The Dow Jones Industrial Average (DJIA) hit another weak patch on Monday, backsliding nearly 500 points and slipping back below the 47,000 handle to start the new trading week with many of the same questions from last week going unanswered. The AI segment continues to see new challenges amid concerns about endpoint revenues, and investors are hoping that a kickstart to official data sources following the reopening of the federal government will help push the Federal Reserve (Fed) to deliver a third straight interest rate cut in December.
Alphabet shares supported by Berkshire investment
Shares in Google parent holding company Alphabet (GOOG) rose over 3% on the day after it was revealed that Warren Buffett’s Berkshire Hathaway (BRK) poured $4.3 billion into a stake in the Google search and YouTube giant at the end of September. Hyper-traditionalist investor Warren Buffett recently announced his retirement by the end of the year to Berkshire shareholders, leading to speculation that a play into Google properties is being spearheaded by more tech-friendly names in the Berkshire flagship.
Berkshire Hathaway continues to unwind its massive holdings of Apple (AAPL) stock, shedding another 15% of its total shares held as of the end of the third quarter. However, the Oracle of Omaha’s investment company’s holdings in Apple still sit at a lofty $60.7 billion.
Too-hot AI rally now faces tough questions about profitability
The AI trade continues to come under renewed pressure, with LLM computing services darling Nvidia (NVDA) falling another 1.8% on Monday. The chipmaker is slated to reveal its latest quarterly earnings after the closing bell on Wednesday, and investors are becoming concerned that the constantly-growing demand for AI-driven compute power still remains woefully outsized compared to revenues and return on investment on the actual deployment side.
US government back open… for now
The US government successfully passed a short-term funding resolution to restart federal operations last week, and investors are immediately pivoting into a wait-and-see stance as backdated labor and inflation data come down the chute. The Trump administration has preemptively warned that October’s labor and inflation data may be “lost forever”, but traders are hoping that September’s Nonfarm Payrolls (NFP) jobs report, while stale, will provide enough ammunition to pave the way to a third straight interest rate cut on December 10.
Fed Chair Jerome Powell signaled at the Fed’s last interest rate decision that a lack of official government data will force the Fed to stand pat until it receives further information on the US economy, battering broad-market expectations for a third straight rate cut in December.
Dow Jones daily chart
AI stocks FAQs
First and foremost, artificial intelligence is an academic discipline that seeks to recreate the cognitive functions, logical understanding, perceptions and pattern recognition of humans in machines. Often abbreviated as AI, artificial intelligence has a number of sub-fields including artificial neural networks, machine learning or predictive analytics, symbolic reasoning, deep learning, natural language processing, speech recognition, image recognition and expert systems. The end goal of the entire field is the creation of artificial general intelligence or AGI. This means producing a machine that can solve arbitrary problems that it has not been trained to solve.
There are a number of different use cases for artificial intelligence. The most well-known of them are generative AI platforms that use training on large language models (LLMs) to answer text-based queries. These include ChatGPT and Google’s Bard platform. Midjourney is a program that generates original images based on user-created text. Other forms of AI utilize probabilistic techniques to determine a quality or perception of an entity, like Upstart’s lending platform, which uses an AI-enhanced credit rating system to determine credit worthiness of applicants by scouring the internet for data related to their career, wealth profile and relationships. Other types of AI use large databases from scientific studies to generate new ideas for possible pharmaceuticals to be tested in laboratories. YouTube, Spotify, Facebook and other content aggregators use AI applications to suggest personalized content to users by collecting and organizing data on their viewing habits.
Nvidia (NVDA) is a semiconductor company that builds both the AI-focused computer chips and some of the platforms that AI engineers use to build their applications. Many proponents view Nvidia as the pick-and-shovel play for the AI revolution since it builds the tools needed to carry out further applications of artificial intelligence. Palantir Technologies (PLTR) is a “big data” analytics company. It has large contracts with the US intelligence community, which uses its Gotham platform to sift through data and determine intelligence leads and inform on pattern recognition. Its Foundry product is used by major corporations to track employee and customer data for use in predictive analytics and discovering anomalies. Microsoft (MSFT) has a large stake in ChatGPT creator OpenAI, the latter of which has not gone public. Microsoft has integrated OpenAI’s technology with its Bing search engine.
Following the introduction of ChatGPT to the general public in late 2022, many stocks associated with AI began to rally. Nvidia for instance advanced well over 200% in the six months following the release. Immediately, pundits on Wall Street began to wonder whether the market was being consumed by another tech bubble. Famous investor Stanley Druckenmiller, who has held major investments in both Palantir and Nvidia, said that bubbles never last just six months. He said that if the excitement over AI did become a bubble, then the extreme valuations would last at least two and a half years or long like the DotCom bubble in the late 1990s. At the midpoint of 2023, the best guess is that the market is not in a bubble, at least for now. Yes, Nvidia traded at 27 times forward sales at that time, but analysts were predicting extremely high revenue growth for years to come. At the height of the DotCom bubble, the NASDAQ 100 traded for 60 times earnings, but in mid-2023 the index traded at 25 times earnings.