The new narrative is that Tesla is a 'Technology Company'. There is Tesla AI for example that is building Robots etc. Musk's competitor to OpenAI (x.AI ?) has raised $6 billion at a $18 billion valuation. Unclear if that is related to Tesla. I guess he decided that if AI is going to destroy humanity he might as well make some coin helping it happen.
New? They have been claiming this from day one when people called out the fact that they produce a fraction of what other car makers produce yet are valued x times over the others.
> There is Tesla AI for example that is building Robots etc. Musk's competitor to OpenAI (x.AI ?) has raised $6 billion at a $18 billion valuation.
This is just giving Musk more runway to make promises that Tesla will fail to deliver on. When the robot fails, he'll pivot to promising something different, and the cycle will repeat.
Tesla has been lying about being a "tech" company to justify its obscene stock price for a decade. "Look we write software so it's okay that we are priced more than the entire rest of the industry combined"
Don't do the crime if you can't do the time. In this case that amounts to $10 billion per month of jail time (net worth $40 billion). Unlikely to actually serve time I bet and he still keeps all his money. Crime pays very well.
I've got a suspicion that there is going to be a lot of waste, regardless. There are a vast number of models, colors, and sizes. The odds that somebody else wants this specific shoe seem low.
At best, they'd need a steep discount. "You want a size 9 right Nike Pegasus in green. We will sell you that for 75% of the cost of the pair. But it turns out we have a single size 9 right Nike Pegasus in red. We'll sell you that for 50% of the pair cost."
At Nike's scale they might be able to make that work. I suspect they'll still have a lot of unsold single shoes, but they'll at least get some goodwill and positive buzz from Paralympians saying nice things about the program.
The cost is distribute across all the PowerPoint, Word, and Excel spreadsheets created to give the illusion that people are doing actual work. Go read a couple of the SFMTA PDF's linked to by a commenter. They are totally enlightening justifications like - reduced congestion blah - better monitoring blah. No meat whatsoever. No analysis backing anything up - just pretty pictures.
I rode Muni for 10 years almost every working day. Do you want to know what reduced congestion the most. Buying new muni cars because the old muni cars door mechanism had been repaired so much they did not open or close %50 of the time and people had to use other doors to get on and off a train on a daily basis.
LOL:) this story seems to resurface every couple of years. My favorite part of the article:
"Jeffrey Tumlin: "It's a question of risk. The system is currently working just fine but we know that with each increasing year risk of data degradation on the floppy disks increases and that at some point there will be a catastrophic failure."
This seems to imply they have been using the exact same disk for the past 20 years (absurd), they have absolutely no idea what is written on the disk and how it can be safely backed up or restored. This would be a problem regardless of the medium used.
Although I hold the line at using paper tape there is nothing wrong with using floppies other than it seems antiquated. It certainly is reliable and cheap. Maybe the only thing that needs replacing is the people running the Muni.
Every sizable manufacturer of floppy disks has exited the market. There are no more (major) suppliers for the tech. They’ve likely been depending on a dwindling supply of functional disks; if at some point they find themselves without enough working disks to operate the system, they will indeed be screwed.
There’s also the chance that they take a disk that’s on the verge of failure, plug it into the system, and some corrupted commands get loaded into the system. That could easily result in a “catastrophic failure”.
Floppy disks are not reliable or cheap. They physically degrade over time, and at this point are nowhere near cheap for “new” disks.
You make a good point. However, even with the disks backed up to a better storage medium, detecting data loss on the floppy and getting a replacement written and deployed to the correct location might take a while. During that time the system may face unacceptable transit delays.
Wait, what? If this thing boots from a floppy, and that floppy has a checksum on it, and the boot sequence involves loading the checksum and the rest of the floppy contents into RAM and computing the checksum, corruption detection would be near instantaneous and the remediation would be as quick as it takes to eject the corrupted floppy, grab another floppy copy from the bin, plug it in, and flip the on switch. So the delay would be (roughly) zero.
Let's say it's not just booting from it, but constantly reading.
Let's say no one implemented the checksum. Edit: I forgot that floppies have a crc check, my bad.
Let's say the machine that can write the new disk is physically far away from the machines that read them. (Or the guy with a stack of new disks -- which are harder to find every year -- his office is some distance from the control machine).
I guess I assumed it was only reading from the floppy, not also writing to it.. that doesn't seem like it would last very long at all without encountering errors (at least based on my memories of reusing floppies until they were completely worn out)
If your lens views Universities as a work training substitute their view would be accurate. If you view the University as Universus (Latin for Universe or everything) then what they offer is quite unique. Arguably all do not fulfill all of these.
1. A kinder gentler form of kicking your child out of the nest and learning to be on their own.
2. A no mac-education environment were students can participate in research and learn how to answer question that are not yet answered as opposed to regurgitation.
3. Learning to socializing as adults.
4. Meeting groups of people that spend their days thinking deeply about specific subjects. These people can then be used as resources for society as a whole to solve problems and make decisions.
5. Exposure to just about everything we know or think we know about everything.
If you do not view them as such then I would agree they are not worth the effort or expense. Industry can afford to train their own automatons. Which is one of the reasons they are salivating over AI at this very moment.
Even universities advertise the job placement rates for their various majors. Kids aren't told by parents, teachers or counselors to go to college to become well rounded, they're told to go because they'll earn more money if they have a degree.
As for #2, that's a very rare thing to encounter in an undergraduate degree. Most of your classes are being fed information, then asked basic comprehension questions about it. Maybe some creative authorship skills in the form of writing courses, but nothing groundbreaking there either.
Many degrees are luxury goods that you either get paid for by someone else or become a wage slave to pay off in a decade or three, depending on how much you borrowed.
Depends on your perception of value. I would/could never pay millions for an NFT any sort. I simply see zero value in them. Others seem to have no hesitation in writing that check.
Don't get me wrong I would like to see that type of education available for a lot cheaper. We always seem to make enough money to not qualify for financial aid of any kind but not enough to pay college fees without having to give up something else. My house needs a paint job for example - going to wait 2 more years until my son is out of college. That's life I guess.
2. In order to create the models one needs lots of compute and access to a lot of text. Google scores higher than OpenAI on both counts.
3. New models are released on a weekly basis by all sorts of companies. So OpenAI has no monopoly on LLM models. In fact their competition is staggering (NVIDIA, Meta, Google, DataBricks, Amazon (numerous other startups)) It will not be long before there are even more.
It seems to me that Altman saw this all as a timing thing. Reveal your cards now and force others to do the same in the hopes of obtaining a strategic position over competitors. Googles cashflow seems to be doing just fine and I haven't had to fight off any urges to use Bing.
You’re missing the final point - the use case beyond Chat. Google has search, GMail, Android, Docs, Developer Tools, etc
Google can put an LLM into everything and sell it. Not just a chatbot. OpenAI can sell theirs to consumers as a chat bot or an API. Google can out monetize them handily.
The best thing Google can do (which it’s starting to do) is open up access to LLMs. And help everyone else do the same. Give it away and flood the internet with more LLaMAs, more Groks, more CLIPs, more Hermes, more Mistal, more SIGLIPS, etc. If they just drown out the competition, and turn good enough” models into a true commodity, they’ll dethrone OpenAI easily.
Also no one mentions YouTube. Surely that data is a massive untapped opportunity. We saw the multi-modal abilities of Gemini today. A few years from now, and some better GPUs, and it might be able to handle video in real-time.
No. The best model wins. I’m currently paying $20/mo for all three leading models (GPT4, Opus, and Ultra). But in the future, when GPT5/Opus2/Ultra1.5 come out, I expect the prices to go up. So I will be choosing the best one. Whatever is on the top of the leaderboard will get my $200/mo (maybe even $2k/mo if it’s really smart).
This is forward looking. Models need to keep getting better. That takes research, and compute, and data. It’s not free, and it’s getting increasingly expensive.
I too pay for multiple services (Gemini, Claude, CodePilot). Not everyone can or will pay $2k, or $200, or even $20 for a massive model. And most flagship models today are significantly better than models 6mo ago, which were already transformative and valuable on their own. There is a huge opportunity to market “good enough” models for tasks that don’t require the latest and greatest abilities (eg summarize this list, write an email). Arguably, we already have much smaller and simpler models for a lot of these tasks.
There is a market for $20/mo assistants, but the potential market for “everything else” is much bigger - and assistants will be moving towards running locally where possible. These companies are burning billions, they’re going to need a bigger revenue prize for investors. And that’s integration of LLMs and AI into every other software product. The less of those products that run with OpenAI models, the less income OpenAI has to compete, and the harder it will be to keep up. That’s why the opportunity exists for big tech companies can flood the market with good but smaller models and ruin opportunities for cash flow to build the better models.
If the next gen of the top models improves as much as I hope they will - we will not need any integration. It will be similar to hiring a human personal assistant. But much cheaper, even at $2k/mo. Even if this doesn’t happen with GPT5, it can very well happen with GPT6 a year later.
> 2. In order to create the models one needs lots of compute and access to a lot of text. Google scores higher than OpenAI on both counts.
If a smaller company with less compute and data commercializes something before Google which has more compute and data, doesn't that mean they are behind? You don't measure a car race by fuel available in the pit and faster top speed. You measure by who gets to the finish first. It just goes to show that Google has a horrible driver.
I guess the point is this is a very long race and, actually, the end is still quite far away (if that end is AGI).
In his Lex Friedman interview Altman asks ‘what has ChatGPT really fundamentally changed about the world?’ - basically making the point that they’re still just getting started.
Having a tonne of compute and cash is still going to be really important in this race. You have to make it to the finish line to win.
Part of the point I was trying to make is that there is less benefit to Google to tout their advances - most of this are trade secrets. I could see them using it to enhance their current offerings in subtle ways.
Now that the cat is out of the bag that will likely change. Just because OpenAI publicly released a produce doesn't mean Google has not developed their own. It doesn't mean they have either.
These models still have a long way to go before they can advise Kirk on running the Enterprise:)
While everyone is hyper-focused on LLMs, Google is able to do more than that and imagine what Google DeepMind has not announced yet.
> It seems to me that Altman saw this all as a timing thing. Reveal your cards now and force others to do the same in the hopes of obtaining a strategic position over competitors. Googles cashflow seems to be doing just fine and I haven't had to fight off any urges to use Bing.
LLMs are something that is already played out to the first movers. Google has already caught up and the moat and monopoly has been evaporated.
President Biden recently announced that software should be using memory safe languages. The command sent to Voyager - poke - is a command to directly set a memory location with a value - totally not memory safe:)
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