Hoja de estrellaun título de acción y aventuras del estudio coreano cambiar hacia arribabajo consideración para computadora Se lanzará en 2025, dijo el desarrollador en su último informe de resultados financieros del martes. El juego se lanzó exclusivamente en PS5 en abril y ha vendido más de un millón de copias hasta junio. Shift Up también informó una ganancia operativa de KRW 36 mil millones (alrededor de Rs 216 crore) en el tercer trimestre, incluso cuando las ventas de Stellar Blade disminuyeron en comparación con el trimestre anterior.
Stellar Blade se lanza para PC en 2025
Shift Up reiteró sus planes de expandir la plataforma Stellar Blade y dijo que espera que el juego tenga un mejor rendimiento comercial en PC. En la sección de preguntas y respuestas Convocatoria de resultados del tercer trimestre del año fiscal 2024La compañía dijo que está considerando el lanzamiento de Stellar Blade en PC en 2025.
“Se está considerando el lanzamiento en 2025. Teniendo en cuenta las tendencias recientes, como la creciente participación de mercado de Steam en el segmento de juegos AAA y el éxito global de Leyenda Negra: Wukong“Esperamos que el rendimiento en PC supere al de las consolas”, dijo el estudio.
La compañía también proporcionó una actualización para su primer juego y dijo que planea mantener la IP popular hasta su lanzamiento en PC. “Después de ser lanzado como exclusivo de PS5 en abril, las ventas continuaron a un nivel estable durante el tercer trimestre. “Para mejorar el valor de la propiedad intelectual y mantener el impulso, lanzamos constantemente parches y actualizaciones de contenido, lo que ayudó a mantener la popularidad del juego”, dijo Shift Up. “Con la incorporación de Nier: Automata DLC y las continuas actividades de marketing, planeamos mantener la popularidad de la IP hasta que la plataforma se expanda”.
A principios de esta semana, el desarrollador Anunciar A finales de este mes se lanzará una nueva actualización para Stellar Blade, que incluirá elementos especiales de Nier: Automático Y el tan necesario modo fotografía.
La actualización también agregará nuevos disfraces, compatibilidad con sincronización de labios, más idiomas y funciones de juego simples. Los usuarios de PS5 recibirán la actualización el 20 de noviembre.
En junio, suba el cambio cierto El juego ha vendido más de un millón de copias en PS5. El estudio también reveló que estaba revisando planes para un port de Stellar Blade para PC. “Se lanzó como exclusivo de PS5, pero la cantidad de distribuciones de PS5 y niveles de activación no eran tan altos como los de PS4”, supuestamente dijo en ese momento el director financiero de Shift Up, Ahn Jae-woo. Recientemente, el principal consumidor de juegos AAA se ha desplazado hacia las PC. Actualmente estamos revisando la versión para PC de Stellar Blade y, si lanzamos la versión para PC, esperamos que el valor de IP aumente nuevamente.
Stellar Blade se lanza exclusivamente en PS5 el 26 de abril. El juego sigue la historia de Eve, una súper soldado enviada para salvar un planeta Tierra invadido por monstruos. en nuestro revisar Del juego, elogiamos el “combate agradable y la presentación ingeniosa”, pero dijimos que estaba “constantemente obstaculizado por casi todo lo demás”.
Apple Watch tiene una función de activación oculta Turno nocturno En el dispositivo, usuario de Reddit Descubierto recientemente. Si preguntas siri En Apple Watch, para activar Night Shift, Siri lo hará y la pantalla adquirirá un color amarillo tenue que reduce la exposición a la luz azul.
No está claro durante cuánto tiempo Siri ha podido activar Night Shift en el Apple Watch, pero parece ser reciente. Apple no tiene ninguna documentación sobre Night Shift en el Apple Watch, ni la ha habido nunca WatchOS 10 opción. Es posible que Night Shift esté relacionado con esto. WatchOS 11Sin embargo, no se limita a dispositivos que ejecutan watchOS 11. Pudimos utilizar la función en Apple Watch Serie 9 Con watchOS 10 instalado.
Night Shift solo se puede activar a través de Siri y no hay alternancia en la aplicación de configuración de Apple Watch ni en ningún otro lugar del dispositivo. Siri menciona programar Night Shift en la aplicación Configuración, pero esa no es una opción en este momento en watchOS 10 o watchOS 11.
Night Shift no parece estar disponible en todos los modelos de Apple Watch, ya que los usuarios de Reddit no pueden activarlo en la Serie 5 o inferior.
La opción de activar repentinamente Night Shift sin una configuración adjunta sugiere que es una característica que se introdujo por error, y la alternancia podría introducirse en una versión futura de watchOS 11 o la próxima actualización de watchOS 10.
Con iOS 18, iPadOS 18 y macOS Sequoia, Apple presenta una nueva experiencia de IA personalizada llamada Apple Intelligence que utiliza modelos en dispositivos a gran escala para mejorar la experiencia del usuario en iPhone, iPad y Mac. Estas nuevas funciones de IA requieren que funcionen los últimos modelos de iPhone 15 Pro y iPhone 15 Pro Max de Apple, mientras que solo funcionarán las Mac y iPad con chips M1 o posteriores.
Apple ha detenido el trabajo en los auriculares Vision Pro de segunda generación para centrarse únicamente en un modelo más económico, informa The Information. Se cree ampliamente que Apple tiene planes de dividir la línea de productos Vision en dos modelos, con un modelo “Pro” y un modelo estándar de menor costo. Según se informa, la compañía ha estado restando prioridad a los próximos auriculares Vision Pro durante el año pasado, gradualmente…
Se espera que los modelos MacBook Pro con chip M4 se lancen en el cuarto trimestre de 2024, según el analista de suministros Ross Young. En un tweet a los suscriptores, Young dijo que los envíos de paneles para los nuevos modelos MacBook Pro de 14 y 16 pulgadas están programados para comenzar en el tercer trimestre de 2024, lo que sugiere un lanzamiento a finales de año. Apple comenzó a actualizar el chip M4 en mayo con el lanzamiento…
Dado el rumoreado plan de Apple de agregar un segmento de gama alta completamente nuevo a su serie iPhone 17 en 2025, este podría ser el año en que Apple traiga a la mesa su modelo más audaz “Pro Max”, el tipo de actualización del iPhone 16 que se destaca en su propio. Se eleva sobre sus hermanos, tanto en sentido figurado como literal. Si ha estado esperando tener en sus manos el iPhone 16 Pro Max, aquí tiene cinco de los cambios más importantes que se rumorea que se avecinan…
Apple dijo hoy que los clientes europeos no podrán acceder a las funciones Apple Intelligence, iPhone Mirroring y SharePlay Screen Sharing que estarán disponibles en iPhone, iPad y Mac el próximo mes de septiembre debido a problemas regulatorios relacionados con la Ley de Mercados Digitales. En una declaración al Financial Times, Apple dijo que habría un retraso mientras trabajaba para descubrir cómo fabricar el nuevo teléfono…
Apple lanzará esta semana su promoción anual de regreso a clases para estudiantes universitarios en Estados Unidos y Canadá, según Mark Gurman de Bloomberg. La oferta de regreso a clases de Apple ofrece a los estudiantes una tarjeta de regalo de Apple gratuita con la compra de una Mac o iPad, y la promoción de este año podría ayudar a Apple a impulsar sus nuevos modelos M2 iPad Air y M4 iPad Pro. El año pasado, Apple presentó en EE.UU….
In “The Structure of Scientific Revolutions,” physicist and philosopher Thomas Kuhn introduced the concept of a paradigm shift, which he used to describe a fundamental change in the basic framework of thinking in natural sciences. Throughout history, however, such paradigm shifts have occurred not just in natural sciences but across the entire spectrum of human endeavor, providing solutions to problems that appeared to be insurmountable under the old paradigm.
The field of data storage and computation is a case in point. As the demand for creation, retention, and data computation only ever increased with time, the current computing paradigm requires enterprises to build data continuously centers the size of football fields and nuclear power plants to power them. Here, the lack of resources and capabilities to build these things quickly enough indefinitely is not as important as the fact that the current computing paradigm is not compatible with a scalable solution.
DNA-based data storage and computation represents a break from the old framework and shows a scalable, sustainable path forward. TechRadar reported on one company, Biomemory, that recently announced an offering for consumers to have messages stored in DNA and shipped to them on a credit card-sized card. The DNA Data Storage Alliance recently announced specifications on recommended approaches to store data in DNA.
Hyunjun Park
CEO and co-founder, CATALOG.
The growing cost of AI
AI delivers innovation at a rate and pace the world has never experienced but comes at a substantial cost. AI generates volumes of data, and machine learning models are expensive to train and maintain.
Last summer, it was reported that it costs more than $700 million daily to keep OpenAI’s ChatGPT up and running. Recently, TechRadar reported that Sam Altman is seeking up to a whopping $7 trillion to build a facility to boost the industry’s ability to produce microprocessors to process AI workloads.
These exorbitant costs point to a limitation of the current computation paradigm.
While the advent of the microprocessor and its exponential development over the decades is largely responsible for the world as we know it today, the basic von Neumann architecture surrounding the microprocessor hasn’t changed much since World War II. And it is this architecture, this computing paradigm, that is increasingly becoming incompatible with the ever-increasing demand for data storage and computation.
Sign up to the TechRadar Pro newsletter to get all the top news, opinion, features and guidance your business needs to succeed!
DNA computation: A paradigm shift
Our cells are DNA-based computers that come together to form our bodies, which collectively process trillions of operations in parallel with very little energy. Scientists have mimicked that and used synthetic DNA to store and compute digital data in laboratory settings.
Compared to existing microprocessor technologies, which process workloads serially, a significant benefit of DNA Computation platforms is the ability to use enzymes or DNA probes to compute in a massively parallel fashion.
Imagine mixing a container of blue liquid with a container of red liquid. The result of this computation –a new color—appears not by serially mixing each color molecule one at a time but by mixing all of them together in parallel. Just as in this thought experiment, computation is performed in a massively parallel manner directly on the data, without having to travel to memory or processor to be processed.
Potential DNA computation application areas
DNA-based computation has the potential to allow the generation of insights from data sets that are not currently possible with existing computers. Early application areas include search, signal processing, and machine learning.
One practical example is satellite imagery of the entire surface of the Earth. We’ll soon have decades’ worth of images taken every second of every day. Given the amount of data, a simple search using conventional technology could become prohibitively expensive, but with DNA, it could be as simple as a COVID test.
Other expected areas of early application are artificial intelligence, machine learning, data analytics, and secure computing. In addition, initial use cases are expected to include fraud detection in financial services, image processing for defect discovery in manufacturing, and digital signal processing in the energy sector.
Borrowing heavily from natural processes and cutting-edge synthetic biology tools, in addition to parallelization, automated and scalable DNA-based computation platforms are divorced from the limitations of traditional electronic systems. They leverage low energy, low physical footprint, and secure computing.
This article was produced as part of TechRadarPro’s Expert Insights channel where we feature the best and brightest minds in the technology industry today. The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc. If you are interested in contributing find out more here: https://www.techradar.com/news/submit-your-story-to-techradar-pro
Although the notion of highly autonomous robotaxis has been around for a number of years now, the space is accelerating at a rapid rate – and now Alphabet subsidiary Waymo has revealed that it will offer paid rides in Los Angeles later this month.
Until now, Waymo has been offering free trips to users as it tests its completely driver-less systems, but last month it received regulatory approval for a paid service, according to NBC News.
The company says it has accumulated over 50,000 users that occupy a waitlist to use the service. However, it also confirmed that it would begin with a fleet of just 50 cars running in a 63-square-mile area for Santa Monica to downtown L.A.
Still, it’s another big moment for robotaxis, with their move towards the mainstream being further bolstered by the news that Cruise, a GM subsidiary that was banned from testing in San Francisco when one of its vehicles ran over a pedestrian, is rekindling its operations.
Cruise laid off almost a quarter of its workforce following several negative incidents, but says that it plans to reboot human-supervised autonomous testing in Phoenix to allow its machine learning systems to improve and get safer with time.
Hyundai has also been operating highly autonomous versions of its popular Ioniq 5 model in Las Vegas for a number of years, even going so far as building a cutting-edge facility in Singapore to mass produce the technologically complex model.
Its work with autonomous specialist Motional has recently culminated in its Ioniq 5 passing a Class C License Exam in Las Vegas with flying colors. However, the test was simulated in a controlled environment, so the vehicle didn’t come away with a full license, but it added further credentials to the service as a whole.
Get the hottest deals available in your inbox plus news, reviews, opinion, analysis and more from the TechRadar team.
Currently partnering with Uber in Las Vegas, customers can hail a highly autonomous Hyundai Ioniq 5 and cruise the strip, but a human driver is sat in a safety seat to take over when required.
Tesla wants in on the autonomous taxi action
(Image credit: Hyundai Motor Group)
Earlier this week, Elon Musk announced that he will be unveiling the Tesla Robotaxi on August 8, adding no further details to the simple post made on X (formerly Twitter).
The announcement followed rumors circulated by news outlet Reuters that Tesla had ditched plans for its more affordable Model 2 EV in favor of pursuing the Robotaxi project. This was quickly dismissed by Musk, but he took the opportunity to jump on the hype by confirming those Robotaxi rumors.
Tesla has long said that it sees a future where high levels of autonomy would allow its customers to create revenue from their vehicles when not in use, which is 96 per cent of the time if research from the RAC Foundation is to be believed.
This utopian vision might be some way off, but Musk revealed on his social media platform X that Tesla is on track to spend more than $10 billion on computing, storage, and networking solutions used to train the model for Tesla’s Full Self-Driving software. That’s no chump change.
Everything points towards the fact that Tesla is pushing its Autopilot and Full Self-Driving systems to the next level, despite its numerous setbacks, further fueling reports that the Californian company is not content with conquering the EV market, but is now hell-bent on shaking up the ride-hailing industry, too.
In today’s dynamic business landscape, data management stands as a critical cornerstone, directly influencing an organization’s agility and innovation capabilities. The digital age demands that companies reassess their data management strategies, particularly the reliance on traditional master data management (MDM) systems. These legacy systems, often entrenched due to the ‘sunk-costs’ fallacy, hinder progress and adaptability, locking businesses into outdated practices that impede growth.
Rules-based MDM solutions, with their rigid frameworks and manual-intensive operations, are increasingly misaligned with the needs of modern data environments. They struggle to manage the diversity and volume of data generated today, leading to inefficiencies that can ripple through an organization, affecting everything from decision-making speeds to customer experience and the ability to capitalize on emerging opportunities.
The shift towards AI-powered data management through data products revolutionizes traditional MDM, offering a solution that transcends its limitations. Data products employ artificial intelligence (AI) and machine learning (ML) to automate and refine data processes, enhancing accuracy, efficiency, and scalability. The integration of AI technologies ensures that data management systems can evolve in tandem with the changing data landscape, ensuring businesses remain at the forefront of innovation.
The advantages of transitioning to AI-driven data management systems are manifold. Beyond improving data quality and operational efficiencies, these systems unlock the most accurate insights, facilitating more informed business decisions, optimizing operations, and enriching customer experiences. This strategic enhancement in data management capabilities is invaluable in driving a company’s growth and competitive edge.
Integrating data products into legacy MDM systems is transformative, yet it’s the partnership between AI and human intelligence that truly unlocks their potential. AI automates and streamlines data management, but human oversight ensures accuracy, ethics, and context. This synergy between human intuition and AI’s capabilities fosters innovation, enhances decision-making, and ensures responsible data use. Businesses embracing this collaborative approach will navigate the complexities of modern data environments more effectively, securing a competitive edge in the digital age.
Anthony Deighton
Data Products General Manager, Tamr.
Take for example the competitive landscape of retail, a large chain might grapple with significant challenges that hinder its efficiency and customer satisfaction. One common issue is inconsistent product data across various platforms such as the website, mobile app, and in-store displays. This inconsistency can confuse customers and lead to inaccurate inventory management. Additionally, many retailers rely on basic customer demographics and purchase history for personalization, which often results in generic marketing campaigns that fail to engage customers on a deeper level. Another critical challenge is reactive inventory management, where manual forecasting and stock level assessments frequently result in either overstocking or understocking, negatively impacting both sales and profitability.
In contrast to traditional MDM solutions, AI-powered data products offer innovative solutions to these pervasive issues in the retail sector. For instance, AI-driven data management can dynamically unify and clean product data across various platforms, ensuring consistency on the website, mobile app, and in-store displays. This not only enhances the customer experience by providing accurate and coherent product information but also improves inventory management by enabling real-time tracking and updates.
Sign up to the TechRadar Pro newsletter to get all the top news, opinion, features and guidance your business needs to succeed!
Moreover, AI-powered systems go beyond basic customer demographics and purchase history to offer advanced personalization. By leveraging machine learning algorithms, these systems can analyze a wide array of data points, including browsing behavior, social media interactions, and even environmental factors, to deliver highly personalized and engaging marketing campaigns. This level of personalization not only enhances customer engagement but also significantly increases the effectiveness of marketing efforts.
When it comes to inventory management, AI-powered data products transform the traditional reactive approach into a proactive strategy. Predictive analytics and machine learning enable more accurate forecasting of demand, taking into account not just historical sales data but also trends, seasonality, and external factors such as economic indicators and social trends. This results in optimized stock levels, reducing the risks of overstocking or understocking, and consequently, improving sales and profitability.
Furthermore, AI-driven solutions can provide valuable insights into customer behavior, market trends, and operational efficiencies through advanced analytics and data visualization tools. These insights can inform strategic decisions, enabling retailers to adapt more swiftly to market changes and customer needs.
Modernization made easy: Integrating AI into existing MDM
For businesses tethered to legacy MDM systems, the path forward doesn’t necessitate a complete overhaul. Integrating AI-driven solutions with existing infrastructures offers a pragmatic approach to modernization, allowing for incremental improvements without substantial disruption or the abandonment of previous investments. This methodical integration can bring about significant enhancements in data management practices, ensuring a smoother transition and immediate benefits.
Embarking on this transition requires a strategic approach, beginning with a thorough assessment of current data management needs and a careful selection of appropriate AI solutions. Companies must navigate potential challenges, including cultural shifts, skill development, and implementation hurdles, with a clear strategy and vision.
Looking to the future, data management must prioritize flexibility, scalability, and agility to support ongoing business growth and adaptability. Embracing AI-powered data products is not merely a tactical move but a strategic imperative to future-proof data management practices. By continuously evolving and adapting to new technologies and data sources, businesses can ensure they remain competitive in an ever-changing digital landscape.
As industries worldwide continue to evolve at an unprecedented pace, the shift from legacy MDM to AI-driven data management is not just a trend but a fundamental requirement for maintaining relevance and competitiveness. The adoption of AI-enhanced systems enables organizations to harness the vast potential of their data, resulting in better and more accurate insights. These insights facilitate faster decision-making, leading to operational efficiencies, improved customer experiences, and increased ROI. Companies that understand the urgency of this shift and act decisively will find themselves at the forefront of the new data-driven era.
This article was produced as part of TechRadarPro’s Expert Insights channel where we feature the best and brightest minds in the technology industry today. The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc. If you are interested in contributing find out more here: https://www.techradar.com/news/submit-your-story-to-techradar-pro
