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

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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...

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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.

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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.

Our key criteria is a desktop application that has basic contact management, leverages Twilio for its back-end (pass the API key + account SID to connect), can use an existing 10DLC registered business phone number + campaign for messaging, and is low- or no-code to setup.

Some automation, such as message scheduling or conditional messaging on response would be nice-to-have but is not critical.

We've examined a few possibilities that don't seem to quite fit our needs: - TalkyTo: good Twilio integration, however, it's an iOS app (not desktop), lacks contact management, and doesn't seem able to connect to an existing 10DLC campaign on Twilio (creates a new one). - OpenPhone: Seems like the perfect solution at first glance, but our efforts to discuss the feature set and our needs with our contact at the company have not been fruitful. - Sendblue.co: Again, seems like a perfect solution, but we've had some challenges connecting with Sales and the cost/conversation means it would be quite expensive relative to our business model, which would create a strong incentive to switch to a different vendor as we scale (we'd like to avoid this). - Front: Could work, but far more than we need (full CRM system) and quite expensive.

Are there any other potential solutions out there that the community can recommend? For this specific vendor, we're highly prioritizing a path of least resistance.

Comments URL: https://news.ycombinator.com/item?id=41675907

Points: 1

# Comments: 2

Edit: Here's a Pubmed article on a study where blind and sighted people were trained to echolocate: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8171922/

Don't know him personally, but here's a tangent for the interested: In the first year of my PhD, I read several of his papers from the 90's on the GATOR family of climate models. At the time, I was interested in a potential intersection with my field. One thing that struck me was the absolutely exquisite attention to detail in one of his papers made to model the perspiration of water vapor from leaf stomata in forests (don't have the paper handy but can find if anyone's interested). It was really quite impressive.

Anyway, just thought I'd share the anecdote :)