Co-Founder of @alpha_insider – building automated trading systems for crypto and stock markets | Coder, investor, and DeFi enthusiast
Miami
Joined December 2025
- Tweets156
- Following138
- Followers24
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Phil retweeted
The more left-leaning the policies, the higher the cost to taxpayers. Socialism is not the solution to affordability; it is, in fact, the polar opposite.
Phil retweeted
You're probably copy trading wrong and that's why you lose money.
What’s verified? How bad are the drawdowns? How much of your account is exposed?
This video walks through what to check—and how to start for free with no risk. 👇
Phil retweeted
Frontier labs are advancing the capabilities in AI for biology but preventing the good guys (scientists, academia, non-profits, health agencies,...) to use, study and understand it with widespread but shallow guardrails that the bad guys are bypassing easily (blocked me to proofread this tweet for example 😅).
This will automatically create massive assymetry and risks in the coming years, just like in cybersecurity, especially now that frontier labs are building wet labs (HF cybersecurity scenario for biology when?).
This is why we created Carbon-X, the best open-source DNA model by midtraining Qwen3-14B on 300B tokens of DNA, English and interleaved data. We also used a hybrid tokenizer that tokenizes English with BPE and DNA with a 6-mer tokenizer.
As a result, Carbon-X outperforms all open language models we evaluated on five benchmarks of DNA understanding and generation. This is a 27-point improvement over Qwen3-14B, showing how much a language model can gain from DNA training. It is also API frontier level at 1,800x less cost than GPT 6.1 Sol!
We hope Carbon-X helps researchers explore DNA in new ways. Releasing it openly means anyone can study its capabilities, limitations, and risks. Let's make the AI biology frontier open-source to make it safe and impactful for the whole world (not just a few companies).
Apache 2.0 Model on @huggingface: huggingface.co/HuggingFaceBi…
Phil retweeted
OpenCode is currently under a sustained cyberattack, and mid-incident they ran into the same problem Hugging Face did: the frontier models they were using for defense began refusing to help fight attacking agents because analyzing the attacks started triggering safety guardrails.
Phil retweeted
(1/6) From @GoogleDeepmind’s AlphaGo to AlphaZero, we saw machines find moves that reached beyond what we’d imagined for them. No one taught them those strategies. They emerged from reinforcement learning: playing, failing, and trying again under a single binary task reward for success or failure. Inspired by them, we couldn’t help but wonder: what might a robot discover if we gave it that same freedom to learn?
That question led us to AlphaNIST. Starting tabula rasa, with that same binary reward plus only a simple control cost, a single policy solves all 20 @NIST assembly tasks at a 98.2% success rate in simulation. More surprising still, AlphaNIST can complete 10 different tasks in a row, receiving that reward only once, after all 10 are done.
Just as AlphaGo’s strategies surprised its creators, AlphaNIST discovered dexterous strategies we couldn’t have come up with ourselves.
Paper: arxiv.org/abs/2610.13354
Website: alpha-nist.github.io
Phil retweeted
Technical moats are mostly over at this point. If you’re building something that is meant to be durable, the only moats now are:
• Proprietary data
• Network effects
• A physical component
Phil retweeted
How I built a crypto bot that trades while I sleep:
• Install one AI skill
• Answer a few questions
• Backtest it (v1 failed)
• One prompt to fix it
• Schedule it for 10pm nightly
• Paper trade before going live
No code. Full build in the video.
Phil retweeted
Jensen Huang: “Safety is paramount. In a lot of ways, it’s job one. However, safety is an engineering problem... If we’re not confident about the safety of the products — like all companies, like you and I, all the companies here — if you build a product or a service and you’re not confident in its functionality, capability, or safety, then don’t release it.
That’s a very obvious thing to do. You pace yourself until you are confident you’re releasing something that the market would appreciate. The market forces are already there. We don’t need any new laws. We don’t need new regulations.”
Phil retweeted
Dario has written that we need to “pace the frontier,” and Sam has agreed. People may be surprised by my response: go ahead.
You guys are the frontier. By any reasonable metric — market share, revenue growth, model capability — the two of you have a duopoly on frontier intelligence. You’ve also claimed the lead is widening because of recursive self-improvement.
I don’t see what you see in the lab. If the unreleased models are scary enough that you think you should slow down, I support your decision to be responsible.
But stop pretending you need anyone else’s permission. Stop pretending antitrust law has to be suspended so you can form a cartel. Stop pretending you need a regulatory approval process that supersedes product liability. Stop pretending METR is independent when it is intertwined with Anthropic’s investors and staff. Stop pretending you need those same evaluators to police competitors who aren’t even at the frontier.
Most of all, stop pretending the motivation to slow down is purely altruistic. You face massive product-liability exposure if your products enable a truly damaging cyberattack. The market already punishes models that behave in unpredictable or unauthorized ways. After the Hugging Face episode, it is simply good business for OpenAI and Anthropic to trade some raw power for reliability and predictability. Call it alignment if you want. It is also just giving customers what they want.
Pacing the frontier would also create breathing room for a more intelligent conversation about regulation than Bernie Sanders’ “shut it all down.” China is very unlikely to join a global agreement, as you know, and that has to be taken into account as well.
So go ahead and pace the frontier. You are the ones setting it. The easiest way not to build superintelligence is for you to agree not to build it. Demanding your preferred regulatory framework as the price of that will look like blackmail of the public and the political system. So just do it.
If you do, you’ll buy goodwill for the next conversation. If you don’t, we’ll know this was just another bid for regulatory capture — or an election-season psyop.
Phil retweeted
KYC needs to be completely abolished rather than reformed
Like many of my Twitter mutuals reading this, I'm a ZK technologist with business instinct and understand the excitement around "verifiable credentials and zero-knowledge proofs of limited identity data" as a clear improvement to the status quo...
...however, it's important not to let opportunity distract you from the real issue at hand: KYC is draconian and needs to be completely abolished rather than reformed.
Your obvious self-interest shows when you advocate for more-advanced gatekeeping technology rather than the policy changes that address the root cause
Phil retweeted
Lighter is becoming more open and easier to build on!
Developers can now use our shared trading core to create their own interfaces, apps, and trading experiences without starting from scratch, for free.
github.com/elliottech/lighte…
Phil retweeted
I spent the weekend using AI to explore renovation ideas for a property. Each concept generated was basically construction-ready, since I fed it land & soil surveys (and generated everything else off Zillow and satellite photos).
The future is going to have very few intermedaries between consumers and the last mile of labor.
And more broadly: consumers will be spending a lot more on custom projects to get precisely what they want, since the reasons they've been cost prohibitive (design and engineering) will no longer matter.
Essentially, a lot more things are going to be custom-fabricated—electronics, clothing, home fixtures. The next era of consumer tech is going to make everyone a hobbyist and builder.
Phil retweeted
Everyone should be able to access high-quality financial assets, wherever they live.
That's what tokenization unlocks: taking the best of US capital markets and making them available on a global scale.
The industry is still small compared with global finance, but the advantages are becoming harder to ignore. Traditional market infrastructure was built around fixed hours, closed networks and layers of intermediaries. It was never designed for 24/7 execution, programmable assets, composability or self-custody.
The needs of investors have moved faster than the rails underneath them. We're working to change that.
What gives me confidence is seeing how many different people are now pushing this industry forward. Founders are building new products, LPs are bringing liquidity, traders are finding new uses, and infrastructure teams are making the whole thing work.
It's a privilege to be in the trenches with all of you.
We are still early, and there is a huge amount left to build. It will also take time and effort for the old guard to get onboard. This is worth fighting for.
Phil retweeted
Most traders never open this tab on #TradingView
Those who do, say "It's all a scam"
What if I told you this tab was the core building block to your next fully automated trading strategy?
Let me show you:
Phil retweeted
1/ We published official AlphaInsider agent skills.
Install them in any skills-compatible coding agent and it can use the AlphaInsider API correctly — and turn a trading idea into a real paper strategy on the site.
github.com/AlphaInsider/skil…
🧵
Phil retweeted
A member of Congress's portfolio is up 230% this year — $MRNA doubled on cancer vaccine news while sitting in it.
So we built an AI that reads every congressional trading disclosure the moment it's filed and turns it into a portfolio anyone can copy. Free.
Phil retweeted
Goodbye, Poseidon!
An epic 8-year, 8-figure rabbit hole in post-quantum cryptography reaches its dream conclusion. The Ethereum Foundation is abandoning Poseidon for L1, pivoting to SHA or BLAKE. This milestone unlocks ultimate security for lean Ethereum and foreshadows a golden era of hash-based cryptography.
Since 2018, the Ethereum Foundation has invested in magic cryptographic bricks, so-called "SNARK-friendly hashes". In 2019, Poseidon was born. It held strong and became the dominant SNARK-friendly hash, securing billions via zkrollups and zkVMs.
In a stunning reversal, breakthrough SNARK designs show that SNARK-friendly hashes aren't necessary after all. Off-the-shelf traditional hash functions like SHA2 and BLAKE2s can now match Poseidon in a SNARK. In hindsight the key was not SNARK-friendly hashes, but hash-friendly SNARKs.
The secret is doing maths over the smallest prime number: 2. So-called "binary fields" natively speak the language of bits, aligning with the boolean operations inside traditional hashes. This is a stark departure from "prime fields", where awkward large-prime arithmetic makes bit manipulation painfully expensive.
We're talking sci-fi cryptography. 1M traditional hash calls proven per second, on a laptop. Just 100x overhead vs native CPU boolean compute. Nobody predicted such performance, not even the handful of binary-field visionaries. Hat tip to the research geniuses: Jim and Ben with Binius in 2023; Ron, Benedikt and William with Flock in June.
With SHA2, the lean aesthetic of minimal assumptions reaches its climax. The EF's principled stance on pure hash-based cryptography has aged like fine wine. We now enjoy foundations the world can trust for decades and centuries, foundations worthy of the dream of an internet of value.
Speed of deployment is a secondary win. There's no longer a need to wait years for Poseidon cryptanalysis to bake. Emile and Thomas from the EF post-quantum team are moving at breakneck speed with binary fields. The strawmap now points to a production-grade leanVM in 2027, with CL, DL, EL deployments in 2028.
As AI becomes exceptional at cryptanalysis, the contrarian bet to avoid riskier structures like lattices and isogenies is visibly paying off. The past weeks have been brutal. Lattice-based "HAWK" and isogeny-based "SQIsign", both signature schemes in NIST's Round 3, have suffered blows. Sources I trust say more blood is coming.
On AI, the open autoresearch trend kicked off by ECDSA[.]fail is spreading fast, with amazing outcomes from zk[.]golf and SNARK[.]fast. Days ago SNARK[.]fast crossed 1.8M BLAKE3/sec proven on an M3 Max. Stay tuned for fresh autoresearch challenges dropping tomorrow.
Also tomorrow: Ethproofs call #10, dedicated to binary fields. Possibly the most noteworthy Ethproofs call yet. Experts leading the charge will present the future of hash-based SNARKs at 2pm UTC. What an incredible time to be alive. To witness history, DM me for a calendar invite :)
Today I can confidently claim that hash-based cryptography has won out for blockchain post-quantum signatures. SNARK succinctness compresses arbitrarily many signatures into one small proof per block. SNARK flexibility yields k-of-n threshold signatures, complex multisigs, and more.
Ultimate security. Uncompromising performance. Full programmability.
Believe in something. Believe in hashes.