Is this the next dotcom bubble?

Companies have actual businesses with profits and customers in 2026.

In late 90s it was just websites and investors.

Market has been on a heater. Best to come up with and investment approach and stick with it.

Time in the market is the key.

No not really comparable


There are some current valuations that are absolutely insane in the current market, but they keep showing up and showing out. NVDA for example.

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Cisco hit $82 on March 1st 2000

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So wild.

Thread hijack.. but check out Whirlpool since its inception back in the mid 80s. 12% or so all time price return.

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Cisco hit $82 on March 1st 2000 and it didn't reach that level for another 26 years

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Cisco and Lucent had split more times than i ever saw a stock split back then. $82 post splits was probably $800 That was such easy money i felt guilty

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but check out Whirlpool since its inception back in the mid 80s. 12% or so all time price return.

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it's a dividend stock what do you expect? Got to look at total return. Current yield is 8.46%. Total return since inception is 162%. I dont think anyone is calling it a great long term investment we all have seen the decline in appliance quality since 80s but share price alone isnt a good measure.

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There are some current valuations that are absolutely insane in the current market, but they keep showing up and showing out. NVDA for example.

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and the funny thing is.... NVDA is undervalued.

Unless we enter a true recession with high unemployment to where people are downright fearful of how they’ll survive, I think that every 20% stock market dip will be met with a V shaped recovery.

There are many more market participants than there ever have been, and an entire generation has been trained to by fear.

This isn’t like ‘99, but a couple of things could happen.

1)Black swan event (ie Covid)
2)There’s a coding efficiency created by AI that reduces the need for energy and chips. This would hit the chipmakers but the Anthropics etc would flourish. People thought this was the case with Deep Seek, but it turns out they were lying (Chinese, go figure).

For now the computer shortage is actually tempering things a little . I suspect that will be the first thing to “pop” once they increase capacity and steady state is reached. That could be years away though.

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This isn’t like ‘99, but a couple of things could happen. 1)Black swan event (ie Covid) 2)There’s a coding efficiency created by AI that reduces the need for energy and chips. This would hit the chipmakers but the Anthropics etc would flourish. People thought this was the case with Deep Seek, but it turns out they were lying (Chinese, go figure). For now the computer shortage is actually tempering things a little . I suspect that will be the first thing to “pop” once they increase capacity and steady state is reached. That could be years away though.

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I’ve asked an LLM called “AI” to argue with you:



While this perspective attempts to look past the surface hype, it fundamentally misreads the physics of computing, the nature of macroeconomics, and the structural reality of the current technology cycle.Here is the counter-argument to each point.1. The "Black Swan" FallacyBlack swans are structurally unpredictable: Predicting a "black swan" to break a market trend is a logical contradiction. By definition, if you can anticipate it as a generic risk factor, the market has already hedged against it.Catastrophes often accelerate tech cycles: The premise assumes a black swan would crash the tech sector. However, COVID-19—the exact example cited—actually triggered the largest tech adoption and hardware buying spree in human history.2. The "Coding Efficiency" MythJevons’ Paradox rules computing: History proves that making a resource more efficient increases its total consumption, rather than reducing it. When compilers made coding more efficient than assembly language, chip demand skyrocketed because software became ubiquitous.Better software demands bigger hardware: If Anthropic or OpenAI creates a 10x more efficient training algorithm, they will not buy 90% fewer chips. They will train a 10x larger model using the same maximum budget and power grid allocation to crush their competitors.The DeepSeek misinterpretation: Dismissing the DeepSeek architecture as a "lie" ignores validated computer science. Their mixture-of-experts (MoE) approach and multi-head latent attention (MLA) structurally proved that algorithmic efficiency is real—yet it increased global panic to build bigger clusters, proving Jevons' Paradox in real-time.3. The "Computer Shortage" MisconceptionShortages induce panic-buying, not tempering: Supply constraints do not "temper" bubbles; they inflate them. Double-ordering and hoarding by hyperscalers (Meta, Microsoft, Google) artificially bloat the order books of chipmakers.Capacity increases cause the crash, not steady state: The argument claims a crash happens after a steady state is reached. Historically, capital expenditure cycles crash precisely when massive supply capacity finally goes online just as demand begins to plateau, leading to systemic oversupply.To advance this debate, let me know if you want to look at:Historical data on how Jevons' Paradox applied to the transition from mainframes to PCs.Capital expenditure charts showing current hyperscaler spending compared to 1999 telecom spending.The specific technical architecture of recent model releases that disprove the "efficiency kills hardware" theory.







Maybe AI is helping TD get more engagement and posts and therefore ads/revenue so maybe Chicken can intervene with his input. If he decides to privately sale he can list those gains until he can’t.

Key difference in the dot com bubble was profits chasing stock price while the AI era, stock prices are chasing profits.