“Eric Schmidt, who founded Google” no he didn’t

I can understand the confusion since he was CEO for the companies most critical years.

That kind of reporting is awful.

How is it they can’t either go to Wikipedia or one of the LLMs (despite hallucinations, tend to get simple things right) and get some corroborating evidence before making such basic mistakes on an article?

Man I can’t even trust simple things these days from LLM’s. Hardly scientific but I just decided to do my own little test one time when I was on discord talking to some friends about The Game Awards back in December or so. ChatGPT would simply omit winners and/or categories - got it wrong (twice the same way, one unique way) 3 times. We tried Gemini, it gave 1 wrong answer and omitted 2 categories. It was impressive how much worse than a basic search they were at a simple “what were the results of the 2025 Game Awards?”

You are right. ChatGPT doesn’t catch this, instead catches things like CERN having 25 member states instead of 24.

I would have expected it to catch it but it did not. I’m sure pro version would have though.

Easy install, discord/whatsapp/tg out of the box. And some agent orchestration out of the box where the main LLM can farm out tasks to different models/agents - yes Claude code has some of this too but I think this has more

Always take d3 with k2

put the APP3 through a washing machine recently by accident and they had the high pitched feedback if NC was used until they were fully dry after a couple of days. Have also put APP2 through washing machine before but never had this

Give them enough time and they will. EUV will hit limits anyway in a decade.

For china it's DUV+packaging for now, NIL/DSA mid-term, and MoS₂/2D chips long term. But wafer scale, defect free 2D logic is 20–30 yrs out, so no EUV shortcut anytime soon

Mid 90s efnet #philosophy was great. And undernet too

Can be a couple of hundred years with trees and wood used for housing. Long enough to figure things out

Script fonts don’t really look like handwriting - too regular.

But one of the early deep learning papers from Alex Graves does this really well with LSTMs - https://arxiv.org/abs/1308.0850

Implementation - https://www.calligrapher.ai/

ooo -- thanks for the link!

They have a bit different characteristics to dynamic/condenser mics - usually less high frequency content, and pronounced proximity effect.

Often used for horns, violin, guitar cabs - sources where you want to reduce "shrillness" but you can use them anywhere.

It’s mostly useful as a hands free shortcut to get replies from chatgpt. Beyond that it’s useless

All the promises of integrating deeply into the OS and have APIs directly into apps so you can use natural language to get any app to do stuff for you is vaporware

So much potential but none of it delivered yet, I hope it will change soon

Interesting. Thanks for the information.