If you change your Fourier transform approach into a time domain convolution, then you can generate it sample by sample. White noise -> FIR filter, this is a pretty simple and direct algorithm as far as DSP goes. The wiki on pink noise mentions this. I've done the FIR filter approach to simulate 1/f phase noise.
Tx/Rx isolation is about -35dB to -40dB depending on the Tx/Rx polarization selection. The QEC image rejection is about -50dBc in Rx, and about -40dBc in Tx (one-time cal, without background cal enabled).
The Tx and Rx are perfectly synchronized. This allows you to easily do things like near-field 4x4 MIMO radar: https://www.youtube.com/watch?v=gVqESemU_AI
> The return of the veteran engineers at Ford cuts against the prevailing wisdom — and fear — that AI will replace all kinds of knowledge workers. But Ford found the machines couldn’t replace experience.
I'm not sure this story is illustrative of that, when you have a VP of engineering saying “Over prior years, we didn’t pay as much attention as we should have to the experience of our most knowledgeable engineers that have been with us through many product cycles.”
He's saving face while almost certainly trying to figure out how to make the new systems work so that next time he won't need to rehire engineers.
> He's saving face while almost certainly trying to figure out how to make the new systems work so that next time he won't need to rehire engineers.
Yup. They jumped the gun. Now they need to hire them back so they can loot their expertise and never hire another senior. I'm not saying this will work, but it's pretty obviously the plan.
Pre-AI version: Oops, you laid off the higher-salaried people without having them train their replacements, so bring them back, long enough to do that.
Now, that training[*] will be for both AI models and lower-salaried hires.
Perhaps a second mistake by those who thought they didn't need their most experienced people: Now they think they just need to train the AI better, and then new-grad "AI native" hires will be the most cost-effective way to operate/oversee the AI and do whatever it can't.
[*] edit: originally typed "replacement" when I meant to type "training"
Is there any substantial number of companies actually training AI? Or do you count writing skills files for Claude as "training"? (Cause it really isn't..)
Well for grandma on the street I can accept that, but shouldn't at least the tech community be more precise in terminology? "AI" is also a misnomer. So many things in our industry are that it always takes some layers of digging in a new area to understand what they actually mean because the words have shifted their meaning.
I intended for the entire sentence to be in terms of the thinking of top leadership.
And to gloss over how that improvement would actually happen. (Not knowing what they've currently done and want to do, but for example, guessing: probably in partnership with vendors, consultants, etc., iterative and experimental process and tools improvements, and involving a variety of approaches and refinements.)
And for people focusing too much on AI, Xiaomi kicked their first vehicle into production with a fully automated factory three years ago [0]. That's where the industry is going and has tried to go for decades now.
They might want to also reduced head out on the designing side, but it's also an ongoing trend that started before the AI boom.
That's not an industry that will keep hiring as much as they did in the past, however it turns out.
Maybe. That's one interpretation. A lot of hiring/firing decisions get read through the lens of AI, hard pro or hard con. Reality is always a mixed bag. They certainly will want to try to build up a better automated pipeline, but the question is can they, and can they cost-effectively vs hiring a few more people?
I'm in the same boat, I code mostly by hand. I really enjoy it. The OP seems to have given it up without a fight, and that doesn't make sense to me. Especially because with 30 years experience I'm guessing they have FU money and are probably better than most people using AI anyways. Keep doing what you love and "surrender to the flow".
Uninformed FUD, not a single dsp "trick" related to passive radar is ITAR controlled. The equivalence the OP mentioned is literally described in every undergraduate dsp textbook.
That's very evil to recommend a graduate electrodynamics book to learn more about passive radar. I would suggest taking a look at Platos Republic to get some intuition on why that is. </s>
A famous quote from Carl Sagan in the marvelous Cosmos documentary where he explains atoms by slicing an apple pie until you can not slice no more because you are down to a single elementairy particle the atom.
Carl also references Plato's Republic when visiting the actual cave where Plato lived.
Carl also references books classical mechanics but not the book the parent comment mentions but earlier ones like Al-Baghdadi, Cristian Huygens, Galileo, Newton.
I'm probably spitting in the wind, but stuff like this is why I removed all my hosted open source projects. I manage several niche projects that I have now converted to binary only releases (to almost no push back). It's niche enough that it's not very hard to get LLMs to output chunks of code that it managed to scrape before I took it offline. I don't see many people talking about this angle, but LLMs ripping off my work killed my open source efforts.
No need to assume, the phrase is literally a link to the blog post the defines it!
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