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 :)

In practice, we've now molecularly characterized most well-studied cancers and know that they tend to have the same mutations. For example, certain DNMT3A mutations are very common in AML and the BCR-ABL fusion protein in CML (and results from an interaction between chromosomes 9 and 22 that produces the mutant 'Philadelphia chromosome'). There are even a wide range of cancers that share similar patterns of mutations and fall under the umbrella of 'RAS-opathies', which all exhibit some kind of mutation in a subset of genes on a specific pathway related to cell differentiation and growth. Examples include certain subtypes of colon cancer, lung cancer, melanoma, among many others.

More generally, when a cancer is subtyped, that subtyping is always done with respect to some quantifiable biological trait or clinical endpoint and – as you've hinted – that subtyping is commonly a statistical assessment. Each cancer is unique and, even within an individual cancer, we have clonal subpopulations – groups of cells with differing mutations, characteristics, and behaviors. That's one of the reasons treating cancer can be so challenging; even if we eliminate one clonal population entirely, another resistant group may take its place. The implication is that cancers that emerge with post-treatment relapse are often 1. more or completely resistant to the original therapy, and 2. exhibit different behaviors and resistance, often to the detriment of the patient's outcome.

- Neutral atoms, while always compelling, are now strongly in the running for state-of-the-art qubit technologies and may well have a durable superiority to other qubits (e.g. ion traps, superconducting, spin qubits, photonics). The photonics used for quantum control appear to have very powerful advantages over physical wire-based control common to spin and superconducting qubits in particular.

- The past few years, since 2019 really, have been incredibly exciting on the experimental side of the field (not that the TCS hasn't been exciting too – quite the contrary). Still, for me, this result and its timing is among the most surprising in this 4 year period. I don't I"m unique in this and I suspect that if you'd asked most folks in the QIS field on December 5th when we'd have a FTQC that can do something a classical HPC can't – even if not practical – they likely would have said somewhere between 5-15 years. Now, the path towards truly practical FTQC is clear and, with the accelerating progress, we'll likely see meaningful scientific advances due to QC technologies by the end of this decade, likely earlier.

- QC is, in many ways, a trailing technology to AI and quite exotic. While the use cases are different, the fact of the matter is that the advances in AI methods, and LLMs in particular, threaten to eat QC's lunch in many areas of scientific computing. Further, there are properties of quantum information that challenge many potential applications (e.g. no cloning theorem). In my mind, this is the greatest risk to QC technologies not gaining wide spread adoption across many STEM over the next 20 years.

- Even though QC may be practically challenged relative to AI, it is nonetheless (and likely will be for many decades to come) an incredibly verdant technological foundation for algorithm development, condensed matter physics, cosmology, etc. The quantum information paradigm is very different than the classical information; those differences provide a powerful lens to help us understand our world and universe.

Altogether, the future looks bright.