Why doesn’t wasm count?
3,894 karma · joined October 14, 2014
Edit: Here’s the incident-https://www.theregister.com/2015/05/27/text_message_unicode_...
note("G2@2 A#2 D@2 G@2 ~ G F@2 D@1.5") .sound("piano")
Could you elaborate?
How did they make that assertion?
In the body of the paper immigration policies were not included as a variable in the data, nor were they a part of the statistical analyses. I couldn't find anything regarding labor movement at all. It feels weird that it was just thrown there in the end.
This plays nicely with the birthday paradox.
Non sequitur.
It’s also still a valid question. I play the scales really well on the guitar. And because the frets are all laid out straight, shifting up by one fret means I’m just playing my chords and scales sharp. It makes transposing music incredibly easy.
I still don’t understand why the piano can’t be laid out like that.
Recently relaunched Clares.ca, a free website for Canadian amateur radio training.
The new site has modern basics: Fast and mobile friendly and will soon incorporate the latest updates to the Canadian test bank.
Additionally, I’m adding progress tracking, logins and notifications to keep users engaged. The previous version of the site was just the course and nothing else. This one is more usable.
> Be kind. Don't be snarky. Converse curiously; don't cross-examine. Edit out swipes.
It’s a play on the rumours that Musk abuses his ketamine prescription. Note that I’m not advocating for the rumours. Merely explaining.
You wouldn’t criticize someone’s kombucha because they didn’t piece their SCOBY (symbiotic culture of bacteria and yeast) together microbe by microbe.
The article says:
> despite the company's claims that DeepSeek only cost $6 million and 2,048 GPUs to train. However, industry analyst firm SemiAnalysis reports that the company behind DeepSeek incurred $1.6 billion in hardware costs and has a fleet of 50,000 Nvidia Hopper GPUs, a finding that undermines the idea that DeepSeek reinvented AI training and inference with dramatically lower investments than the leaders of the AI industry.
The underlying report states:
> The $6M cost in the paper is attributed to just the GPU cost of the pre-training run, which is only a portion of the total cost of the model. Excluded are important pieces of the puzzle like R&D and TCO of the hardware itself. > > https://semianalysis.com/2025/01/31/deepseek-debates/
But we already know this. The DeepSeek paper even gives a breakdown:
> Pre-Training: 2664K > Context Extension: $0.238M > Post-Training: $0.01M > Total: $5.576M > > https://arxiv.org/pdf/2412.19437v1
I’m confused by this question, is 45,000 too little for you? To label genocide you need a large number of of deaths with the intent of destroying a people’s identity.
> What’s the civilian/military ratio ?
If you’re able to find this number, you’re likely able to find that depending on whom you ask the percentage of militants ranges from 10-40%.
And this says nothing about the millions displaced, the destruction of Gaza’s infrastructure and the policies to starve the population. Given the vast amount of attention given to this topic and the information around it, you need to be make a conscious effort to stay ignorant of it. And to be wilfully ignorant of a genocide is to be complicit in it.
I suggest starting here: https://en.wikipedia.org/wiki/Gaza_genocide
As a dev, I hate jargon to dress up trivial products or when distressing things are watered down. Usually I keep my feelings to myself but in this case, allowing a genocide to be watered down would make me complicit.
P.S. I understand this will be downvoted. But HN karma is a small price to pay to call out the softening of a literal genocide. Imagine standing by when someone calls Germany’s genocide “punishments”.
I wonder what skills other people picked up that I didn't.
Some recent example of things I shared:
+ When your belt buckle hangs a little loosely on the front of your pants. You can hook the buckle's prong onto the front button of your pants and it'll stay put. So many people are excited to learn this.
+ Putting a jacket or any open-front garment on quickly. I saw someone struggling to maneuver their second arm in a tight jacket behind their back. I explained that if they hold their jacket out in front of them, put their hands in the arm holds, and slide their arm in further as they swing it around their body they'll get it on in a moment. It's also more stylish. They were so surprised.
I'm baffled by your wilful ignorance. You paint Israel as this benevolent entity. Here are some numbers from this latest conflict alone[1]:
Gaza Strip:
45,484+ killed
Indirect deaths likely to be multiple times higher
6,000 to 10,000+ missing
108,090+ wounded
16,300+ detained
1,900,000 displaced
835 killed
6,250+ wounded
12,100+ detained
1,609 killed
200+ captured
Israel:
952 civilians killed
902 security forces killed
13,572 wounded (as of 22 Jan. 2024)
251 captured or abducted
200,000–500,000 displaced
I recommend reading more about the timeline of events. This conflict is not 15 years old. And the answer isn't this straight-cut. https://en.wikipedia.org/wiki/Timeline_of_the_Israeli–Palest...
You mean occupying Palestinian territories[1] and subjecting them to apartheid[2]
[1]: https://en.wikipedia.org/wiki/Occupied_Palestinian_territori... [2]: https://en.wikipedia.org/wiki/Israeli_apartheid
> I'm sure you can find a way to blame Israel for Hamas attacking them
Which attack? The Oct 7th 2023 attack? You seem to be ignorant of the whole timeline of events[0] that it is a sliver of.
[3]: https://en.wikipedia.org/wiki/Timeline_of_the_Israeli–Palest...
Fixed the title, given that it's so "off the mark", to use the IDF's words. Let's break it down.
AI to generate targets:
To maintain the war’s breakneck pace, the IDF turned to an elaborate artificial intelligence [...] which could quickly generate hundreds of additional targets.
Flawed since any engineer reading these knows how inaccurate these can be. Imagine killing people based on those predictions.
Reviewing reams of data from intercepted communications, satellite footage, and social networks, the algorithms spit out the coordinates of tunnels, rockets, and other military targets. Recommendations that survive vetting by an intelligence analyst are placed in the target bank by a senior officer.
Another machine learning tool, called Lavender, uses a percentage score to predict how likely a Palestinian is to be a member of a militant group, allowing the IDF to quickly generate a large volume of potential human targets. Other algorithmic programs have names like Alchemist, Depth of Wisdom, Hunter and Flow, the latter of which allows soldiers to query various datasets and is previously unreported.
Genocide since:
Genocide charges against Israel brought to The Hague by South Africa question whether crucial decisions about bombing targets in Gaza were made by software, an investigation that could hasten a global debate about the role of AI technology in warfare.
Radio Amateurs of Canada created this public registry.
> A small number of Canadian Amateurs are experimenting with encryption. Most of this experimentation is with some of the digital voice modes. Some of these experiments are on repeaters and some are on simplex frequencies – all in the Amateur VHF and UHF bands. A few experimenters have published their keys on obscure discussion boards on the internet, and a few have approached Innovation, Science and Economic Development Canada (ISED) for guidance on using encryption.
Meshtastic is awesome, I have two T-echos. But it doesn’t compare to being able to whip out a handheld radio, tune into a nearby repeater and dial out with EchoLink to check in with my partner when I’m hiking.