Nvidia Is Now Worth More Than Apple, Thanks to AI
Plus: OpenAI reverse engineers the workings of AI models, New Chinese video generation model beats OpenAI’s Sora.
Hello Engineering Leaders and AI Enthusiasts!
Welcome to the 292nd edition of The AI Edge newsletter. This edition features Nvidia’s ride on the AI wave to becoming the second-most valuable company.
And a huge shoutout to our amazing readers. We appreciate you😊
In today’s edition:
🎧 OpenAI reverse engineers the workings of AI models
🤖 New Chinese video generation model beats OpenAI’s Sora
📊 Nvidia is now the second-most valuable company, overtaking Apple
🧠 Knowledge Nugget: The Alchemy of Scale Transformation by
Let’s go!
OpenAI reverse engineers the workings of AI models
In new research, OpenAI has shared improved methods for finding a large number of "features"—patterns of activity in AI models that are human interpretable. They developed new state-of-the-art methodologies that allow scaling sparse autoencoders to tens of millions of features on frontier AI models.
It demonstrated smooth and predictable scaling, with better returns to scale than prior techniques. And they could find 16 million features in GPT-4. The research also introduces several new metrics for evaluating feature quality.
OpenAI has shared the paper, code, and feature visualizations to foster further exploration.
Why does it matter?
It could bring us closer to understanding the inner workings of neural networks. This interpretability will eventually increase model trustworthiness and steerability.
While OpenAI is being criticized for taking unnecessary risks with AI technology, this shows it is also keen on tackling the risk by making models more explainable.
New Chinese video generation model beats OpenAI’s Sora
Kuaishou, a Chinese tech company, has introduced Kling, an AI model for video generation. It can make videos up to two minutes long at 1080p resolution and 30 frames per second, vs. Sora’s one-minute videos.
Kuaishou claims Kling correctly simulates the physical properties of the real world, including complex motion sequences. Using a diffusion transformer, it can also combine concepts and create fictional scenes, such as a cat driving a car through a busy city.
The model is currently available as a public demo in China.
Why does it matter?
Move over, Sora. This Chinese alternative is blowing everyone’s minds. It is becoming increasingly clear that China is catching up fast with the USA in AI.
Nvidia is now the second-most valuable company, overtaking Apple
Nvidia rallied to record highs on Wednesday, with it’s stock market valuation hitting $3 trillion and overtaking Apple to become the world’s second most valuable company. This comes after Nvidia made a series of major announcements in the past week.
However, Nvidia’s stock has surged 147% so far in 2024, with demand for its top-of-the-line processors far outstripping supply as Big Tech races to build out their AI computing capabilities and dominate the emerging technology.
Microsoft remains the world’s most valuable company, with a market value of approximately $3.15 trillion.
Why does it matter?
Nvidia is now seen as a key company to watch to see how fast AI-powered tech is spreading across the business world, a shift that Nvidia’s founder, Jensen Huang, has declared as the dawn of the "next industrial revolution".
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Knowledge Nugget: The Alchemy of Scale Transformation
This intriguing article by
discusses the transformative power of scale and how it impacts economics, innovation, and the development of technology, particularly in the realm of computing and AI.Changing the scale of something can fundamentally change its nature and quality. In some cases, a lack of scale can inhibit innovation, while in other cases, large-scale economics can drive it.
The general-purpose computer, manufactured at a massive scale, can replace many traditional solutions by being repurposed using different software tools.
The development of LLMs further extends this concept. If the novelty of LLMs is what is at first most striking, their generality is also important. If we compare them to traditional software, they potentially ‘solve’ more user problems than a ‘traditional’ single software tool.
Why does it matter?
The concept of scale is a critical lens for making sense of the rapid technological changes and innovations happening today, especially in the field of AI, which will likely have profound impacts on our future.
What Else Is Happening❗
🚀Adobe’s launches AEP AI Assistant to help brands master customer data and outreach
Adobe’s Adobe Experience Platform (AEP) is a real-time customer experience management (CXM) solution designed for enterprises. AEP AI Assistant is a gen AI chatbot hooked up to the AEP and an enterprise’s storehouse of advertising and customer data, brand assets, and content collateral (at their direction). (Link)
🏆The most comprehensive benchmarking & leaderboard for image models is here!
AI image models have achieved near-photographic quality. But how do they compare? Are the open-source alternatives on par with their proprietary counterparts? The Artificial Analysis Text to Image Leaderboard aims to answer these questions with human preference-based rankings. (Link)
🧬AI used to predict potential new antibiotics in groundbreaking study
Scientists used an algorithm to mine the entirety of the microbial diversity that we have on earth – or a huge representation of that – and find almost 1million new molecules encoded or hidden within all that microbial dark matter. (Link)
🔒Meta gets EU complaints from 11 countries over use of personal data to train AI
Meta rejected the criticism and referred to a May 22 blog in which it said it uses publicly available online and licensed information to train AI as well as information that people have shared publicly on its products and services. (Link)
🔍The Federal Trade Commission is investigating Microsoft-Inflection AI deal
The FTC has sent subpoenas to tech giant and startup, asking whether their partnership evaded the required government antitrust review of the transaction. Microsoft picked off Inflection’s specialized workforce of AI researchers but didn’t purchase the company outright. (Link)
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