I saw an article about this and downloaded the Perplexity app but I was unable to figure out if this was true? Do I need a paid tier? I just quickly worked through the free sign up and couldn't sort it out. The demo looked really slick. Is it worth pursuing?
I understand that a company I work with uses a few, and is migrating away from them.
It seems clear to me that prior to robust systems for orchestrating across multiple servers that you would install a mainframe to handle massive transactional workloads.
What I can never seem to wrap my head around is if there are still applications out there in typical business settings where a massive machine like this is still a technical requirement of applications/processes or if it's just because the costs of switching are monumental.
There are really applications that are large enough and hard enough to parallelize and/or shard that any rewrite on a different platform would turn into a performance catastrophe, even if you hired the best engineers and wrote the whole thing in very efficient C++, which you never hear about them doing because its usually only about saving money and so it's done with as cheap of developers as possible and in Java. I've seen it and it's not pretty. They tend to be dog slow and unresponsive, and even harder to maintain than the crusty old assembler and COBOL, because you have to implement a lot of the report writing and record crunching features built into a domain specific language like COBOL from scratch it you want to write the same application in Java.
That's my biggest pet peeve with people that want to ditch mainframes, which is that they seem to care very little about the quality and performance of the software in my experience or they would only be thinking of replacing COBOL and Assembler code with an equivalently performant modern language and dialect. The desire to migrate is often driven primarily to have cheap, easily replaceable developers.
IBM advertise 8 nines of reliability for the z17 (i.e. a second of downtime per year).
If you have a workload that cannot go down it's going to be more reliable than orchestrating a bunch of cloud servers where you're dealing with the network, hosts going down, failing, or issues with errors in the CPU (yep ... happens at scale).
They also test the hardware to exacting standards - 8.8 magnitude earthquake is one example.
Bank payment processing is the primary example - being able to tell if a specific transaction is or not fraudulent in less than 100 milliseconds - but there are other businesses with similar requirements. Healthcare is one of them, and fraud detection is getting a lot more sophisticated with the on-chip NPUs within the same latency constraints.
I have lived in this state for 5 years. Lyft works great!
The full story is I requested a ride to an Air Force base and the driver was not able to take us there due to restrictions at the base. We requested the driver drop us off at a restaurant just outside of the base. The ride we were on was cancelled, a new one created, and calculated as if we were originating at our point of embarkation at the same time all of this happened. Which happened to be during surge pricing.
I tried support for weeks. I was in an endless loop of scripts and going nowhere. At the time, the extra $200 or so charge was a significant amount for me so I charged it back with my card. The card had no issue with this but every time I try signing into Uber, they insist I pay them the remainder of their error from years ago.
I don't think I've ever used Uber. Have used lyft a few times, just to support a relative 'underdog' compared to Uber. Never had a problem. Probably less than 10 rides in the past 3 years though, so I'm possibly not a huge data point.
As some of the other commenters have directly and indirectly pointed out, I believe this is the crux of the AI Agent problem. Each user has a customized workflow they’re trying to achieve. This doesn’t lend well to a “product” or “SaaS”. It leads to thousands of bespoke implementations.
I’m not sure how you get over this hurdle. My email agent is inevitably different than everyone else’s email agent.
Counter-intuitively this is especially true with international flights... The main stressor for a plane is not like a car, where it's miles driven/flown. Its in pressurization/depressurization. And so a plane doing domestic skips an hour or two away will wear out way faster than one doing transatlantic trips, and so you're more likely to see the shiny new plane on a short domestic trip than on a big international one.
Incidentally this also applies similarly to risk issues. The biggest risk in a flight is not in flying, but in takeoff/landing. This is why the commonly cited deaths/mile metric is not only misleading but completely disingenuous by the people/organizations that release it, knowing full well that the vast majority of people don't understand this. If some person replaced their car with a plane (and could somehow land/take off anywhere), their overall risk of death in transit would be significantly higher than if they were using e.g. a car. 'Air travel being safer than cars' relies on this misleading and meaningless death/miles statistic.
Sure, replacing the car with a plane for your grocery shopping would be probably more dangerous, but do you have any data at what distances do the risks flip?
When I see those statistics I think about flights like Austria to Finland and I imagine that is indeed safer by plane.
It would be fascinating to see this trend data matched with statistics on how many Canadians are embarking on their journey from the US. Historically, Canadians will drive across the border in search of cheaper airfare in the US. Cities like Buffalo, NY, Burlington, VT, Detroit, MI, Minot and Grand Forks, ND.
At least that's been my anecdotal experience flying in and out of those cities. In Buffalo for example I distinctly remember literal bus loads of Canadians staying at nearby hotels before boarding US carriers headed for warmer destinations.
I suspect with the current environment, both are down. Still would be interesting though.
> Historically, Canadians will drive across the border in search of cheaper airfare in the US. Cities like Buffalo, NY, Burlington, VT, Detroit, MI, Minot and Grand Forks, ND.
I don't see that being the case for quite a few years. USD 1 has been ~ CAD 1.30 for a few years, so any US flight would need to be 24% cheaper dollar-to-dollar to even consider it. And that is before taking into account driving costs, traffic jams and wait times at the border crossing.
So if my Canada-origin flight price is CAD 100, and the equivalent flight out of a US airport is USD 76 (24% less dollar-to-dollar), I'm not saving any money.
Flying from Canada to non-US destinations is often MUCH cheaper because there's no TSA fees (which the US puts on the departing airport) for the return leg.
As someone from Buffalo it is (anecdotally) pretty common for Canadians to come here to fly to other parts of the US for cheaper, and for us to go to Toronto for cheaper international flights.
I just spent a few minutes on Google Flights looking at trips to various US holiday destinations like Miami, Las Vegas, Honolulu and Los Angeles. Every single destination was a lot cheaper (in some cases less than half price) when flying out Toronto compared to Buffalo. I wonder is a reflection on the collapse of demand for flights to the US.
It's a real thing, my family would frequently travel to SeaTac from Vancouver to travel to sunny destinations because airfare was substantially cheaper, and there were more direct flight options, especially to the Caribbean. We also travelled frequently to Seattle for MLB, NFL, and NHL games. During the first Trump administration we stopped due to outright hostility from some, individual, border agents, but picked up again over the last few years. That all stopped in December when Trump started "joking" about annexation, and threatening Canada and other allies.
I have also set expectations with my leaders at work that even work travel to the US beyond previously booked trips (the last of which is next week) is off the table, and I would prefer to find a new job than continue to travel to a country that is treating it's allies so poorly.
With Google’s recent constant popup about switching to the app in iOS Safari, I’ve pretty much 100% dumped Google for search. I use either DDG or ChatGPT search.
I dunno seems like a decent area to start with. A team that collects detailed data on customer service interactions as well as satisfaction of outcomes should be able to create a decent dataset. Then you grade outputs in a simulator to train the model. No need to train on the fly, at least not at first.
- service interactions are pretty complicated
- the satisfaction is dependent on a lot of factors
- customers mostly give 7/10 mostly because giving nps is so unnatural
When I recently upgraded to the iPhone 16 I was cautiously optimistic that maybe Apple would finally deliver on some of the tech promises of a personal "agent" in my pocket. It seems that all we really got was a better voice transcription and slightly worse intent understanding.
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