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Items tagged with: technology


Oof, I felt that.

#technology #tech #innovation #engineering #business #technews #gadgets

Edit - since this got so much attention, come join the Inkican Crew. We offer encouragement, guidance, and a place for members to connect

inkican.com/join-inkican-crew-…


John Oliver piece on LLM slop and it's damage to the whole internet is so good, I want to ask you to take the time to watch it twice.

Sublime, this is the vid of the day for me

youtube.com/watch?v=TWpg1RmzAb…

#LLM #slop #technology #AI #bad #spam #meta #google #youtube #Alphabet #tiktok


Speaking of the #RaspberryPi CM5, there's a new carrier board coming out - an open-hardware design which adapts it into a mini-ITX form factor complete with x16 (mechanical, it's still one-lane) PCI Express slot.

hackster.io/news/sanctuary-sys…

#Technology #SingleBoardComputer #News #Hackster


When the #RaspberryPi Compute Module 5 came out, you couldn't use the IO Case's bundled fan and heatsink at the same time - which was spun as letting people try out passive and active cooling separately.

Well, that definitely-not-a-design-flaw-honest has been fixed: the latest IO Case shifts the fan to allow clearance underneath for the heatsink.

hackster.io/news/raspberry-pi-…

#Technology #SingleBoardComputer #News #Hackster


More #science next with an iron-on material which makes integrated soft circuits into clothing and other fabrics as easy as ironing on a patch.

hackster.io/news/researchers-m…

#Technology #Wearables #News #Hackster


There's still one in the queue (and one embargoed until tomorrow,) but here's my latest for #Hackster - starting with one from last week I hadn't mentioned yet: a project to generate sound which can be picked up by smartphone microphones to help locate people (or, I guess, their phones) buried under rubble after a disaster.

hackster.io/news/sound-generat…

#Technology #News #Science


I Went All-In on AI. The MIT Study Is Right.


Just want to clarify, this is not my Substack, I'm just sharing this because I found it insightful.

The author describes himself as a "fractional CTO"(no clue what that means, don't ask me) and advisor. His clients asked him how they could leverage AI. He decided to experience it for himself. From the author(emphasis mine):

I forced myself to use Claude Code exclusively to build a product. Three months. Not a single line of code written by me. I wanted to experience what my clients were considering—100% AI adoption. I needed to know firsthand why that 95% failure rate exists.

I got the product launched. It worked. I was proud of what I’d created. Then came the moment that validated every concern in that MIT study: I needed to make a small change and realized I wasn’t confident I could do it. My own product, built under my direction, and I’d lost confidence in my ability to modify it.

Now when clients ask me about AI adoption, I can tell them exactly what 100% looks like: it looks like failure. Not immediate failure—that’s the trap. Initial metrics look great. You ship faster. You feel productive. Then three months later, you realize nobody actually understands what you’ve built.