It incredible how far the "Do not evil" marketing won the hearts of computing nerds, Google only got positive karma for doing with Android exactly what Microsoft did with J++.
To this day Android Java is not fully compatible with Java proper, and Kotlin became Google's version of C#.
Come on, that's a completely different story, Google made their own independent SDK using but incompatible with Java. Nobody's arguing you should do that.
Plus last time I checked Oracle lost that lawsuit.
That list should surely had to prepend "pay off debt, live within your means"
Listening to Dave Ramsey on YT gets me amazed on how some people can be so irresponsible and accumulate debt on credit cards and cars they can't afford.
I think this comment relates to the fact that article mentions AFTNews Updater app as a way to install SmartTube... not yet released version of software?
Elon Musk must be one. Seems enough techy to me: Tesla, SpaceX, Starlink - software being used for the hardware in innovative ways.
Edit: Oh, wow, mentioning this guy is surely controversial, sorry. However discussing whether he is a nerd, understands engineering on very deep level/gets his hands dirty OR he only manages people - there must be some psychological aspect related, a form of disagreement to discredit or have a hard time believing it can actually be true.
Maybe he used to be one, who knows. But I doubt he read a book or seen a movie in the past few decades. He got roasted by Joyce Carol Oates on X recently for being an oaf and he immediately started replying to tweets about acclaimed movies. And nothing insightful that proved he had seen them, just 'this is a great movie' or some other stupid oneliner. It would be hilarious if it wasnt so sad that the richest man on earth is such a pathetic little man.
The list is missing my #1 quote from Jim Keller (an epic engineer type) although unfortunately quote is in middle of a long YouTube vid. See https://news.ycombinator.com/item?id=33662764
Aside: I don't understand why they even mention what journalists think - only engineers opinions matter when judging engineering ability.
Middle of a long YT video is nothing: you can make links to auto seek to a specific place in YT video. When you share link on computer, it even allows you to check-a-box that will include timestamp within link
Or append &t=1h2m3s to the link to prevent writing long sentences on where to seek and save users from manual seeking :)
I think Elon Musk just wants to be Tony Stark and cultivates the appropriate image for that.
And possibly a genuine obsession with (rightwing-ish) meme/youth culture, which I think got him a lot of his initial followers on twitter/reddit/4chan/etc.
A lot of people miss how much of a tit Tony Stark (at least the Robert Downey Jr. version) was.
Smart, but not as smart as he thinks he is. Not good with anything interpersonal. Flair for the dramatic (and dad jokes) at the expense of those working with him.
Musk is a complicated character. He's had nerdy times programing, fascist turns including the famous salute, emperor delusions - he was named after The Elon, a fictional ruler of Mars.
Spoiler: He is not. But he is very good at faking it.
Anytime he tries to give a serious opinion on anything related to computers: It is laughably bad and out of touch (SQL, compilers, languages, performance, etc... ).
He definitively has a scientific background but definitively not "Tech" as far as computer are concerned.
I don’t see how “tech” is limited to software. While your case might be made for software, according to many accounts Musk is a strong driver on the hardware side. For instance, I’ve read the Tesla and SpaceX books by Eric Berger, which are much more focused on technical things compared to the more mainstream books. And while Musk is not in the trenches with a screwdriver, he’s not faking it either.
To be honest, I’m actually interested in this hypothesis: is he legitimately skilled/knowledgeable, or is he indeed faking it? And for either side I would like to see evidence. This question is interesting to me because some of his companies have made substantial contributions to pushing the frontier of technology (reusable landing, high launch cadence, electric cars, energy).
If he is really faking it, that might even be good, because the success of his companies might be replicable and could continue without him. But what if he is not?
He has a public image of "geek/need hero" that is honestly inspiring.
And that benefits him a lot because it bring people to trust his decisions. He has all the interest of the world to maintain this image.
> some of his companies have made substantial contributions to pushing the frontier of technology (reusable landing, high launch cadence, electric cars, energy).
People he hired for these companies made contributions.
Unlike the more common pattern, Elon doesn't hesitate to make straight up engineering decisions for his businesses, including ones that look unnecessarily high risk to a lot of his own engineers. Chopsticks catching spaceships made of stainless steel and self driving cars without lidar are well known examples. The success of those choices earns him legit nerd cred.
Disagree. The current limitations of Tesla self driving are not around difficulties in judging distances that lidar solves. They're around inference deficiencies with accurate geometry.
If the AI was good enough, vision-only self-driving would be at least as good as the best human.
The AI isn't good enough. I'm starting to suspect that current ML learning rates can't be good enough in reasonable wall-clock timeframes due to how long it takes between relevant examples for them to learn from.
It's fine to lean on other sensory modalities (including LIDAR, radar, ultrasound, whatever else you fancy) until the AI gets good enough.
It's safer than human drivers now. That's good enough. It will take more than that to convince world, and it should. I applaud the well earned skepticism. But I'm an old guy who has no problem qualifying for a driver's license, and if you replaced me with FSD 14.2, especially under not ideal conditions like at night or in a storm, everyone would be safer.
I predict a cusp to be reached in the next few years when safety advocates flip from trying to slow down self driving to trying to mandate it.
I can't speak to your driving level, but everything I see about Tesla's FSD has unfortunately been giving me "this seems sus" vibes even back when I was extremely optimistic about them in particular and self driving cars more generally (so, last decade).
Unfortunately, the only stats about Tesla's FSD that I can find are crowd-sourced, and what they show is that despite recent improvements, they're still not particularly good.
Also unfortunately, the limited geo-fencing of the areas in which the robo-taxi service operates, and that they initially* launched the service without the permits to avoid needing a human safety monitor, strongly suggests that it hasn't generalised to enough domains yet.
Lack of generality means that it's possible for you to be 100% right about Tesla's FSD on the roads you normally use, and yet if you took them a little bit outside that area you might find the AI shocking you by reliably disengaging for no human-apparent reason while at speed and leaving you upside down in a field.
* I'm not sure what has or hasn't changed since launch: all the news reporting on this was from sites with more space dedicated to ads than to copy, so IMO slop news irregardless of if it was written by an AI or not
No reason we can't rely on other sensory modalities after the AI "gets good enough," either. Humans don't have LIDAR, but that doesn't mean that LIDAR is a "cheat" for self-driving cars, or something we should try to move past.
In principle, I agree; but remember that people like to save money, and that includes by not spending on excessive sensors when the minimum set will do.
What I think went wrong with Musk/Tesla/FSD is that he tried to cut costs here to save money before it would actually save money.
Im sorry that is just not true. You can never achive the kind of data with vison-only tech. its easy to confuse, you need lidar. anybody that thinks they can achieve self driving safety without that tech is lost.
> Elon was an enthusiastic reader of books, and had attributed his success in part to having read The Lord of the Rings, the Foundation series, and The Hitchhiker's Guide to the Galaxy.[11][28] At age ten, he developed an interest in computing and video games, teaching himself how to program from the VIC-20 user manual.[29] At age twelve, Elon sold his BASIC-based game Blastar to PC and Office Technology magazine for approximately $500 (equivalent to $1,579 in 2024).[30][31]
I think it's fair to say he at least was a nerd. He was a dweeb getting beaten up in school, burying himself in books and computers at home. His skills are doubtlessly outdated now, but does that really mean much? Woz's skills (which to be perfectly clear, outclassed Musk's by miles) are doubtlessly out of date now too, but nobody would say Woz isn't a nerd.
I think the part where he grew into an unstable dirtbag might be influencing the way people see him now. Saying that is is, or at least was, a genuine nerd shouldn't be seen as any sort of excuse for his scamming, lying, etc.
He definitely has talked about a lot of nerdy books. Don't know about his attention span and not sure how to square what he likes with his values. He brings up the Culture all the time but I have my doubts that he's actually read them
I don't know either, I haven't read the Culture books (yet) either so I can't really evaluate that.
I do believe he read a lot of sci-fi in his youth, if only because that would fit the pattern of a young boy who doesn't get along well with their peers and turns towards solitary pursuits like computer programming. He seems exactly the sort to have read lots of Heinlein.
Almost everything about The Culture will be immediately apparent from stuff Musk talks about, but only about half of it would look like he's understood it.
The only real crimes are reading/writing someone's brain without permission (at which point others may call you names and stop inviting you to social events) or destroying a consciousness without backups (where you'll get permanent supervision to make sure you don't do it again). Most biological citizens have a full-brain computer interface for backups and general fun, called a "neural lace".
The AI Minds in charge of everything give themselves fanciful names, which Musk has used for his SpaceX drone ships.
For the reverse:
Almost every biological citizen is gender-fluid, can change physical gender by willing it, and there's a certain expectation that you try things both ways around so you know how to be a good lover. They dislike explosive population growth regardless of if it's organic or machine reproduction, and as everyone can get pregnant if they want to (because everyone can be a woman if they want to and it all works), it's considered quite scandalous to have more than one child.
It's sufficiently post-scarcity that money is considered a sign of poverty. They mostly avoid colonising planets, instead living on ships, or on habitats so large that if one was located at any Earth-Sun Lagrange point (including the one on the far side of the sun), we could see it.
Anyways, I work with .NET Framework and .NET. Being a developer is a joy where you can learn daily new tricks and satisfy your curiosity.
So to me this reads so alien that people fail to learn new tricks within .NET world. For me it's like a stream of amazement: Ohh, this is so much better with new language features. Ohh, this code is so much more clean. Woa, logging is so simple with ILogger and I can plug whatever underlying log engine I want! Configuration via JSON files, niice. I can override with Env variables out of the box? Amazing. This all follows particular rules and patterns. Ohh, I can customize the way I read configuration any way I want if I need it so. Ohh, I can build and run from CLI using simple commands! Ohh, I can package in docker and run on Linux. Oh, wow, .csproj is so much more clean, gotta use SDK-style project for my .NET Framework projects too!
I love it! And yeah .NET Framework is still critical for some workloads, most notably C++/CLI and WCF for certain apps where deep win32 APIs make their net8.0+ alternatives too much of a headache :)
To temper my comment, the resistance I faced as the new guy brought in to modernize is natural for these engineers who knew their tools and systems well, in their defense. Eventually they warmed up from full pushback to friendly banter “Mr. Linux and command line over here” and accepted that running my little scripts helped address the confusion/frustration of Visual Studio disagreeing with Jenkins/GitHub Actions automations and runtime behavior in Kubernetes.
Funny... I actually kind of hate ILogger... at least the output implementations I've seen. I really like line-delimited JSON for standard logging with a pretty-printed version for local dev. With say a node project, I will usually attach a few bits of context as well as a details object with the simple log message... this is easy enough to ship to another system, or say with AWS, the built in logging platform handles it brilliantly.
I haven't seen a good logger implementation for .Net that does a similar good job without a bunch of byzantine configurations.
Name me global, redundant systems that have not (yet) failed.
And if you used cloudflare to protect against botnet and now go off cloudflare... you are vulnerable and may experience more downtime if you cannot swallow the traffic.
I mean no service have 100% uptime - just that some have more nines than others.
As yourself more the question, is your service that important to need 99.999% uptime? Because i get the impression that people are so fixated on this uptime concept, that the idea of being down for a few hours is the most horrible issue in the world. To the point that they rather hand over control of their own system to a 3th party, then accept a downtime.
The fact that cloudflare can literally ready every bit of communication (as it sits between the client and your server) is already plenty bad. And yet, we accept this more easily, then a bit of downtime. We shall not ask about the prices for that service ;)
To me its nothing more then the whole "everybody on the cloud" issue, when most do not need the resource that cloud companies like AWS provide (and the bill), and yet, get totally tied down to this one service.
Not when you start pushing into the TB's range of monthly data... When you get that dreaded phone call from a CF rep, because the bill that is coming is no joke.
Its free as long as you really are small, not worth milking. The moment you can afford to run your own mini dc at your office, you start to enter the "well, hello there" for CF.
> The moment you can afford to run your own mini dc at your office, you start to enter the "well, hello there" for CF.
As someone who has (and is) runs (running) a DC with all the electrical/UPS, cooling, piping, HVAC+D stuff to deal with: it can be a lot of just time/overhead.
Especially if you don't have a number of folks in-house to deal with all that 'non-IT' equipment (I'm a bit strange in that I have an interest in both IT and HVAC-y stuff).
> There are many self-hosted alternatives to protect against botnet.
What would some good examples of those be? I think something like Anubis is mostly against bot scraping, not sure how you'd mitigate a DDoS attack well with self-hosted infra if you don't have a lot of resources?
On that note, what would be a good self-hosted WAF? I recall using mod_security with Apache and the OWASP ruleset, apparently the Nginx version worked a bit slower (e.g. https://www.litespeedtech.com/benchmarks/modsecurity-apache-... ), there was also the Coraza project but I haven't heard much about it https://coraza.io/ or maybe the people who say that running a WAF isn't strictly necessary also have a point (depending on the particular attack surface).
There is haproxy-protection, which I believe is the basis of Kiwiflare. Clients making new connections have to solve a proof-of-work challenge that take about 3 seconds of compute time.
Well if you self host DDoS protection service, that would be VERY expensive. You would need rent rack space along with a very fast internet connection at multiple data centers to host this service.
If you're buying transit, you'll have a hard time getting away with less than 10% commit, i.e. you'll have to pay for 10 Gbps of transit to have a 100 Gbps port, which will typically run into 4 digits USD / month. You'll need a few hundred Gbps of network and scrubbing capacity to handle common DDoS attacks using amplification from script kids with a 10 Gbps uplink server that allow spoofing, and probably on the order of 50+ Tbps to handle Aisuru.
If you're just renting servers instead, you have a few options that are effectively closer to a 1% commit, but better have a plan B for when your upstreams drop you if the incoming attack traffic starts disrupting other customers - see Neoprotect having to shut down their service last month.
We had better uptime with AWS WAF in us-east-1 than we've had in the last 1.5 years of Cloudflare.
I do like the flat cost of Cloudflare and feature set better but they have quite a few outages compared to other large vendors--especially with Access (their zero trust product)
I'd lump them into GitHub levels of reliability
We had a comparable but slightly higher quote from an Akamai VAR.
But at the same time, what value do they add if they:
* Took down the the customers sites due to their bug.
* Never protected against an attack that our infra could not have handled by itself.
* Don't think that they will be able to handle the "next big ddos" attack.
It's just an extra layer of complexity for us. I'm sure there are attacks that could help our customers with, that's why we're using them in the first place. But until the customers are hit with multiple ddos attacks that we can not handle ourself then it's just not worth it.
> • Took down the the customers sites due to their bug.
That is always a risk with using a 3rd party service, or even adding extra locally managed moving parts. We use them in DayJob, and despite this huge issue and the number of much smaller ones we've experienced over the last few years their reliability has been pretty darn good (at least as good as the Azure infrastructure we have their services sat in front of).
> • Never protected against an attack that our infra could not have handled by itself.
But what about the next one… Obviously this is a question sensitive to many factors in our risk profiles and attitudes to that risk, there is no one right answer to the “but is it worth it?” question here.
On a slightly facetious point: if something malicious does happen to your infrastructure, that it does not cope well with, you won't have the “everyone else is down too” shield :) [only slightly facetious because while some of our clients are asking for a full report including justification for continued use of CF and any other 3rd parties, which is their right both morally and as written in our contracts, most, especially those who had locally managed services affected, have taken the “yeah, half our other stuff was affected to, what can you do?” viewpoint].
> • Don't think that they will be able to handle the "next big ddos" attack.
It is a war of attrition. At some point a new technique, or just a new botnet significantly larger than those seen before, will come along that they might not be able to deflect quickly. I'd be concerned if they were conceited enough not to be concerned about that possibility. Any new player is likely to practise on smaller targets first before directly attacking CF (in fact I assume that it is rather rare that CF is attacked directly) or a large enough segment of their clients to cause them specific issues. Could your infrastructure do any better if you happen to be chosen as one of those earlier targets?
Again, I don't know your risk profile so can say which is the right answer, if there even is an easy one other than “not thinking about it at all” being a truly wrong answer. Also DDoS protection is not the only service many use CF for, so those need to be considered too if you aren't using them for that one thing.
I want in Text to speech (TTS) engines, transliteration/translation and... routing tickets to correct teams/persons would also be awesome :) (Classification where mistakes can easily be corrected)
Anyways, we used TTS engine before openai - it was AI based. It HAD to be AI based as even for a niche language some people couldn't tell it was a computer. Well from some phrases you can tell it, but it is very high quality and correctly knows on which parts of the word to put emphasis on.
Automatic captions has been transformative, in terms of accessibility, and seems to be something people universally want. Most people don't think of it as AI though, even when it is LLM software creating the captions. There are many more ways that AI tools could be embedded "invisibly" into our day-to-day lives, and I expect they will be.
To be clear, it's not LLMs creating the captions. Whisper[0], one of the best of its kind currently, is a speech recognition model, not a large language model. It's trained on audio, not text, and it can run on your mobile phone.
It's still AI, of course. But there is distinction between it and an LLM.
It’s an encoder-decoder transformer trained on audio (language?) and transcription.
Seems kinda weird for it not to meet the definition in a tautological way even if it’s not the typical sense or doesn’t tend to be used for autoregressive token generation?
Whisper is an encoder decoder transformer. The input is audio spectrograms, the output is text tokens. It is an improvement over old school transcription methods because it’s trained on audio transcripts, so it makes contextually plausible predictions.
Idk what the definition of an LLM is but it’s indisputable that the technology behind whisper is a close cousin to text decoders like gpt. Imo the more important question is how these things are used in the UX. Decoders don’t have to be annoying, that is a product choice.
Do you have an example of a good implementation of ai captions? I've only experienced those on youtube, and they are really bad. The automatic dubbing is even worse, but still.
On second thought this probably depends on the caption language.
I'm not going to defend the youtube captions as good, but even still, I find them incredibly helpful. My hearing is fine, but my processing is rubbish, and having a visual aid to help contextualize the sound is a big help, even when they're a bit wrong.
Your point about the caption language is probably right though. It's worse with jargon or proper names, and worse with non-American English speakers. If we they don't even get right all the common accents of English, I have little hope for other languages.
Automatic translation famously fails catastrophically with Japanese, because it's a language that heavily depends on implied rather than explicit context.
The minimal grammatically correct sentence is simply a verb, and it's an exercise to the reader to know what the subject and object are expected to be. (Essentially, the more formal/polite you get, the more things are added. You could say "kore wa atsu desu" to mean "this is hot." But you could also just say "atsu," which could also be interpreted as a question instead of a statement.)
Chinese seems to have similar issues, but I know less about how it's structured.
Anyway, it's really nice when Japanese music on YouTube includes a human-provided translation as captions. Automated ones are useless, when it doesn't give up entirely.
I assume people talk about transcription, not translation. Translation in youtube ime is indeed horrible in all languages I have tried, but transcription in english is good enough to be useful. However, the more technical jargon a video uses, the worse transcription is (translation is totally useless in anything technical there).
Automatic transcription in English heavily depend on accent, sound quality, and how well the speaker is articulating. It will often mistake words that sound alike to make non-sensible sentences, randomly skip words, or just inserts random words for no clear reason.
It does seem to do a few clever things. For lyrics it seem to first look for existing transcribed lyrics before making their own guesses (Timing however can be quite bad when it does this). Outside of that, AI transcribed videos is like an alien who has read a book on a dead language and is transcribing based on what the book say that the word should sound like phonetically. At times that can be good enough.
(A note on sound quality. It not the perceived quality. Many low res videos has perfectly acceptable, if somewhat lossy sound quality, but the transcriber goes insane. It likes prefer 1080p videos with what I assume much higher bit-rate for the sound.)
In the times I have noticed the transcription be bad, my speech comprehension itself is even worse. So I still find it useful. It is not substitution for human created (or at least curated) subtitles by any means, but better than nothing.
Do you have an example? YT captions being useless is a common trope I keep seeing on reddit that is not reflected in my experience at all. Feels like another "omg so bad" hyperbole that people just dogpile on, but would love to be proven wrong.
There are projects that will run Whisper or another transcription service locally on your computer, which has great quality. For whatever reason, Google chooses not to use their highest quality transcription models on YouTube, maybe due to cost.
I use Whisper running locally for automated transcription of many hours of audio on a daily basis.
For the most part, Whisper does much better than stuff I've tried in the past like Vosk. That said, it makes a somewhat annoying error that I never really experienced with others.
When the audio is low quality for a moment, it might misinterpret a word. That's fine, any speech recognition system will do that. The problem with Whisper is that the misinterpreted word can affect the next word, or several words. It's trying to align the next bits of audio syntactically with the mistaken word.
Older systems, you'd get a nonsense word where the noise was but the rest of the transcription would be unaffected. With Whisper, you may get a series of words that completely diverges from the audio. I can look at the start of the divergence and recognize the phonetic similarity that created the initial error. The following words may not be phonetically close to the audio at all.
Ah yes, one of the standard replies whenever anyone mentions a way that an AI thing fails: "You're still using [X]? Well of course, that's not state of the art, you should be using [Y]."
You don't actually state whether you believe Parakeet is susceptible to the same class of mistakes...
It's an extremely common goalpost-moving pattern on HN, and it adds little to the conversation without actually addressing how or whether the outcome would be better.
Try it, or don't. Due to the nature of generative AI, what might be an issue for me might not be an issue for you, especially if we have differing use cases, so no one can give you the answer you seek except for yourself.
I doubt that people prefer automatic capitations over human made, no more than people prefer AI subtitles. The big AI subtitle controversy going on right now in anime demonstrate well that quite a lot is lost in translation when an AI is guessing what words are most likely in a situation, compared to a human making a translation.
What people want is something that is better than nothing, and in that sense I can see how automatic captions is transformative in terms of accessibility.
ML has been around for ages. Email spam filters are one of the oldest examples.
These days when the term "AI" is thrown around the person is usually talking about large language models, or generative adversarial neural networks for things like image generation etc.
Classification is a wonderful application of ML that long predates LLMs. And LLMs have their purpose and niche too, don't get me wrong. I use them all the time. But AI right now is a complete hype train with companies trying to shove LLMs into absolutely anything and everything. Although I use LLMs, I have zero interest in an "AI PC" or an "AI Web Browser" any more than I have a need for an AI toaster oven. Thank god companies have finally gotten the message about "smart appliances." I wish "dumb televisions" were more common, but for a while it was looking like you couldn't buy a freakin' dishwasher that didn't have WIFI and an app and a bunch of other complexity-adding "features" that are neither required or desired by most customers.
> a. Data Collection. The software may collect information about you and your use of the software, and send that to Microsoft. Microsoft may use this information to provide services and improve our products and services. You may opt-out of many of these scenarios, but not all, as described in the software documentation. There are also some features in the software that may enable you and Microsoft to collect data from users of your applications. If you use these features, you must comply with applicable law, including providing appropriate notices to users of your applications together with a copy of Microsoft�s privacy statement. Our privacy statement is located at https://aka.ms/privacy. You can learn more about data collection and its use in the software documentation and our privacy statement. Your use of the software operates as your consent to these practices.
> You may not work around any technical limitations in the software:
> * reverse engineer, decompile or disassemble the software, or otherwise to derive the source code for the software, except and only to the extent required by third party licensing terms governing use of certain open-source components that may be included with the software;
> ...
> * share, publish, rent, or lease the software; or
> * provide the software as a stand-alone offering or combine it with any of your applications for others to use, or transfer the software or this agreement to any third party.
So you are not, for example, allowed to ship this in your application's docker image, you are in fact not allowed to redistribute it at all. So if you wanted to get a .NET debugger into your staging environment, you are not actually allowed to, unless you directly install it then-and-there with nuget. (I'm assuming we're talking about any type of enterprise context, where any given application is touched by contractors or employees from n>1 legal entities, so you are always distributing/sharing/transferring/making available).
Ya ya, I know you shouldn't have debuggers near prod, chiseled images, living off the land, yaddayadda. Regardless, it's needed or at least the easiest way at times, to actually be able to debug an application in staging or similar scenarios.
Also I'm not sure if e.g. blocking outgoing connections of the telemetry (even if by blanket policy) would already technically violate the license.
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