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Apple Releases Open Source AI Models That Run On-Device

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Apple today released several open source large language models (LLMs) that are designed to run on-device rather than through cloud servers. Called OpenELM (Open-source Efficient Language Models), the LLMs are available on the Hugging Face Hub, a community for sharing AI code.

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As outlined in a white paper [PDF], there are eight total OpenELM models, four of which were pre-trained using the CoreNet library, and four instruction tuned models. Apple uses a layer-wise scaling strategy that is aimed at improving accuracy and efficiency.

Apple provided code, training logs, and multiple versions rather than just the final trained model, and the researchers behind the project hope that it will lead to faster progress and “more trustworthy results” in the natural language AI field.

OpenELM, a state-of-the-art open language model. OpenELM uses a layer-wise scaling strategy to efficiently allocate parameters within each layer of the transformer model, leading to enhanced accuracy. For example, with a parameter budget of approximately one billion parameters, OpenELM exhibits a 2.36% improvement in accuracy compared to OLMo while requiring 2x fewer pre-training tokens.

Diverging from prior practices that only provide model weights and inference code, and pre-train on private datasets, our release includes the complete framework for training and evaluation of the language model on publicly available datasets, including training logs, multiple checkpoints, and pre-training configurations.

Apple says that it is releasing the OpenELM models to “empower and enrich the open research community” with stage-of-the-art language models. Sharing open source models gives researchers a way to investigate risks and data and model biases. Developers and companies are able to use the models as-is or make modifications.

The open sharing of information has become an important tool for Apple to recruit top engineers, scientists, and experts because it provides opportunities for research papers that would not normally have been able to be published under Apple’s secretive policies.

Apple has not yet brought these kinds of AI capabilities to its devices, but iOS 18 is expected to include a number of new AI features, and rumors suggest that Apple is planning to run its large language models on-device for privacy purposes.

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Apple to bring on-device AI to iPhones with iOS 18 to differ from Samsung

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Samsung introduced several AI-powered features with the Galaxy S24. Samsung called the Galaxy S24 its first AI Phone. It is the first smartphone brand to go big with AI, seeing the AI boom. And Apple will soon follow Samsung, but its approach will be a bit different compared to its South Korean rival.

Apple could only bring on-device AI features to iPhones with iOS 18

According to a report from Mark Gurman (via 9To5Mac), AI features on iPhones will be powered entirely by a Large Language Model (LLM) developed by Apple, and all the AI processing will happen on-device. We can expect Apple to heavily market the privacy and speed benefits of using on-device AI processing. These AI features will reportedly debut with iOS 18 and will be showcased during WWDC 2024.

While on-device AI has privacy and speed benefits, it isn’t as powerful as AI processing offered by dedicated servers in the cloud. However, it is possible that Apple will only introduce AI features that work well with on-device AI processing. For example, it could offer better auto-replies and Siri requests.

Samsung Galaxy AI

This differs from Samsung’s approach of using a mix of on-device and cloud-powered AI features. Samsung uses a mix of its own LLM and Google’s Gemini for AI processing. Users have to option to process AI data locally on the device with a simple toggle. As seen on the Galaxy S24 and older phones that have received One UI 6.1 with AI features, some AI features work fast, while others are slow, depending on the workload and complexity.

While Apple hasn’t revealed any AI feature that could debut with iOS 18, it could bring better language translation, more reliable autocorrect while typing, and advanced image editing features. A few weeks ago, it was revealed that Apple was in talks with Google about using Gemini to power some AI features in iOS 18. However, it isn’t clear if that deal has been agreed upon.

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Apple Acquires French AI Company Specializing in On-Device Processing

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Apple has acquired the Paris-based artificial intelligence startup Datakalab amid its push to deliver on-device AI tools.

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Datakalab specializes in algorithm compression and embedded AI systems. The acquisition, finalized on December 17 last year, was quietly conducted but noted in a European Commission filing spotted by French publication Challenges (via iPhoneSoft). While the financial details of the transaction remain undisclosed, the move is almost certainly part of Apple’s broader strategy to bring more sophisticated AI technology to its devices, such as those expected to be introduced in iOS 18.

The company was established in 2016 by Xavier and Lucas Fischer and made significant strides in AI technology focusing on low-power, high-efficiency deep learning algorithms that function without relying on cloud-based systems. This approach aligns with Apple’s oft-touted commitment to user privacy, data security, and reliable performance, as processing data locally minimizes the risk of data breaches and ensures faster processing times. The startup’s expertise in compressing neural networks to work effectively on portable devices like smartphones and tablets is likely a key factor in Apple’s interest.

Bloomberg‘s Mark Gurman recently reported that Apple’s LLM will run entirely on-device, rather than via the cloud like most existing AI services. Apple’s AI tools may be less capable in certain instances than its direct cloud-based rivals, but Gurman suggested that the company could “fill in the gaps” by licensing technology from Google and other AI service providers.

Before its acquisition, Datakalab engaged in various high-profile projects, including collaborations with the French government and Disney. The company developed technology capable of analyzing human emotions by facial recognition and visual data, which were later used to monitor audience reactions in real-time during cinema screenings. The first look at Apple’s new AI strategy is widely anticipated to arrive alongside previews of its next-generation operating systems at WWDC in early June.

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iOS 18 AI features could run entirely on-device

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iOS 18 concept video
Apple could run iOS 18’s AI features on-device on the iPhone.
Concept: Kevin Kall

Apple’s large language model (LLM) that will power iOS 18’s AI features could entirely run locally. This would prioritize user privacy and offer faster response times.

However, running AI features on-device will have downsides as they might not be as powerful as on some Android phones.

iOS 18’s AI features might value privacy and experience

Android phones with generative AI features offload all the processing and heavy lifting to the cloud. This makes them powerful and ensures the phone’s AI processing capabilities do not limit them.

The catch is the privacy risk involved, as your data might be shared and uploaded to the cloud. Plus, the high response times lead to a poor user experience.

Apple aims to bypass these problems with on-device processing. So, the phone will process the AI commands locally instead of offloading them to the cloud. This is a more privacy-friendly approach, though Apple might have to limit its AI features based on the chip’s AI processing capabilities.

Apple is behind Google and Microsoft in the generative AI features race. Running its LLM locally could give Apple’s AI features a unique advantage over its competition. Plus, the company can tout the privacy benefits of its approach.

A previous report claims that the iPhone 16 will ship with a more powerful Neural Engine to power some of iOS 18’s Generative AI features. This purportedly means that some demanding AI features might not come to existing iPhones.

Apple could reportedly partner with Google and integrate Gemini to power iOS 18’s more powerful generative AI features.

Apple’s marketing strategy could help its AI features stand out

Additionally, in the latest edition of the Power On newsletter, Bloomberg‘s Mark Gurman claims Apple will adopt a different marketing strategy for iOS 18’s AI features. Instead of highlighting the generative AI tools, the company will show how the AI features will benefit users in daily use.

Apple’s marketing prowess could help its generative AI features stand out even if it’s less powerful.



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Gurman: Apple Working on On-Device LLM for Generative AI Features

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Apple is developing its own large language model (LLM) that runs on-device to prioritize speed and privacy, Bloomberg‘s Mark Gurman reports.

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Writing in his “Power On” newsletter, Gurman said that Apple’s LLM underpins upcoming generative AI features. “All indications” apparently suggests that it will run entirely on-device, rather than via the cloud like most existing AI services.

Since they will run on-device, Apple’s AI tools may be less capable in certain instances than its direct cloud-based rivals, but Gurman suggested that the company could “fill in the gaps” by licensing technology from Google and other AI service providers. Last month, Gurman reported that Apple was in discussions with Google to integrate its Gemini AI engine into the iPhone as part of iOS 18. The main advantages of on-device processing will be quicker response times and superior privacy compared to cloud-based solutions.

Apple’s marketing strategy for its AI technology will apparently be based around how it can be useful to users’ daily lives, rather than its power. Apple’s broader AI strategy is expected to be revealed alongside previews of its major software updates at WWDC in June.

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Nothing Phone 3’s big upgrades could include on-device generative AI

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The rumored Nothing Phone 3 could switch back to Qualcomm chips and use a Snapdragon 8s Gen 3 to help power onboard generative AI features, according to 91mobiles’ “industry sources who work closely with Nothing.”

This suggests that we could see something more powerful than the recently launched Nothing Phone 2a. This aligns with the idea that the Phone 3 will offer near-flagship performance while maintaining Nothing’s reputation for making affordable phones. After all, both the Nothing Phone 1 and Phone 2 used slightly older hardware and some speculation pointed to Phone 3 following suit.

Snapping up Snapdragon



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Snapdragon 7+ Gen 3 chip brings on-device AI for affordable high-end phones

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Qualcomm has unveiled a new processor—Snapdragon 7+ Gen 3—for higher mid-range phones and flagship killer devices. It’s the first Snapdragon 7 series mobile processor to feature on-device AI processing, Wi-Fi 7 connectivity, and a Cortex-X4 CPU core.

OnePlus, Realme, and Sharp will be among the first smartphone brands to launch devices with the Snapdragon 7+ Gen 3.

Snapdragon 7+ Gen 3 is a higher mid-range processor for smartphones

The Snapdragon 7+ Gen 3 (SM7675) is fabricated on TSMC’s 4nm (N4P) process node. It is the most affordable processor from Qualcomm to feature a Cortex-X4 CPU core.

CPU

It has one Cortex-X4 CPU core clocked at 2.8GHz, four Cortex-A720 CPU cores clocked at 2.6GHz, and three Cortex-A520 CPU cores clocked at 1.9GHz. Looking at its CPU cores and their clock speeds, it is clear that the Snapdragon 7+ Gen 3 is a trimmed-down version of the Snapdragon 8s Gen 3, which was launched last week.

Qualcomm Snapdragon 7+ Gen 3 Features

GPU

The GPU inside the Snapdragon 7+ Gen 3 is the Adreno 732. It can drive 4K 60Hz or QHD+ 120Hz screens. It supports Dolby Vision, HDR, HDR10+, and HLG. It supports variable refresh rates from 1Hz to 240Hz at Full HD+ resolution, and it can support a resolution of up to 8K with a 30Hz refresh rate. HDR gaming and Adreno Frame Motion Engine 2.0 are supported, but the Snapdragon 7+ Gen 3 doesn’t support ray-tracing.

AI, RAM, Storage

Qualcomm is promising a performance uplift of 15% in CPU, 45% in GPU, and 5% in power efficiency. The chip supports up to 24GB LPDDR5x RAM (quad-channel) and UFS 4.0 storage. The built-in Qualcomm Hexagon NPU can run many Large Language Models (LLMs) and Large Vision Models (LVMs) natively.

Cameras

The Snapdragon 7+ Gen 3 has the built-in Qualcomm Spectra Cognitive ISP (triple 18-bit) that supports up to 200MP camera sensors. It can stream visuals from three 36MP camera sensors, a 64MP+36MP dual-camera setup, or one 108MP camera sensor simultaneously with zero shutter lag. It allows phones to record up to 4K 60fps HDR videos or 1080p 240fps slow-motion videos. Supported HDR formats include Dolby Vision, HDR, HDR10+, HLG, and Ultra HDR.

Advanced camera features, including Computational HDR, Multi Frame Noise Reduction, AI-based autofocus and auto-exposure, AI-based face detection, Real-Time Semantic Segmentation, and Video Super Resolution, are supported as well.

Connectivity

The Snapdragon 7+ Gen 3 uses the Snapdragon X63 5G modem that supports mmWave and sub-6GHz 5G networks (with SA and NSA). It supports peak download speeds of up to 4.2Gbps and peak upload speeds of up to 3.5Gbps. It also supports 5G+5G Dual-SIM Dual Active connections.

Thanks to FastConnect 7800, the Snapdragon 7+ Gen 3 is the first Snapdragon 7 series chip to support Wi-Fi 7 and Bluetooth 5.4 (with LE Audio and Auracast). Support for dual-frequency satellite-based navigation is present, and it supports Beidou, Galileo, GLONASS, GPS, NavIC, and QZSS. It supports lane-level accuracy for cars and sidewalk-level accuracy while walking.

NFC and USB 3.1 Gen 2 Type-C are supported as well.

Fast charging and fingerprint

It supports up to Qualcomm 3D Sonic Max fingerprint reader and Quick Charge 5 (based on USB PD) for up to 100W fast charging.


Qualcomm expects the Snapdragon 7+ Gen 3 processor to be used in phones priced in the $400-$600 price segment. Although, most phones powered by this chipset are expected to be launched only in China, India, and other Southeast Asian countries.

Author’s Note: The Snapdragon 7+ Gen 3 processor is an improvement over last year’s Snapdragon 7+ Gen 2. It brings notable improvements in CPU and GPU performance but lacks ray-tracing support for games. To get that feature, consumers would have to opt for slightly higher-priced phones that use at least the Snapdragon 8s Gen 3 processor that was launched a few days ago.

This chipset would be good enough in terms of camera performance for most users. However, enthusiasts who want features like 8K video recording would have to upgrade to phones with the Snapdragon 8 series processors. This chipset would be a great fit for phones like the Galaxy S24 FE or Galaxy S25 FE, but knowing Samsung, it might not use this processor in its phones.

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