Being able to point a camera at something and have AI tell me “that’s a red bicycle” is a cool novelty the first few times, but I already knew that information just by looking at it.

Visual search is already useful. People go through the effort of posting requests to social media or forums asking “what is this thing” or “help me ID these shoes and where I can buy them” or “what kind of spider is this” all the time. They’re not searching for red bicycles, they’re taking pictures of a specific Bianchi model and asking what year it was manufactured. Automating the process and improving the reliability/accuracy of that search will improve day to day life.

And I have strong reservations about the fundamental issues of inference engines being used to generate things (LLMs and diffusers and things like that), but image recognition, speech to text, and translation are areas where these tools excel today.

The eyebrow raiser in the Slate’s base configuration is that it doesn’t come with any audio systems: no radio antenna/tuner, no speakers. It remains to be seen how upgradeable the base configuration is for audio, how involved of a task it will be to install speakers in the dash or doors, installing antennas (especially for AM, which are tricky for interference from EV systems), etc.

I’d imagine that most people would choose to spend few thousand on that audio upgrade up to the bare minimum expectations one would have for a new vehicle, so that cuts into the affordability of the package.

The analog dials were an illusion. That information has been processed digitally for at least the last 25 years.

What I’m saying is if YouTube is sharing $10 million of revenue with channel owners in a month that has 1,000,000,000 total views across YouTube, that’s a penny per view.

Then, if the next month the reconfigure the view counts to exclude certain bots or views under a particular number, you might see the overall view count drop from 1,000,000,000 to 500,000,000, while still hitting the same overall revenue. At that point, it’s $0.02 per view, so a channel that sees their view count drop in half may still see the same revenue despite the drop in view count.

If it’s a methodology change across all of YouTube, a channel that stays equally popular as a percentage of all views will see the revenue stay the same, even if the view counts drop (because every other channel is seeing their view counts drop, too).

Isn’t that the formula? They take all of the revenue, set aside the percentage they’ve set for revenue share, and then divide that among all channels based on viewer counts. Dropping viewership for all channels proportionally means that the same amount of revenue will still be distributed to the channels in the previous ratios.

Most 4k streams are 8-20 Mbps. A UHD runs at 128 Mbps.

Bitrate is only one variable in overall perceived quality. There are all sorts of tricks that can significantly reduce file size (and thus bitrate of a stream) without a perceptible loss of quality. And somewhat counterintuitively, the compression tricks work a lot better on higher resolution source video, which is why each quadrupling in pixels (doubling height and width) doesn’t quadruple file size.

The codec matters (h.264 vs h.265/HEVC vs VP9 vs AV1), and so do the settings actually used to encode. Netflix famously is willing to spend a lot more computational power on encoding, because they have a relatively small number of videos and many, many users watching the same videos. In contrast, YouTube and Facebook don’t even bother re-encoding into a more efficient codec like AV1 until a video gets enough views that they think they can make up the cost of additional processing with the savings of lower bandwidth.

Video encoding is a very complex topic, and simple bitrate comparisons only barely scratch the surface in perceived quality.

Article is paywalled for me.

Does it describe the methodology of how they use the transmitter and receiver?

What specifically are they transmitting? Is it actually wifi signals within the 802.11 protocols, or is “wifi” just shorthand for emitting radio waves in the same spectrum bands as wifi?

Yeah I’m with you.

“Using this technological advancement to improve health care is good”

“Not in countries where health care is publicly run”

“What” is the correct response here.

“The only difference between the two emails was the link,” the memo said. “ActBlue delivered. WinRed got flagged. That is not a coincidence.”

It could also be that winred is more often associated with spam because emails with winred links use a style more associated with other actual spam. Like if spammers use words like Trump a lot to try to scam victims, and a lot of those emails get flagged as spam, then the word Trump itself becomes more highly correlated with spam. And since the word Trump is highly associated with winred links, maybe winred gets caught up in the rule set/heuristics that associate Trump fundraisers with spam.

You were talking about $1.34 in damages, which doesn’t sound like downtime or disruption.

you will get prison for DDoS in USA

Who said anything about DDoS? I’m using ad blockers and saving/caching/archiving websites with a single computer, and not causing damage. I’m just using the website in a way the owner doesn’t like. That’s not a crime, nor should it be.

Thats a crime yeah and if Alphabet co wants to sue you for $1.34 damages then they have that right

So yeah, I stand by my statement that anyone thinks this is a crime, or should be a crime, has a poor understanding of either the technology or the law. In this case, even mentioning Alphabet suing for damages means that you don’t know the difference between criminal law and civil law.

press charges for the criminal act of intentional disruption of services

That’s not a crime, and again reveals gaps in your knowledge on this topic.

No, but it is a starting point for passing some kind of sanity check. Someone who was making $81k in 1990 was making an exceedingly high salary in the general population, and computer-related professions weren’t exactly known for high salaries until maybe the 2000’s.

[This report] (https://www.bls.gov/ocs/publications/pdf/white-collar-pay-private-goods-producing-industries-march-1990.pdf) has government statistics showing that in March 1990, entry level programmers were making on average about $27k. Senior programmers were making about $34k. Systems analysts (which I understand to have primarily been mainframe programmers in 1990) were making low 30s at the entry level and high 60s at the most senior level. Going up the management track, only the fourth and highest level was making above $80k, and it seems to me that those are going to be high level executives.

So yeah, $81k is a very senior level in the 1990s tech industry, probably significantly less common than today’s $200k tech jobs.

I was a dual major Electrical Engineering/Philosophy. The rigorous logic in some branches of philosophy was very helpful for programming principles. And the the philosophy of mathematics and philosophy of mind has overlaps with and supplements modern AI theory pretty well.

I’m out of the tech world now but if I were hiring entry level software developers, I’d consider a philosophy degree to be a plus, at least for people who have the threshold competency in actual programming.

You have to expect that OP, who is well established in his field, to compare accordingly, not with average pay of 1990.

I’m talking about a number that is 1.4x the 95th percentile generally. It’d be weird to assume that programmers were getting paid that much more than doctors and lawyers and bankers.

According to this survey series, median IEEE members were making about $58k (which was also the average for 35-year-olds in the survey. Electrical engineering is a closely related discipline to programming.

So yeah, an $81k salary was really, really high in 1990. I suspect the original comment was thinking of the 90’s in general, and chose a salary from later in the decade while running the inflation numbers back to 1990, using the wrong conversion factor for inflation.

Edited to add: this Bureau of Labor Statistics publication summarizes salaries by several professions and experience levels as of March 1990. The most senior programmers were making around $34k, the most senior systems analysts were making about $69k, and the most senior managers, who could fairly be described as executives, were making about $88k.

I’m gonna continue to use ad blockers and yt-dlp, and if you think I’m a criminal for doing so, I’m gonna say you don’t understand either technology or criminal law.

Who is making $165k out of college?

Computer science and engineering grads at the top of their class at top schools who choose not to go to grad school. This thread claims to cite Department of Education data to show median salaries 3 years after graduation, and some of them are higher than $165k. Sure, that’s 3 years out, but it’s also median, so one would expect 75th or 90th percentile number to be higher.

Anecdotally, I know people from Stanford/MIT who did get their first jobs in the Bay Area for more than $150k more than 10 years ago, so it was definitely possible.

But this NYT article has stories about graduates from Purdue, Oregon State, and Georgetown which are good schools but also generally weren’t the schools producing many graduates landing in those $150k jobs as that very top tier. I would assume the kids graduating from Cal Tech, MIT, Stanford, and UC Berkeley are still doing well. But the middle is getting left behind.

Were people getting paid $81k in 1990? This site shows that 95th percentile in 1990 was $58k, and doesn’t have more granular data than that above the 95th percentile. So someone making $81k was definitely a 5 percenter, maybe even a 2 percenter.

to decide for what purpose it gets used for

Yeah, fuck everything about that. If I’m a site visitor I should be able to do what I want with the data you send me. If I bypass your ads, or use your words to write a newspaper article that you don’t like, tough shit. Publishing information is choosing not to control what happens to the information after it leaves your control.

Don’t like it? Make me sign an NDA. And even then, violating an NDA isn’t a crime, much less a felony punishable by years of prison time.

Interpreting the CFAA to cover scraping is absurd and draconian.

What counts as an algorithm? Surely it can’t be the actual definition of algorithm.

Because in most forum software (even the older stuff that predates reddit or social media) if I just click on a username, that fetches from the database every comment that the user has ever made, usually sorted in reverse chronological order. That technically fits the definition of an algorithm, and presents that user’s authored content in a manner that correlates the comments with the same user, regardless of where it originally appeared (in specific threads).

So if it generates a webpage that shows the person once made a comment in a cooking subreddit that says “I’m a Muslim and I love the halal version” next to a comment posted to a college admissions subreddit that says “I graduated from Harvard in 2019” next to a comment posted to a gardening subreddit that says “I live in Berlin,” does reddit violate the GDPR by assembling this information all in one place?