bnjemian
Joined 10 years ago
Joined 10 years ago
--
Lead systems engineer, senior research scientist, and former technical founder (B2C) with 13 years of experience.
Background in quantum computing, digital watermarking, AI data, and computational biology.
Well-versed in algorithm development and translation into production, quantum machine learning, quantum applications, data governance, cloud infrastructure, security/cryptography, HIPAA, full-stack engineering.
--
Looking for founding engineer, technical leadership, or staff/principle engineering roles where innovation meets genuine impact.
Languages: Rust, TypeScript, Node.js, Python, PostgreSQL, Redis.
“…a legislative intern, accused Baumgardner of sexual harassment in which he slapped her butt…”
You can’t make this stuff up.
While an LLM isn’t what you’d traditionally consider a weak learner, the theorems on learning systems clearly point to them being so in this context. The feigned surprise at combining them to yield better results seems disingenuous.
Even so, the work to predict which models are best suited for which task, how to delegate, and how to combine their outputs is interesting, especially if you’re placing a cost minimization objective on it. That said, this isn’t too far off from what many AI labs are already doing.
As a loose comparison, hardware bit errors happen probabilistically, yet they’re so rare that we can effectively ignore them in day-to-day use assuming no specialized application (e.g. defense, space, critical infrastructure).
LLMs aren’t there yet, but it’s entirely plausible that structures may can be developed to solve the problem, and those structures aren’t known or commonly conceived of in the present.
Remote: Remote/Hybrid/On-Site
Willing to relocate: California, Washington, Canada, EU, or UK (no visa required)
Languages: Python, Rust, TypeScript, JavaScript, HTML/CSS, SQL
Technologies: PyTorch, JAX, Tensorflow, CUDA, LangChain, LangGraph, NumPy, SciPy, Polars, Pandas, Numba, Cirq, QISkit, Pennylane, Node.js, Deno, Express, Hono, PostgreSQL, PL/pgSQL, Redis, AWS, Azure, Docker, CI/CD — plus whatever you throw at me; I learn fast.
Resume: https://drive.google.com/file/d/1kdtM2vPpLmTu3HI51Guetj82CPe...
LinkedIn: https://linkedin.com/in/benjamin-cordier-phd
Background: Staff-level full-stack engineer (13 YoE), both product and research. PhD in quantum computing/machine learning, applications in computational biology. MS in bioinformatics, applications to cancer genomics. I’m also the founding engineer behind June Dating (0-to-1). Our founding team bootstrapped the company to profitability, we’re currently on a product development hiatus. For my day job, I work in Rust and am building a data watermarking system for a flagship NIH consortium centered on ethical AI and FAIR data, currently around 160M files watermarked (1.9PB of data).
Open to: Founding engineer, staff/senior-staff engineer, and engineering manager roles. Industry/domain agnostic. I do especially well in high ownership and high impact roles.
If you instead decide that the Upload Queue can't be circumvented, now you're increasing the duration a patch for a CVE is visible. Even if the CVE disclosure is not made public, the patch sitting in the Upload Queue makes it far more discoverable.
Best as I can tell, neither one of these fairly obvious issues are covered in this blog post, but they clearly need to be addressed for Upload Queues to be a good alternative.
--
Separately, at least with NPM, you can define a cooldown in your global .npmrc, so the argument that cooldowns need to be implemented per project is, for at least one (very) common package manger, patently untrue.
# Wait 7 days before installing > npm config set min-release-age 7
Alice: x Bob: y Alice : z ...
While the analysis was mostly coherent with the exception of said misattributions, I filed away the mental note that this misattribution error happened frequently in these type of exchanges.
I guess this time they were undaunted. Perhaps they received an AI assist and felt validated by AI sycophancy.
Much of the technical evidence cited is weak (e.g. strong knowledge of public-key cryptography, both used C++, etc.). Still, the (somewhat lazy) forensic linguistics is interesting.
That said, the TSA is in some respects the lesser concern. Don't get me wrong, the TSA not having free rein with facial and biometric technologies is a good thing. But when companies like Clearview AI (https://www.clearview.ai) sell their facial recognition technologies to local police departments – technologies that were built on illegally obtained data and have a history of substantial racial bias – we have bigger issues. It's opaque, unregulated, invites a wellspring of social injustice, and doesn't past muster under any ELSI framework.
Government regulating government is important. But we, as a society, need to stop giving private companies like Clearview AI a pass on harmful, exploitative behavior – especially when they're run by founders like Hoan Ton-That who offer post-hoc rationalizations that amount to (and I'm paraphrasing here) 'Well, if we hadn't done it, someone else would have, so why not us?'
We need a bigger bill that enshrines and elevates privacy for the modern world.