Do we think this is not already happening, but on an "unconscious" level? I mean, if ChatGPT is trained on the internet, wouldn't it make sense that most recommended content would be sponsored ads. This is a serious question because I don't really have a full understanding of how the training is done.
I had a similar experience. A few months ago, I was in the city for a weekend and took Waymo for most of my rides. The one time I chose to use Lyft/Uber, the driver floored it before we even had a chance to shut the door or get buckled! The rest of the time we took Waymo.
I rarely use ride-sharing but other experiences include having been in a FSD Tesla Uber where the driver wasn't paying attention to the road the entire time (hands off the wheel, looking behind him, etc.).
I don't know if I trust Waymo cars with my life, but at least there are SOME standards, compared to the natural variance of humans.
> I don't know if I trust Waymo cars with my life, but at least there are SOME standards, compared to the natural variance of humans
I’ve ridden in a lot of Waymos – 800km I’m told! – and they’re great. The bit that impresses me most is that they drive like a confident city driver. Already in the intersection and it turns red? Floor it out of the way! Light just turned yellow and you don’t have time to stop? Continue calmly. Stuff like that.
Saw a lot of other AI cars get flustered and confused in those situations. Humans too.
For me I like Waymos because of the consistent social experience. There is none. With drivers they’re usually chatty at all the wrong moments when I’m not in the mood or just want to catch up on emails. Or I’m feeling chatty and the driver is not, it’s rarely a perfect match. With Waymo it’s just a ride.
I did have one drive straight through a big pothole in LA once, and I also felt like it chose extremely boring routes. But neither of those are very surprising.
Oh, and it doesn't like to pull into hotel entrances but instead stops randomly on the street outside it.
Or "pay $10 extra and it'll drive extremely aggressively" (in the acceleration/braking/taking turns at speed sense, i.e. only ways that don't affect safety, not "cutting people off").
The sane default is obviously "boring", as it projects an image of safety and control, is comfortable, and reduces wear on the car... but if the user pays for the wear and wants an uncomfortable ride, why not?
Maintaining safety across multiple driving "modes" multiplies the complexity of the problem, in a space where safety incidents can shift public opinion of the whole industry. This is a bad idea...
roads are shared resources. As long as it's not breaking any laws then sure but please don't ask it to raise the risks to other people on the road. Just tune out on your phone/tablet/laptop and ignore the boring safer ride.
I imagine most traditional taxi drivers converted into Uber and Lyft drivers. Unique regulatory circumstances in places like NYC might have delayed that process some of course (eg trying to pay off a medallion).
What a stupid process. It bothers me that farmers rarely own the land too. We can't shake our tendency to let wealth turn us into tiny little kings that live off the rent. (not so tiny in the case of farms, but you get it).
If you raise crops or farm animals, you are a farmer.
The USDA is not trying to pull a fast one with the definition of a farmer.
We could have a discussion about farmers that have other jobs and so are part time farming and part time something else. That tends to correlate with less intensive farming like corn and soybeans.
Is a massive agribusiness conglomerate a farmer? Most farmland in the US is "owner operated". But really, that just means it's not rented out by a non-operator landlord, which is the distinction that USDA article makes.
It's funny how "exploit workers worse (medallions) and worse (rideshares) until we can fully cut them out" has played out in such a perfect microcosm, and yet somehow people here don't seem to register that it was never the workers' own fault.
Taxis didn't lose because rideshares played the game better, they lost because rideshare companies used investor money to leapfrog their apps, ignored actual commercial transport regulations that would have made them DOA, and then exploited workers by claiming they weren't even employees, all so they could artificially undercut taxis to kill them off and capture the market before enshittifying.
Taxi drivers were already not employees, they were exploited contractors for the taxi companies.
And do you not remember what using Yellow Cab was like in the Bay? It was like being kidnapped. They'd pretend their credit card reader was broken and forcibly drive you to an ATM to pay them.
When I first moved here I went to EPA Ikea, afterwards tried to get home via taxi, and literally couldn't because there was a game at Stanford that was more profitable so they just refused to pick me up for hours. I had to call my manager and ask him to get me. (…Which he couldn't because he was drinking, so I had to walk to the Four Seasons and use the car service.)
Taxis lost at least partly because the workers were assholes. Refusing to take credit card payments (the card reader is "broken") or not picking up members of certain ethnic groups or not driving to certain areas. Sure some cabbies were nice, honest people with good customer service skills but those were the exception in many cities.
There was nothing stopping taxi companies from raising investor capital to build better apps and back end technology infrastructure. They were just lazy and incompetent.
Taxi companies didn't have any apps to leapfrog in the first place. Uber and Lyft created a superior product that people wanted. Doesn't matter whose fault it is, the buyers preferred something that was more convenient.
There was never a situation where uneducated cabbies on shoestring budgets were going to be able to develop an Uber/Lyft alternative.
> uneducated cabbies on shoestring budgets were going to be able to develop an Uber/Lyft alternative.
Are you under the impression that most cabs are/ were independent? That wasn't the case since at latest the 1980s. Having a radio dispatcher is a huge necessity as a cab driver.
I think you have to go market by market to make that statement. In NYC, for example, it was explicitly illegal for yellow cabs to accept radio/pickup calls, which was the domain of the livery cabs (black cars). The tradeoff was that only yellow cabs could do street hails. That worked for everybody for years - yellow cabs did a volume business, livery cabs were for outer boros or luxury/business travel and would sneakily try to pick up street hails.
In those days if you needed a car to take you someplace, aside from the outer boro examples, it was always faster to get a yellow cab. The car services could maybe get there in 45 minutes if you were lucky - big companies would often have deals with car service companies to have a few cars stationed at their buildings for peak times, so execs didn't have to wait for a car.
The yellow cab operators were essentially all independent - many rented their medallion/vehicle, either from a colleague or an agency, but they worked their own schedules and their own instincts on where to be picking up fares at given times.
No one expected something like uber - what is essentially a street hail masquerading as a livery cab. This basically destroyed yellow cabs and the traditional livery cab companies, but some of it is attributable to the VC spend, lowering prices (yellow cab fares are set by the city, livery cab fares are market-regulated) and incentivizing drivers. They made it so lucrative to drive an uber that you had thousands of new uber drivers on the road, or taxi drivers who stopped leasing their medallions and started driving uber.
At some point, though - the subsidies dried up, prices went up, and now its often faster to get a yellow cab than an uber/lyft. This is anecdata, but I take cabs a lot, and I've spoken with ~6 taxi drivers in the last year who either started with driving uber and shifted to driving a taxi, or went taxi-uber-taxi. Then I've had a lot more taxi drivers where they need passengers to put the destination into the driver's waze or google maps, even for simple things like intersections - I suspect they're uber drivers who became depedent on the in-app directions and native language interactions.
But the broader point I'm making is that in NYC, the drivers themselves were essentially unable to do anything about the changing market. The only power they had was to shift between the type of fares they were getting. And today when you order an uber, sometimes you get a yellow cab.
In a society where having a job is, for that vast majority not in the non-gilded classes, the only mechanism by which a person can secure their core needs.. losing a job is indeed a pitiable situation for most.
If we've built a society that when it "pivots" leaves swathes of people smeared out as residual waste, I'd argue we should feel bad.
We've certainly reached a point of technological advancement where many of these consequences at the individual level are avoidable. If they're still happening, it's because we've chosen this outcome - perhaps passively. But the clear implication of would be that we're collectively failing ourselves, as a species that tends to put some degree of pride in our intelligence.
And we should feel bad about that failure. It's OK to feel bad about that failure. We tend not to improve things we don't feel bad about.
It's interesting that we're on the cusp of a major change in our world and no one is really talking about it. Self driving cars will have a profound impact on society. Everything from real estate to logistics will be impacted.
Looking forward to when they get rid of traffic lights and the networked cars just whiz through and avoid hitting each other. They'll also seamlessly zip lanes together on the highway, and traffic waves will be a thing of the past. Maybe China will do it first.
You could still have pedestrian crossings with buttons etc which signal the cars to stop, just the same logic as we have now. Maybe even physical lights for redundancy. Pedestrians are pretty rare in most places though so this shouldn't slow things down too much.
Walk? Waymo already stops at crosswalks (marked or unmarked) if a pedestrian looks like they are crossing or starting to cross. That is more than I can say for human drivers. I’m confused why you don’t think this is just a win for pedestrians given how messed up things are now.
More likely that Waymo's will make it a paradise for pedestrians. It should be possible to cross any road at any point without so much as looking either way.
If a programmer is more efficient with AI then you need fewer programmers, assuming a fixed amount of work is needed. So in that sense AI would be replacing programmers.
> I don't know if I trust Waymo cars with my life, but at least there are SOME standards, compared to the natural variance of humans.
The one thing you can trust Waymo to do is spy on you. Hurray, more surveillance-on-wheels! Every one of these things has 29 visible-light cameras, 5 LIDARs, 4 RADARs, and is using four H100s to process all of its realtime imagery of you: https://thelastdriverlicenseholder.com/2024/10/27/waymos-5-6...
> A few months ago, I was in the city for a weekend and took Waymo for most of my rides.
> [...]
> I don't know if I trust Waymo cars with my life [...]
I'm curious to hear which one you forked and found useful? I've looked at the awesome MCP list but was a bit struck by decision paralysis when trying to figure out what to try, so I ended up just not trying any.
We use an outdated on-premise version of Azure DevOps (nee. Team Foundation Server) for our sorry excuse of task management. We also use some horrible plugin for time tracking so our bosses can be sure we're keeping the seat warm for the correct amount of time.
I forked [this existing MCP server for azure devops](https://github.com/Tiberriver256/mcp-server-azure-devops) but I had to make a lot of changes to have it work on our env and I also added some tools for working with that shitty time tracking plugin.
The funny thing is that this article makes the author sound like the "lazy" one here. They're completely engulfed in their own experience with no ability to put themselves in a student's shoes.
Students ask for lecture slides and that bothers you? Pare down your slides so the content is rendered useless unless they come to class.
Attendance is down? Mark attendance with a simple, 1-question quiz every lecture that students need to be in class to access (QR code, iClicker, etc.). Make it count towards a whole grade-letter percentage of your grade.
Students leaving to "use phones" during class? Students can take classes back to back. Sometimes with almost no break in between (unless you consider racing across campus from one class to the next a break). It's not easy to switch subjects like that and meaningfully contribute to both spaces.
If you find this interesting, the Theories of Everything podcast with Curt Jaimungal does a good job exploring this topic. The neuroscience-centered conversations focus mostly on consciousness, but they still discuss similar problems with measuring and explaining how consciousness comes about from a collection of matter.
I just interviewed someone for a Senior position who's been using these AI copilots for 1.5 years as a contractor. In the interview I politely said I wanted to evaluate their skills without AI, so no Cursor/Copilots allowed. They did not remember how to map through an array, define a function, add click/change handlers to input, etc.
What I've found after developing software for many decades and learning many languages is that the concepts and core logical thinking are what is most important in most cases.
Before the current AI boom I would still have had a problem doing some tasks in a vacuum as well. Not because I was incapable, but because I had so much other relevant information in my head that the minutia of some tasks was irrelevant when I had immediate access to the needed information via auto-complete in an IDE and language documentation. I know what I needed to look up because of all that other knowledge in my head though. I knew things were possible. And in cases where I didn't _know_ something was possible, I had an inkling that something might be possible because I could do it in another language or it was a logical extension of some other concept.
With the current rage of AI Coding Copilots I personally feel like many people are going down a path that degrades that corpus of general knowledge that drives the ability to solve problems quickly. Instead they lean on the coding assistant to have that knowledge and simple direct it to do the tasks at a macro level. On the surface this may seem like a universal boon, but the reality is they are giving up that intrinsic domain knowledge that is needed to be functional at understanding what software is doing and how to solve the problems that will crop up.
If those two paragraphs seem contradictory in some manner, I agree. You can argue that leaning on IDE syntax autocomplete and looking up documentation not foundationally different than leaning on a coding assistant. I can only say that they don't _feel_ the same to me. Maybe what I mean is, if the assistant is writing code and you are directly using it, then you never gain knowledge. If you are looking things up in documentation or using auto-complete for function names or arguments, you are learning about the code and how to solve a problem. So maybe it's just, what abstraction level are we, as a profession, comfortable with?
To close out this oddly long comment, I personally use LLMs and other ML models frequently. I have found that they are excellent at helping me formulate my thoughts on a problem that needs to be solved and to surface information across a lot of sources into a coherent understanding of an issue. Sure, it's possible that it's wrong, but I just use it to help steer me towards the real information I need. If I ask for or it provides code, that's used as a reference implementation for the actual implementation I write. And my IDE auto-complete has gotten a boost as well. It's much better at understanding the context of what I'm writing and providing guesses as to what I'm about to type. It's quite good. Most of the time. But it's also wrong in very subtle ways that require careful reading to notice. And I'll sum this paragraph up with the fact that I'm turning to an LLM more and more as a first search before I hit a search engine (yet I hate Google's AI search results).
The situation opened up a very interesting discussion on our team. All of us on the team use AI tools in our job (you'd be a fool not to these days). I even use the copilot tool that the candidate used. But the difference is that I don't rely on it, and any code it produces I'm actively registering in my head. I would never let it write something that I don't understand without taking the time to understand it myself.
I do agree though. Why do intellisense and copilots feel so different from one another? I think part of it is that with intellisense you generally need to start the action before it auto suggests, whereas with copilots you don't even need to initiate the action.
I have a friend whose son is named Dawson and the father is David. When naming my own kid, I was curious of the origin of Dawson and finally put two and two together. Apparently it was intentional!
I gave my daughter a toy camera around age 2.5 or 3 and didn't realize it also captured video. She had unintentionally discovered the video function and has since captured many conversations, photos of our old house, videos of car rides, and loving moments between our family.
She's had it for almost 3 years now and it's been one of her longest lasting toys and is, without a doubt, the most meaningful. It gives "seeing the world through her eyes" a whole new meaning.
My 4yo child recently received a $10 digital camera at a generous birthday party and independently has figured out how to take videos (in addition to photos). Some self interviews, some videos of his sibling, his family. It really is amazing to see things from his eyes.
Is it just me, or does it feel like a significant proportion of psychological research nowadays comes to "no-brainer' conclusions? I find myself more often looking at an article and thinking, "Well, duh."
This is a genuine question. It may just be an environmental shift. Since I used to be deep in the field, I had access to any scientific journal I could think of and the latest research studies. Now I'm mainly seeing pop culture psychology. Has it always been this way?
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