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- Apple finally reveals big AI plans, boosting their stock price
Apple finally reveals big AI plans, boosting their stock price
Plus, AI reveals that elephants call each other by name
Steve Brown
June 13, 2024
Sponsored by
This Week in AI
Apple Intelligence is here (well, soon, maybe)
In a highly polished video keynote delivered at WWDC 2024, the Apple developer conference, Apple began to reveal its plans to incorporate AI across its platforms and services. The announcement led to a nice pop in Apple stock, briefly restoring its position as the most valuable company on earth before falling back. Here are the key takeaways:
Apple Intelligence - In the same way Apple branded its chips Apple Silicon, Apple has decided to brand the cross-platform AI capabilities it’s building into its operating systems. Apple Intelligence will provide OS-level AI capabilities across iOS, MacOS, and iPadOS. No word on VisionOS, WatchOS, or TVOS, but perhaps that’s a project for 2025 and beyond.
System-wide - Apple is making Apple Intelligence capabilities available system-wide in their operating systems and exposing AI functions to developers so they can take full advantage of them in their applications. So, AI-generated text will be available across apps like Pages, Mail, Notes, and many others.
Privacy - Apple wants to deliver an AI experience that feels truly personal but also wants to maintain its privacy promises. So it’s doubling down on its privacy approach with Apple Intelligence by committing that user data will never be stored, data is only used to fulfill your requests, and that independent verification will back up their promises.
Hybrid Architecture - Apple Intelligence is natively hybrid. Scheduling software will automatically determine whether your request can be executed locally on-device. If the task requires more neural processing than is available, computation will be offloaded to secure Apple cloud servers based on Apple Silicon. This process is invisible to users.
OpenAI connection - Apple realizes their AI capabilities lag behind OpenAI's. So, they made a deal to give Apple device users free access to ChatGPT capabilities, specifically ChatGPT-4o. OpenAI is doing the deal for free to boost its distribution. Privacy users are unimpressed. Elon Musk, after dropping his lawsuit against OpenAI, has threatened to ban Apple products from his company campuses in response, claiming ChatGPT integration is an ‘unacceptable security violation.’ Apple says it plans to provide access to other third-party models, for example, Google’s Gemini, in the future.
Action-oriented - Apple Intelligence seems to be oriented toward helping users get things done with their devices. It will be able to take actions that span across multiple apps.
Siri unlobotomized - Siri, the very first personal voice assistant, never fulfilled its promise. Anyone with an iPhone will complain about how borderline useless it is. In the age of impressive LLMs like ChatGPT-4o, Siri looked ready to be put out to pasture. Apple plans to rehabilitate Siri and actually make it useful by combining Apple Intelligence with the fruits of its partnership with OpenAI. Your move, Alexa.
Don’t hold your breath - Apple Intelligence will be available in upcoming Apple operating system releases for iOS 18, iPadOS 18, and MacOS Sequoia, but only in ‘beta’ this fall. Many of the features discussed or demonstrated at WWDC will follow at some point in the future. Apple has clearly signaled they plan a multi-year rollout of AI-based features. As one commentator argues, Apple is taking a thoughtful, pragmatic approach to AI integration, and Apple Intelligence is right on time.
Speaking at the AI Summit in London, OpenAI chief architect Colin Jarvis told attendees, “Don’t build for what’s available today because things are changing so fast.” Jarvis predicts that future models will be smarter, cheaper, more multimodal, and more customized using reinforcement learning to tackle specialist tasks and domains.
Competition is heating up in the text-to-video market. After OpenAI set the standard with its Sora platform, there has been a flurry of activity with Veo from Google DeepMind and Kling AI from China. The latest entry in the space is Dream Machine from Luma AI. Unlike Sora, this is open to the public to try.
Videos: How realistic are today’s robots?
Robots have improved in leaps and bounds over the last decade, and particularly in the last 18 months. The combination of advanced machine vision, better batteries, new motors, learning algorithms, LLM integration, and lower-cost components has yielded a plethora of cool new humanoid robots that can perform valuable work. This episode of ColdFusionTV explores the current state of the art and asks where it all goes from here. (17m 49s)
AI Tech and Innovation
Stock market darling Nvidia is the undisputed champion of the AI world right now. With a multi-year advantage over their competitors, Nvidia’s proprietary hardware and software stack is the platform of choice for anyone serious about building foundation or frontier models. Proprietary technology components, including NVLink, CUDA, and NIMs, make a nice wide moat around Castle Nvidia. NVLink is Nvidia’s proprietary interconnect technology that enables customers to connect tens of thousands of their GPUs to behave like one giant, mega-powerful GPU. Competitors are fighting back with an alternative based on open standards. Customers desperately want that, too. Nvidia makes great products, but without much competition, they come with a price tag to match. The new open standard, known as the Ultra Accelerator Link (UALink), will allow system builders to connect together accelerator chips from a range of different suppliers. The standard is based on technology contributed by both Intel and AMD and is complimentary with Ultra Ethernet (see diagram below), another new open standard. Other companies involved in the consortium include Cisco, Meta, HPE, and Broadcom. First systems using UALink won’t be available until 2026 at the earliest. This will be AI’s Betamax vs VHS battle of the 2020s. In the long haul, open standards nearly always win (e.g., USB beat Firewire), and Intel, in particular, is very adept at driving open standards into the market.
MLPerf, the AI benchmarking suite sometimes known as the “Olympics of machine learning,” makes it easier to do apples-to-apples testing of different AI platforms. A large system based on Nvidia chips just took the honors for benchmarks related to the tuning of large language models and running graph neural networks.
AI Insights
“Why a physician would ever have to use Epyc I don’t know. They shouldn’t need to. An AI will do that for them.”
Elephants call out to each other using individual names that they invent, according to a new study that used AI to analyze hundreds of hours of audio recordings of the calls made by two wild African elephant herds in Kenya. Elephants and humans are now the only two species known to invent names for each other.
Todd McKinnon, CEO of cybersecurity firm Okta, thinks that without the massive, ongoing R&D investments that Google makes to develop its own in-house AI models, Microsoft may be relegated to being an AI “consultancy” in the future. While they have had several public missteps with Gemini, Google remains well-placed to win the AI race in the long term. Speaking on CNBC, McKinnon sees high potential for AI but warned, “I actually expect the swing of regulation to go so far that we leave only the biggest, most powerful companies in control of AI.”
The Walton Foundation has released a new survey on the role AI is playing in the classroom. Teacher awareness of ChatGPT has risen to 79%, up from 25% a year ago. The full report shares details on how AI chatbots are being used by K-12 students, undergrads, teachers, and parents and their attitudes toward them. Across the board, people agree that chatbots have had more of a positive than negative impact, have legitimate educational uses, and they expect to increase their AI use in the next five years.
Building on last week’s article, Synthetic makes the case that academia must adapt quickly to embrace AI so it can fulfill its vital role preparing society for the monumental AI-driven transition ahead. Our education system needs to cut costs, transition its focus to lifelong learning, and reimagine tuition and pedagogy to meet the needs of the 21st century.
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