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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…
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Today we’ve raised $52M Seed and we are announcing the public launch of S2.1 Pro.
>It can clone a voice from 5 seconds of audio
>2x faster than Cartesia & 1/6th the cost of Eleven Labs
>most expressive model with word level control over emotion, intonation, pacing etc
We support frontier AI companies including HeyGen, LiveKit, Retell, Sanas, and OpenArt all run our model in production.
If you're a business and we can't cut your voice AI costs by 50%, we'll give you 1 year of Fish Audio for free.
Book a demo: s.fish.audio/tmapke
To celebrate our first birthday, we'll give you 1 month of S2.1 Pro for free. Like, retweet, and comment “Fish” to get it.
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Our modern crises are intertwined: a warming planet, a rising human footprint, and societies strained by inequality and political polarization. And yet, Marten Scheffer approaches these problems with a fundamentally hopeful outlook in his new book, Tipping out of Trouble: How Societies Transformed and How We Can Do So Again.
The book argues that societies, like other complex systems, can shift suddenly from one stable state to another, and asks how ours might move toward one where humans and other species can thrive in the centuries to come, writes SFI External Professor Tim Kohler in this book review.
santafe.edu/news-center/news…
What will it take to bring AI into the physical world?
@drewhenry joins @Emerj AI Research CEO Daniel Faggella to discuss the compute foundations needed for Physical AI, from energy-efficient, heterogeneous compute to the importance of digital twins for real-world deployment.
🎧 Listen: okt.to/vj8ue1
"We have almost a control tower view of the entire industry. We see everything. We talk to everyone."
On @TBPN, Arm CEO Rene Haas shared how our position at the center of the world's compute ecosystem gives us a unique perspective on the technology and trends shaping the next era of AI and computing.
Watch the full interview, starting at 01:05:36: okt.to/MnhWOY
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🆕 The most powerful chip Amazon has ever built is now available to all AWS customers. AWS Graviton5: up to 25% better performance, 192 cores, and efficiency that meets demands of agentic AI workloads.
Learn more: go.aws/4eAlShO
Join Arm and Sumo Digital live on the @UnrealEngine YouTube channel to explore how Neural Dawn became the first mobile game to use Unreal Engine MegaLights. 🛑🎥
Hear directly from the teams behind the project as they discuss Arm Neural Technology, dynamic lighting, ray-traced shadows, performance optimization and the future of mobile graphics. youtube.com/live/XG5W2Ei_J0Q
Join us tomorrow at 11AM ET as we're joined by experts from @SumoDigitalLtd and @Arm to talk about how game developers and hardware engineers worked together to bring desktop-class graphics to mobile
Don't miss this behind-the-scenes look at how Arm Neural Technology can help unlock more ambitious real-time visuals for mobile!: youtube.com/live/XG5W2Ei_J0Q
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youtu.be/ihksB57zwB8 #ad
Today @Arm is announcing Neural Dawn, a to-be downloadable and playable game from @SumoDigitalLtd, showcasing the capabilities coming to future Mali GPUs. The game uses Arm Neural Technology to unlock Unreal MegaLights, which enables deep immersive visuals normally only seen on desktop. I got the briefing in advance to understand why this means future game development on smartphones can be more like a console or PC workflow.
macOS 27 Golden Gate is coming—and it's designed exclusively for Arm-based Apple silicon.
Another strong signal that the future of computing is AI-native and built on Arm. 🚀
okt.to/Tu6VZ8
Introducing Neural Dawn. 📱
Developed by Arm and Sumo Digital, Neural Dawn is a new project to deliver a production quality game, showcasing the capabilities of Arm Neural Technology in next-generation Arm Mali GPUs coming to Arm CSS for mobile later this year.
The first mobile game to use @UnrealEngine MegaLights. okt.to/xIagWr
📣 82% of internet traffic is video.
That means the challenge isn’t just delivering every stream, it’s doing it without
❌Buffering
❌Dropped frames
❌Ballooning power demands
The Arm AGI CPU helps deliver more streams, more AI, and smoother video experiences at scale.
A look behind the scenes at #COMPUTEX2026.
The keynote may be over, but the conversations, collaboration, and momentum from the week continue.
From final rehearsals and partner meetings to moments on stage and around the event, here’s a glimpse of what it took to bring our COMPUTEX story to life.
Thanks to everyone who joined us in Taipei. 👇
A standout moment at #COMPUTEX2026.
Rene Haas welcomed NVIDIA CEO Jensen Huang to the stage to spotlight the Arm-based RTX Spark and the momentum shaping the future of Windows on Arm.
Built for the agentic AI era, this new generation of computing will redefine what’s possible—transforming how we create, build, work, and play. okt.to/0b4EJT
AI is changing what’s expected from a PC.
The next generation of devices won’t just run applications—they’ll help observe, reason, plan, and act across increasingly complex workflows.
At #COMPUTEX2026, the Arm-based NVIDIA RTX Spark marked an important step forward for Windows on Arm and the future of agentic computing.
Powerful AI. Advanced graphics. Exceptional efficiency.
That future requires powerful, efficient compute built for AI from the ground up, built on Arm: okt.to/e7834n
“Arm is nowhere without Taiwan.”
At #COMPUTEX2026, Arm CEO Rene Haas thanked Taiwan’s technology ecosystem for its role in Arm’s success—from powering more than 250 billion Arm-based chips to helping bring Arm’s flagship AGI CPU to life.
Thank you to the engineers, innovators, and our partners driving what’s next.
🎥🔴 We’re live now from #COMPUTEX2026.
Arm CEO Rene Haas takes the stage to share how the compute landscape is changing with the rise of agentic AI.
Watch here: okt.to/d7NoFh
Today’s the day.
In just a few hours, Rene Haas takes the stage at #COMPUTEX2026 to explore the shift to agentic AI — and how Arm is powering the next era of AI compute across cloud, AI PCs, and the intelligent edge.
Plus, we'll be joined by NVIDIA CEO, Jensen Huang to share more about how their Arm-based products are shaping the future of AI
Watch live: okt.to/QLnhis
The countdown is almost over.
Tomorrow at #COMPUTEX2026, Rene Haas takes the stage to discuss how we're powering the future of AI compute.
Plus, we'll be joined by NVIDIA CEO, Jensen Huang to share more about how their Arm-based products are shaping the future of AI.
📅 June 2 | Register to join the keynote: okt.to/R2ATxy
📹 Catch the livestream: okt.to/SZL2r0























