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🚨 $QBTS exposed!
🧵Compilation of rigorous HARD EVIDENCE exposing annealer's failures: scientific papers & benchmarks proving it's outclassed by classical systems & rival optimization tech; proving it's useless for real-world problems; debunking misleading claims & outright lies
DrocDolf retweeted
Let’s tear down the fantasy vs. reality for $MRNA
The Bull Math (The Trap):
• 120k US melanoma cases × $100k/tx = $12B TAM
• 20% net margin = $2.4B profit • 50/50 split with $MRK = $1.2B to Moderna
• 400M shares = +$3.00 EPS• “Easy multi-bagger ,right?!”
The Clinical & Commercial Reality:
Grossly exaggerated TAM:
Intismeran is ONLY for resected high-risk Stage IIB–IV melanoma. That’s ~22k US patients/year, NOT 120k. 80% of melanoma is early Stage 0/I cured with a scalpel in 15 minutes.
Real-world peak penetration: At 40% adoption of the eligible pool, that’s ~9k patients = $900M gross revenue, not $12B.
The net earnings haircut: At a generous 20% margin (bespoke mRNA sequencing & cold-chain logistics aren’t cheap):
• Total program profit: $180M
• $MRNA’s 50% cut: $90M
• Actual EPS contribution: +$0.23 (on ~400M shares)
You won't see meaningful commercial revenue until 2029 at the earliest. Even with late-stage data, regulatory filings, PDUFA reviews, reimbursement coding, and commercial ramp-up take years.
You are waiting until nearly the end of the decade, absorbing clinical & regulatory execution risk, all to net under a quarter per share in melanoma.
$MRNA with the single most hilarious possible outcome in this study. EFS HR 0.58. Down the the hundredth, EXACTLY what *NEO*-adjuvant treatment with pembro yielded against adjuvant pembro (the nerfed comparator $MRNA studied against) in SWOG S1801.
What does this mean in English? $MRNA’s drug is showing the exact same benefit versus adjuvant pembrolizumab as NEOadjuvant pembrolizumab did.
Even more simply? If you just give patients a few doses of the pembrolizumab BEFORE you cut their cancer out, you do what $MRNA does for you, except with just the free tumor that’s already inside your body. No need to pay for this $400K drug.
And this makes rational sense, right? The whole point of $MRNA’s vaccine is to produce stuff that looks like the tumor.
You know what looks A LOT like the tumor does? THE FREAKING TUMOR!!!!!!
Absolutely poetic that $MRNA produced the EXACT HR benefit as neoadjuvant pembro did. Truly, the most hilarious possible outcome.
Now can we move on from this bullshit? $MRK and $MRNA should feel free to study their vaccine against the REAL standard of care now - NEOadjuvant immunotherapy.
From my perspective, this has been total fugaze, and an amateurish pump and dump worthy of much lesser enterprises.
A new potential source of selling pressure for $GSIT's overhyped 6MB memory scam 🚨
Its $155M market cap is closing in on the $146.4M lower bound of the June Russell 2000
October 30 is Rank Day. If GSIT falls out of the Russell 2000, index-tracking funds could be forced to sell
Thanks to $QBTS, SQT can finally heal Italians properly 😂
Funny how, in their desperation, D-Wave no longer even bothers to hide the scam, playing the SQT card again.
Replying to @DrocDolf
Amazing find from @MtnYardSale:
Seems new $QBTS partners need quantum annealing and "wrapping" for tissue regeneration, pain therapy, & encryption to secure data from therapy sessions. They also do S-Wave 😂 for diamagnetotherapy.
Obviously D-Wave was missing in their catalog...
DrocDolf retweeted
Replying to @commonsenseplay @QuantumBullHQ
He has a youtube channel that pumps these stocks over and over - with CEO's of all these sh*tco's like $IONQ shilling their stock to Retail.
And he charges $7.49 a month for it!!!
DrocDolf retweeted
UPDATE: One of the worst public stock recommendation lists you'll find.
On November 6th, @QuantumBullHQ published this list of "long" ideas.
Performance since then:
$LAES: -70%
$RGTI: -70%
$OONEF: -60%
$BTQ: -70%
$ARQQ: -75%
$QUBT: -50%
$QBTS: -65%
$CCCX (now $INFQ): -50%
$IONQ: -50%
$QNCCF: -70%
This is why fundamentals matter. Hype can drive stocks higher for a while, but eventually valuations reconnect with reality.
Anyone who blindly followed this list could be sitting on devastating losses.
Be careful who you follow - I called him out and he blocked me!
2/2
It's never too late to start listening to reason instead of grifters and snake oil salesmen.
DARPA's Quantum Benchmarking Initiative can help you separate quantum hype from reality 👇
$IONQ $RGTI $INFQ $QBTS $QUBT $QNT $XNDU
$GSIT's next catalyst could hit any minute now: preparations for massive dilution. Hear it straight from a GSIT exec yourself 🔊👇
$GSIT will take every opportunity to massively dilute shareholders, killing any potential pump.
Listen 🔊 to GSI executive himself👇
Gemini-2 was a $175M fiasco that generated zero sales.
Lasserre revealed that Plato is going to be built on a cheap, uncompetitive process node.
This guy is one of the best short signals you can get. I guess that's why he's followed by 3K+ people.
#payback_time_bitch
True breakdown begins now🚨
In Oct '25 Cornell confirmed $GSIT's chip has a severe external memory bottleneck & lacks the memory (6MB) and compute power for AI
$GSIT should've dropped from around $5 to $2 immediately!
Looks like the market is finally correcting that mispricing
$GSIT
THE MARKET STILL HAS NOT FULLY PRICED IN WHAT CORNELL ACTUALLY SHOWED 🚨
👇👇
Downward $GSIT momentum remains strong 💪
A break below $4.60 level looks imminent as more people come to terms with the 6 MB reality.
Once $4.60 is lost, that's when the real breakdown begins 🚨
$GSIT
The elephant in the room 🐘
This is the single most important fact you need to know about this scam 👇
1/
Dozens of studies converge on one point: SRAM-based CIM is a bad idea due to its very low density & high energy leakage.
It's common knowledge by now
Examples👇
$GSIT insistence on building Plato around an already failed SRAM concept reveals the nature of the scam: selling BS
3/
Because $GSIT's 6MB is so tiny, the data has to live somewhere else, and still has to be moved to and from external memory.
GSIT solves nothing, and it shows.
Independent NeurIPS showed APU required 11.6x the energy consumption of an A100 to solve simple vector search tasks.













































