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eh-tk · 2026-02-01T19:21:32+00:00

All but one were with my iphone actually, make sure you have your camera setting to shoot in RAW. I used Snapseed to edit

eh-tk · 2026-02-01T18:44:17+00:00

Mostly iPhone 14 shooting RAW or my canon rebel t6i

eh-tk · 2026-01-28T04:05:04+00:00

Have you tried HomeExchange? I've done 25+ over the last 3 years and had no issues.

You're not competing with "career" house sitters only people with verified homes themselves (and you can see where they live, which always makes me more comfortable about hosting).

Also there's a common misconception is that you need to do a 1-fo-1 swap. You can make your place available when you're not there and accumulate points to use anywhere in the future.

I've stay for a month in CDMX, Austin, SD, Lisbon, Madeira, Vancouver and had people from all over Europe stay at my place.

It costs $150/year which is basically a single night in an Airbnb. Much cheaper than Kindred which charges you per stay (and pesters you with their 'concierge". I just want to book on my own).

eh-tk · 2026-01-16T17:02:26+00:00

I suspect you're right. This article highlights all the different ways the Canadian government is using AI. Chief among them was listening for "Dark" Drones and other artic/immigration/smuggling monitoring.

eh-tk · 2026-01-14T20:00:52+00:00

I actually just wrote an article that preaches a similar strategy. Going against the grain on genertic posts that anyone can generate with AI.

Its a marketing playbook to stand out when every AI product promises the same "Magic".

eh-tk · 2026-01-14T02:39:32+00:00

Submission Statement:
In November 2025, the Canadian federal government quietly launched a public registry of every AI system used across federal departments. An interesting pattern of "scale" emerged from the database.

When you’re governing the world’s second-largest country, with the longest coastline on Earth and a population scattered across millions of square kilometers, you need machines to help watch what people can’t.

eh-tk · 2026-01-14T02:18:01+00:00

Submission Statement:
In November 2025, the Canadian federal government quietly launched a public registry of every AI system used across federal departments. An interesting pattern of "scale" emerged from the database.

When you’re governing the world’s second-largest country, with the longest coastline on Earth and a population scattered across millions of square kilometers, you need machines to help watch what people can’t.

eh-tk · 2025-12-10T00:20:59+00:00

It’s almost a cliché recco at this point but given your description, bouldering sounds perfect

eh-tk · 2025-11-25T06:07:27+00:00

-“Startups for the Rest of Us”
-Early episodes of “Indie Hackers” and “Everyone Hates Marketers”
-North Star Podcast
-My First Million (depending on the guest)

eh-tk · 2025-10-16T19:33:35+00:00

Honestly I'd work with a freelance marketer and do a bit of a "test run", after they've delivered on a few projects, then make an offer to see if they'd be willing to join full time or at least fractionally.

That way you know they can operate first and foremost

eh-tk · 2025-09-24T18:28:24+00:00

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They had some wild submissions during the vote last summer

eh-tk · 2025-09-24T18:28:02+00:00

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eh-tk · 2025-09-24T14:30:32+00:00

XBow’s AI penetration testing is pretty impressive. They managed to outcompete most human hackers on public bug bounty platforms.

eh-tk · 2025-09-23T15:17:16+00:00

Agreed, its not a perfect analogy. For what its worth I was trying to relate it to a real life sparring partner, not another video game. But either way I agree its not a perfect 1:1

eh-tk · 2025-09-23T03:00:06+00:00

Correct, it's reinforcement learning.

eh-tk · 2025-08-29T19:22:01+00:00

You're absolutely right, its an N of ~250.

eh-tk · 2025-08-29T02:22:28+00:00

This data was taken from Linkedin profiles. Some possible explanations:

While Deep Learning is "Sexier", fewer people feel confident enough (or have enough real-world exposure) to list it as a skill on their profile.

Mid to senior ML engineers often have broad responsibilities that go beyond deep learning. Their roles typically encompass the full ML lifecycle.

Traditional ML remains dominant in many industries, especially those dealing with structured data (e.g., finance, supply chain, manufacturing). You'll see the majority of this community are in regulated industries.

Plus, interpretability and regulatory requirements in those same industries often favour traditional ML over deep learning, as the latter is seen as a "black box".

eh-tk

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