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Samsung Home Up update brings icon scaling feature to Galaxy phones

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Last updated: April 16th, 2024 at 10:21 UTC+02:00

Samsung has released a new update to Good Lock’s Home Up module. This new version of Home Up brings an additional home screen and app drawer customization feature. It lets you change the size of the icon to match your preferences better.

Home Up update brings the option to change the size of app icons in One UI

The Home Up app’s latest version (15.0.01.19) brings a new feature called App Icon Setting in the Home Screen section. This section has a new slider to adjust the app icon size. It ranges from 80% to 120%, with 100% being the default setting. You can increase or decrease the size of app icons as per your liking, and this affects app icons on both the app drawer and home screen.

The screenshots below show how app icons look when the size is set to 80%, 100%, 110%, and 120%, respectively. Some people like their app icons to appear slightly bigger than the default setting. We found the 110% setting to be a great choice. Some other settings, including displaying the app icon label on the home screen and app tray, have been moved to the App Icon Setting section of the Home Up app.

This new version of the Home Up module is now available on the Galaxy Store. However, it hasn’t been released in all the countries and markets yet, so you may not be able to spot it on the Galaxy Store in your country. Until then, you can download the new version of the app via the Google Drive link here (via @TarunVats33).



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OpenAI insider discusses AGI and Scaling Laws of Neural Nets

OpenAI insider discusses AGI and Scaling Laws of Neural Nets

Imagine a future where machines think like us, understand like us, and perhaps even surpass our own intellectual capabilities. This isn’t just a scene from a science fiction movie; it’s a goal that experts like Scott Aaronson from OpenAI are working towards. Aaronson, a prominent figure in quantum computing, has shifted his focus to a new frontier: Artificial General Intelligence (AGI). This is the kind of intelligence that could match or even exceed human brainpower. Wes Roth explores deeper into this new technology and what we can expect in the near future from OpenAI and others developing AGI and Scaling Laws of Neural Nets.

At OpenAI, Aaronson is deeply involved in the quest to create AGI. He’s looking at the big picture, trying to figure out how to make sure these powerful AI systems don’t accidentally cause harm. It’s a major concern for those in the AI field because as these systems become more complex, the risks grow too.

Aaronson sees a connection between the way our brains work and how neural networks in AI operate. He suggests that the complexity of AI could one day be on par with the human brain, which has about 100 trillion synapses. This idea is fascinating because it suggests that machines could potentially think and learn like we do.

OpenAI AGI

There’s been a lot of buzz about a paper that Aaronson reviewed. It talked about creating an AI model with 100 trillion parameters. That’s a huge number, and it’s sparked a lot of debate. People are wondering if it’s even possible to build such a model and what it would mean for the future of AI. One of the big questions Aaronson is asking is whether AI systems like GPT really understand what they’re doing or if they’re just good at pretending. It’s an important distinction because true understanding is a big step towards AGI.

Here are some other articles you may find of interest on the subject of Artificial General Intelligence (AGI) :

Scaling Laws of Neural Nets

But Aaronson isn’t just critiquing other people’s work; he’s also helping to build a mathematical framework to make AI safer. This framework is all about predicting and preventing the risks that come with more advanced AI systems. There’s a lot of interest in how the number of parameters in an AI system affects its performance. Some people think that there’s a certain number of parameters that an AI needs to have before it can act like a human. If that’s true, then maybe AGI has been possible for a long time, and we just didn’t have the computing power or the data to make it happen.

Aaronson also thinks about what it would mean for AI to reach the complexity of a cat’s brain. That might not sound like much, but it would be a big step forward for AI capabilities. Then there’s the idea of Transformative AI (TII). This is AI that could take over jobs that people do from far away. It’s a big deal because it could change entire industries and affect jobs all over the world.

People have different ideas about how many parameters an AI needs to reach AGI. These estimates are based on ongoing research and a better understanding of how neural networks grow and change. Aaronson’s own work on the computational complexity of linear optics is helping to shed light on what’s needed for AGI.

Scott Aaronson’s insights give us a peek into the current state of AGI research. The way parameters in neural networks scale and the ethical issues around AI development are at the heart of this fast-moving field. As we push the limits of AI, conversations between experts like Aaronson and the broader AI community will play a crucial role in shaping what AGI will look like in the future.

Filed Under: Technology News, Top News





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New Intel Edge platform unveiled for scaling AI applications

New Intel Edge platform unveiled for scaling AI apps

Intel has recently unveiled an advanced Edge AI Platform that is set to transform the way artificial intelligence (AI) applications are deployed and managed. This new platform is designed to make operations simpler and more cost-effective, similar to the services provided by cloud computing, but it operates at the edge of the network. The introduction of this platform is a significant milestone in the journey of digital transformation.

In the fast-paced world of digital technology, AI has become a critical component. Intel’s new Edge Platform is specifically designed to accelerate this technological evolution, with a focus on AI applications that are situated at the network’s edge. By processing data closer to where it is generated, the platform allows for immediate decision-making, which is crucial for applications that require quick responses.

New Intel Edge platform

Edge computing faces unique challenges, including maintaining high performance, meeting diverse requirements, securing data, and managing complex systems. Intel’s platform addresses these challenges by providing low-latency, advanced AI analytics that enable faster and smarter decision-making in a variety of settings, such as industrial automation and smart city projects.

“The edge is the next frontier of digital transformation, being further fueled by AI. We are building on our strong customer base in the market and consolidating our years of software initiatives to the next level in delivering a complete edge-native platform, which is needed to enable infrastructure, applications and efficient AI deployments at scale. Our modular platform is exactly that, driving optimal edge infrastructure performance and streamlining application management for enterprises, giving them both improved competitiveness and improved total cost of ownership.” –Pallavi Mahajan, Intel corporate vice president and general manager of Network and Edge Group Software

The platform is built with an open, modular architecture that allows for easy integration with existing systems. It includes the OpenVINO AI inference engine, which is designed to optimize AI workloads on Intel hardware. The platform also focuses on secure automation to simplify tasks for both IT and operational technology teams.

AI applications

One of the key features of Intel’s platform is a centralized dashboard that allows for the management of edge nodes and devices. This centralization streamlines control, enhances security, and simplifies the deployment and maintenance of edge infrastructure. To enhance operations, the platform utilizes closed-loop automation, which improves performance and reduces the total cost of ownership (TCO). This type of automation streamlines routine tasks, enabling organizations to focus their resources on strategic business goals.

Security is a top priority in today’s digital environment, and Intel’s Edge Platform is designed with this in mind. It combines deep hardware expertise with zero-trust security principles to protect data and applications. The platform also includes tools for orchestrating applications and developing AI models, ensuring that they perform optimally on Intel’s architecture.

Intel’s Edge Platform is not just a technological breakthrough; it offers a strategic advantage for organizations looking to scale their AI applications. With its focus on operational simplicity, adaptability for various use cases, and robust security, the platform is poised to become a key component of edge computing. As companies navigate the complexities of digital transformation, Intel’s Edge Platform provides a valuable tool for moving forward in an AI-driven world. For more information jump over to the official Intel newsroom.

Filed Under: Technology News, Top News





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