Apple's Powerful New AI Advancements
Plus: Stability AI's new features, Google’s MetNet-3: A SoTA AI weather model.
Hello Engineering Leaders and AI Enthusiasts!
Welcome to the 138th edition of The AI Edge newsletter. This edition brings you Apple’s new advancements in AI.
And a huge shoutout to our incredible readers. We appreciate you😊
In today’s edition:
🍎 Apple’s new AI advancements: M3 chips and AI health coach
🔥Stability AI’s new features to revolutionize business visuals
🤖 Google’s AI model makes high-resolution 24-hour weather forecasts
📚 Knowledge Nugget: Why open-source LLMs matter by
Let’s go!
Apple’s new AI advancements: M3 chips and AI health coach
Apple unveiled M3, M3 Pro, and M3 Max, the most advanced chips for a personal computer. They have an enhanced Neural Engine to accelerate powerful ML models. The Neural Engine is up to 60% faster than in the M1 family of chips, making AI/ML workflows faster while keeping data on device to preserve privacy. M3 Max with 128GB of unified memory allows AI developers to work with even larger transformer models with billions of parameters.
(Source)
A new AI health coach is in the works. Apple is discussing using AI and data from user devices to craft individualized workout and eating plans for customers. It next-gen Apple Watch is also expected to incorporate innovative capabilities for detecting health conditions like hypertension and sleep apnea.
(Source)
Why does this matter?
Apple’s release of Macs powered by the M3 chips shows it is embracing AI through custom hardware (as usual). Apple is also keeping pace with rivals like Qualcomm, who made a similar claim last week that their Snapdragon X Elite can run a 13B model on-device.
In addition, the inclusion of AI features in the new Apple Watch shows it is staying at the forefront of AI trends and innovation.
Stability AI’s new features to revolutionize business visuals
Stability AI shared private previews of upcoming business offerings, including enterprise-grade APIs and new image enhancement capabilities.
Sky Replacer: It is a new tool that allows users to replace the color and aesthetic of the sky in original photos to improve their overall look and feel (thoughtfully built for industries like real estate).
Stable 3D Private Preview: Stable 3D is an automatic process to generate concept-quality textured 3D objects. It allows even a non-expert to generate a draft-quality 3D model in minutes by selecting an image or illustration or writing a text prompt. This (below) was created from text prompts in a few hours.
Stable FineTuning Private Preview: Stable FineTuning provides enterprises and developers the ability to fine-tune pictures, objects, and styles at record speed, all with the ease of a turnkey integration for their applications.
Why does this matter?
It democratizes 3D content creation with AI. Stable 3D levels the playing field for designers, artists, and developers, enabling them to create thousands of 3D objects cheaply. These features are also valuable for many industries like entertainment, gaming, advertising, etc.
Google’s MetNet-3 makes high-resolution 24-hour weather forecasts
Developed by Google Research and Google DeepMind, MetNet-3 is the first AI weather model to learn from sparse observations and outperform the top operational systems up to 24 hours ahead at high resolutions.
Currently available in the contiguous United States and parts of Europe with a focus on 12-hour precipitation forecasts, MetNet-3 is helping bring accurate and reliable weather information to people in multiple countries and languages.
Why does this matter?
The race is on to bring AI to weather forecasting, but I think Google is already winning here. The U.K. Met Office, which runs one of the world’s top weather forecast models, is teaming up with the Alan Turing Institute to develop highly accurate, lower-cost models using AI/ML. In the USA, NOAA is also examining how forecasters can utilize AI.
The bottom line– cost savings and accuracy from AI forecasts are highly appealing to weather and climate agencies.
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Knowledge Nugget: Why open-source LLMs matter
There has been extensive discussion around the merits of open-source LLMs from the community at large. Most of it is vague, so,
and list specifics in this article on what value would we gain at large from having truly open-source LLMs:Community oversight
Re-creation of models
Self-hosting and custom deployments
Specialization
The article also gives specifics of what does it mean for an LLM to be open source:
Publicly available weights
Publicly available datasets
Publicly available training code & infrastructure
Why does this matter?
The discussion in the article leads to an evident conclusion: Open-source models don’t need to get better, but smaller and more focused. For instance, Code-LLaMa 34B is a great example of the success of domain-specific models. These insights help optimize AI development, ultimately benefiting both developers and end-users.
What Else Is Happening❗
🪙New AWS service lets customers rent Nvidia GPUs for quick AI projects.
AWS launched Amazon Elastic Compute Cloud (EC2) Capacity Blocks for ML, enabling customers to buy access to these GPUs for a defined amount of time, typically to run some sort of AI-related job such as training a machine learning model or running an experiment with an existing model. (Link)
👥LinkedIn hits 1 billion members, adds more AI features for job seekers.
Paying users will get new AI features that can tell a user, who may be plowing through dozens of job postings, whether they're a good candidate based on the information in their profile. It can also recommend profile changes to make the user more competitive for a job. (Link)
🤖Instagram spotted developing a customizable ‘AI friend’.
It seems Instagram has been developing an “AI friend” feature that users could customize to their liking and then converse with, brainstorm ideas, and much more. Users will be able to select their gender, age, ethnicity, personality, name, etc. (Link)
❄️Snowflake makes leading AI models and LLMs accessible to all users with Cortex.
Snowflake Cortex is a fully managed service that enables organizations to more easily discover, analyze, and build AI apps in the Data Cloud. It underpins the LLM-powered experiences in Snowflake, including the new Snowflake Copilot and Universal Search. (Link)
🏆AI named word of the year by Collins Dictionary.
The use of the term has quadrupled this year. The increase in conversations about whether it will be a force for revolutionary good or apocalyptic destruction has led AI to be given this title by the makers of Collins Dictionary. (Link)
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