Tafv

Investor and technology enthusiast focused on AI, biotechnology, robotics, energy, and fintech innovation.

[Tafv @Tafvy_]

@Kaizen_Investor $PL, $RKLB, Looks like bottoming here at 200d ema

[Tafv @Tafvy_]

@MacroCRG $CGNX maybe $VPG which I sold too early and couldn't find myself to buy back in.

[Tafv @Tafvy_]

@kobesobased How are you maintaining the events? Scraping luma, eventbrights and other websites?

[Ren @ren_stocks]

Most people think the AI buildout is just a couple of stocks – Memory, CPU, GPU, NeoClouds, Photonics..

$SNDK, $MU, $ARM $INTC, $AMD, $NBIS, $LITE, $AAOI, $TSEM, $SIVE

The reality is there’s so much more to it.. I built a complete map of the AI buildout – at least the one I’ve been trading around for the last year.. I put that map on my Substack… 12 layers deep.

Since I’ve seen it circulating on here, I’ll just post it myself.

The hard part isn’t knowing the full stack – it’s making sense of it.

Why is photonics down today but memory isn’t? Why is CPO so relevant in the AI buildout?

Bullish AF on AI infrastructure.

Go check out the full article for free on my Substack, and if you’re going to share it – please do, but link back to my article.

Here is the link: https://t.co/AqKTdxnlmJ

Let’s go find the next 1000% stock ⚡️⚡️

[Tafv @Tafvy_]

@ether_fi @grok Who are the eligible merchants?

[Tafv @Tafvy_]

@jvb_xyz @grok verify if there are many versions of the Quran

[Opulent Vocation @OpulentVocation]

Give the bears their due: Peak concentration, euphoric flows, a flashing Bull & Bear sell signal, a wobbling President, a bear-flattening curve it reads like a checklist for a top.

The problem is that it’s a sentiment and positioning argument wearing a fundamentals costume. Strip away the literary framing, and the case rests on one buried assumption: that the AI complex is a bubble inflating on hope, the way TMT did in 1999. That assumption is wrong, and once it falls, three of the four pillars fall with it. Let’s go through them.

[Abdulkadir | Cybersecurity @cyber_razz]

“A man who has not hit his Claude limit by noon has wasted his morning.”

-Socrates

[Midjourney @midjourney]

A technical dive inside our new "Midjourney Scanner"

[Tariq | Goldsand @thesubmitter_]

Here’s an underrated prophecy from 1500 years ago:

In 1311, a Christian merely arguing that paying usury was okay was a heresy (acc to Council of Vienna).

In 2026, the US alone pays $1T of usury every year.

The Prophet ﷺ spoke the truth when he said "A time will surely come in which none will remain but that he consumes usury. If he does not consume it, he will be afflicted by its dust."

[Tafv @Tafvy_]

@jonaswillett1 Very nice what’s your tech stack? I’m working on something similar, a community map for people with dietary restrictions

[Tafv @Tafvy_]

@AviFelman What about Bio tech?

[Tafv @Tafvy_]

@IncomeSharks Robotics, Metals and energy

[Tafv @Tafvy_]

@aleabitoreddit Is that a typo in the GS report '8417' vs '8147', which seems to be the actual ticker?

[Alex Corrino @AlexCorrino]

"Memory is cyclical, everyone knows that, and the recent run up in memory names is an obvious bubble."

That's the easy, reflexive view. But I think the people who hold it are missing the simple scale of what AI is doing to memory demand.

The first clue that there might be more to the memory story came in January of this year when it came out that NVDA's next gen Rubin platform would require 16 TB of NAND per GPU, or 1152 TB per rack, and that required HBM bandwidth for the system would be 70% higher than what had been previously reported.

That was the first time it became obvious to outside observers that memory would need to scale exponentially to keep up with already-known GPU demand.

One under-appreciated fact is that while GPU compute has largely scaled with Moore's Law (doubling in compute ~every 2 years), memory density and speed hasn't. As GPU compute continues to scale, existing memory manufacturers must produce exponentially more chips.

These chips will also need to be faster than ever, which introduces an incredible technical challenge: how can memory manufacturers find the required speed improvements that have eluded them for decades?

When you combine this added technical complexity with an exponentially expanding demand for the product, memory starts to look less like the "commodity" everyone knows it to be, and much more like a high-margin proprietary chip.

This hasn't even touched on memory's role in inference (compute needed for inference is expanding exponentially as well, and is highly memory-dependent), long context, etc.

Agentic AI requires agents to pull massive amounts of data into their context, which increases the number of tokens per "turn" and also the amount of memory required to run them. True agentic systems will require both dramatically higher context, and also many more "turns" or iterations of each task (as they improve an output over and over until it reaches a target quality level). Longer context = more memory per workload, and more "turns" = more workload per output.

To put a specific number on that, Micron SVP Jeremy Werner said recently on The Circuit that agentic AI is causing context length to grow 30x a year.

Michael Dell recently framed the problem in extremely simple terms: H100 had 80GB of HBM; by 2028, accelerators could carry ~2TB. That is 25x more memory per accelerator. Over the same period, he expects roughly 25x more accelerators deployed.

That's 25 x 25 = 625x more accelerator memory demand by 2028.

Everyone knows memory stocks are cyclical, and they always look cheap right before the bubble bursts. But what if there are structural changes happening in the memory markets that could prove the consensus wrong?

Does anyone remember another traditionally cyclical company that has rerated to a growth story due to the demand from AI? Hint: It's now the most valuable company in the world.

Reminder: this is not a recommendation to buy or sell any securities. It's a framework for thinking about how the AI buildout may be changing the memory market.

[Tafv @Tafvy_]

@conzimp Greener pastures in equities (AI Cappex stuff)

[Tafv @Tafvy_]

@aleabitoreddit Also $LWLG. Got out of AXTI after a 3x and can't seem to bring myself to get back in...

[Tafv @Tafvy_]

Semis - short-term bearish / long-term bullish
Software - Shoter-term slightly bullish / long-term bullish
S&P - short-term bearish / long-term bearish

[Ozzy @ozzy_livin]

🥐 fresh crumbs

We're gonna play a little game called Bullish or Bearish

$SPX
→ short term at the money puts
→ medium term out of the money puts

Live from Canada 🇨🇦

@jam_croissant with @wealthsimple

Full interview
https://t.co/w8IIjcXTsp

[Arrakis Global @ArrakisGlobal]

Shifting from an investor... to a trader. A few thoughts.

LT Investing died for me in 2022. The nature and structure of markets, the geopolitical paradigm and how asset pricing works today meant I had to shift my approach.

[Tafv @Tafvy_]

My Watchlist. https://t.co/P4AyxuTbmE