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Forget NVDA. The New Backbone Of AI Is Here

Timothy SykesAvatar
Written by Timothy Sykes
Updated 10/28/2025 4 min read

In this article

  • GSIT-5.14%
    GSIT - NYSEGSI Technology Inc.
    $11.49-0.62 (-5.14%)
    Volume:  6.12M
    Float:  21.70M
    $11.01Day Low/High$12.20
  • NVDA+4.98%
    NVDA - NYSENVIDIA Corporation
    $203.91+9.54 (+4.98%)
    Volume:  297.99M
    Float:  23.29B
    $191.91Day Low/High$203.15

NVIDIA Corporation (NASDAQ: NVDA) was the undisputed king of the AI boom.

From early 2023 to October 2025, it surged over 1,300%*.

Early believers made a fortune. But here’s what most traders won’t tell you …

The market is shifting.

As AI matures, the industry’s needs are evolving. NVDA built the “brain” of the AI revolution, the GPUs.

But now, as AI scales into every sector, from healthcare, to robotics, to logistics, the demand is moving from brains to infrastructure.

That’s where the new opportunity lies for traders.

Wall Street is already sniffing it out … A “picks & shovels” play that’s quietly powering the next phase of the AI boom.

This stock is under-the-radar, it’s still cheap, and it has all the makings of the next NVDA.

Early bullish signals are already flashing this week, but the mainstream hype has yet to kick in.

If you missed the surge on NVDA, this could be your shot at redemption.

Because once the momentum hits, it’s game over for the latecomers …

There are a bunch of small-cap AI runners that I’ve traded in 2025.

And I plan to use the same trading process on the next biggest AI stock spike.

Small-Cap Spikes

tim sykes in sedona arizona with laptop of stock chart
© 2025 Millionaire Media, LLC

One of the most recent examples of AI strength in the small-cap market is GSI Technology Inc. (NASDAQ: GSIT).

The stock spiked 250%* on October 20 after the company announced findings from Cornell University that confirmed its APU technology has computation power that rivals GPU chips at a fraction of the energy cost.

And the stock followed my framework perfectly.

I traded the initial spike on October 20 and I traded it again during the number five bounce on October 27.

My notes are below:

More Breaking News

Source: Profit.ly
Source: Profit.ly

Here’s a chart of the GSIT spike thus far.

Every candle represents 10 minutes:

GSIT chart multi-day, 10-minute candles Source: StocksToTrade
GSIT chart multi-day, 10-minute candles Source: StocksToTrade

As you can see, I left a lot on the table.

There’s so much potential for small-account traders to make gains from these runners.

As it stands now, this stock’s technology has the potential to carry the price higher … But there’s a lot of upward resistance right now.

It likely needs another catalyst to carry it through those levels with strong volume. Like a new contract for its APU chips.

It’s still on my watchlist, but the catalyst for GSIT pales in comparison to the massive AI infrastructure catalyst that’s currently at work behind the scenes.

There’s a stock that has already gained traction in the real-world AI sector as an industry supplier, and its importance is growing. Early investors are loading up on shares.

Yes, GSIT spiked 250%*, but we’re tracking the next NVDA-sized move.

A stock that could erupt +1,000% as the AI market continues to grow.

And there’s already key support to help us build a position:

This is the biggest AI trade in the market right now!

Don’t miss your NVDA moment.

Cheers

 

 

*Past performance does not indicate future results


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Author card Timothy Sykes picture

Timothy Sykes

Tim Sykes is a penny stock trader and teacher who became a self-made millionaire by the age of 22 by trading $12,415 of bar mitzvah money. After becoming disenchanted with the hedge fund world, he established the Tim Sykes Trading Challenge to teach aspiring traders how to follow his trading strategies. He’s been featured in a variety of media outlets including CNN, Larry King, Steve Harvey, Forbes, Men’s Journal, and more. He’s also an active philanthropist and environmental activist, a co-founder of Karmagawa, and has donated millions of dollars to charity.
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In this article (YTD Performance)


* Results are not typical and will vary from person to person. Making money trading stocks takes time, dedication, and hard work. There are inherent risks involved with investing in the stock market, including the loss of your investment. Past performance in the market is not indicative of future results. Any investment is at your own risk. See Terms of Service here

The available research on day trading suggests that most active traders lose money. Fees and overtrading are major contributors to these losses.

A 2000 study called “Trading is Hazardous to Your Wealth: The Common Stock Investment Performance of Individual Investors” evaluated 66,465 U.S. households that held stocks from 1991 to 1996. The households that traded most averaged an 11.4% annual return during a period where the overall market gained 17.9%. These lower returns were attributed to overconfidence.

A 2014 paper (revised 2019) titled “Learning Fast or Slow?” analyzed the complete transaction history of the Taiwan Stock Exchange between 1992 and 2006. It looked at the ongoing performance of day traders in this sample, and found that 97% of day traders can expect to lose money from trading, and more than 90% of all day trading volume can be traced to investors who predictably lose money. Additionally, it tied the behavior of gamblers and drivers who get more speeding tickets to overtrading, and cited studies showing that legalized gambling has an inverse effect on trading volume.

A 2019 research study (revised 2020) called “Day Trading for a Living?” observed 19,646 Brazilian futures contract traders who started day trading from 2013 to 2015, and recorded two years of their trading activity. The study authors found that 97% of traders with more than 300 days actively trading lost money, and only 1.1% earned more than the Brazilian minimum wage ($16 USD per day). They hypothesized that the greater returns shown in previous studies did not differentiate between frequent day traders and those who traded rarely, and that more frequent trading activity decreases the chance of profitability.

These studies show the wide variance of the available data on day trading profitability. One thing that seems clear from the research is that most day traders lose money .

Millionaire Media 66 W Flagler St. Ste. 900 Miami, FL 33130 United States (888) 878-3621 This is for information purposes only as Millionaire Media LLC nor Timothy Sykes is registered as a securities broker-dealer or an investment adviser. No information herein is intended as securities brokerage, investment, tax, accounting or legal advice, as an offer or solicitation of an offer to sell or buy, or as an endorsement, recommendation or sponsorship of any company, security or fund. Millionaire Media LLC and Timothy Sykes cannot and does not assess, verify or guarantee the adequacy, accuracy or completeness of any information, the suitability or profitability of any particular investment, or the potential value of any investment or informational source. The reader bears responsibility for his/her own investment research and decisions, should seek the advice of a qualified securities professional before making any investment, and investigate and fully understand any and all risks before investing. Millionaire Media LLC and Timothy Sykes in no way warrants the solvency, financial condition, or investment advisability of any of the securities mentioned in communications or websites. In addition, Millionaire Media LLC and Timothy Sykes accepts no liability whatsoever for any direct or consequential loss arising from any use of this information. This information is not intended to be used as the sole basis of any investment decision, nor should it be construed as advice designed to meet the investment needs of any particular investor. Past performance is not necessarily indicative of future returns.

Citations for Disclaimer

Barber, Brad M. and Odean, Terrance, Trading is Hazardous to Your Wealth: The Common Stock Investment Performance of Individual Investors. Available at SSRN: “Day Trading for a Living?”

Barber, Brad M. and Lee, Yi-Tsung and Liu, Yu-Jane and Odean, Terrance and Zhang, Ke, Learning Fast or Slow? (May 28, 2019). Forthcoming: Review of Asset Pricing Studies, Available at SSRN: “https://ssrn.com/abstract=2535636”

Chague, Fernando and De-Losso, Rodrigo and Giovannetti, Bruno, Day Trading for a Living? (June 11, 2020). Available at SSRN: “https://ssrn.com/abstract=3423101”

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