AI Deployment Yet to Come...
AI Changing the World? Stock Invader Ahead of the Curve.
AI Bubble Popping?:
From Information to Deployment
Ever since the release of ChatGPT, AI has quietly infiltrated everything. Everyone agrees the ecosystem is ridiculous: partnerships everywhere, hype feeding hype, GPU shortages and pre-revenue promises ensuring the future…
And now OpenAI just announced that they would be starting Ad-rolls to manage the debt heading into 2026. That coupled with diminishing returns, faltering market share and researchers abandoning LLMs for World Models the bubble looks about ready to pop.
But I don’t think this marks the end just yet, another AI winter might have returned in research but not in deployment.
Artificial Intelligence is Artificial?
Today everyone is an expert stating AI is overhyped because of the Blackbox problem, arguing that we don’t actually know how these models work.
It’s an oversimplification in my opinion, if we didn’t have clue whatsoever then we wouldn’t be able to build them.
AI models like ChatGPT, Gemini or Claude operate on pattern recognition + probabilistic guessing which means same prompt → slightly different results each time.
You ask for a specific image? You’ll get similar but never identical ones.
That’s a problem. Additionally it can hallucinate meaning it can reach wrong conclusions confidently.
Accelerationists vs Skeptics
People are building entire careers talking about the current state of AI: some just report news, others market their own tools and the rest split between utopian singularity hype and outright dismissal of current models.
Accelerationists promise imminent AGI and post-scarcity utopias. David Shapiro famously declared AGI achieved as early as GPT-4.5.
Skeptics most prominently Gary Marcus, argue that LLMs are fundamentally incapable of real intelligence and therefore economically overstated.
Both extremes miss the point. But personally I have a much bigger problem with Gary Marcus. He keeps moving the goalposts regarding what quantifies as actual intelligence and if that fails he points to efficiency gains or economic ones.
LLMs aren’t conscious(true) but they excel at tasks humans struggle with. However Gary Marcus continues to double down on it not being real intelligence given it only predicts based on its training data.
Which is utterly wrong given Google’s Alphafold was trained on known protein folding, and is able to predict with dead accuracy un-solved protein structures.
Information enters Deployment
Luckily we are still in the information age and I believe these large language models to be the final stage before discovery. The primary use-case of these models remains as an aggregated search tool for information.
It’s effective enough that it will be used for more research. And I predict the next discovery frontier to be biological.
AI doesn’t have to solve the entire human genome to be recognized but rather just do more; more hypotheses, more patterns, more combinations than a researcher could ever do in a lifetime, and it can.
Over time this will leapfrog, slowly but surely into decades then centuries.
How so? When AI models can eventually screen millions of compounds overnight, simulate fruit-fly trails while we sleep, or propose viable drug candidates before a human lab manages to get funding…
Medicine won’t continue to advance incrementally but exponentially.
The Real Bottleneck?
Data.
I’m serious. At this point the bottleneck is data or the lack thereof.
The dead internet theory is proven to be true, more and more content online that people engage with is generated by an AI. Now the corporations don’t care anymore, they take what they can get raw or synthetic.
Within the sphere of biotech and pharma, data is the weapon of the future.
It took Novo Nordisk 30 years to perfect Semaglutide. The next breakthrough can’t afford 30 years and it won’t need to. AI will speed things up, LLMs will make a difference.
But they need data thus I am predicting tons of acquisition by Big Pharma in the coming decade. Tom Lee is calling for a crypto-supercycle? I’m calling for a biotech-supercycle.
My Move?
I don’t believe in artificial super intelligence anytime soon but augmented intelligence is already here waiting to be deployed. We are still too early to gauge definitive winners but it’s starting to boil and that’s usually when you find next-gen asymmetric winners…
Early contenders have emerged and already sparked the interest of the public eye, nothing astounding for the one versed in biotech, but not to be underestimated either:
Recursion Pharmaceuticals: Jensen Huangs secret ace, AI drug discovery.
Tempus AI: Precision medicine’s data engine. Bullish but valuation…
Schrödinger : Computational drug discovery pioneer.
Eli Lilly: Stable bet, no alpha though.
Each years off from a payday… Recursion and Tempus both look interesting.
I am betting my money on these:
INVIVYD : Antibody play which is becoming a platform play with real science stacked behind it. High likelihood of being acquired. (HIGH RISK)
SANA Biotechnology: My biggest biotech bet, the cure for type 1 diabetes looks promising if all goes well their HIP tech it could be a platform play applicable to almost ANY cell or organ transplant. (HIGH RISK)
BICO Group AB: A lab automation & life-science platform.
It combines lab automation, 3D bioprinting, robotics and AI to modernize biological research. Needs a turn-around, best infra play for the future if it works out… (HIGH RISK)Vertex Pharmaceuticals: I don’t own this, but they are quietly positioning for AI. In fact it’s the only Pharma on the verge on leveraging CRISPR(via Casgevy) to their advantage while having a total monopoly on ‘Cystic Fibrosis’. Ultimate defensive-growth pick. (LOW-RISK)
This future is inevitable, question is:
WILL YOU BE AHEAD OF THE CROWD WHEN IT COMES?
🛰 Signal LOST: End of transmission — INVADER out… ☕
Disclaimer: This post is for informational and entertainment purposes only. It reflects personal opinions and is not intended as financial advice. Always do your own research before making investment decisions.
Well written today! 😎