Tests of all the power needed to run AI chatbots back our case for 3 data center plays
Every weekday, the CNBC Investing Club with Jim Cramer releases the Homestretch — an actionable afternoon update, just in time for the last hour of trading on Wall Street. Market moves: Stocks were trading higher again, and the S & P 500 was nearing its record close of 6,144 from Feb. 19. The Nasdaq 100 – an index made up of the 100 largest non-financial stocks listed on the Nasdaq stock market – has already hit record highs, powered by the recent surge in stocks tied to AI infrastructure and technology. Club stock Nvidia closed at a record high Wednesday and was on track to do it again. With only days left in June, Nvidia is our best month-to-date performer with a gain of more than 15%. Outside of tech, Club name Goldman Sachs ' over 14% monthly gain is a close second. AI power needs: Joanna Stern, technology reporter at The Wall Street Journal, wrote a fun article exploring the energy demands of AI prompts run on large language models like ChatGPT. Her process included visiting an Equinix -run data center in Virginia, which houses a "SuperPod" of Nvidia H100 graphics processing units (GPUs). The story mentions some rough estimates on the watt-hours used to execute a text, image, and video prompt on some models. The main takeaway from the story is that data centers are being built at an accelerated pace to keep up with demand, and those are going to require a lot of energy sources. The power needs aren't just from running the prompts – technology to keep the temperature of these GPUs cool is another major need. The story does a great job contextualizing why the data center power generation theme has been one of the strongest in the market over the past few years, and we're playing it in the portfolio through GE Vernova for its gas turbines and grid solutions, Eaton for its electrical power equipment, and Dover as a maker of thermal connectors used for liquid cooling. Private markets: BlackRock 's private market solutions are finding their way into retirement portfolios. On Thursday, the company announced it was selected by Great Gray Trust Company to provide an investment strategy across both public and private markets within target-date retirement funds. While the news isn't entirely surprising, it does offer further validation of CEO Larry Fink's long-term strategy. As we've noted before, BlackRock has made a major push into private markets through a series of multibillion-dollar acquisitions. With investors continually seeking ways to enhance returns, BlackRock believes that incorporating private market solutions into target-date funds could boost annual portfolio performance by 50 basis points over the lifecycle of the fund. That's a meaningful lift when projected over a 40-year horizon. For BlackRock, private markets also command significantly higher fees than traditional index funds — underscoring the economic appeal of this strategy. Shares of BlackRock have had a strong week to date, gaining more than 5%. The market's return to its highs may have something to do with it. Higher values in investment accounts translate into more fee income. Up next: Nike reports after Thursday's close, providing a look into the health of the consumer in both the U.S. and China. There are no major earnings reports on Friday morning. On the data side, before Friday's opening bell, we'll get the Fed's preferred inflation gauge in the personal consumption expenditures (PCE) price index. Later in the morning, it's the final read on June's University of Michigan consumer sentiment survey, looking at their feeling about the economy and inflation. (See here for a full list of the stocks in Jim Cramer's Charitable Trust.) As a subscriber to the CNBC Investing Club with Jim Cramer, you will receive a trade alert before Jim makes a trade. Jim waits 45 minutes after sending a trade alert before buying or selling a stock in his charitable trust's portfolio. If Jim has talked about a stock on CNBC TV, he waits 72 hours after issuing the trade alert before executing the trade. THE ABOVE INVESTING CLUB INFORMATION IS SUBJECT TO OUR TERMS AND CONDITIONS AND PRIVACY POLICY , TOGETHER WITH OUR DISCLAIMER . NO FIDUCIARY OBLIGATION OR DUTY EXISTS, OR IS CREATED, BY VIRTUE OF YOUR RECEIPT OF ANY INFORMATION PROVIDED IN CONNECTION WITH THE INVESTING CLUB. NO SPECIFIC OUTCOME OR PROFIT IS GUARANTEED.
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Stock market today: Dow, S&P 500, Nasdaq futures rise as investors bet on Fed rate cut
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Super Micro Computer, Inc. Announces Closing of Private Offering of $2.3 Billion of Convertible Senior Notes Due 2030
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Enterprises can't overlook security when embracing AI
Amara's Law, coined by the American scientist and futurist Roy Amara, says humans 'tend to overestimate the effect of a technology in the short run and underestimate the effect in the long run.' If the first half of 2025 is anything to go by, in the AI era, the 'runs' are getting shorter, and the effects of the technology will be larger than we've seen in a generation. In a matter of months, the conversation in companies has accelerated far beyond if AI is a useful productivity tool, to where and when it can be applied. Across industries and geographies, executives are acknowledging that AI is a general-purpose business solution, not just a technical one. Despite widespread workplace adoption, the focus on cybersecurity has not kept pace. In the rush to adopt AI systems, applications and agents, companies are failing to consider that rapid deployment of these new technologies could lead to data breaches and other security risks. 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At the same time, existing models can see their security score slip over time. Why? Because the attacks keep progressing and bad actors learn new tricks. More techniques and capabilities of breaking or bypassing AI model securities keep being invented. Simply, the attack techniques are getting better and they're causing AI models that have only recently launched to become less secure. That means that organizations that begin using an AI system or agent today, but don't stay up to date with the latest threat intel, will be more vulnerable as attack techniques increase in capability and frequency. As corporate AI systems gain autonomy and access to sensitive data, what is safe today may not be safe tomorrow. The research firm Gartner has forecast that 15% of day-to-day business decisions will be made autonomously by agents by 2028, though that percentage may increase by then. Against that backdrop, virtually all the security protocols and permissions in enterprises are built for human workers, not for AI agents that can roam through company networks and learn on the job. That mismatch opens up vulnerabilities, such as the possibility of agents accessing sensitive information and sharing it inappropriately. Poorly secured agents will be prime targets for hackers, particularly where they have access to valuable data or functions such as money transfers. The consequences include financial loss and reputational damage. Final thoughts Securing these new systems will be critical to AI adoption and to successful return on investment for the companies involved. A new security paradigm, using the capabilities of agentic AI to secure enterprise AI, is needed to allow innovation to thrive and agents to reach their potential. While the development of AI models and systems so far can reasonably be summarized as ' better, cheaper, less secure, the final part of that equation must improve significantly as the emerging application-first AI era accelerates. Once that happens, Roy Amara seems certain to be proven right once again.
