Real-time Automatic Speech Recognition (ASR) is a fundamental building block for many commercial applications of ML, including live captioning, dictation, meeting transcriptions, and medical scribes. Accuracy and latency are the most important factors when companies select a system to deploy. We present WhisperKit, an optimized on-device inference system for real-time ASR that significantly outperforms leading cloud-based systems. We benchmark against server-side systems that deploy a diverse set of models, including a frontier model (OpenAI gpt-4o-transcribe), a proprietary model (Deepgram nova-3), and an open-source model (Fireworks large-v3-turbo).Our results show that WhisperKit matches the lowest latency at 0.46s while achieving the highest accuracy 2.2% WER. The optimizations behind the WhisperKit system are described in detail in this paper.

The Cupertino, Calif., company said a new M4 chipset used in its Pro models contains a more powerful "neural engine" to drive features in third-party apps and its own software that rely on AI and machine learning. These engines have been part of Apple's chips since 2017 but have grown considerably more powerful since then, the company said. Tim Millet, the company's vice president of platform architecture, claimed the M4's neural engine is capable of performing 38 trillion operations per second, more than doubling operations per second compared with the base-level M3 chipset found in the company's MacBook Air, MacBook Pro and iMac.

Apple released its new MacBook Air on Monday, touting the updated device as being twice as fast as previous generations. The'world's most popular laptop' starts at 1,099 and features the tech giant's new M3 chip released in 2023. The upgraded chip increases speeds up to 60 percent faster than its M1 predecessor and makes it 13 times quicker than the Intel-based MacBook Air, Apple has claimed. The 13- and 1,299 15-inch screen options are currently available for pre-order starting today and deliveries are set for Friday, March 8, the company announced. 'MacBook Air is our most popular and loved Mac, with more customers choosing it over any other laptop.

Apple has been working of Artificial Intelligence and Machine Learning for decades, but longtime Apple analyst Tim Bajarin believes that Apple is more cautious about publicly touting its own AI prowess in light of the recent controversies surrounding Microsoft's Bing AI and Google's Bard ChatGPT competitor. From a historical standpoint, Apple began showing off early AI models when they introduced their futuristic Knowledge Navigator in 1987 And by 1990, Apple started a significant speech recognition project under Kaifu Lee who today is one the top researchers and experts in AI. Of course, Apple's Siri employs modern-day AI and advanced machine learning to deliver answers to spoken questions or requests and is at the heart of Apple Maps. Apple not jumping into the ChatGPT fray now is reasonable, given the current arrows aimed at Microsoft and Google's AI ChatGPT solutions. Although Bing's ChatGPT and Google's Bard are excellent products with great potential, it was clear that researchers and savvy media would poke holes in its capabilities and make those failures the headlines.

ChatGPT is all the tech world can talk about lately, and with good reason. But there are also starry-eyed tech companies who see the future–the ability for computers to converse naturally and create content that businesses can actually use, at a scale, speed, and cost humans can't possibly match. But ChatGPT, Google Bard, and Microsoft's Bing chat are just one small part of the generative AI revolution. These tools aren't just a flash in the pan. Big tech companies like Google and Microsoft see this new generative AI as a massive part of all our futures.

This week, Apple revealed macOS Monterey, an update to its desktop operating system that will roll out this fall. It comes with a whole host of new features that the company highlighted in its keynote presentation at its annual WWDC event. But if you're stuck on a Mac with an Intel chip, some of those improvements won't make it to your computer at all. Apple computers have been largely powered by Intel chips since 2006. Last November, the company announced that it would switch to its own ARM-based M1 chips. Now with macOS Monterey, Apple has started to leave Intel behind.

The future of machine learning is at the "edge," which refers to the edge of computing networks, as opposed to centralized computing. In a centralized machine learning network, users send data to a server, which makes a prediction, and sends that back to the user. This is slower, more expensive, less reliable, and less secure than edge computing, where predictions are made directly on the user's device. The problem with edge computing is that mobile and IoT devices are generally weak and low-powered, while AI models often have intense compute requirements. Apple's M1 chip is the answer.

Once in a while, a young company will claim it has more experience than would be logical -- a just-opened law firm might tout 60 years of legal experience, but actually consist of three people who have each practiced law for 20 years. The number "60" catches your eye and summarizes something, yet might leave you wondering whether to prefer one lawyer with 60 years of experience. There's actually no universally correct answer; your choice should be based on the type of services you're looking for. A single lawyer might be superb at certain tasks and not great at others, while three lawyers with solid experience could canvas a wider collection of subjects. If you understand that example, you also understand the challenge of evaluating AI chip performance using "TOPS," a metric that means trillions of operations per second, or "tera operations per second."

Apple, at their latest event'Time Flies', introduced an all-new iPad Air that houses a powerful A14 Bionic chip, a 5 nm chipset. This makes the iPad Air, the world's first device to operate on a 5nm chip. "We're excited to introduce Apple's most powerful chip ever made, the A14 Bionic," said Greg Joswiak, Apple's senior vice president of Worldwide Marketing. Traditionally, Apple would launch new chipsets with iPhones. Instead, the A14 Bionic was announced alongside the new iPad Air.

Machine learning (ML) and artificial intelligence (AI) now permeate nearly every feature on the iPhone, but Apple hasn't been touting these technologies like some of its competitors have. I wanted to understand more about Apple's approach, so I spent an hour talking with two Apple executives about the company's strategy--and the privacy implications of all the new features based on AI and ML. Despite this, Apple has included dedicated hardware for machine learning tasks in most of the devices it ships. Machine intelligence-driven functionality increasingly dominates the keynotes where Apple executives take the stage to introduce new features for iPhones, iPads, or the Apple Watch. The introduction of Macs with Apple silicon later this year will bring many of the same machine intelligence developments to the company's laptops and desktops, too.