As far as we understand from anecdotal reports and scattered news articles, build quality problems are mostly from cars built at the Fremont factory, i.e. all Model S and X, all American Model 3 and most American Model Y.

If you buy a Model 3 made in Shanghai, you may get a better car.

Model Y production is about to start up in Texas, which has a better reputation in manufacturing.

Yeah I don't know, I'm not an electricity man. But they can't ignore it forever. I'm happy with my used Leaf, but I think between the limited fast charge options and the battery management I wouldn't recommend people but a new one.

Also dumb and untrue on many many levels.

We have the technology

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We paid just under 2k last year for Hootsuite and they want 3k this year. I have a real problem paying a license fee for a piece of software. Microsoft takes about 70 a year from us for office and Windows 10/11 is built into our PCs and it’s the entire platform you must have to even use something like Hootsuite. I don’t appreciate their customer support especially for that amount of money.

I’m moving to SocialBee, Hootsuite renews for us at the end of March so hoping to get up to speed and see if this is a good reasonably priced alternative.

They still have negative margins so it might be awhile

Classic r/technology take. Cool new technology being discussed, "yea but what about all this other bullshit that makes this trash and we shouldn't be excited or talk about it in any way shape or form."

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Digital gatekeepers, all it takes is money

When you don't want your wife to find out you play video games

GPT language model (or broadly generative AI) is climbing the usual 'peak of inflated expectation' of Gartner Hype Cycle. Everyone is excited about the possibility and are expecting unreasonable things.

But soon, the peak will pass, and enthusiasm will wane as people start to understand the limitations of new technology, and the gap between reality and expectation becomes evident.

Of course, there will be an impact in the long run as the technology matures and people find ways to deploy them to improve efficiency and expand capability.

I see 2 problems with the technology as it stands today. 1) it is still not user-friendly. 2) the technology is unsuitable for precision analysis. I'll elaborate.

1. Not user-friendly. Sure, you can communicate to it in natural language, and generate prose that sound plausible and interesting. But to date, you have no control over what learning material the model uses. You are reliant on few GPT providers for their discretion on what training material to use. But real productive marketable work, the content creators need to be able to train the model on training data they choose.

For instance, if you are lawyer building a case, you want the language model trained on case books, regulations, past judgements, etc., that are relevant to the profession. You are likely to get either nothing useful or uninformed opinion based on public information.

Another example, if you are an animation studio or comic artist, you would want to train the art-generating model (like Stable Diffusion, Dall-E, etc.) on your own portfolio of arts, so that when you create new show or content, it will be uniquely in your own style. None of the tools today let you do that, unless you're a programmer who can tinker with code. Sure, Pixar or ILM may be able to do this in a few years, but not if you are a lone artist.

So the AI software tools have some ways to go before they become prevalent.

2. Unsuitable for precision analysis. Neural networks do not store precise information. It stores association between inputs values. In a way, NN stores approximate 'impression' or generalization of data set. (In fact, you don't want to over fit and simply store the information.) However, a lot of information we deal with is binary: it's either one way or another. Answers that looks and sound correct, but actually incorrect is useless. But that's what generative neural network delivers: output does not seem to be out of place next to the learning material.

Sure, scientists use generative AI to generate innovative 'ideas' to test, but they still have to tested for actually validity. Generative AI is a good brainstorming tool, but not necessarily a generator of correct answers.

In time, these limitations will be realized by laymen, and the hype will fade.

But eventually those who figure out these imperfect tools will make them work despite shortcomings.

The tragedy is knowing that, we have these great and powerful tools, but, once everyone has made them “safe” “for us” all they can do will be producing 5 ingredients baking recipes!

My friend bought 2 and had to wait overnight lol that was before the price drop.

Why is it necessary to be so negative. They’re the first successful new car company in how many decades? They’re also American made (or wherever you happen to live now) - and the most American made car (they have the most parts made here. I know Elon is controversial but they did something amazing and it’s so stupid to keep shitting on them over and over again. They have their own issues but the company is only 20 years old if you can even say that. They literally changed the industry.

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Rule 34 is going to really take off

Once again, you've misunderstood the discussion I fear

Have you seen the lead times? A week is a short lead time and hasn’t been seen in years. Last year, I went to a Tesla showroom and they had 0 vehicles on display and a Model Y had a lead time of about 8 months. They clearly can’t keep up with demand, so the must not be charging more than the market will bear.

Why? Nobody can tell a difference over ~70 fps anyway.

15 years is not a few years

Quite a few mobos of that era supported tpm, just didn't install one. It may be as simple as buying, installing on the right pins, and enabling in bios.

Who said they couldn't keep up with demand at that time?

Then clearly the market will bear what they are charging.