Somewhat off-topic, but why are all the men in the film wearing hats? Was this some sort of dress code?
2,257 karma · joined February 25, 2024
We could also say AI-literate too, I suppose. I guess I just like to focus on ML generally because 1) most modern AI is possible only due to ML and 2) it’s more narrow and emphasizes the low level of how AI works.
For example, I believe that if we were to ask the average developer about why LLM's behave randomly, they would not be able to answer. This to me exposes a fundamental hole in their knowledge of AI. Obviously one shouldn't feel bad about not knowing the answer, but I think we'd benefit from understanding the basic mathematical and statistical underpinnings on these things.
It's a bit snarky of me, but whenever I see some web developer or product person with a strong opinion about AI and its future, I like to ask "but can you at least tell me how gradient descent works?"
I'd like to see a future where more developers have a basic understanding of ML even if they never go on to do much of it. I think we would all benefit from being a bit more ML-literate.
Also question: is there much of a reason to switch to neovim after learning vim motions in vscode?
What is the 'big idea'?
I'm a VSCode user and when I hear people talk about neovim and it customizability or its productivity, I think to myself "VSCode is also very customizable and there's a lot of ways to get a lot of productivity out of it, why would I use neovim?".
Surely there's something I'm missing? Does it help you stay more in the flow or something? Is it because it's faster? Maybe it's because it's an editor you can easily use while ssh'd into a remote machine? Please enlighten me!
... though I honestly do wish that the current LLM interfaces I use would just implement something like this. Maybe they could acquire you guys :D
The fans don’t totally block out the tinnitus, but they sorta act as an undistracting distraction.
As a weird example, a web app may be like the exposed plant above ground while the roots are that developer’s knowledge. The plant is what others see, but the roots are the intricate system that was required to create the plant.
Question also: do you somehow keep a "mental catalogue" of related articles or do you use some tool to find these?
It makes really nice use of python docstrings and is overall just really easy to use!
Can you someone provide a summary of this breakthrough?
> Duolingo has gotten bad press from writers who try the app and don’t learn much. But Von Ahn promises only to get users to a level between advanced beginner and early intermediate. “A significant portion of our users use it because it’s fun and it’s not a complete waste of time,” he says.
> He’s been logging 15 to 20 minutes of French every day since November, and when asked to describe what he did the previous weekend he says, “Je fais du sport. Je suis mange avec mes amis. Je suis boire du biere en un bar,” mangling his tenses. (Rough translation: I play sports, I am eat with my friends. I am drink beer in a bar.)
> Bob Meese, Duolingo’s 42-year-old chief revenue officer, has been studying Duolingo Spanish for more than six months. In response to the question, “¿Hablas español?” he freezes, then says, “Could you repeat that?”
[0] https://www.forbes.com/sites/susanadams/2019/07/16/game-of-t...
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Also, having worked in the language learning industry myself, readers may be curious to learn that Duolingo is seen as a pariah that no one takes seriously as a learning tool. And I'm not one to use the term "scam" lightly, but if that word is to mean anything, then it definitely applies to Duolingo!
I imagine it won’t necessarily be used in long scenes with subtle body language, etc involved. But maybe it’ll be used in other types of scenes?
I’ve seen a lot of people make predictions like this and it will be interesting to see how this turns out. But my question is, what should happen to a person’s credibility if their prediction turns out to be wrong? Should the person lose credibility for future predictions and we no longer take them seriously? Or is that way too harsh? Should there be reputational consequences for making bad predictions? I guess this more of a general question, not strictly AI-related.
I probably haven't been around as long as you. Could you provide an example of one that comes to mind?
Something ironic I found when I was on my last job search (and applying to some YC startups) was that, despite startups often being critical of big tech, when describing their past experience, the founders (and their teams) never failed to ‘name drop’ the brand-name companies they’ve worked for.
Additionally, I think the reason a lot of founders threw my resume in the trash was because they couldn’t recognize the no-name startups I’ve worked at… Luckily I’m at a household name company now and even non-tech people recognize the company I work at.
I know for example that in Canada and Europe, we're mostly all pretty disturbed about these trade disruptions, but I'm curious if Korean's feel equally 'put off'. Are they as dependent on the US as Canada and Europe?
I understand that not updating your dependencies when new patches are released reduces the chance of accidentally installing malware, but aren’t patches regularly released in order to improve security? Wouldn’t it generally be considered unwise to not install new patches?