Xiaomi Es posible que pronto permita jugar juegos de PC con Windows en su línea de PC Androide Las tabletas, según un adelanto reciente que la compañía compartió en las redes sociales. Se dice que se está probando un nuevo sistema llamado WinPlay que brinda soporte para juegos de Windows en tabletas Xiaomi. Aunque aún está en desarrollo, Xiaomi dice que su motor WinPlay solo resultará en una pérdida marginal en el rendimiento de la GPU al jugar. Supuestamente también es compatible con Steam y su gran repositorio de juegos de PC.
El sistema WinPlay se prueba en Xiaomi Pad 6S Pro 12.4
La compañía mostró su motor WinPlay en una publicación en Weibo, la plataforma de redes sociales china. Xiaomi afirma que esto produce sólo una pérdida del 2,9 por ciento en términos de rendimiento de la GPU al jugar. Dado que está en desarrollo, Xiaomi está reclutando probadores voluntarios en China para utilizar su motor. Actualmente, este programa está limitado a iPad 6S Pro Propietarios. El dispositivo funciona con el chipset Snapdragon 8 Gen 2 de Qualcomm y está emparejado con hasta 16 GB de RAM y hasta 1 TB de almacenamiento UFS 4.0.
WinPlay Engine funciona con HyperCore de Xiaomi, una plataforma de tecnología de núcleo central de desarrollo propio que, según se afirma, mejora el rendimiento, los gráficos, la red y la seguridad. Fue pie Con el sistema operativo Android 15 de la compañía hiperOS 2 En octubre.
La arquitectura del kernel de la compañía presenta un programador de microarquitectura patentado, que puede reducir el tiempo de inactividad de la CPU en un 19 por ciento. Además, da como resultado velocidades de inicio de aplicaciones hasta un 54,9 por ciento más rápidas en teléfonos inteligentes al mejorar los ciclos de tareas y los tiempos de acceso a la memoria.
HyperCore es desarrollado por un equipo de más de 3000 ingenieros para lograr la optimización de más de 25 000 escenarios.
Xiaomi dice que su motor WinPlay admitirá esto vapor Y su propia biblioteca de juegos. Sin embargo, aún se desconoce si también se admitirán otras tiendas, como Epic Games Store y GOG.
Intel La compañía lanzó el martes sus unidades de procesamiento de gráficos (GPU) de la serie Arc B. Las nuevas GPU, con nombre en código Battlemage, apuntan a precios accesibles para creadores y jugadores, permitiéndoles jugar juegos populares con una resolución de hasta 1440p y a más de 60 fotogramas por segundo, según el fabricante de chips estadounidense. La Serie B incluye dos modelos de GPU llamados Intel Arc B580 y Arc B570, los cuales admiten funciones como la tecnología de escalado XeSS 2, generación de fotogramas y trazado de rayos acelerado por hardware.
Precio y disponibilidad de las GPU Intel Arc serie B
La tarjeta gráfica Intel Arc B580 también lo será disponible De socios de placa adicionales como Acer, ASRock, GUNNIR, ONIX Technology, MAXSUN y Sparkle a partir del 13 de diciembre a un precio inicial de $249 (aproximadamente Rs. 21,000).
Mientras tanto, la GPU Intel Arc B570 se podrá comprar a partir del 16 de enero a un precio inicial de 219 dólares (aproximadamente 19.000 rupias).
Especificaciones de la GPU Intel Arc serie B
Intel dice que las nuevas GPU de la serie Arc B ofrecen hasta un 70 por ciento mejor rendimiento por núcleo Xe y hasta un 50 por ciento mejor rendimiento por vatio en comparación con la generación anterior. Ambas GPU se basan en la última arquitectura Xe2 de Intel utilizando el proceso de fabricación N5 de TSMC. ellos apoyan inteligencia artificial (AI) y aproveche los controladores Intel Xe Matrix Extensions (XMX).
La compañía dice que XeSS 2 incluye tres tecnologías clave: XeSS Supersolution, XeSS Frame Generation y Xe Low Latency. XeSS Supersolution proporciona ampliación impulsada por IA con soporte para más de 150 juegos. Mientras tanto, XeSS Frame Generation aprovecha la IA para agregar fotogramas interpolados con la ayuda del flujo óptico y la proyección vectorial. Por otro lado, Xe Low Latency está integrado con el motor del juego para ofrecer respuestas de entrada más rápidas.
La GPU Intel Arc B580 está equipada con 20 núcleos Xe de segunda generación y 20 unidades de trazado de rayos. Según la compañía, tiene una velocidad de reloj máxima de 2670MHz y está equipado con 12GB GDDR6 VRAM con un ancho de banda de memoria de 456GB/s. Tiene una potencia total de placa (TBP) de 190W y una potencia aritmética de 233 billones de operaciones por segundo (TOPS).
Mientras tanto, el Intel Arc B570 tiene 18 núcleos Xe y 18 módulos de trazado de rayos. Viene con 10 GB de memoria DDR6, ancho de banda de memoria de 380 GB/s y una velocidad de reloj máxima de 2500 MHz. Su potencia informática máxima es de 203 TOPS con 150 W TBP.
Las GPU de la serie B, combinadas con el software Intel Graphics, brindan acceso a una variedad de configuraciones de pantalla, como modos de color y escala y compatibilidad con frecuencia de actualización variable (VRR).
Google is paying Apple a lot to be Safari’s default search engine. Photo: Rajesh Pandey/Cult of Mac
Google paid Apple $20 billion for Google to remain the default search engine across all Apple devices. This figure came to light through court documents submitted in the US Justice Department’s lawsuit against Google.
During the course of the hearing, Google and Apple tried their best not to reveal the amount publicly.
Apple prefers Google because it is the best
An October 2023 report also estimated Apple receiving $18-$20 billion from Google in 2022. This time around, the documents reveal the exact figure of $20 billion, coming directly from Apple’s SVP of services, Eddy Cue.
The Bloomberg report details that during last fall’s trial, Apple said Google paid them “billions” to be the default search engine. A Google witness later accidentally testified that the company pays Apple 36% of the revenue from search ads.
While it is vital for Google to remain the default search engine on iPhone and Mac, the money also plays a big role in Apple’s bottom line. As per the document, Google’s payment accounted for 17.5% of Apple’s revenue.
However, as Eddy Cue testified during the hearing, Apple prefers Google not because of the billions of dollars it receives but because it is “the best.”
During the trial last year, Microsoft CEO Satya Nadella revealed that it was offering Apple multiple concessions to move away from Google. These include sharing 90% of the advertising revenue and hiding the Bing logo in Safari on iPhone. The switch would have been “game changing,” which is why Microsoft was willing to make these concessions.
Google’s deal with Apple could put it into trouble
Given the iPhone’s popularity in the US, it’s crucial for Google to remain the default search engine on the devices. This also explains why Google paid Apple more than $1.5 billion monthly in 2022. But this move will now probably get the company into trouble.
If the US Justice Department wins its lawsuit against Google’s alleged monopoly in search and advertising, the latter might have to cancel its deal with Apple.
Google and the Justice Department will submit their closing arguments on Thursday and Friday. The court’s final decision will arrive later this year.
Google paid Apple $20 billion in 2022 to be the default search engine for Safari on iPhone, iPad, and Mac, reports Bloomberg. The information was revealed in court documents Google provided in its antitrust dispute with the United States Department of Justice.
The DoJ has accused Google of having a monopoly on search, and in the lawsuit against Google, the search engine deal with Apple has been a major focus. In November, lawsuit documents indicated that Google was paying 36 percent of the total revenue that it earns from searches conducted on Safari, and now it turns out that equates to $20 billion.
Google has been the default search engine on Apple devices since 2002, though the deal has been renegotiated several times. Apple and Google have worked to keep the terms of the search engine agreement under wraps during the trial and before, but it has been well known that Google is paying Apple billions per year.
Last October, Microsoft CEO Satya Nadella testified that the agreement between Apple and Google has made it impossible for search engines like Bing to compete. Microsoft at one point wanted Apple to buy Bing, but Apple was not interested. Microsoft blamed Google, but Apple’s Eddy Cue said that Aplple was concerned that Bing could not compete in “quality and capabilities.” Cue claimed that Apple uses Google as the iPhone’s default search engine because Apple has “always thought it was the best.”
Google is the default search engine on Apple devices in most countries, but users can opt to swap to Yahoo, Bing, DuckDuckGo, and Ecosia as alternatives. Changing browser engines requires opening up the Safari settings.
In Europe, the Digital Markets Act has required Apple to make changes to how browsers work. Users are able to choose a default browser when setting up their iPhone, and there are more options than the handful of providers that Apple allows in the United States.
If Google loses the antitrust lawsuit against it, the deal between Apple and Google could be dissolved. Closing arguments are expected on Thursday and Friday, with the judge’s ruling set to come later in 2024.
In today’s digital landscape, where time is of the essence, a new tool with investment from Amazon’s Jeff Bezos, NVIDIA and others is making waves by providing quick and precise answers to our questions in a more comprehensive way when compared to search engines such as Google. Perplexity AI stands out as a sophisticated AI answer engine that cuts through the clutter of traditional search engines. Instead of presenting you with a list of links to sift through, it directly serves up the information you’re looking for, making your quest for knowledge smoother and more efficient.
Imagine typing a question into a search bar and getting an immediate, accurate answer complete with links to references where you can dig deeper into certain topics and see the credibility of the sources. That’s the promise of Perplexity AI, which uses the power of artificial intelligence to understand and respond to your queries. This technology is not only fast but also smart, giving you the answers you need without the hassle of clicking through multiple web pages. It’s a time-saver that allows you to concentrate on the important stuff.
Trust is key when it comes to information, and Perplexity AI doesn’t disappoint. Every answer it provides comes with source citations, so you can be sure the information is reliable. The engine draws from a diverse pool of reputable sources, giving you peace of mind about the credibility of the answers you receive. Perplexity’s Copilot feature provides a guided Al search experience, allowing you to explore topics in depth and learn new things.
Ease of use is another hallmark of Perplexity AI. The interface is clean and straightforward, making it accessible to users of all skill levels. Whether you’re a tech novice or a seasoned pro, you’ll find navigating the platform to be a breeze. The design is focused on providing a seamless search experience, free from frustration.
How to get the best results from Perplexity AI
“Perplexity is your AI-powered Swiss Army Knife for information discovery and curiosity. It’s not just about answering questions; it’s about empowering you to do more—whether you’re looking to summarize content, explore new topics, or even get a little creative.”
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When you compare Perplexity AI to traditional search engines, the difference in efficiency is clear. It’s optimized to grasp the context of your questions and deliver specific answers, minimizing the need for additional searches. This means you get what you need with just a few clicks, saving you time and effort.
AI answer engine
For those who need to dig deeper, Perplexity AI has advanced search options that are particularly useful for students and researchers. You can look up academic papers or ask follow-up questions, allowing for a more thorough exploration of your topic. This can greatly enhance your research process, providing a richer understanding of the subject matter.
The platform also includes interactive features that add another layer to your search experience. The co-pilot feature acts as a personal guide, offering tailored responses and helping you refine your searches. If you’re working on a complex project, the collections feature lets you group related questions and answers, making it easier to organize your findings.
Collaboration and knowledge sharing are essential in today’s interconnected world, and Perplexity AI supports this by allowing you to share your discoveries with others. Whether you’re working with colleagues or want to post your findings on social media, the platform makes it simple. There’s even a discovery section where you can find the latest news and content that aligns with your interests.
Accessibility is a priority for Perplexity AI, which is why it offers a free license with basic features. For those with more advanced search needs, there’s a Pro Plan that provides additional tools and functionalities to further enhance your information retrieval experience.
Perplexity AI is making a significant impact on how we search for information. It sets itself apart with its ability to deliver direct answers, backed by credible sources, all within a user-friendly interface. With options to suit various needs, interactive features for comprehensive research, and plans for every type of user, Perplexity AI is well-equipped to meet the demand for fast, accurate, and trustworthy information. Whether you’re a casual browser or a dedicated researcher, this tool is poised to streamline your search for knowledge. More information on getting started with the Perplexity AI answer engine jump over to the official website.
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Since the launch of the OpenAI GPT Store earlier this month thousands of custom GPTs have been made available for ChatGPT Plus, Team and Enterprise users to adopt to improve their productivity and workflows. One such custom GPT that has taken the GPT store by storm is Consensus a search engine that uses AI to find insights in research papers.
Searching for vetted, unbiased information use to be a long been an arduous and painful process. Consensus has been specifically designed to change this harnessing the power of artificial intelligence. Whether you are a lifelong researcher or an everyday consumer, Consensus aims to be your go-to source in the search for expert knowledge.
Consensus GPT
The Consensus GPT provides an easy way to refine the way we seek out and validate scientific knowledge. ChatGPT’s Consensus custom GPT is a sophisticated search engine that is quickly becoming an essential resource for researchers, students, and professionals who require reliable, science-based information. Unlike traditional search engines, Consensus is designed to cater specifically to research-oriented inquiries, providing answers that are not just accurate but deeply rooted in scholarly work.
The integration of Consensus into the ChatGPT OpenAI Store has been met with enthusiasm from the academic community. Its ability to draw from an expansive database of over 200 million academic papers makes it a standout tool for anyone looking to support their research with authoritative sources. The feature’s popularity stems from its unique capability to deliver answers that are backed by scientific research, ensuring that users have access to the most credible information available.
How to use the Consensus custom GPT
To begin using Consensus, one must access the feature through the OpenAI Store. The key to harnessing the full potential of this tool lies in posing clear and concise questions. The precision of the questions asked directly influences the accuracy and comprehensiveness of the answers provided. Academic research papers, which form the backbone of Consensus’s database, are typically subjected to a stringent peer-review process. By leveraging these documents, Consensus offers direct quotations that not only enhance the credibility of your research but also ensure that your citations are precise.
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Navigating Consensus is straightforward, even for those with minimal technical expertise. Once inside the ChatGPT interface, users can input their queries and expect to receive responses that are grounded in scientific evidence. The system is adept at sifting through its vast database to present information that is not only pertinent but also up-to-date with the latest research findings.
For inquiries that extend beyond the scope of academic literature, Consensus also incorporates Bing to facilitate broader searches. This integration provides users with a more comprehensive search experience, ensuring that all possible avenues of information are explored.
Direct quotes for academic papers
One of the most significant advantages of using Consensus is its ability to provide direct quotes from academic papers. This feature is particularly beneficial for those who require exact citations, as it helps maintain the integrity of their work and ensures that the information used is accurate.
Crafting effective questions is crucial when using Consensus. The specificity of a query leads to more targeted and definitive answers. The tool is engineered to keep searches focused and relevant, ensuring that the information provided is not just accurate but also directly related to the user’s inquiry. Consensus GPT allows users to find answers, search for papers, and draft content grounded in scientific research by searching our database of 200M+ papers directly within the ChatGPT interface.
ChatGPT’s Consensus feature is a powerful resource that can significantly enhance the research process. By tapping into a vast repository of academic knowledge, users can secure science-based answers that will elevate the quality of their research endeavors. Whether you are a seasoned researcher or a student just beginning to navigate the world of academic inquiry, Consensus offers a reliable and efficient way to access the wealth of scientific knowledge that is available at our fingertips. With its intuitive design and robust database, Consensus is poised to become an indispensable tool for anyone seeking to substantiate their research with solid, scholarly evidence.
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If you are interested in chess or perhaps coding and programming your very own chess engine. You are sure to enjoy this quick guide and overview provided by Bartek Spitza. Programming a chess engine or chess computer is a complex task that necessitates a profound understanding of both chess and computer science. This process involves a series of meticulously planned steps, each contributing significantly to the overall functionality, efficiency, and effectiveness of the chess program.
The initial step in this intricate process is the representation of the chessboard and its pieces. This is achieved using a method known as the Bitboard technique. This technique uses a 64-bit integer to represent the chessboard, with each bit in the integer corresponding to a square on the chessboard. This provides a compact and efficient representation of the game state, offering a clear and concise snapshot of the current state of play.
How to build an AI chess engine from scratch
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The Evaluation Function and Piece Value Assignment
After accurately representing the chessboard and its pieces, the next step involves evaluating the game’s state. This is done using an evaluation function, a vital component of the program that assesses a position’s strength. The function assigns numerical values to each chess piece, considering their worth in the game. For example, a queen, due to its superior mobility and power, might be assigned a higher value than a pawn.
Position Adjustment and Strength
The evaluation function also considers the pieces’ position on the board, a factor known as position adjustment. A piece’s value can change depending on its location on the board. For instance, a knight positioned on the board’s edge is less valuable than a knight situated in the center because it has fewer potential moves, thus limiting its potential game impact.
Identifying the Optimal Chess Move
Minimax Algorithm and Game Tree Search
The program uses the minimax algorithm to identify the best possible move. This algorithm works by searching down the game tree, considering all possible moves and their potential outcomes. It operates under the assumption that the opponent will always make the move that minimizes the player’s maximum advantage, thereby ensuring the most strategic move is chosen.
Alpha-Beta Pruning: Enhancing the Search Process
To further enhance the search process, the program employs the alpha-beta pruning technique. This algorithm prunes, or eliminates, branches of the game tree that do not need to be searched because they cannot possibly influence the final decision. This significantly reduces the number of nodes that the program needs to evaluate, thereby increasing its efficiency and speed.
Predicting the Strategy
Recursion and Opponent’s Potential Moves
The program also uses recursion, a programming technique where a function calls itself, to explore the opponent’s potential moves. This allows the program to predict the opponent’s strategy and make the best possible move in response, providing a strategic advantage.
Optimizing and Refining the Chess Engine
While the program is already efficient due to the use of the minimax algorithm and alpha-beta pruning, there is always scope for further optimization. This could involve refining the evaluation function or implementing more advanced search techniques, thereby enhancing the program’s ability to compete effectively.
Programming a chess computer is a challenging task that requires a deep understanding of both chess and computer science. However, with the right techniques and algorithms, it is possible to create a program that can compete with human players at a high level. For further insights into the alpha-beta algorithm, consider watching a video by Sebastian Lague, a renowned programmer and chess enthusiast. Additionally, the Wikipedia page on chess programming provides a wealth of information on this fascinating subject, offering a comprehensive overview of the process and the techniques involved.
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If you are searching for a way to expand your creativity with Unreal Engine 5, it might be worth your while checking out Project Avalanche. Which stands out for its ability to combine 2D and 3D assets in real-time, a feature reminiscent of the combined capabilities of Cinema 4D and After Effects. This real-time operation not only enhances the efficiency of the creative process but also opens up new possibilities for dynamic and immersive motion graphics. The toolset also boasts a robust geometry toolset, providing users with extensive control over solids, and the ability to import and manipulate SVG files, giving users complete control over logos or other imported items.
Project Avalanche
In the realm of motion graphics, Project Avalanche offers creators a unique toolset designed specifically for motion. Built within the powerful Unreal Engine 5, Project Avalanche offers a wide range of features and capabilities that can enhance the creative process and open up new possibilities for dynamic and immersive motion animations and graphics.
Project Avalanche also boasts a robust geometry toolset, providing users with extensive control over solids. This feature allows artists to manipulate the shape, size, and orientation of solid objects, enabling them to create intricate designs and complex visual effects.
New UE5 motion graphic tools
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Another noteworthy feature of Project Avalanche is its ability to import and manipulate SVG files. This feature gives users complete control over logos or other imported items, allowing them to adjust and modify these elements to fit their specific project requirements. This is particularly useful for branding and logo animation projects, where precise control over the visual elements is crucial. The timeline in Project Avalanche has been modified to be more intuitive for motion graphics artists. This modification allows artists to easily track and adjust the timing of their animations, making the animation process more efficient and user-friendly.
Unreal Engine 5
Project Avalanche also includes an autosize text feature, which allows users to set parameters for text size that can be easily adjusted. This feature simplifies the process of text animation, making it easier for artists to create dynamic and engaging text-based motion graphics. The toolset also features a layer-based system for material stacking, similar to systems used in Photoshop and Illustrator. This system allows users to stack different materials on top of each other, creating complex textures and visual effects.
Project Avalanche also includes cloners and effectors, providing users with creative control over their designs. These tools allow artists to duplicate and modify elements in their designs, creating complex patterns and structures. Together with a font selector, making it easier for users to change fonts within the Unreal Engine. This feature simplifies the process of text design, allowing artists to easily experiment with different fonts and typography styles.
Project Avalanche is a powerful and versatile toolset for motion graphics artists. Its wide range of features and capabilities, combined with the power of Unreal Engine 5, make it a valuable tool for any motion graphics artist. Whether you’re a seasoned professional or a beginner in the field, Project Avalanche offers a range of tools and features that can enhance your creative process and help you create stunning motion graphics.
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At the Adobe MAX 2023 creativity event, Adobe unveiled a slew of innovative technologies and features that have the potential to transform the way we interact with digital content. Among the highlights of the event were the introduction of Project Stardust, an AI-powered object-aware editing engine, and a host of new generative AI capabilities that span across photo, video, audio use cases, and 3D, design, and fashion applications.
In addition to Project Stardust, Adobe also showcased 11 early-stage innovations, including a range of new generative AI capabilities. These capabilities are powered by Adobe Firefly, Adobe’s family of creative generative AI models, which is now commercially available. The commercial availability of Adobe Firefly expands the range of new applications beyond image generation, further enhancing the creative possibilities for users.
Among the new generative AI capabilities showcased at the Adobe MAX 2023 conference was Project See Through, an AI-powered tool that simplifies the process of removing reflections from photos. This tool has the potential to significantly streamline the photo editing process, enabling users to create high-quality images with less effort.
Another notable innovation was Project Fast Fill, which brings the power of Firefly generative AI to video. This technology offers an early look at what human-prompted generative AI could enable inside Adobe video editing tools. It’s a promising development that could revolutionize the way we edit and produce video content.
Highlights from the Adobe Max 2023 conference
Adobe photo innovations
Project Stardust is a powerful new object-aware editor that revolutionizes image editing and magically moves or removes objects simply by clicking on them. With Project Stardust, users can easily select, edit and delete complex elements in any image – enabling them to select persons in a photograph, move them to a different place in the composition and fill in the background where they were previously standing. Users can also change elements like the color of a person’s clothing and the position in which they’re standing – treating any image like a file with layers.
Project See Through is an AI-powered tool that makes it simple to remove reflections from photos. Glass reflections are an annoyance that everyone is familiar with in photos, obscuring the subject of the image, and often making it unusable. Though it’s difficult if not impossible to remove reflections using existing software, See Through dramatically simplifies the process.
Adobe video and audio
Project Fast Fill brings the power of Firefly generative AI to video for the first time. Leveraging Generative Fill technology – which Adobe Photoshop already uses to ease the addition, removal, or expansion of content in images with simple Firefly-powered text prompts – Project Fast Fill offers an early look at what human-prompted generative AI could enable inside Adobe video editing tools including Premiere Pro and After Effects.
Project Dub Dub Dub automates the video dubbing process, making a historically labor- and cost-intensive process as easy as clicking a button. Thanks to Project Dub Dub Dub’s AI capabilities, a recording or audio track of a video can be automatically translated to all supported languages while preserving the voice of the original speaker, temporally aligned with the original dialogue and ready to publish.
Project Scene Change makes it easy for video editors to composite a subject and scene, from two separate videos captured with different camera trajectories, into a scene with synchronized camera motion.
Project Res Up is a tool that easily converts video from low- to high-resolution using innovative diffusion-based upsampling technology.
Design projects teased by Adobe
Project Poseable represents a breakthrough in AI-based image generation models, making it easy for the image generator to seamlessly interact with large 3D objects, including poses from photos of real people. The prototype is integrated with Project Poseable which can create a 3D rendering from text input, take depth and perspective into consideration, and re-align the object. While creating 3D scenes with traditional skeletal systems is technically complex and time-consuming, Project Poseable offers an effortless alternative that makes it possible for anyone to expand their creative horizons.
Project Neo enables creators to incorporate 3D shapes in their 2D designs – all without requiring technical expertise in 3D creation tools. Today, creators of 2D designs such as infographics, posters, or logos are often limited in their ability to incorporate 3D elements given the complexity of those workflows, which can require years of experience. Project Neo enables creators to embrace simplified 3D design within 2D tools and methods.
Project Primrose blurs the line between technology and fashion, demonstrating the potential for flexible textile displays – and turning clothes into creative canvases. This interactive dress can offer infinite style possibilities, displaying content created with Adobe Firefly, After Effects, Stock,and Illustrator.
Project Glyph Ease makes customized lettering more accessible by streamlining the tedious design process of glyphs – the specific design and shape elements of each letter character. Beginning with a hand-drawn letter shape, Project Glyph Ease uses AI to automatically generate an entire set of glyphs matching the input lettering style. Users can then easily edit the generated glyphs in Illustrator.
Project Draw & Delight offers a suite of generative AI tools that helps anyone along their creation journey, from transforming initial ideas – often represented as rough doodles or scribbles – into polished and refined sketches, then experimenting with color palettes, style variations and different backgrounds.
Source : Adobe
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As well as unveiling a wealth of AI features it has rolled out to its suite of image and video applications. Adobe also teased projects that it is currently working on perhaps for a future release. As well as innovations in other areas such as the innovative interactive dress known as Project Primrose.
One of Adobe’s showcased future projects is Stardust, an object-aware editing engine that leverages artificial intelligence (AI) and generative AI to revolutionize the image editing process. This groundbreaking technology is designed to automate some of the most time-consuming aspects of image editing, such as filling in backgrounds, cutting out outlines for selection, blending lighting and color, and more.
Adobe Project Stardust
Project Stardust’s object-aware editing engine is a game-changer in the field of image editing. Unlike traditional image editing software like Adobe Firefly, which allows for object-specific modifications, Project Stardust takes this concept a step further. It offers a more automated and AI-driven approach, understanding the objects within an image and allowing for specific manipulations like cutting out outlines for selection. This object-awareness is a significant leap forward in image editing technology, enabling users to make precise modifications with ease and efficiency.
AI object-aware editing engine
“Project Stardust is an object-aware editing engine that uses artificial intelligence and generative AI to revolutionize image editing. This technology automates sometimes time-consuming parts of the image editing process — filling in backgrounds, cutting out outlines for selection, blending lighting and color, and more. In addition, the generative AI features let you add objects and make creative transformations. Stardust makes image editing more intuitive, accessible and time efficient for any user, regardless of skill level.”
“Aya Philémon is a product manager at Adobe who aims to empower others to make the most of their creative potential. Her research projects are inspired by both her professional and personal life experiences.”
Object-Awareness: The engine understands the objects within an image, allowing for specific manipulations like cutting out outlines for selection.
Generative AI Features: It goes beyond mere editing to generate new elements within the image, such as adding objects or creatively transforming existing ones.
Automation: The tool automates labor-intensive tasks like filling in backgrounds, blending lighting, and adjusting color, which speeds up the editing process.
Accessibility: It aims to be intuitive and user-friendly, making advanced image editing accessible to users of all skill levels.
But Project Stardust doesn’t stop at mere editing. It also incorporates generative AI features, which go beyond simple modifications to generate new elements within the image. This could include adding objects or creatively transforming existing ones. These generative AI features open up a world of creative possibilities, allowing users to make unique and imaginative transformations to their images.
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Automation and accessibility
One of the most significant advantages of Project Stardust is its automation capabilities. The tool is designed to automate labor-intensive tasks like filling in backgrounds, blending lighting, and adjusting color. This automation not only speeds up the editing process but also reduces the potential for human error, resulting in a more seamless and efficient editing experience.
Perhaps one of the most exciting aspects of Project Stardust is its accessibility. The tool aims to be intuitive and user-friendly, making advanced image editing accessible to users of all skill levels. This accessibility is a testament to Adobe’s commitment to democratizing image editing, making it more accessible and intuitive for everyone, regardless of their skill level.
Adobe’s Project Stardust represents a significant advancement in image editing technology. Its object-aware editing engine, generative AI features, automation capabilities, and accessibility make it a powerful tool for anyone involved in image editing. Whether you’re a professional graphic designer or a hobbyist looking to enhance your photos, Project Stardust promises to make the image editing process more intuitive, accessible, and time-efficient.
What is an AI object-aware editing engine?
An AI object-aware editing engine is a software algorithm that uses artificial intelligence to identify and segregate different objects within a given visual medium. This enables more targeted editing capabilities. For example, in a photo containing people, animals, and landscapes, the engine could automatically recognize and isolate these elements so that the user can manipulate them independently. You could change the color of just the sky, blur only the background, or apply a filter to a specific person’s face, all without affecting other parts of the image.
In the video editing context, this engine could identify moving objects from frame to frame, allowing the user to apply edits to a specific object throughout the entire video clip without manually tracking it. The object-aware engine would automate the tedious task of frame-by-frame editing, making it easier for editors to create complex visual effects or adjustments. Overall, the engine would make the editing process more efficient and intuitive, letting users focus on creativity rather than technical details.
As soon Adobe releases more details on its new Project Stardust AI object-aware editing engine we will keep you up to speed as always. In the meantime you can check out all the new features that have been rolled out to Adobe Firefly.
Filed Under: Technology News, Top News
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