Working on a python library for combining shell commands and python functions with pipeline operator syntax. Hasn't progressed beyond an experimental prototype, some of the tests (i.e. test_bash_pipe.py) show how it works.
I can't say I know much about AI stuff or BEAM. But my best guess is that elixir native ML should integrate well with OTP's distributed computing capabilities. As an outsider to the elixir ecosystem, I've seen glimpses of elixir ML here and there but no mention of attempting to bridge the python ML ecosystem into elixir.
Is it a matter of not finding the problems solved by LAMP/js frameworks interesting? Or in the cases where you solve the same issues as the frameworks, are you not finding the upsides of using frameworks compelling enough to justify learning them enough to become more productive?
Could be worded better but I would interpret it as "No web development skills required to start developing web apps entirely in R/Python". You're still expected to learn web development but within the context of an R/Python environment
I was about to disagree but the automated risk evaluation (ARE) part definitely qualifies your whole statement. Going to go off on a tangent: how do we introduce automated risk evaluation to environments outside of software development. Implementing ARE as software is probably the most efficient method in terms of time and resources. But ideally (some) users of ARE should be able to improve on it. In the case of "traditional" engineering (civil/electrical/chemical etc.) there are engineers who specialize in numerical methods and can improve on ARE. But what about professions where software development skills are not as widespread (or seen as a legitimate contribution to the field). There are still probably going to be members of these professions with software development abilities but is there a point where other methods could be considered (i.e. electrical/mechanical methods) for ARE implementations.
Text-based interfaces still have the same issue with being able to make a typo or tab completing without checking. Seems like the major advantage is that these text based tools are able to be versioned well through scripts. This might be fixed with a GUI version of autohotkey, turning these gui interactions into a script.
Platforms such as Etsy, Gumroad and ironically Substack are significantly (if not totally) targeted towards the long tail. An argument can be made that these platforms are not successful enough to justify serving the long tail, but the author started the article with concern for counterculture and then ties widespread financial success as a metric for healthy countercultures. A better metric would be the amount of viable lifestyle businesses operating within cultural niches but no data on this is present within the article.
The author makes several references to a consulting project where they also state that serving niches is not viable, this is probably true for whatever client was looking to branch into this. With the provided examples, the article reads as a defense of those previous findings.
You can model passive circuits with RLC ordinary differential equations (depending on the setup of the equations there's some algorithms such as Runge Kutta to solve them numerically). Afaik you can model some active components with ordinary differential equations, but I wouldn't be surprised if you had to resort to partial differential equations (More or less a "complete" electromagnetic simulation at that point).
The water molecules aren't chemically bonded to the ions, but they are "bonded" by intermolecular forces. Although weaker than a chemical (intramolecular) bond, the intermolecular forces are still strong enough to "bond" water molecules to the ion. So either only water molecules not "bonded" to ions can pass through these channels, or the pressure differential across the channel can free the water molecules from the ions.
That's part of the issue in research though, you don't know what will have value. The actual problems that particle/nuclear physicists attempt to solve might not be valuable but the engineering required for the experimental apparatus could be revolutionary.
With the dismal quality of search engines being a relatively common topic on HN, I could definitely see the role of reference librarian seeing a resurgence, with a stronger focus on internet based resources.
Is the ChatGPT threat to knowledge workers an actual threat (let's say in the timeframe of a decade) or only a perceived one? I don't think at the current performance of ChatGPT and similar models are enough to displace genius knowledge workers. Although I could see the possibility of ChatGPT-like models allowing more work to be done by fewer knowledge workers. And in this scenario, there is no guarantee that an "unfound" genius makes it through the new system.
From a brief look at the citations, there doesn't seem to be any scientific basis behind it. The cited patents are either from the same inventor, describe optical manipulation of the nervous system or are related to systems where EM human exposure is relevant (e.g. MRI and X-ray machines). The one paper cited talks about a threshold voltage required to excite neurons but nothing about intensity levels relevant for this patent. I might be wrong as I didn't do an indepth search of the cited patents made by the same inventor.
While resonance is possible, the resonating wave must still overcome the resistance (or whatever analagous "friction" like quantity for the system) in order for the amplitude of the wave. Given the loss from screen-to-skin propagation through air and the loss of the reflected component from air to skin transmission, it is highly unlikely that the wave can be sustained from the initial intensity of a screen.
I think its more a comment of how we should be open to people contributing to these efforts (while still being mindful of wild claims). While the concept of perpetual motion machines is flawed, the effort put into reducing kinetic energy loss is very useful. Flywheels are being actively studied as a method to store excess energy storage. In the long-term view I don't think you can consider anything not worth spending time on, the result just might not be applicable to the original goal.
Labour costs would be cheaper with self-driving cars, UberEats/SkipTheDishes/Arbritrary Food Delivery App would most likely own the cars. They would definitely factor the vehicle depreciation cost into delivery fees. If the gig worker provides the car, I'm not even sure if it would be that much cheaper to pay someone to sit in a self-driving car for the car to door delivery.
If you can afford to take a lower salary, you could try getting a position as research technician in an engineering lab. No guarantee that you'll develop the skills you want, but at least it would solve the problem of professor recommendation.
I think it's more about how can you make the most of your life despite being "pipelined". It's not realistic for everyone to pursue fulfillment by aiming to be world renowned in a specific area, for both the reasons you mentioned and there aren't enough areas where everyone to have their own individual hyperspecialized niche. However, your point does apply at a more modest level as well; if you're fulfillment requires costly institutional education, your socioeconomic background could close doors prematurely
- repo: https://github.com/JanukanS/cudgel/tree/main