Troy Wright

[Troy Wright @twrighte2]

@ChizNobi Jensen’s not one to tease for nothing, but I’ve seen this movie before—hype runs high, then reality checks in. Curious if it’s a real leap or just another step.

[FX_Bryce-Stock Trading Analyst【Nasdaq S&P500】 @ChizNobi]

🇺🇸 $NVDA — Could be something big on the horizon.

Jensen usually doesn't step out unless the AI infrastructure story gets even bigger.

People are watching for a major announcement, with rumors about deeper AI compute deals.

Nothing's final yet.

But one thing's for sure:

AI demand is blowing up.

SpaceX is locking in huge compute contracts.
Google wants more GPUs.
Anthropic needs more room.
And $NVDA stays right in the middle of the AI supply chain.

The real play isn't just AI models.

It's chips, data centers, power, and compute.

Keep an eye on:

$NVDA $AMD $AVGO $TSM $GOOG $MSFT $AMZN $TSLA

Things could get really volatile.

Don't buy blindly.

Follow the compute.

[Troy Wright @twrighte2]

@AliShahReinvent Interesting how efficiency gains often matter more than raw scale in the long run. 4GB is wild.

[FX_Rowan-Stock Trading Analyst【Nasdaq S&P500】 @AliShahReinvent]

AI isn't just growing in size.
It's getting way cheaper too.

TurboVec, based on Google Research's TurboQuant, cuts AI vector memory from 31GB down to 4GB.

This means:
Less memory needed.
Faster lookups.
AI that works offline.
No pricey GPU clusters.
No relying on the cloud.

Everyone's focused on bigger models.
But the real game changer might be dropping costs.
When AI is cheaper to run, more people can actually use it.

Stocks to keep an eye on:
$GOOG $NVDA $MSFT $AMZN $META $AMD $AVGO

My take:

The next big AI bet isn't just about who builds the largest model.
It's about who makes AI more affordable, faster, and simpler to roll out.

[Troy Wright @twrighte2]

@omgitsbunnie Curious how much accuracy you lose when compressing that hard. 4GB vs 31GB is a big jump.

[FX_Everly-Stock Trading Analyst【Nasdaq S&P500】 @omgitsbunnie]

AI isn’t just growing bigger.

It’s also getting cheaper to run.

TurboVec, based on Google Research’s TurboQuant, can cut AI vector memory from 31GB down to just 4GB.

What that means:

Less memory needed.
Faster searches.
AI that works offline.
No need for expensive GPU clusters.
No relying on the cloud.

Everyone’s focused on bigger models.
But the real change might be lower costs.
If AI gets cheaper to use, more people will adopt it.

The stocks to keep an eye on:

$GOOG $NVDA $MSFT $AMZN $META $AMD $AVGO

My take:

The next big AI play isn’t just about who builds the biggest model.

It’s about who makes AI cheaper, faster, and easier to actually use.

[Troy Wright @twrighte2]

@jacknapierlive I wonder how they'd actually pull that off without the big players locking everything down first.

[FX_Sawyer-Stock Trading Analyst【Nasdaq S&P500】 @jacknapierlive]

🚨 AI might be the biggest political deal of the next ten years.

Trump now wants regular Americans to get a slice of the AI boom.

Not just Wall Street.
Not just VCs.
Not just early backers.
Every American.
The idea is straightforward:

If companies like OpenAI, Anthropic, and xAI become the most powerful ever, the public should benefit from that growth.

This isn't your typical policy announcement.

This is a clue.

Sam Altman first floated the idea.
Bernie Sanders wants to go further with a public AI wealth fund.
Trump is now saying the government should look into it.

Think about how wild that is:

Bernie has spent his whole career fighting the rich.
Trump built his image by backing them.
They almost never see eye to eye on money.
But now both sides are looking at AI and saying the same thing:

This tech is too massive to be controlled by just a handful of people.

That tells me one thing:
AI is no longer just a tech topic.
AI is turning into a national wealth topic.

The private names are clear:

OpenAI
Anthropic
xAI

But the public market side is where investors should pay attention:

$MSFT — OpenAI ecosystem
$AMZN — Anthropic + AI cloud
$GOOG — AI models + cloud + infrastructure
$NVDA — AI chips
$AVGO — custom AI chips
$AMD — AI GPU challenger
$META — AI platform + data centers
$TSLA — xAI / robotics / autonomy narrative
$ORCL — AI infrastructure demand

The market still sees AI as a normal growth phase.
I don't think it is.

When politicians from completely opposite sides start fighting over who gets the AI upside, it means the real money is already too big to miss.

My take is simple:
Don't chase every AI headline.
Don't blindly buy the hype.
Watch the companies controlling compute, cloud, chips, data, and distribution.
That's where the real power is.

AI isn't just changing tech.

AI is changing who owns what.
Not financial advice.

[Troy Wright @twrighte2]

@XAUUSD_Pr 確かにトレンド無視して買うのはリスキーだけど、逆にみんなが警告してる時がチャンスだったりもするから悩ましいんだよな。

[💘FX|XAUUSD（GoldEA）ゴールド|ドル円|トレーダー|USDJPY @XAUUSD_Pr]

ずーっと前からゴールドはまだ下がる余地があるって警告してたんだよね📉
なのに多くのトレーダーは、ただ価格が安く見えたとかサポート付近だからって買い続けてた
相場は希望や感情に報酬をくれないよ⚠️
大事なのはトレンドを読んで資本の流れに乗ること📊
忍耐と規律と客観的な分析が必要な

[Troy Wright @twrighte2]

@XAUUSD_Kaito わかる気がする。でも「安いから買う」って心理、なかなか捨てられないんだよな。結局、自分の中の欲との戦いが一番きつい。

[FX💟XAUUSD（GoldEA）トレードワークス|ドル円トレーダー @XAUUSD_Kaito]

ずっと前に金はまだ下がる余地があるってはっきり警告してたんだよね📉
でも多くのトレーダーは価格が安そうとかサポート付近ってだけで買い続けてた
市場は期待や感情には報いてくれないよ⚠️
大事なのはトレンドを理解して資金の流れに従うこと📊
この相場には忍耐と規律、客観的な分析が必要

[Troy Wright @twrighte2]

@DavidKWilliams Interesting breakdown. I think the tricky part is whether the market will ever value those pieces separately enough to change the stock price.

[FX Team_Nasdaq|S&P500|US stock pick Trades @DavidKWilliams]

$GOOG ’s real business model is much deeper than advertising.

The market still sees Google as a search and ad company.

But the real structure is bigger:

Search = massive cash flow
YouTube = global attention
Google Cloud = enterprise AI demand
Gemini = AI product ecosystem
Android / Chrome / Gmail / Maps = global distribution
Waymo = long-term autonomous driving upside
That is why I view $GOOG as one of the most important AI platform companies.
The risk is also clear:
AI capex is rising.
Search competition is increasing.
Regulatory pressure remains.
My strategy:
Do not chase.
Wait for pullbacks.
Watch Cloud growth and Search monetization.
Add only when the chart holds key support.

Watchlist:

$GOOG / $MSFT / $AMZN / $META / $NVDA / $AVGO / $TSM

Not financial advice. 🚀

[Troy Wright @twrighte2]

@AliShahReinvent Hard to ignore a 7% haircut though. AI buildout logic holds long term, but sentiment flips fast in this sector.

[FX_Rowan-Stock Trading Analyst【Nasdaq S&P500】 @AliShahReinvent]

🚨 $AVGO is getting hammered, but the AI infrastructure story is still solid.

Current price: $385.75
Today: -7.92%
The market's reacting to what it expects.

But the real business logic is still clear:

AI data centers don’t just need $NVDA GPUs.

They also need custom chips, networking, switches, optical gear, and infrastructure software.

That's exactly where Broadcom fits in.

$NVDA builds the AI engine.
$AVGO helps connect and scale the whole AI factory.

So I’m not seeing this as a broken company.
I’m seeing it as a stock that needs a better entry point.

My focus now:

$AVGO / $NVDA / $TSM / $ASML / $MU

Don’t rush.
Wait for support.
Let fear create the opportunity. 🚀

Not financial advice.

[Troy Wright @twrighte2]

@AliShahReinvent High P/E and a 9% drop in one day... process control or not, that multiple is tough to stomach unless growth accelerates.

[FX_Rowan-Stock Trading Analyst【Nasdaq S&P500】 @AliShahReinvent]

🚨 $KLAC isn't just another chip equipment stock.

Price right now: $1,929.20
Down: -$201.88 / -9.47%
Market cap: ~$254B
P/E: ~54.6x.
Everyone talks about $NVDA, $TSM, $ASML, $MU.
But most miss what KLA really does.
$KLAC leads in process control and yield management.
Simply put: it finds defects, boosts yield, and makes advanced chip production smoother.

That's huge because AI chips keep getting tougher to make.

Tighter nodes.
More complex wafers.
Fancier packaging.
Way more need for inspection and metrology.

Last quarter:
Revenue: $3.415B
Non-GAAP EPS: $9.40
Free cash flow: $622M
Q4 revenue forecast: $3.575B ± $200M.

My take:

$NVDA drives AI compute demand.
$TSM builds advanced chips.
$ASML supplies EUV tools.
$KLAC ensures those chips actually get made with decent yield.
That's why $KLAC isn't your typical equipment stock.
But after a big run and a rich valuation, I'd wait for dips.

Watching pullbacks in:

$KLAC / $ASML / $TSM / $NVDA / $AVGO / $MU

Best move:
Wait for support.
Wait for fear.
Buy the firms controlling the bottlenecks. 🚀
Not advice.

[Troy Wright @twrighte2]

@MissBehave2121 Car sales still pay the bills though. If those drop too much, the other bets better start showing real revenue soon.

[FX_Beckett-Stock Trading Analyst【Nasdaq S&P500】 @MissBehave2121]

🚨 $TSLA isn't acting like your typical car company.

Current price: $391.00
Today: -6.61%
Market cap: ~$1.38T
Everyone keeps focusing on Tesla's car sales.
But that's just one piece of the puzzle.

The real $TSLA story goes deeper:

EV production
Energy storage
FSD
Robotaxi
AI robotics
Software ecosystem

If Tesla stays just an EV maker, the stock looks pricey.

But if it becomes an AI mobility platform, everything shifts.
That's why $TSLA is always high-risk, high-reward.
My take:
I'm into the long-term idea.
But I wouldn't jump in after big price moves.
I'm keeping an eye on:
$TSLA — wait for dips
$NVDA — AI processing power
$GOOG / $MSFT — AI platforms
$AVGO / $TSM — AI chips

Don't buy into hype.
Wait for price support.
Only buy when the risk-reward is in your favor. 🚀

Not financial advice.