I love how this comment proves the need for audio2audio. I initially read it as sarcastic, but now I can't tell if it's actually sincere.
111 karma · joined September 22, 2018
If from scratch, quite impressive that the model is capable of understanding natural language prompts (English presumably) from such a small, targeted training set.
I work with large text datasets, and I typically have to go through hundreds of samples to evaluate a dataset's quality and determine if any cleaning or processing needs to be done.
A tool that lets me sample and explore a dataset living in cloud storage, and then share it with others, would be incredibly valuable, but I haven't seen any tools that support long-form non-tabular text data well.
It seems like you think MetricFlow should be the data mart layer and not just the metrics layer. If that's true...why? Why would I join my fact and dimension tables in metricflow instead of in dbt? One of the value adds of dbt is that it centralizes business logic in a single place. Joins are business logic. The industry seems to be moving towards creating very wide data mart tables in dbt and surfacing them to the semantic layer 1:1, or building the metrics layer on top of them.
There's a difference between emotional intuition and emotional reasoning (the cognitive distortion in OP's example).
Emotions are extremely valuable for decision-making (e.g. this house ticks all my boxes but do i love it?) and making judgements (e.g. this situation does not feel right to me).
Emotional reasoning is when people distort reality in favor of their (often self-destructive) emotional impulses, discarding physical evidence in favor of their emotions.
That being said, isn't it a bit late for a Launch HN post? :P
Some things don't change.
This solves the problem of getting high quality connectors built, but how do you plan to maintain them? What if the original contributor falls off the face of the earth?
It looks like we are generally as lonely as we were throughout the 20th century. Perhaps that's a sign the internet hasn't yet lived up to its promise as the great unifier. The fact that the greatest and most accessible communication technology in history hasn't put a dent in loneliness shows that we still have a lot of work to do in making it serve that end.
However with the advent of 5G and now satellite internet, it seems like high-speed wireless internet will be ubiquitous in relatively short order without the need for mesh networks. So that dream is probably dead.
That said, I make a point of using ETL-as-a-service whenever it's available, because there's no use solving a problem someone else has solved already.
Airflow 2.0 will have some pretty nice features for ML development as well.
Is it possible for me to work for one of these companies using a TN visa? Does my degree have to be "engineering" if the role is "data engineer"?
I'd be surprised to see if the same tendency to blur life and work, such as by working on evenings and weekends, persists once life returns to its previous form.
Acting as if people are unaware of data collection is disingenuous. If you told the average facebook user how much facebook and its third-party partners knew about them, I doubt many of them would stop using the platform.
Sidenote: I disagree that Apple Maps' success puts pressure on Google to up their privacy game. On the contrary, Google Maps comparative advantage is their data trove, as there are many more users of Google Maps than Apple Maps, so they seem more likely to lean on that to succeed.
I wouldn't look to the market to improve privacy, since as I said above, the market clearly doesn't care about privacy much at all. Without a seismic shift in public attitudes towards privacy, it's up to the government or the companies themselves to adapt.
If we ever get serious about increasing competition in the tech sector, an easy place to start is letting users set default browsers, maps, and email clients on their devices.