rgavuliak

4 ms·

1.
by rgavuliak 7d ago
I have a hard time understanding your opinion. What do you even mean by garbage? There's thousands of legitimate music bands/musicians on these platforms. Naturally you won't care for a majority of it, but an interpret being
2.
by rgavuliak 13d ago
Julia is going to overcome Python in usage, any decade now.
3.
by rgavuliak 16d ago
I like how this discussion has focused on Netflix where as the point is something different. There are 2 useful rules to consider when building stuff: * Your user might not necessarily be like you - this applies even more when we tech peopl
4.
by rgavuliak 21d ago
Interesting. I have had mostly the opposite experience. CEO(s) that changed strategy + focus every month and the middle management having to pick up the pieces. Keep people motivated and deliver.
5.
by rgavuliak 22d ago
When was this? MS Copilot has gotten a lot better lately IMO.
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by rgavuliak 24d ago
This seems to be one of the cases where what people say in a survey and what they do are two very distinct things.
7.
by rgavuliak 29d ago
Databricks on Azure went down too yesterday
8.
by rgavuliak 1mo ago
Exactly, especially in long trips this usually resulted to a fight among parents.
9.
by rgavuliak 2mo ago
Fair point, but before business people relied on other people to pull it for them. Sure, it was checked by human, but a technical human often lacked the business context and there's been plenty of instances, where the business person k
10.
by rgavuliak 3mo ago
There's a difference between a hyperbole and being tone deaf.
11.
by rgavuliak 3mo ago
Well paid engineers compare their experience to a labour death camp just confirms how out of touch they are.
12.
by rgavuliak 3mo ago
Ultimately the management should care about what brings in the most revenue. A feature that brings low revenue but has no fire is something no-one cares about. If you have a ton of revenue and no bugs, you likely can get recognition.
13.
by rgavuliak 3mo ago
European Roads and US roads are very different. US is much more car friendly.
14.
by rgavuliak 5mo ago
For me the whole piping felt like making everything less readable and harder to debug compared to a string of commands.
15.
by rgavuliak 5mo ago
> This has a great SQL-ish API. Python is similar but starts to be a little clunky since it requires you to think about indices: groupby has an as_index parameter for this very purpose > Deducting the discount You focus on doing the s
16.
by rgavuliak 5mo ago
> The value-add that Microsoft brings to Github Copilot is near zero compared to directly buying from Anthropic or OpenAI Over here in the EU, we need to store sensitive data in an EU server. Anthropic only offers US-hosted version of th
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by rgavuliak 7mo ago
I would measure data by time to action. If you're not actioning data it's worthless.
18.
by rgavuliak 9mo ago
I do usually have a beer at the airport, but having more means you have more usage out of the plane bathroom which I can do without.
19.
by rgavuliak 1y ago
I like the saying - weeks of coding can save us hours of planning.
20.
by rgavuliak 1y ago
Why do you expect an LLM to provide an accurate distance metrics?
21.
by rgavuliak 1y ago
I have recently joined a corporation after years in start ups and 99 % of these apply too.
22.
by rgavuliak 1y ago
France is all about big government
23.
by rgavuliak 1y ago
Because it doesn't seem to work?
24.
by rgavuliak 1y ago
I don't think it's about perfect predictions. It's more about going all in on Metaverse and then on AI and backtracking on both. As a manager you need to use your resources wisely, even if they're as big as what Meta has
25.
by rgavuliak 1y ago
Having worked in such companies, switching to that mode requires very different processes.
26.
by rgavuliak 1y ago
Interesting point
27.
by rgavuliak 1y ago
I think especially for Data Science, a lot of the curriculum got taken over by universities and new university programmes for Data Science were created since then so in a way it became common knowledge for fresh graduates.
28.
by rgavuliak 1y ago
> MOOCs never achieved the transformative potential promised during the early hype. I would disagree, I saw a lot of people, especially in the Data Science field that got up-skilled by back then free Coursera.
29.
by rgavuliak 1y ago
> Nobody wants people who can do easy things, people want people who can do hard things. No, people want people that can provide value regardless of the difficulty. What you're describing is how we end up with not invented here synd
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by rgavuliak 1y ago
If anyone knew how to spot unicorns, the industry would be very different.

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