I'm a big fan of Karl Popper's work. I learned about him when reading the book Empirical Linguistics by Geoffrey Sampson. At the time, it was a pretty iconoclastic publication, since it directly struck against the assumption of nativism by framing the study of language as something that could be evidence-based in a way where hypotheses were truly falsifiable. The ability to collect and process large amounts of data pertinent to language make it a lot easier to strike down some of the more inscrutable theories of the '90s and '00s -- at least to those who are willing to do real science.
Having more data and being able to consistency process it actually can say a lot about the hypotheses that linguists have. All other science is evidence-based. The challenge for linguistics has been that many theorists pick and choose armchair examples rather than back their assertions up with statistical validity.
I feel like if you need to utilize a tool like this, odds are pretty good you may have picked the Wrong Tool For the Job, or, perhaps even worse, the wrong architecture.
This is why it's so important to do lots of engineering before writing the first line of code on a project. It helps keep you from choosing a tool set or architecture out of preference and keeps you honest about the capabilities you need and how your system should be organized.
It’s almost as though choosing a single-threaded, GIL-encumbered interpreted scripting language as the primary interface to an ecosystem of extremely parallelized and concurrent high-performance hardware-dependent operations wasn’t quite the right move for our industry.
Ha. The question now is whether the ML industry will change directions or if the momentum of Python is a runaway train.
I can't guess. Perl was once the "800-pound gorilla" of web development, but that chapter has long been closed. Python on the other hand has only gained traction since that time.
Strange opinion. Plenty of apps have more than one language. I might end up using this.
Why? Because my app is built in Elixir and right now I’m also using a python app that is open source but I really just need a small part of the python app. I don’t wanna rewrite everything in Elixir because while it’s small I expect it to change over time (basically fetching a lot of data sources) and it will be pain to keep rewriting it when data collections needs to change (over a 100 different sources). Right now I run the python app as an api but it’s just so overkill and harder to manage vs just handling everything except the actually data collection in Elixir where I am already using Oban.
Sometimes the "right tool for the job" philosophy leads to breaking down a larger problem into two small problems, each which has a different "right tool".
Choosing a single tool that tries to solve every single problem can lead to its own problems.
I disagree, using python for a web-server and something like celery for background work is a pretty common pattern.
My reading of this is it more or less allows you to use Postgres (which you're likely already using as your DB) for the task orchestration backend. And it comes with a cool UI.
Wait until you find out about some people not writing pure python apps but also have some code in JavaScript. Crazy to mix more than one language in one machine.
Thinking 220GBP for a high-limit Claude account is the kind of thinking that really takes for granted the amount of compute power being used by these services. That's WITH the "spending other people's money" discount that most new companies start folks off with. The fact that so many are painfully ignorant of the true externalities of these technologies and their real price never ceases to amaze me.
That's the problem with all the LLM based AI's the cost to run them is huge compared to what people actually feel they're worth based on what they're able to do and the gap seems pretty large between the two imo.
reply