AI Geekly: Going Nuclear

Welcome back to the AI Geekly, by Brodie Woods, brought to you by usurper.ai. This week we bring you yet another week of fast-paced AI developments packaged neatly in a 5 minute(ish) read.

TL;DR AI Gamma Rays; NYT AI C&D; x86 v ARM

This week we have a quick note for you. Big tech players are signing major contracts to spin-up nuclear reactors —Artificial General Intelligence (AGI) aspirations hinge on converting electrons into inference/reasoning and nuclear is emerging as a major potential source. The NY Times is making the news instead of covering it this week, firing-off a firmly worded cease & desist order to Perplexity, a popular AI search tool that the Times itself is partly responsible for popularizing (the irony!). Finally, we look at the unholy alliance of AMD and Intel as they join forces to fend-off the growing popularity of rival ARM’s architecture in the chip space. Read on below!

Splitting the Atom
Several recent nuclear deals by Big Tech and AI players

What it is: Desperate for incremental electrons to feed insatiable demand, as AI datacenters scale up to train bigger, more powerful models, major tech companies are turning to nuclear power to meet the escalating energy demands. Amazon recently announced three new agreements to support the development of nuclear energy projects, including a $500 million investment in (Small Modular Reactor) SMR developer X-energy and a partnership with Energy Northwest to build four advanced SMRs in Washington. Google has hopped on the nuclear bandwagon, signing a power purchase agreement with Kairos Power for 500 megawatts of power from their proposed SMR plants. These developments follow a similar deal struck by Microsoft last month with Constellation Energy to restart a reactor at the Three Mile Island nuclear plant in Pennsylvania (not the reactor that nearly melted down, mercifully).

What it means: The tech industry's sudden love of nuclear energy is a positive development in the growing recognition of its potential as a reliable, scalable, and carbon-free source of power. As the demand for electricity to fuel AI data centers continues to surge (not just keeping pace with the growth in necessary compute, rather anticipating the growth in that growth), tech giants are seeking long-term solutions to ensure a stable and sustainable energy supply. The investment in SMRs, a newer and more flexible type of reactor, could help to scale-up a more distributed network of nuclear power sources.

Why it matters: This pendulum swing in interest and investment in nuclear power could drive meaningful changes in the structure of both tech and energy. The influx of investment from tech giants could revitalize the nuclear industry, an industry which has seen dozens of plants shuttered over the past decade as poor economics and high maintenance costs have deterred investment. This incremental capital could drive meaningful innovation, accelerating the development and deployment of advanced reactor designs. However, the long lead times for new nuclear projects, coupled with potential regulatory hurdles and public perception challenges, could create uncertainty for investors seeking more immediate returns —part of the reason that larger, diversified tech companies with the balance sheets and the patience to invest long term have been the ones to step up.

Another Day, Another NYT AI Legal Move
AI search provider Perplexity receives Cease & Desist from the Times

What it is: Finding itself once again in the headlines instead of writing them, the New York Times sent a cease & desist letter to popular AI search provider Perplexity on copyright grounds similar to its lawsuit against OpenAI. The newspaper alleges that Perplexity is violating copyright law by utilizing its content to generate summaries and other outputs without permission, echoing similar claims made by other publishers (incl. Conde Nast and Forbes) earlier this year.

What it means: Perplexity, while denying the use of scraping for model training, argues that it is simply indexing web pages and presenting factual information, which it claims is not subject to copyright restrictions. The action follows the Times' ongoing lawsuit against OpenAI and Microsoft over the alleged misuse of its content for AI model training. Sharing similarities with the many legal moves launched by news publishers, and nations, against Google and Facebook for their news aggregation, content creators are wrestling with managing data rights in the AI age.

Why it matters: This is just another action in the avalanche of C&Ds and lawsuits since the popularization of Generative AI. With tech companies choosing to train their proprietary AI models largely through the un-permissioned scraping of large swaths of publishers’ copyrighted content, this is inevitable. Content publishers across mediums are rightly fighting for compensation and recognition for their labors. It’s possible with the high volume of lawsuits that AI companies could change their tact and pursue a more equitable data acquisition approach that prioritizes licensing, but we think this unlikely.

Moral Hazard: With limited legal ramifications to date, and many examples of lawsuits being settle via licensing agreement there is little rationale for AI companies to contract ahead of litigation —public and private capital markets have not penalized these companies’ copyright flippancy either, in fact, they’ve rewarded it! With loftier and loftier valuations (as we covered last week with OpenAI’s $6.6 Bn raise). Ultimately, as a society we will need to come-up with a mechanism to compensate those creators whose data has been used to train AI models.

Burying the Hatchet
Intel and AMD join forces in new x86 consortium to tackle growing ARM dominance

What it is: In a historic move, Intel and AMD have announced the formation of the x86 Ecosystem Advisory Group, a collaborative effort to standardize and shape the future of the x86 instruction set (the x86 architecture was created by Intel in the 70s and licensed to AMD). Joining the two chip giants are major tech companies, including Dell, Google Cloud, HPE, Lenovo, and Microsoft, along with “industry luminaries” Linus Torvalds (creator of the Linux operating system) and Tim Sweeney (CEO of Epic Games of Fortnight fame). The group's primary objective is to address the growing fragmentation within the x86 ecosystem, driven by years of incompatible tweaks and custom instructions added by both Intel and AMD, and to ensure a more unified and developer-friendly platform.

What it means: This unprecedented partnership is the result of a major upset in the dynamics of the chip market over recent years. The rise of ARM-based processors in the data center and laptop (including Apple famously dropping Intel as chip supplier in 2020 with the introduction of its proprietary M-series ARM architecture chips), coupled with Intel's recent struggles and AMD's resurgence, has forced Intel to swallow its pride and prioritize collaboration over competition. By working together to standardize x86, Intel and AMD aim to create a more cohesive and robust ecosystem, hoping to fend off the growing threat from ARM and maintain x86's relevance in a world where AI-driven datacenter growth favors greater performance and flexibility.

Why it matters: A standardized and well-defined x86 architecture would simplify software development, enhance compatibility across platforms, and potentially accelerate innovation by providing developers with a clear roadmap for future development (for example building-in functionality that coincides with expected features in chip designs). The success of this collaboration hinges on the ability of Intel and AMD to set aside their long-standing rivalry and win back the confidence of customers who have been tempted by the higher efficiency of ARM designs when it comes to power, heat, and compute.

About the Author: Brodie Woods

As CEO of usurper.ai and with over 18 years of capital markets experience as a publishing equities analyst, an investment banker, a CTO, and an AI Strategist leading North American banks and boutiques, I bring a unique perspective to the AI Geekly. This viewpoint is informed by participation in two decades of capital market cycles from the front lines; publication of in-depth research for institutional audiences based on proprietary financial models; execution of hundreds of M&A and financing transactions; leadership roles in planning, implementing, and maintaining of the tech stack for a broker dealer; and, most recently, heading the AI strategy for the Capital Markets division of the eighth-largest commercial bank in North America.