Raika Research retweeted
this might be my last normal tweet before biotech goes vertical
i'm not a whistleblower. I don't work at Lilly, Novo or any of the big labs
but there is a massive shift happening in human biology right now.
it's sitting in press releases and almost nobody reads them
the last 6 months alone:
- a once-daily pill roughly doubled median survival in metastatic pancreatic cancer (13.2 vs 6.6 months)
- a one-time gene editing infusion cut hereditary angioedema attacks 87%, and 62% of patients stayed attack-free and off all other prevention for 6 months
- a one-time gene edit for cholesterol dropped LDL up to 62%, and it held for over a year
- a personalized mrna vaccine beat keytruda alone in a 1,137 patient melanoma phase 3
- retatrutide hit ~28% weight loss in a phase 3
- an ai-designed drug entered phase 3
- a pill that regrows hair passed its second phase 3
- an immunotherapy that could let some rectal cancer patients skip surgery, chemo and radiation just got fda approved
- a man lived 271 days off dialysis on a pig kidney
- human cells were caught passing chromosome-sized chunks of DNA to their neighbors, and it changes how the neighbors behave
we are on the verge of an era where the human body is a software problem and the update cycle gets shorter everyday
stick around, it's going to get weird
bio/acc
Raika Research retweeted
I don't recommend anyone scramble to move their funds to new wallets today. But we should take the risks to cryptography from AI-accelerated math seriously, and minimize our exposure to not just quantum-vulnerable cryptography, but also potentially AI-vulnerable cryptography.
The core new area of risk from this viewpoint is, unfortunately, ML-DSA / FHE / lattices.
(and it's also another reason, along with quantum, why ECDSA might fall even faster than expected, hence the "fresh address" recommendation)
So far most people have been in the mode of thinking "elliptic curves broken, hashes safe, lattices safe". But there is a good chance that the concrete security of lattices will take serious hits from the next two years of AI math.
The basic threat model is: factoring is something that naively takes 2^(n/2) time, but over decades smart people have found and optimized number field sieves, and degraded that to 2^O(n^(1/3)), which is why RSA keys and signatures need to be ~400 bytes (and not 64 bytes). What if there are skeletons in the closet like that, both for elliptic curves and lattices, that we are simply not smart enough to discover - but bots soon will be?
This is a major part of the reason why for the past year ethereum's lean roadmap has been going in the "hash-only" direction: no lattices, no ML-DSA, no Falcon, no lattice-based commitments inside ZK proofs, etc. Signatures in lean ethereum are all hash-based, either WOTS or SPHINCS-.
For signatures and proofs, we already know how to go hash-only. The bigger challenge is for *public-key encryption* - and this goes far beyond blockchains. Secure communication, anonymizing protocols, lots of things need public-key encryption.
And unfortunately there are long-standing mathematical theorems showing why public-key encryption cannot be done with hashes alone. You have to have some kind of trapdoor object that has at least one form of usable "structure" - either group theory (incl. isogenies) or lattices or code-based or potentially in the future even more newfangled and spooky things (local mixing?). But for anything that has structure, you should assume that AI will make at least some progress in breaking that structure. Here, one reasonable inference is that if you want to make something plausibly long-term secure, multiply the key sizes by 10.
To me that's a very plausible world and something not at all extreme to predict. If AI will bring us 50 years of math in 2 years, then that 50 years of math may very plausibly include a "naive factoring -> GNFS" level of improvement to our ability to break lattices. In that world, lattices will still exist, but they will have to be significantly bigger to guarantee the same level of safety.
And at those new larger sizes, hash-based constructions will beat lattice-based constructions on concrete efficiency in every use case where hash-based constructions are possible at all.
Theoretically, of course it's possible that hashes are broken too (eg. P = NP would imply that). But I think P = NP is very unlikely. And intuitively, it's much more likely that a mathematical object has exactly no exploitable structure (like hashes are intended to), than that a mathematical object has exactly ~3 forms of exploitable structure (for elliptic curves: associativity, Schoof, pairings) and not some secret fourth form of structure we have not yet discovered that greatly degrades its security (for elliptic curves, ECDLP and pairing security). Similar for LWE, SVP, RLWE and the zoo of lattice problems.
For this reason, we do not yet see any reason to worry and start padding the byte size of hashes (if we start to worry more, we would pad the round count first before doing anything to the byte size).
Concrete TLDR, my own personal views:
* Hash-based > lattice-based, in those situations where hash-based is possible at all
* For anything lattice-based, be much more paranoid on param sizes. Remember that blockchains are only a small portion of the cryptography story; this point goes far beyond blockchains and applies to eg. access to websites, secure messaging, Tor / VPNs ...
* For privacy protocols, strongly favor NOT putting encrypted notes onchain. Instead, send them offchain through some third-party mechanism.
* If it's not difficult for you, keeping your funds in addresses which have not yet been used to make a transaction is a good idea. If it's easy for you, do it. **But be careful about migrations; I personally have lost more money in botched migrations than I have lost in all hacks combined**.
* For multisig wallets, doing confirmations offchain is better than onchain, because this way the signatures of signer wallets do not get exposed to the public, so if ECDSA falls to AI much faster than expected, at least the multisig "gracefully degrades" to a 1-of-1 where the 1 is whoever was gathering the signatures - a much better place to be than "anyone can take the money"
firefly.social/post/x/210783…
Raika Research retweeted
Second, Bitcoin priced in gold (below) is showing a lot of strength as well as flows return to the BTC ecosystem. Bitcoin is only 30% correlated to the S&P 500 and uncorrelated to Treasuries. That makes it a good diversifier now that a new 4-year cycle is potentially underway. 🧵(2/2)
Raika Research retweeted
Bitcoin’s power law math continues to suggest that a new cyclical bull market is underway after holding $60k, targeting $300k in 2029.
Raika Research retweeted
A lot of important progress on Frames (EIP-8141) has been quietly happening over the last few months. Highly recommend reading this, also the updated EIP eips.ethereum.org/EIPS/eip-8…
firefly.social/post/x/209626…
Raika Research retweeted
If I had to build one basket of safe bets to get full exposure of Robinhood eco:
- $HOOD: direct Robinhood exposure
- $ARB: the stack behind the chain + revenue share
- $UNI: main spot liquidity
- $MORPHO: lending and Robinhood Earn
- $LIT: perps inside Robinhood Wallet
- $PONS: chain native launchpad
- $NET: native DeFi/RWA play
- $CASHCAT: main meme beta
most of my size would stay in all these coins.. and then yeah i’d rotate small bets into day to day new coins on Fomo or pumpfun
The filter i’m using before aping any meme on Robinhood now..
- at least $1M market cap
- $100K + real liquidity
- paired with a tokenized stock or ETF that actually fits the meme
- LP locked with no deployer control
- top holders aren’t bundled or linked
- volume coming from new buyers, not the same wallets farming themselves
- enough activity to make LPing or yield farming worth it
- survived its first big sell-off and still held a decent base
what else should i look for before buying anything?
Raika Research retweeted
📂 Projects To Watch Through 2027
┃
┣ 📂 Wall Street Onchain
┃ ┣ 📁 @OndoFinance
┃ ┣ 📁 @Securitize
┃ ┣ 📁 @xStocksFi
┃ ┗ 📁 @RobinhoodCrypto
┃
┣ 📂 Beyond Crypto Perps
┃ ┣ 📁 @HyperliquidX
┃ ┣ 📁 @Lighter_xyz
┃ ┣ 📁 @variational_io
┃ ┗ 📁 @extendedapp
┃
┣ 📂 Financial Chains
┃ ┣ 📁 @Mantle_Official
┃ ┣ 📁 @solana
┃ ┣ 📁 @base
┃ ┗ 📁 @CantonNetwork
┃
┣ 📂 Prediction Markets
┃ ┣ 📁 @Polymarket
┃ ┣ 📁 @Kalshi
┃ ┣ 📁 @trylimitless
┃ ┗ 📁 @opinionlabsxyz
┃
┣ 📂 Onchain Credit
┃ ┣ 📁 @Morpho
┃ ┣ 📁 @maplefinance
┃ ┣ 📁 @eulerfinance
┃ ┗ 📁 @centrifuge
┃
┣ 📂 Crypto Bank Accounts
┃ ┣ 📁 @ether_fi
┃ ┣ 📁 @gnosispay
┃ ┣ 📁 @RedotPay
┃ ┗ 📁 @KASTxyz
┃
┣ 📂 Yield Infrastructure
┃ ┣ 📁 @pendle_fi
┃ ┣ 📁 @ethena
┃ ┣ 📁 @ResolvLabs
┃ ┗ 📁 @sparkfinance
┃
┗ 📂 Financial Data
┣ 📁 @chainlink
┣ 📁 @PythNetwork
┣ 📁 @redstone_defi
┗ 📁 @chaoslabs
Raika Research retweeted
Las empresas más inteligentes del mundo están saliendo a bolsa todas al mismo tiempo.
SpaceX. OpenAI. Anthropic. Databricks. Valuación combinada: cerca de $3 trillones.
No salen porque necesitan la plata. Salen porque ven algo que el resto del mercado todavía no quiere ver.
La última vez que este patrón se repitió fue en 2000 y en 2021. El NASDAQ cayó 78%. El 95% de los que compraron esos IPOs perdieron prácticamente todo.
Pero esto no es sobre si el S&P se cae mañana. Es sobre algo más grande: el ciclo ya giró, y la mayoría está mirando hacia el lado equivocado.
La Fed está expandiendo liquidez nuevamente.
($40B/mes). Ya está pasando.
Las reservas bancarias tocaron mínimos de 4 años. La ventana de emergencia de la Fed tuvo uso récord. Los bancos estaban tan cortos de efectivo que tuvieron que pedir prestado a tasas de emergencia.
La Fed se asustó. Prendió las impresoras.
¿Qué pasa cuando imprime? Los activos suben, las valuaciones se vuelven absurdas, y el capital inteligente ve la ventana perfecta para salir.
Eso es exactamente lo que está pasando.
El problema de fondo: el S&P 500 ya no representa la economía real.
Si comparás el US Stock Fundamental Index contra el S&P 500, el precio sigue marcando máximos pero el fundamental lleva meses en terreno cero o negativo.
Eso mismo pasó antes de 2000, de 2008 y de 2020.
Y medido contra mercados emergentes, el S&P está en niveles de sobrevaluación que superan la burbuja del año 2000.
Cuando ese retardo con el dólar index se cierre, el ajuste puede ser de hasta 60%.
Los IPOs gigantes no son la causa. Son el síntoma.
SpaceX preparando un IPO de trillón de dólares. 60x sus ingresos. OpenAI queriendo la misma valuación. Anthropic a $350 mil millones. Todas corriendo a la salida al mismo tiempo.
Si son tan buena inversión a largo plazo, ¿por qué los primeros inversores están tan apurados por venderte a vos?
Este patrón ya se repitió dos veces en 25 años.
1999: 457 IPOs en un año. El 86% perdía plata. El NASDAQ se cayó 78%. Pet Supplies, Accessories, and Pet Food - Pet Stores | PetSmart , Webvan, eToys desaparecieron.
2021: La Fed imprimió $4 trillones. Rivian levantó $12 mil millones sin ingresos reales y valía más que Ford y GM juntas.
Para 2023, solo el 5% de las empresas que listaron cotizaban por encima de su precio de IPO.
El frenesí no estaba casualmente cerca del techo. El frenesí era el techo.
Acá está la parte que cambia todo: la plata no desaparece, rota.
Cuando el capital se cansa de lo sobrevaluado, busca lo opuesto: lo barato, lo real, lo tangible.
Los commodities contra el S&P 500 están en el punto de entrada más barato de la historia.
Si el ratio vuelve a su media, es una suba de 100%. Si entramos en una crisis inflacionaria grande, 8 o 9 veces a favor de los commodities.
La plata fue el activo que más subió el año pasado y todavía tiene aire. El S&P medido en oro ya está perdiendo poder adquisitivo aunque nominalmente suba.
Y la joya del ciclo: Latinoamérica.
Los mercados emergentes tienen un ciclo de manufactura que se está volviendo positivo de nuevo. Históricamente, cuando esto pasa, vienen movimientos muy fuertes hacia arriba.
Soja con divergencias ocultas alcistas entre 2019 y 2024. Dólar australiano en piso. Metales rompiendo momentum.
El capital que salga del S&P sobrevaluado tiene que ir a algún lado. Los indicadores apuntan al mismo lugar: activos reales y emergentes.
La línea de tiempo.
Etapa 1 ya pasó: economía débil, Fed bajando tasas, impresoras prendidas.
Etapa 2 es ahora: dinero nuevo entrando, valuaciones insanas, todos sintiéndose genios.
Etapa 3 viene: los IPOs grandes lanzan, el retail compra, la música para.
Hay un lockup de 6 meses post-IPO. Si SpaceX y OpenAI salen en 2026, la ola de venta de insiders pega a fin de año, justo en midterms, cuando la incertidumbre política pica.
El año 2 de un mandato presidencial es históricamente débil. Patrón certero en más del 90% de los casos desde 1933.
Hay 5,000 acciones ya listadas con track record. Un IPO nuevo no tiene nada: sin historial, sin prueba, solo promesas y un pitch deck.
El mercado probablemente vaya más arriba antes de ir más abajo. La impresión de dinero hace eso.
Pero las personas más inteligentes del mundo están preparadas para venderte sus compañías a las valuaciones más altas de la historia.
Se están posicionando.
La pregunta útil no es "¿cuándo cae el S&P?".
Es ¿a dónde va el capital cuando el ciclo cambia?
La respuesta ya está en los gráficos.
Línea alta = Los commodities están caros comparados con las acciones.
Línea baja = Los commodities están baratos comparados con las acciones.
Ahora mismo la línea está tocando el piso (el punto más bajo en décadas). Todavía estas a tiempo.
Raika Research retweeted
🧵 THREAD: We just proved Bitcoin's 4-year halving cycle is a fundamental eigenmode of the system
Using eigenvalue decomposition (SSA + DMD), we discovered something remarkable about Bitcoin's price dynamics. Let me explain what we did and why it matters...
1/ What are eigenvectors?
Think of Bitcoin price as a complex signal - like a symphony with multiple instruments playing at once. Eigenvectors are the "fundamental notes" that compose this symphony.
Each eigenvector captures a distinct pattern in the data, ranked by importance.
2/ How we found them: Singular Spectrum Analysis (SSA)
We worked in LOG SPACE (critical!) because Bitcoin spans 6 orders of magnitude ($0.05 → $125k).
We created a "trajectory matrix" from the price history and decomposed it using SVD (Singular Value Decomposition).
Think of it as separating the signal into layers.
3/ What we discovered:
Eigenvector 1:
98.70% of variance→ This IS the power law: Price ∝ t^5.7 → The fundamental attractor of the system → Bitcoin's "base note"
Eigenvectors 2-6: 1.29% of variance→ Oscillations around the trend → This is where the magic happens...
4/ Then we applied Dynamic Mode Decomposition (DMD)
DMD extracts the "Koopman eigenvalues" - these tell us the frequencies and growth rates of oscillations.
We found:
Short cycles: 15-30 days (market microstructure)
MODES 5-6:
Period = 1,530 days = 4.19 YEARS
The halving cycle!
5/ Why this matters:
The 4-year cycle isn't just a coincidence or narrative - it's a fundamental eigenmode of Bitcoin's dynamics.
Eigenvalue |λ| = 0.9985 (slightly decaying, stable oscillation).
It exists as a persistent oscillation in log-space around the power law attractor.
6/ The physics:
This is exactly what renormalization group theory predicts for complex systems:
A power law fixed point (dominant eigenvalue)
Log-periodic oscillations (subdominant eigenvalues)
Stable, bounded dynamics (all |λ| ≈ 1)
Bitcoin behaves like a critical system near a phase transition.
7/ Why log space was critical:
In LINEAR space: 4-year cycle INVISIBLE (buried in noise) In LOG space: 4-year cycle CLEAR (eigenmode 5-6)
Why? Halvings affect price MULTIPLICATIVELY (% changes), not additively.
Log space reveals the true geometry of the dynamics.
8/ Reconstruction:
Blue line = Eigenvector 1 + Eigenvectors 2-6 Red line = Power law fit
R² = 0.9678 (better than raw data!)
We reconstructed Bitcoin's full price dynamics from just 6 eigenvectors. The math works. The physics checks out.
9/ Bottom line:
The Bitcoin power law isn't just a trend line. The 4-year cycle isn't just protocol mechanics.
They're fundamental eigenmodes of a complex dynamical system - proven through eigenvalue decomposition.
This is physics, not hopium.
TL;DR:
Decomposed BTC price into eigenvectors (SSA)
Found power law = dominant eigenmode (98.7%)
Found 4-year halving = oscillatory eigenmode (DMD)
Reconstructed full dynamics from 6 components
Log space was key
Math + physics confirm: Bitcoin is a critical system
Raika Research retweeted
Second retest of this 5Y Hyperphone, both retests qualify as a small megaphone themselves.
Target: ±$340k
Raika Research retweeted
MUST-READ
Since 2009:
+ After every halving, $BTC has broken above the channel midline before retesting the 210k-block SMA / lower trend line.
+ Every midline break has ended in a blow-off top at the upper trend line (orange)
This cycle:
+ 3 midline rejections → bounce at the 0.382 line → price now sitting on 0.382 again.
The next logical move is the upper trend line around $350K–$400K. 🚀🟧
Then bear market and retest of the 210k-block SMA / lower trend line.
Raika Research retweeted
Q2-Q3 of 2026 has the potential to be very bullish.
In this video I discuss how the items listed below could pump the $SPX & Bitcoin...in mid to late 2026:
1) Fed Fund rate cuts ending
2) ISM (Business Cycle)
3) $7.5T in Money Market Funds
4) $2,000 Trump tariff checks
5) QT/QE
6) 50w MA
Bitcoin Prediction:
Mid to late 2026 has the potential to be extremely bullish for Bitcoin (and most asset classes).
IMO, both of these could occur around June/July 2026.
1) Market Market Fund liquid rotation:
The current projected last rate cut is scheduled for July 29th. History shows us that once rate cut cycles are complete, liquid rotates out of money markets and into assets.
2) Trumps $2,000 Tariff Dividend:
Trump has hinted at a $2,000/check for qualifying households, very similar to covid stimulus checks. The timing is still unsure, however, the projections show it would be sometime in June/July of 2026. The Supreme Court still has to vote on the legality of the tariffs. If approved, then Congress will need to vote on the $2,000 dividends.
This could lead to a shorter and shallower bear market in 2026, as I've shown in other posts. Along with a new ATH before the next halving, like we saw in 2024.
Raika Research retweeted
Most people have no idea how deep Consensys’ roots go.
Everyone knows MetaMask, but Infura is the quiet backbone of Web3. It’s basically AWS for crypto, powering connections for uniswap, aave, Opensea and half the space without anyone realizing it.
Now that same team runs Linea, and it’s why institutions like SWIFT are comfortable testing there. It’s not some random L2.
It’s being built by the same people who’ve kept Ethereum’s infrastructure running for years.
$LINEA
Raika Research retweeted
Base is beginning to explore a network token
We’re in the early phases of exploration, and don’t have any specifics to share around timing, design, or governance. We’re committed to bringing the community along with us, and building in the open.
Raika Research retweeted
base is exploring a network token
it’s still day one, and the best part of being early is that the story is ours to write
$ETH treasury companies are stimulating the next #DeFi and #RWA wave.
Looking at small-medium caps that could benefit from this upside. Get exposure while no one pay attention.
@KasuFinance TGE not announced yet, but weeks from that.
Kasu is thrilled to announce a $1M strategic investment from leading Trade Finance chain @XDC_Network_.
Native XDC integration → seamless stables, real yield, liquid wrapper, + top-tier institutional deal flow.
Onwards & Upwards!
Read more: bit.ly/420BlBe





























