Musk Unveils World’s Most Powerful AI Training Cluster
Plus: Robotics won’t have a ChatGPT-like explosion: New Research, NeuralGCM predicts weather faster than SOTA climate models.
Hello Engineering Leaders and AI Enthusiasts!
Welcome to the 323rd edition of The AI Edge newsletter. This edition features the world’s most powerful AI training cluster.
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In today’s edition:
🔋 Musk unveils the world’s most powerful AI training cluster
🤖 Robotics won’t have a ChatGPT-like explosion: New Research
🌦️ NeuralGCM predicts weather faster than SOTA climate models
🧠 Knowledge Nugget: The serious science of trolling LLMs by
Let’s go!
Musk unveils the world’s most powerful AI training cluster
Elon Musk, the CEO of xAI, has announced that his company has begun training its large language model, Grok, on what he claims is the "world's most powerful AI training cluster." The cluster in Memphis, Tennessee, is equipped with 100,000 Nvidia H100 AI chips and is touted as the world's most potent AI training system.
Musk said that this new training cluster would give xAI's AI model, Grok, a "significant advantage" and that the company aims to release Grok 2 in August and Grok 3 in December to make it the "world's most powerful AI by every metric" by the end of this year.
Why does it matter?
The scale and ambition of this project demonstrate Musk's determination to make xAI a powerful player in the fast-moving generative AI market. However, Musk is known for setting ambitious deadlines that aren’t always met, so it remains to be seen if xAI can deliver this promise.
Robotics won’t have a ChatGPT-like explosion: New Research
Coatue Management has released a report on AI humanoids and robotics's current and future state. It says robotics will unlikely have a ChatGPT-like moment where a single technology radically transforms our work. While robots have been used for physical labor for over 50 years, they have grown linearly and faced challenges operating across different environments.
The path to broad adoption of general-purpose robots will be more gradual as capabilities improve and costs come down. Robotics faces challenges like data scarcity and hardware limitations that digital AI technologies like ChatGPT do not face. But investors are still pouring billions, hoping software innovations could help drive value on top of physical robotics hardware.
Why does it matter?
We’re on the cusp of a gradual yet profound transformation. While robotics may not suddenly become ubiquitous, the ongoing progress in artificial intelligence and robotics will dramatically alter the landscape of numerous fields, including manufacturing and healthcare.
NeuralGCM predicts weather faster than SOTA climate models
Google researchers have developed a new climate modeling tool called NeuralGCM. This tool uses a combination of traditional physics-based modeling and machine learning. This hybrid approach allows NeuralGCM to generate accurate weather and climate predictions faster and more efficiently than conventional climate models.
NeuralGCM's weather forecasts match the accuracy of current state-of-the-art (SOTA) models for up to 5 days, and its ensemble forecasts for 5-15 day predictions outperform the previous best models. Additionally, NeuralGCM's long-term climate modeling is one-third as error-prone as existing atmosphere-only models when predicting temperatures over 40 years.
Why does it matter?
NeuralGCM presents a new approach to building climate models that could be faster, less computationally costly, and more accurate than existing models. This breakthrough could lead to accessible and actionable climate modeling tools.
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Knowledge Nugget: The serious science of trolling LLMs
In this article,
discusses the practice of "trolling" LLMs - intentionally trying to get the models to say something outrageous or nonsensical and then sharing the result online. While some view this as pointless, the author argues that it serves an essential purpose.The author believes that LLM vendors are more focused on making their models appear human-like and avoiding embarrassment rather than making them robust and capable. By probing the models' limitations through trolling, researchers can better understand where the models' reasoning falls short rather than relying on their performance on curated benchmarks.
Why does it matter?
“Trolling” LLMs is becoming a legitimate way to scientifically probe and understand the boundaries of their capabilities beyond memorizing training data. Essentially, it helps pierce through the illusion crafted by LLM companies and reveal where these models' true reasoning abilities end.
What Else Is Happening❗
💊 VeriSIM Life’s AI platform can accelerate drug discovery
VeriSIM Life has developed an AI platform, BIOiSIM, to help speed up drug discovery and reduce animal testing. The platform contains data on millions of compounds and uses AI models to predict how potential new drugs will work in different species, including humans. (Link)
📷 Anthropic is working on a new screenshot tool for Claude
This tool will allow users to capture and share screenshots from their desktop or browser directly within the Claude chat interface. It will streamline the sharing of visual information and code snippets when asking Claude for assistance on tasks like coding or troubleshooting. (Link)
🔂 Luma’s “Loops” feature in Dream Machine transforms digital marketing
The “Loops” feature allows users to create continuous video loops from text descriptions or images. It does so without visible cuts or transitions, opening up new possibilities for engaging content creation and advertising. (Link)
🤖 Tesla will use humanoid robots internally by next year
Elon Musk has announced that Tesla will use humanoid robots at its factories by next year. These robots, called Optimus, were expected to be ready by the end of 2024. Tesla aims to mass produce robots for $20,000 each and sell them to other companies starting in 2026. (Link)
🎤 Perplexity launches Voice Mode for its AI assistant on iOS
Perplexity has introduced a new feature for its iOS app called Voice Mode. It allows subscribers with Pro accounts to interact verbally with the AI-powered search engine. Users can now engage in voice-based conversations and pose questions using various voice options. (Link)
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