Good morning. Yesterday, NASA launched its Europa Clipper mission, a 5.5-year, 1.8 billion mile-long journey to determine whether the oceans beneath the crust of the Jupiter moon Europa possess the necessary ingredients to create life.

The mission has the potential to return groundbreaking results.

— Ian Krietzberg, Editor-in-Chief, The Deep View

In today’s newsletter:

AI for Good: Wildfire mitigation

Wildfires have been steadily worsening for years. Certain applications of generative AI are increasingly being explored as a potential aid to human firefighters. 

The details: The intention is in highly accurate early warning systems that enable first responders to mitigate before things get out of control. 

Colorado recently advanced a bill that would appropriate $7.5 million in funding to continue its partnership with Lockheed Martin to develop and deploy AI-enabled tools in firefighting. 

A regularly complex element to the deployment of AI tools to help fight environmental disasters is the environmental toll the tools themselves exact; small, precise models, operating out of clean data centers, are the ideal here. Large, energy-intensive models operating out of dirty data centers could well cause more harm than good. 

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Adobe launches new video model 

Adobe on Monday launched a beta version of its Firefly video generation model, which is now accessible through a number of Adobe’s applications.

The details: Embedded directly in the video-editing software, Premiere Pro users can now employ something called Generative Extend, which can add up to two seconds of additional footage to the beginning or end of a given clip. 

Why it matters: Here, we have yet another publicly accessible generative video model while OpenAI’s heavily hyped Sora remains elusive. As I’ve said before, there is no moat. 

The release of this suite of generative tools comes amid ongoing copyright and ethical concerns regarding the formation and deployment of generative AI; Adobe claims that the model is trained using only “licensed and public domain” content, a marked difference from most developers who use the phrase “publicly available” content to refer to the vast reaches of the internet. 

Adobe additionally said that it would attach content credentials to all clips generated by the system to ensure creators and consumers can track the authenticity and provenance of the content being produced using Adobe’s tools. 

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Study: Generative AI and the embers of autoregression 

In determining the reasoning capabilities (or lack thereof) of Large Language Models (LLMs), a team of researchers recently decided to examine the models a bit differently. Arguing that studying LLMs through human benchmarks will not reveal any LLM-unique capabilities, they chose to study LLMs through the lens of the original task the models were designed to accomplish: autoregression, or next-word prediction over text. 

The details: The researchers predicted that LLMs would perform better when the correct output was highly probable, and when the correct task variance was highly probable. 

The same team recently published an addendum to this study that explored OpenAI’s o1, a model that was designed not for next-word prediction, but for reasoning. 

They found that, though it performed “substantially” better than the other LLMs they studied, it showed the same tendencies and capabilities around high (and low) probability scenarios. 

Nvidia on the brink of becoming the world’s most valuable company

Shares of Nvidia opened strong on Monday, rallying nearly 3% by the end of the day to $138 per share, surpassing Nvidia’s previous highest-close record of $135.58, notched on June 18. 

The firm, whose stock has spiked some 180% this year alone — began a rally in early 2023 that has yet to, even slightly, diminish. 

Regarded by most as the most obvious way to invest in the artificial intelligence boom that has absorbed such a massive quantity of venture capital funding and investor attention alike, Nvidia is in an enormously powerful position. 

For a variety of reasons, the technology sector is spending a remarkable amount of money to establish AI infrastructure. As TD Cowen analysts recently wrote: “We believe the major companies in AI ... face an investment environment characterized by a Prisoner's Dilemma — each is individually incentivized to continue spending, as the costs of not doing so are (potentially) devastating.”

The biggest names — xAI, Microsoft, Meta — are talking about the purchase and application of hundreds of thousands of the chips that power generative AI. 

Nvidia supplies those chips. 

This is why the firm is considered by many on Wall Street to be the “picks and shovels” of the AI gold rush; even if there is no gold to be found, the business of picks and shovels is a hard cash business, and Nvidia’s picks are in very high demand. For now. 

Meta said in January that by the end of 2024, it would have more than 350,000 of these H100 chips in its arsenal. 

Nvidia is expecting record revenue of $32.5 billion for its third-quarter results, the bulk of which will come from its data center business. 

What’s been going on with Nvidia points very well to the circular economy of AI. These Big Tech names are feeding billions of dollars directly into Nvidia and the resulting spend is elevating everyone’s stock prices. But the fruits of that expense are not, in turn, deriving much in the way of value, as most of Big Tech is right now subsidizing this enormous cost just to get users on board with generative tech. 

The circle is really between Nvidia and Big Tech, while Wall Street watches in excitement. 

It’s not a sustainable scenario. 

At some point, the companies that are paying into the Nvidia charitable fund will need to come up with a way to justify that expense. Before that happens, any sign of slowdown in the AI economy will be evidenced first by Nvidia as a reduction in demand and spending, a result that will likely send Wall Street jumping overboard.

This is why Nvidia’s earnings are so important to the broader ecosystem. If — which I don’t expect — Nvidia reports below its expectations, I would imagine that the investment environment of AI would suddenly become very, very challenging.

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