r&d ~ open, verifiable, crypto-physically secure hardware (TEEs) ~ https://xitter.cf/t.co/2mO1ykHbyf

Planet Earth
Joined February 2009
In the works ... for the anti-TEE maxis out there; a cry to the cypherpunk culture to enter into the hardware world and take the power back. Research Directions for Verifiable Crypto-Physically Secure TEEs arxiv.org/abs/2410.03183
13
17
8
93
12,287
Sylvain Bellemare 💫✨🧮 retweeted
I’m reminded of this quote by Satoshi: “I'm sure that in 20 years there will either be very large transaction volume or no volume.” Compared to 2013 when I started, the crypto ecosystem and industry is so rich, large, diverse, and simply remarkable. Never in my wildest dreams did I think crypto would grow to be so large and impactful. So even if you think it is boring on this exact day, the speed of growth is simply astounding.
4
2
1
18
1,583
Sylvain Bellemare 💫✨🧮 retweeted
AI-GREEMENT cool, but ultimately inevitable, work from the EPFL folks: arxiv.org/pdf/2610.30114v1 Consensus and replication are rich search spaces with near-trivial safety properties, and so it makes total sense that LLMs combined with formal tools will search the space well.
4
5
45
4,692
Sylvain Bellemare 💫✨🧮 retweeted
I see how some people can watch flashy robot demos on the timeline and think with a shiver that the robot apocalypse is around the corner, but reality check: There is no robot in the world that can change the batteries in a jack-o-lantern. If you have a robot friendly door handle it might be able to walk outside, pick it up, and carry it back inside. The robot could open the drawer with your batteries in it, but then things get tough. Opening the package of AA batteries? Extracting a precision screwdriver from its case? Unscrewing four tiny screws that require a hard press and twist? Popping batteries out of the case? Yes, you could build and train a specialist robot to do that today, but there is a very long way to go to replace the full range of human capabilities. Near term doomer scenarios should stop at “secretly controlling humanity” instead of “wiping humanity out” 😀
723
413
105
7,575
1,227,730
Sylvain Bellemare 💫✨🧮 retweeted
So this is a silly story, but for a year or two before in 2013/2014 I went around telling everyone I could find about this little cryptography library called “OpenSSL” and how it was used everywhere, but had almost no developers or security budget.
10
24
5
358
24,689
Sylvain Bellemare 💫✨🧮 retweeted
Countless people have been asking where to find a decision model running with private inference. Here you are. Kev 4B, a fast and cheap open weights decision model close to Jev. Powered by dstack and served @PhalaNetwork and @redpill_gpt
2
4
1
23
1,639
Sylvain Bellemare 💫✨🧮 retweeted
Seen some mentions that anti tampering would have prevented Ledger supply chain attack - it's actually difficult to get right, and harder to test. Definitely need more eyes - I'd consider the attached screenshot the common state of things. + some history media.ccc.de/v/gpn24-533-tam…
3
5
2
33
10,515
Sylvain Bellemare 💫✨🧮 retweeted
I've been using Ledger devices for many years, and the recent discoveries of hardware implants haven't changed my trust in them. If anything, they've reinforced something I strongly believe in: you should be able to inspect the hardware you entrust with your Bitcoin. Bitcoin was built around a simple principle: don't trust, verify. That principle shouldn't stop at software or cryptography. It should extend to the physical devices holding our keys. Sealed or tamper-evident designs are perfectly fine, as long as they're transparent and don't prevent independent inspection. Ledger devices are relatively easy to open and examine. That's one of the reasons these malicious implants could be discovered and investigated. No hardware wallet is immune to supply-chain attacks. But security shouldn't depend entirely on trusting the manufacturer or distributor. Physical inspection isn't a guarantee of security, but it's an essential part of being able to verify what you're actually using. Trust comes from the ability to verify, not from being told something is secure.
85
99
22
811
72,937
Sylvain Bellemare 💫✨🧮 retweeted
Dusting off this tweet from April because this gap in shared understanding of LLM capability is *widening*. It's now less "two groups of people speaking past each other" and more a sharp funnel. - Napkin math somewhere around 6B people (~75% of the population) have barely come in contact with LLMs at all. - Around 1-2B (~20%) are casual and infrequent users of free-tier ChatGPT-like products. This group sees derpy chatbots and treats them a bit like a better Google search, a writing aid, or etc. Maybe an agent tries to book you a flight. I have non-tech friends who (reasonably, imo) say they have not much use for it at all. Even many professionals outside of math&code are in this tier. For example, execs and many other functions spend a lot of their time talking to other people, so while they understand what is happening intellectually, it is still second-hand and a bit abstract. - Now we get to professional use of frontier-grade LLMs in math&code. Somewhere around 20M people (0.2%) see first-hand that large, complex projects that used to take them weeks/months can now be completed by agents with a prompt. Building apps, copying apps, translating apps, decompiling apps from binaries... This has all happened very quickly and recently - less than 1 year ago, I was writing code manually by hand, typing memorized computer code commands into a code editor character by character, occasionally pressing Tab to autocomplete a little chunk of code. - And finally we get to the ~5,000 people (~0.00006%) with access to frontier-grade systems internally. The external world has seen the preview. It looks like swarms of thousands of agents collaborating over weeks on software mega projects: minting zero days, running cyber attacks and defenses at machine speeds, discovering new science, advancing the frontier of mathematics. Things that would have taken top professionals in the industry years of work. Meanwhile, human review and comprehension are starting to fall behind. For example, people are still involved in the "archeology" of the OpenAI-HF incident from many months ago. Mathematicians may be poring over the 722 manuscripts on frontier mathematics for a while. The funnel is driven by a combination of factors: 1. The impact scales with ambition, problem size, and horizon. A question with a paragraph answer barely stresses the system. You need a reservoir of big, difficult problems that you really care about. This aspect drives the consumer / professional dimension of the funnel. 2. The jaggedness of the system (which I have written about a lot separately). Capability peaks in domains that are digital, verifiable and economically valuable. This is because LLM capability emerges from reinforcement learning on verifiable rewards on a curated environment mixture driven by revenue potential. This aspect primarily drives the area (e.g. math&code) dimension of the funnel. 3. Access. Free-tier, paid-tier, internal. So this is the weirdness of the moment. The general public has mostly not interacted with these systems. When they have, it looks like a derpy chatbot. The majority of professionals still see only a modest uplift. And a small sliver of professionals are experiencing the vertigo of the curve going vertical. And it is all happening at the same time.
Judging by my tl there is a growing gap in understanding of AI capability. The first issue I think is around recency and tier of use. I think a lot of people tried the free tier of ChatGPT somewhere last year and allowed it to inform their views on AI a little too much. This is a group of reactions laughing at various quirks of the models, hallucinations, etc. Yes I also saw the viral videos of OpenAI's Advanced Voice mode fumbling simple queries like "should I drive or walk to the carwash". The thing is that these free and old/deprecated models don't reflect the capability in the latest round of state of the art agentic models of this year, especially OpenAI Codex and Claude Code. But that brings me to the second issue. Even if people paid $200/month to use the state of the art models, a lot of the capabilities are relatively "peaky" in highly technical areas. Typical queries around search, writing, advice, etc. are *not* the domain that has made the most noticeable and dramatic strides in capability. Partly, this is due to the technical details of reinforcement learning and its use of verifiable rewards. But partly, it's also because these use cases are not sufficiently prioritized by the companies in their hillclimbing because they don't lead to as much $$$ value. The goldmines are elsewhere, and the focus comes along. So that brings me to the second group of people, who *both* 1) pay for and use the state of the art frontier agentic models (OpenAI Codex / Claude Code) and 2) do so professionally in technical domains like programming, math and research. This group of people is subject to the highest amount of "AI Psychosis" because the recent improvements in these domains as of this year have been nothing short of staggering. When you hand a computer terminal to one of these models, you can now watch them melt programming problems that you'd normally expect to take days/weeks of work. It's this second group of people that assigns a much greater gravity to the capabilities, their slope, and various cyber-related repercussions. TLDR the people in these two groups are speaking past each other. It really is simultaneously the case that OpenAI's free and I think slightly orphaned (?) "Advanced Voice Mode" will fumble the dumbest questions in your Instagram's reels and *at the same time*, OpenAI's highest-tier and paid Codex model will go off for 1 hour to coherently restructure an entire code base, or find and exploit vulnerabilities in computer systems. This part really works and has made dramatic strides because 2 properties: 1) these domains offer explicit reward functions that are verifiable meaning they are easily amenable to reinforcement learning training (e.g. unit tests passed yes or no, in contrast to writing, which is much harder to explicitly judge), but also 2) they are a lot more valuable in b2b settings, meaning that the biggest fraction of the team is focused on improving them. So here we are.
2,200
5,865
2,257
43,798
6,794,879
Sylvain Bellemare 💫✨🧮 retweeted
As I predicted just a few days ago. I said Microsoft and Excel were going to be next. Brandon Thomas isn't just trying to provide compatible replacements for these tools. He's attempting to break the entire enshittified business model that produced them. More power to him! tomshardware.com/software/mi…
217
424
66
3,349
173,934
Sylvain Bellemare 💫✨🧮 retweeted
BTW it's like that for ALL industries, there's a conflict of interest AND the best thing you can hope for is that big LLM providers don't come after your lunch. I believe if your niche is small enough then you should be safe but who knows :D
NYU math professor Tristan Buckmaster says OpenAI’s Tuesday drop of 722 AI-generated math papers wiped out entire research programs: “This recent dump of papers on Tuesday destroyed the careers of early career mathematicians.”
1
3
1,140
Sylvain Bellemare 💫✨🧮 retweeted
Proud to support @AntSeed as a truely p2p inference marketplace
What BitTorrent did for files, we want to do for AI inference. Antseed lets anyone buy and sell access to AI models, on their own terms. The Antseed Foundation has raised $2.4M in a token round led by Spark Capital to help make that happen.
4
2
35
2,164
Sylvain Bellemare 💫✨🧮 retweeted
Privacy for Bitcoin. Without compromising scale. Going live to talk about Shielded CSV ⛊ xitter.cf/i/broadcasts/1mGPaZeOZ…
3
15
1
43
4,803
Sylvain Bellemare 💫✨🧮 retweeted
“The best that most of us can hope to achieve in physics is simply to misunderstand at a deeper level.” - Wolfgang Pauli
42
164
18
1,142
36,822
Sylvain Bellemare 💫✨🧮 retweeted
Don't trust. Verify.
We are very happy to announce that we have formally verified the techniques of Liam Eagen's eprint.iacr.org/2022/596 in Lean 4, using only the standard axioms: magicgrants.org/2026/09/29/D… github.com/zksecurity/eagen-… 🧵1/6
1
10
1,046
Sylvain Bellemare 💫✨🧮 retweeted
"Controlling complexity is the essence of computer programming." — Brian Kernighan
20
246
28
1,662
38,452
Sylvain Bellemare 💫✨🧮 retweeted
Bitcoin Wizards love Shielded CSV
Andrew Poelstra of @blksresearch breaks down Shielded CSV: a model in development by Blockstream Cryptography Lead @n1ckler where blockchain validation gets flipped. Users verify coin history themselves. The chain becomes an ordering layer, not an execution engine.
6
18
1,618
Sylvain Bellemare 💫✨🧮 retweeted
We're taking a bet that the future development and growth of space computing will resemble a lot what we've seen on earth: - Open and interoperable - Cryptographically verifiable and secure - Shared resources will unlock utility and scale Today we're announcing the first mission of @SpaceComputerIO, a custom design and implementation of our Space Fabric architecture. Our payload will be integrated aboard a spacecraft traveling from LEO to GEO and will be planned to operate in GEO for full 12 months or longer. Thanks to @spacereportr and @SpaceNews_Inc for the coverage 👽🙏🏻 1/
3
12
4
43
2,964
Sylvain Bellemare 💫✨🧮 retweeted
This is how mature enterprises solve security problems (vs braggadocios press releases that create panic instead).
Today, with over 100 industry partners, we introduced the NVIDIA Open Agent Safety Platform, bringing together OpenShell and Sentry. Artificial intelligence is extraordinary technology that will advance discovery, productivity, security, health, and prosperity for generations to come. But its full promise can only be realized when people have confidence that AI is being built to be safe and deployed with wisdom and responsibility. This is bigger than a single product. It's the beginning of an open ecosystem to build the trust layer for safe agent systems. Together, we are building the foundation of the AI economy. Trust and innovation are not in conflict. Safety is how trust is earned. We must build not only the most capable AI, but the most trusted AI, so that this extraordinary technology can realize its enormous promise for the world. nvda.ws/4hcoq7m
101
218
17
2,495
161,560