Apple is using artificial intelligence processors from Amazon Web Services to build and power some Apple Intelligence and other services.
While Apple has long used AWS for services like iCloud and Apple One, this relationship now includes AI, with Apple tapping into AWS’s cutting-edge processors to enhance its own offerings.Apple is also testing advanced AWS chips to pretrain some of its AI models as it continues its rapid pivot toward becoming the world’s most widely deployed AI platform.
Apple has used AWS servers for years, in part to drive its iCloud and Apple One services and to scale additional capacity at times of peak demand. “One of the unique elements of Apple’s business is the scale at which we operate, and the speed with which we innovate. AWS has been able to keep the pace,” Dupin said.
One of the standout features of this partnership is Apple’s use of AWS’s advanced chips. Dupin shared that Apple is using AWS’s Graviton and Inferentia processors for machine learning tasks, such as search and streaming. The results have been impressive, with a 40% improvement in efficiency compared to older systems. Apple is also exploring AWS’s Trainium 2 chips for pretraining its AI models, expecting a 50% jump in efficiency. These kinds of gains are essential for keeping Apple’s AI projects fast, cost-effective, and environmentally friendly.
On the AWS connection to Apple Intelligence, he explained: “To develop Apple Intelligence, we needed to further scale our infrastructure for training.” As a result, Apple turned to AWS because the service could provide access to the most performant accelerators in quantity.
Dupin revealed that key areas where Apple uses Amazon’s services include fine-tuning AI models, optimizing trained models to fit on small devices, and “building and finalizing our Apple Intelligence adapters, ready to deploy on Apple devices and servers".This collaboration allows Apple to roll out powerful new features seamlessly, whether they’re running on an iPhone, Mac, or iPad.
Apple Intelligence is a work in progress and the company is already developing additional services and feature improvements.As Apple expand the capabilities and feature of Apple Intelligence, the company will continue to depend on the scalable, efficient, high-performance accelerator technologies AWS delivers.
It’s clear that Apple’s increasing reliance on AI is part of a long-term plan. While CEO Tim Cook hasn’t shared specific details, he’s made it clear that the company is deeply committed to projects that are “years in the making.” Meanwhile, AWS is positioning itself as a strong alternative to Nvidia, offering AI processors that are both powerful and cost-effective.
But Apple being Apple, there’s always the question of whether it will eventually take this expertise in-house. With its track record of designing innovative hardware like Apple Silicon, it wouldn’t be surprising to see Apple developing its own server processors down the road to gain even more control over its AI systems.
The field of weather forecasting has reached a significant milestone: researchers have introduced GenCast, an AI-driven weather prediction system developed by Google DeepMind. This system demonstrates faster and more accurate forecasts than the ENS model from the European Centre for Medium-Range Weather Forecasts (ECMWF), which has long been regarded as the global leader in weather prediction.
GenCast outperformed ENS by up to 20% in short-term weather forecasts and showed remarkable precision in predicting the paths of extreme weather events, such as hurricanes and cyclones, including their landfall locations.
Unlike traditional physics-based models that require hours of computation on supercomputers, GenCast delivers results in just 8 minutes using a single Google Cloud TPU, a machine-learning-optimized processor.
The model was trained on 40 years of historical weather data (1979–2018), encompassing a wide range of atmospheric variables such as wind speed, temperature, pressure, and humidity. GenCast builds on its predecessor, GraphCast, by producing probabilistic ensembles of 50 or more forecasts, offering greater reliability for predicting uncertain weather events.
For now, GenCast is designed to complement rather than replace traditional physics-based methods, providing additional clarity for events such as heatwaves, cold spells, and high winds. Its applications could extend to sectors like renewable energy, where accurate forecasts help optimize power generation.
While GenCast's performance is promising, certain challenges remain. The authors have not answered whether their system has the physical realism to capture the ‘butterfly effect’, the cascade of fast-growing uncertainties, which is critical for effective ensemble forecasting.
The data GenCast trained on combines past observations with physics-based “hindcasts” that need sophisticated maths to fill gaps in historic data.
There is still a long way to go before machine learning approaches can completely replace physics-based forecasting.It remains to be seen whether generative machine learning can replace this step and go straight from the most recent unprocessed observations to a 15-day forecast.
GenCast is unlikely to replace traditional forecasting systems in the near future. Instead, it is expected to serve as a powerful assistive tool, augmenting current models and contributing to more accurate predictions. National weather services and industries reliant on precise weather information, such as energy and disaster management, are poised to benefit significantly.
If you want to catch more latest trending stories, please visit:Batteryone.co/blog
Get the best batteries for your business and professional needs here at Batteryone.co. Get in touch with us today for all your battery needs.
The debate over whether Macs are immune to viruses or whether they need antivirus software has been a longstanding one, and the rise of AI-driven malware has only added fuel to the fire.
Many Apple fans and users have long subscribed to the idea that Macs are immune to viruses, bolstered by macOS's built-in security features like Gatekeeper, XProtect, and its Unix-based architecture. These features certainly make Macs more secure compared to Windows PCs, and indeed, Macs are less likely to be targeted by malware overall. But this doesn’t mean Macs are completely immune to threats.
Over the years, malware specifically designed for Macs has been on the rise. Mac users are still susceptible to phishing attacks, adware, spyware, trojans, and more, even if the incidence of traditional viruses is lower. The truth is, Macs can get viruses, and this is becoming increasingly clear as hackers target this growing user base.
The introduction of AI tools like ChatGPT has added a new dimension to the cybersecurity landscape. Hackers, even those with minimal technical skills, are finding that AI can help them write malware more efficiently. This is where the Moonlock report comes in—highlighting the potential for AI-powered malware creation.
The report highlights examples of inexperienced hackers using ChatGPT to generate working malware. For instance, the hacker “barboris” posted examples of malware code generated through ChatGPT on a forum, noting how they had no prior experience in malware development but were able to leverage AI to create malicious code.
However, the effectiveness of AI-generated malware is not a foregone conclusion. While it’s true that AI tools like ChatGPT can help generate code quickly, the result often requires troubleshooting, debugging, and fine-tuning—tasks that would likely trip up an inexperienced hacker. In other words, ChatGPT is far from a foolproof malware creation tool, especially for someone with no background in cybersecurity.
That said, the ability for novice hackers to leverage AI to create malware represents a significant shift. As AI tools improve and become more accessible, the barriers to entry for malware creation are lower than ever before, which may lead to an increase in targeted attacks on Macs—and indeed, other platforms as well.
While it's true that the threat of AI-driven malware is real, it’s also important not to panic. macOS has strong built-in security features, and Apple has made improvements over the years to protect users. Plus, even if novice hackers are creating malware with the help of AI, the actual risk to individual users is still relatively low—at least for now.
However, it’s important to remain vigilant. Even Macs are vulnerable to more sophisticated attacks, such as zero-day exploits (where hackers take advantage of security flaws not yet patched by Apple). Relying solely on macOS’s built-in defenses may not be enough if you engage in risky online behaviors, like downloading software from untrusted sources or visiting sketchy websites.
This is where the debate becomes more nuanced. Antivirus software on Macs is often seen as unnecessary by many users, especially since macOS’s built-in tools are generally effective at detecting and blocking threats. However, there’s no harm in adding an extra layer of protection—especially for those who might be less tech-savvy or are particularly concerned about the rise in AI-driven attacks.
Popular antivirus programs for Macs, such as Malwarebytes, Bitdefender, or Norton, can offer additional protections, particularly for adware, spyware, and more sophisticated threats that might bypass macOS’s built-in tools.
But the decision of whether or not to install antivirus software on your Mac comes down to personal preference and how much risk you're willing to take. For most users, safe browsing habits and relying on macOS's built-in security features are enough. However, for those who are particularly concerned about emerging threats or engage in riskier online behaviors, installing antivirus software can provide peace of mind.
If you want to catch more latest trending stories, please visit:Batteryone.co/blog
Samsung is poised to make waves in the tech world with the anticipated launch of its first smart glasses, a groundbreaking step in the wearables market. According to Yonhap News, these glasses are likely to be unveiled during the company's January 2025 Galaxy Unpacked event, where the Galaxy S25 series will also take center stage. However, the smart glasses may steal the spotlight with their innovative features and sleek design.
Weighing approximately 50 grams, Samsung’s smart glasses aim to closely mimic traditional eyewear, providing a familiar and lightweight user experience. This design ethos aligns with the trend of creating subtle, unobtrusive wearable devices. Unlike earlier AR devices, these glasses reportedly forego complex hardware like built-in displays or projectors for augmented reality applications, focusing instead on functionalities such as gesture recognition, audio playback, and possibly payment capabilities.
This approach contrasts with Samsung’s ongoing collaboration with Qualcomm and Google on an ambitious XR device powered by smartphones. The new smart glasses, designed in-house, suggest a more conservative and refined take on wearable technology, emphasizing comfort and everyday usability.
Samsung's foray into smart glasses is not its first venture into high-tech eyewear. The company previously launched the Samsung Gear VR, a virtual reality headset co-developed with Oculus. While the Gear VR offered an immersive experience, it was hampered by its reliance on specific smartphone models, leading to its eventual discontinuation.
In crafting these new glasses, Samsung appears to be drawing inspiration from the success of Meta’s Ray-Ban smart glasses, which combine stylish designs with practical features. By leveraging its Galaxy AI technology, Samsung may incorporate advanced functionalities, potentially integrating AI assistants like those seen in Solos AirGo 3 smart glasses.
While the January Unpacked event will likely feature only a teaser for the smart glasses, a full launch is expected in the third quarter of 2025. Samsung's history of unveiling innovative wearables, such as the Galaxy Ring in 2024, highlights its capability to deliver cutting-edge devices.
The introduction of these smart glasses signifies a growing competitive landscape in the wearable tech market. As Meta, Apple, and other players continue to expand their offerings, Samsung's entry is poised to bring more choices to consumers, driving innovation across the industry.
By combining user-friendly design, innovative technology, and its established ecosystem, Samsung's smart glasses could redefine what consumers expect from wearable devices, ensuring a competitive edge in this burgeoning market.
If you want to catch more latest trending stories, please visit:Batteryone.co/blog
According to CNBC, Benoit Dupin, Senior Director of Machine Learning and Artificial Intelligence at Apple, spoke at Amazon's AWS re:Invent conference in Las Vegas about how Apple leverages custom AI chips from Amazon Web Services (AWS) in many of its cloud services. Apple is also evaluating Amazon's latest AI chips for pre-training its Apple Intelligence models.
“We have a strong relationship, and the infrastructure is both reliable and capable of serving our customers worldwide,” said Dupin.
Apple's participation in Amazon's conference and its adoption of the company's chips signify a strong endorsement of AWS as it competes with Microsoft Azure and Google Cloud for AI investments. Apple also utilizes these competing cloud services.
During the event, Dupin highlighted that Apple has been using AWS chips, such as the Graviton and Inferentia, for over a decade to power services like Siri, search, the App Store, Apple Music, Apple Maps, and more. By leveraging these chips, Apple has achieved a 40% improvement in efficiency compared to Intel and AMD’s x86 chips.
Dupin further confirmed that Apple is currently testing AWS’s latest AI training chip, Trainium2. He stated that Apple expects “up to a 50% improvement in efficiency with pre-training” using the Trainium2 chip.
AWS CEO Matt Garman, in an interview with CNBC, mentioned that Apple was an early adopter and beta tester of the Trainium chips.
“Apple approached us and said, ‘How can you help us enhance our generative AI capabilities? We need infrastructure to build this vision,’” Garman told CNBC’s Kate Rooney. “They had a clear vision for developing Apple Intelligence.”
This fall, Apple launched its first major generative AI product, Apple Intelligence, a suite of services that can summarize notifications, rewrite emails, and generate new emojis. According to the company, Apple Intelligence will integrate with OpenAI’s ChatGPT later this month, and Siri will gain new capabilities for app control and natural speech next year.
Unlike leading chatbots such as OpenAI’s ChatGPT, which rely on large clusters of Nvidia-based servers in the cloud, Apple employs a different approach. It processes as much as possible on local devices, such as iPhones, iPads, or Macs, and delegates complex queries to Apple-operated servers powered by its proprietary M-series chips.