, slide it where you need it, and search images with a tent in exactly the spot and scenery you desire. Eventually, you will even be able to engage several images in your search, choosing an object from one, the colors from another, and the composition from a third.

“Find similar” image search results of a tent in the forest, based on a sample image’s attributes (content, color and composition) “Find similar” image search results of a tent in the forest, based on a sample image’s position – with the tent being displayed on the left side

Looking ahead: How Search Will Create the Things We Imagine

The journey with AI and visual search is just beginning. As the tools become smarter, search and creation will come together in a complimentary way. Eventually, AI won’t just help us find things, it will generate what we’re actually seeking. The evolution of smarter search is like a dance—humans are
creating the data from which AI learns. Smarter tools, combined with the indelible spark of human creativity, will usher in new avenues for creative expression that we haven’t previously imagined.

For example, imagine you’re searching for an image of a person with an umbrella on a sunny day, but all the images you find are rainy days. Search will be able to apply machine learning to blend assets and create an image that never existed before—an image that’s exactly what you had in your imagination. Think of layering Photoshop-like magic to your search query and applying that to find the image you envisioned.

For creatives, visual search harnessing the power of AI means cutting out a lot of the grunt work and the frustrating, clumsy keywords. By doing this, the search becomes more deeply integrated into the creative side of the work, and people have more time free to devote to the innately human side of creativity—developing and exploring new ideas.

About the author: Scott Prevost is Vice President of Engineering for Adobe Sensei, where he oversees development of the company’s AI and machine learning (ML) technology powering the design and delivery of digital experiences. He has a long history of delivering AI/ML features and solutions for both consumer and enterprise products – from web-scale search to computer vision, and was a pioneer in the field of intelligent agents. Prior to Adobe, he was vice president of product management at eBay, responsible for the global search and buying experience. Scott began working in search at Powerset, a startup specializing in semantic search, which was acquired by Microsoft in 2008. Before eBay, Scott spent several years at Microsoft managing the integration of Powerset into Bing.

Image credits: Header image licensed via Deposit Photos.

#editorial #software #technology #adobe #adobesensei #adobestock #ai #aisearch #artificialintelligence #artificialintelligencesearch #machinelearning #scottprevost #search

Making Visual Search Smarter: How AI Understands Creative Intent

AI can make image search more intuitive and less of a mind-numbing drag.

Photoshopを学ぶ高校生の皆さんへ

Content Aware Scaling(コンテンツに応じた拡大・縮小)について

昨日のツイートで「保護用アルファチャンネル」を解説しました。
この写真の女性2人も、AI(Adobe Sensei)に参照領域を教えれば、完璧に保護してくれますよ!

#Photoshop #AdobeSensei #CCDojo
https://twitter.com/commonstyle/status/1099683870222344194?s=21

Mr. Creative.Edge @Adobe MAX + Adobe Sensei専用 on Twitter

“Photoshopを学ぶ高校生の皆さんへ Content Aware Scaling(コンテンツに応じた拡大・縮小)について 昨日のツイートで「保護用アルファチャンネル」を解説しました。 この写真の女性2人も、AI(Adobe Sensei)に参照領域を教えれば、完璧に保護してくれますよ! #Photoshop #AdobeSensei #CCDojo https://t.co/u0tz2ySSp0”

Twitter

これは楽しみ
今年は何が出るか
来年何が残って何が消えるか

この後 #AdobeMAX では #AdobeResearch で研究中の技術を披露する #Sneaks が始まります。 #AdobeSensei の最新のマジックが炸裂するか。最近の傾向としてはだいたい2年くらいで製品への採用が始まっている印象。今回のアートワークのテーマは90年代? #AdobePartner
https://twitter.com/taromatsumura/status/1052348090261225472?s=21

Taro Matsumura 松村太郎 on Twitter

“この後 #AdobeMAX では #AdobeResearch で研究中の技術を披露する #Sneaks が始まります。 #AdobeSensei の最新のマジックが炸裂するか。最近の傾向としてはだいたい2年くらいで製品への採用が始まっている印象。今回のアートワークのテーマは90年代? #AdobePartner”

Twitter
Photoshop CC 19.1にアップデート。「被写体を選択」は人工知能Adobe Senseiが被写体を自動で認識するというので試してみた。数クリックで、長崎駅前に池島で撮影したネコを寝転ばせることができた。 #adobe #adobesensei #photoshop #cat #アドビ先生
https://twitter.com/tomatoyasan/status/955820988377137152 https://mstdn-workers.com/media/vHujurZTGHbOEemIiYQ
飛騨トマト屋 on Twitter

“Photoshop CC 19.1にアップデート。「被写体を選択」は人工知能Adobe Senseiが被写体を自動で認識するというので試してみた。数クリックで、長崎駅前に池島で撮影したネコを寝転ばせることができた。 #adobe #adobesensei #photoshop #cat #アドビ先生”

Twitter