AI Geekly: Fall Flash

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 Quarterly Earnings and AI Code Learnings

This week we have a bit of a shorter note; we take a peek at the quarterly results for the major tech co’s (ex-Apple who we’ve left out this week as their investments in AI to date are significantly less than its peers) and the readthroughs for AI. We’ll walk through how their considerable investments are panning-out, with particular attention to plans to expand spending even further. Next we’ll zero-in a little more on Google’s efforts to incorporate AI into its own software development processes, with the company’s CEO sharing that a surprisingly large portion of its code is now AI generated (and human approved). Read on below!

Big AI (Tech)’s Quarterly Earnings Extravaganza
Strong results but significant returns needed to justify AI investment

What it is: Big Tech's September quarter earnings painted a mixed picture: strong top and bottom-line results, driven in part by burgeoning AI businesses, were overshadowed by significant capital expenditure increases and cautious forward guidance. While all four companies (ex-Apple) —Microsoft, Meta, Google, and Amazon—beat earnings expectations, their aggressive investments in AI infrastructure continue to raise investor concerns about profitability and the long-term return on this spending. Microsoft's capital expenditures hit $20 billion, up 50% year over year, while Meta increased its full-year capex guidance to $38-$40 billion, projecting further growth in 2025. Amazon, after a record $22.6 billion capex outlay in Q3 (up 80% year over year), is on track for roughly $75 billion in capex this year and anticipates even higher spending in 2025. Google's $13.1 billion Q2 capex also showed a substantial 62% year-over-year jump.

What it means: The tech giants are engaged in a high-stakes gamble on AI. Microsoft's Azure cloud revenue, while growing 33% annually with 12 percentage points attributed to AI, saw a slight dip in its growth rate. Meta, despite beating earnings estimates, posted slower revenue growth than previous quarters. Google Cloud bucked the trend with accelerating revenue growth (35%, up six percentage points from the prior quarter) and record operating profits, driven by AI spending from customers like Snap and by enforcing pre-existing customer contracts. Amazon Web Services (AWS) grew a steady 19%, with CEO Andy Jassy highlighting its AI business as a "multibillion-dollar run rate" growing at triple-digit percentages. However, all companies acknowledged the ongoing challenge of meeting the surging demand for AI-related infrastructure and services.

Why it matters: The market's reaction to these earnings underscores investor unease about the magnitude and duration of the AI investment cycle. Microsoft's stock experienced its worst day in two years, falling 6%, following its earnings announcement. While Amazon's stock rose 5% after hours, likely buoyed by AWS' strong performance and operating margins, the overall market sentiment remains cautious. As we have stated previously, investors demand meaningful returns on these massive capital outlays for AI infrastructure necessary to train more powerful models… While there are some promising implementations and use cases (here’s a great summary from Google Cloud) based on the numbers invested to date, returns will have to be of a nearly revolutionary scale to justify the dollars spent (that’s not even counting the future spending commitments!). Still a show me story, but we expect the patient and innovative to be rewarded.

Drinking Their Own Bathwater
Google puts its AI to work for internal projects

What it is: Google CEO Sundar Pichai revealed during the company's Q3 2024 earnings call that AI systems are now generating over 25% of all new code for Google's products. This AI-generated code is then reviewed and approved by human engineers, highlighting the growing integration of AI into Google's software development workflows. This internal use of AI for coding complements Google's publicly available AI coding tools and reflects a broader trend in the industry, as highlighted by recent surveys showing widespread adoption of AI coding assistants by developers.

What it means: Google is leveraging AI to streamline its development processes, improve coding efficiency, and accelerate product development cycles. The company's use of AI-generated code, overseen by human engineers, suggests a collaborative approach where AI augments human capabilities rather than replacing them entirely.

Why it matters: Google's embrace of AI-assisted coding highlights the transformative potential of AI in software development (and serves as a showcase for how it can impact other industries). While concerns remain about the potential for AI-generated code to introduce errors and security vulnerabilities, the widespread adoption of these tools suggests that they are becoming an indispensable part of the developer's toolkit. As of today, coding and software development seems to be the strongest application of the technology to date.

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.