kajecounterhack

Wow Beej it's you!! I loved your guide to network programming in undergrad <3 you're probably not part of the problem here, lol.

Isn't this just solved by better student teacher ratios, which you could totally have in public schools if they were funded better and societally we valued teachers more?

What are private schools doing that you couldn't implement in public schools with adequate political will and money?

I felt frustrated that the professors didn't ever teach. They had slides. They read off slides, verbatim. They explained things sometimes if you asked them, but most often in a very elitist and condescending tone

+10000. The goddamn slides. If I were a student now going to engineering school, I'd basically take the slides and throw them into NotebookLM and get way better lectures. Then I'd ask claude or GPT all my hard questions. Hell, I'd get the PDF version of my textbooks and do the same.

The number of lectures actually worthy of your time was so low.

That was definitely not the subreddit where I got my info.

Have you found Gemma 4 31B better than Qwen 3.6 27B Q8? I just started using Qwen + Pi agent and it's great, but "which model works best" is still totally crowdsourced and I was going off of peoples' opinions on reddit. Would love to hear more opinions if people have them.

You should probably disclaimer that you're the author of swival.dev, but nice project :)

+10000 that Azure is a steaming pile of shit. Like what's this -- `azcopy` broken at head, and the working one doesn't guarantee correctness after a copy (99.6% copied successfully! good luck figuring out what went wrong!) compare that to migrating data with GCS or S3 -- they provide first class tools that do it right quickly (aws-cli, gsutil).

Want a VM? You'll also need this network security group, network interface, network manager, ip, virtual network... and maybe it'll be connected to the internet so you can SSH in? Compare to GCP or EC2 -- you just pick an instance and start it. You can SSH in directly, or even do it in the browser.

Billing also a nightmare: if you're running a startup, AWS and Google make it relatively easy to see how many credits you have left. The Azure dashboard makes you navigate a maze, and the button to click that says "Azure Credits" is _invisible_ for 30s until ostensibly some backend system finds your credits, then it magically shows up. Most people don't wait around and just assume there's no button.

And if you click it, maybe you will happen to be in the correct billing profile, maybe not! Don't get confused: billing profile and billing scope are different concepts too! And in your invoice, costs just magically get deducted, until they don't. No mention of any credits. Credits inaccessible through API (claude tried everything).

VMs, bucket storage, and copying data are the _simplest_ parts of the stack. Why would anyone bother trying to use other services if they can't get these right?

They literally give startups 2x the credits as GCP, 20x the credits of AWS and nobody wants to use them.

Agree it doesn't generate wealth. It's explicitly a store of wealth.

Investment is a weird term because most people would consider keeping cash or cash equivalents (gold) to be investments, even if they don't generate wealth. Cash is also an opinion, in terms of the market.

It has utility though: unlike the dollars in your mattress, it can't be printed into oblivion by your central bank. It is relatively portable, and people have flocked to it as a store of value especially during periods of socioeconomic instability when assets are going down and gov't spending is going up. It's tradeable for fiat in any country, so it allows you to bring value along if you relocate.

Its price reflects that utility and like any modern asset, a lot of speculation. You can speculate on whether it's more or less useful given current events -- nothing wrong with speculating that it is only going to be increasingly useful.

They are used in thin-film solar panel development. Not sure anyone has cracked the big problem with them, which is durability.

I tried mapping back to closest token embeddings. Here's what I got:

    global_step = 1377; phase = continuous; lr = 5.00e-03; average_loss = 0.609497
  current tokens: ' Superman' '$MESS' '.");' '(sentence' '");' '.titleLabel' ' Republican' '?-'

    global_step = 1956; phase = continuous; lr = 5.00e-03; average_loss = 0.589661
  current tokens: ' Superman' 'marginLeft' 'iers' '.sensor' '";' '_one' '677' '».'

    global_step = 2468; phase = continuous; lr = 5.00e-03; average_loss = 0.027065
  current tokens: ' cited' '*>(' ' narrative' '_toggle' 'founder' '(V' '(len' ' pione'

    global_step = 4871; phase = continuous; lr = 5.00e-03; average_loss = 0.022909
  current tokens: ' bgcolor' '*>(' ' nomin' 'ust' ' She' 'NW' '(len' ' pione'

This was for classifying sentiment on yelp review polarity.

I'm similarly puzzled by "uncured bacon" which afaik still uses naturally occurring nitrites. How they're allowed to call it uncured when it's clearly still cured is beyond me.

A lot of people use them together (cursor for IDE and claude code in the terminal inside the IDE).

In terms of performance, their agents differ. The base model their agents use are the same, but for example how they look at your codebase or decide to farm tasks out to lesser models, and how they connect to tools all differ.

Unrelated: my man, I loved your C vision library back in the day.

Cool stuff! Is the goal of this project personal learning, inference performance, or something else?

Would be nice to see how inference speed stacks up against say llama.cpp

I know what you mean, but still Tiger Beetles are an insect https://en.wikipedia.org/wiki/Tiger_beetle

OK but also note there's also not a "both sides" to everything. Some stuff can just suck.

Tesla could have more camera data in sum (that's not even clear - transmitting and storing data from all the cars on the road is no easy task - L4 companies typically pysically remove drives and use appliances to suck data off the hard drives), but Waymo has more camera data per car (29 cameras) and higher fidelity data overall (including lidar, radar, and microphone data). Tesla can't magically enhance data it didn't collect.

This is a crippling disadvantage. Consider what it takes to evaluate a single software release for a robotaxi.

If you have a simulator, you can take long tail distribution events and just resimulate your software to see if there are regressions against those events. (Waymo, Zoox)

If you don't, or your simulator has too much error, you have to deploy your software in cars in "ghost mode" and hope that sufficient miles see rare and scary situations recur. You then need to find those specific situations and check if your software did a good job (vs just getting lucky). But what if you need to A/B test a change? What if you need to A/B test 100 changes made by different engineers? How do you ensure you're testing the right thing? (Tesla)

And if you have a simulator that _sucks_ because it doesn't have physics-grounded understanding of distances (i.e. it's based on distance estimates from camera), then you can easily trick yourself into thinking your software is doing the right thing, right up until you start killing people.

Another way to look at it is: most driving data is actually very low in signal. You want all the hard driving miles, and in high resolution, so that you can basically generate the world's best unit testing suite for the software driver. You can just throw the rest of the driving data away -- and you must, because nobody has that much storage and unit economics still matter.

This is to say nothing of the fact that differences between hardware matter too. Tesla has a bunch of car models out there, and software working well one one model may not actually work well on another.

Segmentation that's not feasible at the current scale but will be in the future.

So you _do_ agree that willingness to pay is only helpful if there is segmentation.

Pre-Uber, we had both standard yellow cabs and black car services at different levels

There is more to the gap between yellow cab and black car than cleanliness. Stuff like service / helping you with bags, ETAs, partitions between yourself and the driver, niceness of the car itself, etc.

I'm sure we'll see segmentation along the lines of vehicle size and capability, but I expect cleanliness to be the same across those segments.

Services often launch with non-scalable attention to detail to control the initial public impression (eating the cost), and then relax over time.

I don't think cleaning is the burden you're making it out to be. These cars return to depot when their battery is down. If you're to clean them at all, you should clean them when they return for charging, and then to your set standard. It's not a big knob for controlling costs.

That's exactly what I'm saying would happen. We already have it with Uber Black.

But I'm saying we _don't_ have that for Waymo, and it's very unlikely to happen, for many reasons. A big reason is simply that managing a fleet in heterogeneous fashion as you're describing (different cleaning schedules for the cars) doesn't really make sense IRL. It's a purely imagined scenario on your part.

Incorrect.

Pray tell how I can pay for a cleaner car when there's only one option, car or no car?

No, I'm not assuming that.

Then please explain how cars would get dirtier as the service scales up? If today is already seeing the cars at full utilization, barring a cost-cutting measure that determined that cleaning less frequently would be a significant cost savings (which is a big assumption on your part), then we should be seeing roughly how clean the cars will be into perpetuity.

Again, Uber Black.

Uber Black achieves higher standards for cleaning by farming that out to the people renting out their personal vehicles. The drivers are incentivized to clean the cars more (than UberX drivers) to get more expensive fares.

But again, fleet management companies already do this for _all_ their cars. So for Waymo this is moot.

I guess. But bringing new products to market requires distribution, and do you have a better way for people to crack that? Targeted advertising through say, Instagram, has enabled a lot of small businesses whom would otherwise struggle to aggregate demand.

So it's not like pure evil. In many cases there's a service being provided to match users to products they want / that don't suck.

with targeted ads in the mix, there's a huge incentive to collect it and correlate it with all the other data Google has, which is creepy.

Strongly agree that in theory this shit can be used nefariously. That said, Google is far from the scariest of the bunch despite being the biggest. Telecom for example wants to deep inspect your network packets, and they can tell where you are physically today, anywhere in the country without even having cameras driving around 5 US cities.

Stronger regulations around data rights and privacy have been proven to work by the EU. I don't really see another solution apart from a legislative one.

Higher willingness to pay does not matter unless the market is segmented. So if the tech gets cheaper, unless they explicitly make an expensive "oft-cleaned" tier and a less expensive "less-oft-cleaned" tier, what matters is average willingness to pay.

"Once the tech becomes cheap, expect the car quality and cleanliness to go down" -- here you were positing that the _average_ willingness to pay for cleanliness will go down enough to affect things, barring any market segmentation. And I disagree:

1. You're assuming that the reason _why_ Waymo's cars tend to be cleaner than your typical Uber / Lyft is to satisfy a wealthy clientele. This elides a big reason for the existing gap: Uber / Lyft drivers aren't professionally managed. You don't directly pay for your Uber driver's interior car cleaning when you buy a ride, but the salary of folks managing Waymo's fleets is factored directly into pricing. Even if Waymo's clientele were less wealthy, you have to clean your cars and pass the cost on to all users. Additionally, interior cameras are pretty motivating to not mess up cars!

2. You're assuming that the cars today don't get maximum utilization, and that with more utilization you'd see dirtier cars. This is a pretty bad assumption - the cars are being utilized about as heavily as you can hope. In SF for most of Waymo's existence demand has outstripped supply. And the cars are still very clean :)

So if the usage is the same, and peoples' expectations for cleanliness are the same, why would rate of cleaning change as time goes on for the service?

The only thing I can think is if no reasonable alternatives to Waymo arise - in that case, cleanliness could go down but it has less to do with the clientele / willingness to pay, and more to do with competition / monopoly.

As another note, I just don't see how cleaning-based market segmentation would make good operational sense. Is cleaning the car slightly less frequently really gonna help the bottom line? Is the price differential big enough at single-ride scale? Do even rental car companies do this for their fleets - the cheap ones still seem to clean their cars.

That makes sense.

Honest question - what's the harm in being targeted by ads? Is it just scrolling youtube more often than you should? Or is there a nefarious side that I'm failing to consider?

For me the thing I hate about location tracking and the ilk is primarily about its harmful externalities (e.g. put into use by gov't, abusive users, or by Google for anticompetitive reasons), not targeted advertising itself.

I guess my question is - will Waymo really cause that much more tire noise vs today? Wherever car tires are making noise, I doubt Waymo is going to generate that much _additional_ noise.

I agree in principle that a privately run company could use information in nefarious ways internally, and that barring any additional knowledge you should not trust them.

That being said, I have an anecdote as a former googler: the reality with Google though is very thoughtful and favorable for users if you ask Googlers who've worked on their software products. There are audit trails that can result in instant termination if it's determined that you accessed data without proper business justification. I've known an engineer who was fired for an insufficiently justified user lookup (and later re-hired when they did a deeper look -- hilariously they made this person go through orientation again).

And safeguards / approvals required to access data, so it's not just any joe shmoe who can access the data. Wanna use some data from another Google product for your Google product? You're SOL in most cases. Even accessing training data sourced from youtube videos was so difficult that people grumbled "if I were outside of Google at OpenAI or something I'd have an easier time getting hold of youtube videos -- I'd just scrape them."

This isn't to say any of this is a fair thing to make decisions on for most people, because companies change and welp how do you actually know they're doing the right thing? Imo stronger industry-wide regulations would actually help Google because they already built so much infra to support this stuff, and forcing everyone else to spend energy getting on their level would be a competitive advantage.

Haha yep! I meant that as a rhetorical question, it's just silly to not move to sliding power doors.

I don't think the Jaguars are particularly spacious or nice. They just got a good deal on the platform. If anything, given the commodity nature of vehicles I'd expect car quality to improve.

Cleanliness doesn't seem that related to how expensive the tech is either - if anything it would only go down if it ceased to affect willingness to pay. As it stands, clean cars are important to their customers. If usage increases, cleaning can ostensibly increase too, no?

They won't have to if they use sliding power doors (the geely cars have them). They should have had them for the jaguar generation :)

Dooring people aside, what do you do if someone just leaves the door open when they leave their ride?!

Totally fair to be concerned about pervasive surveillance for the _potential_ of privacy violation. Not sure what to do about that.

That being said, just speaking with some knowledge of current state: the scans don't live forever. At this point, all the data they collect is way too big to store even for a short period. They'll only keep data in scenarios that are helpful for improving driving performance, which is a tiny subset.

Personally identifiable information is also redacted.

You should probably be more worried about what gmail knows about you than Waymo.

They gotta supplement mass transit for dense cities, not replace it.

Full agreement here. AVs are great for last-mile transit.

horrible use of space until they become autonomous buses on dedicated bus lanes, or trains

This is where we disagree. The whole point of AV TaaS is that they can go where bus lanes and trains can't. Last mile transportation.

I also wouldn't say they do "jack shit" for traffic in the sense that they reduce the need for parking, and reduce accidents which are the source of a lot of unpredictable congestion.

Surely there are tradeoffs. They indirectly incentivize sprawl and taking more taxi rides overall. And I get the tire residue argument (especially since AV fleets are mostly electric with high torque generating more tire wear). But is tire noise really a fair complaint? They're just going where cars already go and tires are engineered pretty well to minimize noise...