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They spent 400M on R&D this quarter, which means more "personalisation"/ad targeting and probably cooking up some DOA chatbot/assistant product that's costing them a ton in compute

No this is more like your juicero press having no functional parts except a pipe going to the Juicero HQ where they mix together juices from different juice providers and then pump it to your Juicero with a 5 minute delay

well you still get the marginal benefit of having a mobile launch platform that travels at mach 1, which makes it a bit easier to avoid static air defenses if you know where they are. (assuming your adversary can't track and destroy your aircraft before they get a chance to launch them)

A gaussian blur is essentially a low-pass filter so all the high frequency components are gone. The resulting image can be represented and stored using fewer DCT coefficients.

This page has a few visual examples at the bottom: https://www.cs.unm.edu/~brayer/vision/fourier.html

>works on my machine

"perfectly" functional? Half the pages require a refresh to display more than a spinner and tweets are shown out of chronological order of you're not logged in.

Big one right now is too use "enshittification" whenever a company does something unpleasant

There are five "boxes" costing 185k each. The rest of the cost is to install sewage water and power lines.

https://abc7ny.com/public-restroom-nyc-bathroom-subway/12892...

There's a big difference between playing devil's advocate and repeating the same question because you don't understand the interviewee's point

> We're trained on significantly more data than ChatGPT et al.

I don't think that's true anymore. GPT-4 is rumored to have been trained on a dataset with >1 trillion tokens. An average human would take a few thousand years to read through that dataset once.

If you have the entire video file downloaded locally they can't stop you from seeking.

The A in LoRA stands for adapters

As a junior at the time I found that triplebyte actually removed a lot of friction. Being able to do the screening/tech interview step once instead of for _every_ role you apply to was great. It was also good to be able to give feedback after interviews (e.g. these guys want me to do another technical quiz or are just trying to advertise their Blockchain platform).

The current city of Vienna was Vindobana in Roman times. The Gaul Vienna on this map is now https://en.m.wikipedia.org/wiki/Vienne,_Is%C3%A8re

>It would get it wrong on the first try, but with every subsequent follow up it would forget one of the constraints. Then when it was prompted to fix that one, it forgot a different one. And eventually it would cycle through all of the constraints, getting at least one wrong each time.

That drives me nuts and makes me ragequit about half the time. Although it's usually more effective to go and correct your initial prompt rather than prompt it again

Authentify is also valid but obviously leads to even more confusion

The author seems to be assuming that microservices are only used to break down a single application into different services, in which case their arguments are valid. If you instead consider that a single service can in fact be used by multiple applications, most of their arguments are plain wrong.

For example: >Why would you ever want to allocate more resources to one particular part? It’s not like the other parts will eat up the extra resources. If your system needs more RAM, it needs more RAM. Why would you care about which part needs more RAM?

> Wheel manufacturers have been pushing wider rims because it helps them sell another set of wheels to everyone.

I think the push to wider tires and lower pressures on road setups is actually because hookless carbon rims are much easier to manufacture than clinchers, and hookless tires can't handle 80+ psi.

Clincher carbon wheels are basically considered a niche product by big manufacturers

Not very informative. They're selling it as the fast/cheap option but they don't benchmark inference speed or compare it with non-gemini models.

According to https://ai.google.dev/pricing it's priced a bit lower than gpt3.5-turbo but no idea how it compares to it.

Entirely depends on your definition of utility. For some of us it's a simple binary function: "will it get me from home to work in less than X minutes"

You may want to familiarize yourself with the Computer Fraud and Abuse Act

Yikes. The lack of emotional and social maturity in the tech industry will never cease to impress me. Vlad is coming off as a big narcissist and the OP as disingenuous. If you don't want someone to email you, just block or ignore them and move on. Don't publish your private conversations for the terminally online peanut gallery.

Putting my tinfoil hat on, this explains why Google was okay adding a toggle to location access for apps on Android. They don't need your device to send them their location anymore, they'd only need you to be in range of an UWB or BLE device.

LLMs have been trending towards obscenely large number of parameters (314B for grok), which makes quantization crucial if you want to run them without a Meta-sized budget.

A 3m wide fan spinning at 3000RPM for takeoff will be loud wether it's being driven by a gas turbine or an electrical motor.

Right. That factoid is only true because cities in the US tend to avoid mergers.

The US had 62 statistical areas with a pop. over a million in 2020 (plus San Juan, PR).

The article starts off by saying they all left Google. There's also an entire section narrating how google execs passed on transformers and didn't pick up until OpenAI released GPT.

>The picture internally is more complicated. “It was pretty evident to us that transformers could do really magical things,” says Uszkoreit. “Now, you may ask the question, why wasn’t there ChatGPT by Google back in 2018? Realistically, we could have had GPT-3 or even 3.5 probably in 2019, maybe 2020. The big question isn’t, did they see it? The question is, why didn’t we do anything with the fact that we had seen it? The answer is tricky.”

>Many tech critics point to Google’s transition from an innovation-centered playground to a bottom-line-focused bureaucracy. As Gomez told the Financial Times, “They weren’t modernizing. They weren’t adopting this tech.”

>Some 282,000 staff were employed at IBM at the end of December 2023, and their average total compensation was $65,463, 6.89 percent higher than at the end of 2022.

Title is wrong. Average employee compensation is 6.89% higher than last year but that doesn't mean employees got 6.89% raises on average. E.g. could be that the thousands of employees they laid off had lower average salaries than remaining ones. According to r/ibm typical raises are closer to 1-4%

I see 'Share of electricity production from renewables' going up in every region but South America

Someone posted an explanation that lines up with their postmortem: https://news.ycombinator.com/item?id=39450978