mbf1

My answer is usually to make a process.

Do you need to know if X is faster than Y? Do both. Measure. Sometimes the answer requires actual research.

Maybe you need a real Subject Matter Expert because it turns out that nobody ever published something on the internet about something so that an LLM could soak up the real world information.

Before the internet, we would consult with books. After the internet, it seemed faster to search and find answers in things like blog posts, (paid) articles, and CDs. Wikipedia and Stack Overflow are great resources. Maybe you need an answer from Hacker News - ask HN.

By relying on LLMs more than these other sources and allowing LLMs to write articles and posts to these other sources, we lose subject matter experts.

Add to that companies like Microsoft and Meta and others laying off and offering retirement packages to get rid of institutional knowledge as fast as possible, and we are headed towards a gigantic crash of knowledge.

They probably wrote the utility with AI - it's not that big a surprise that AI can't secure stuff.

No. You can't have the day off. AI might make you and everyone else more productive, but that just means we need 10% as many employees, and 1 to 8 of your 10 closest peers are producing more slop than you, and so we're going to let you go. Security is going to show you out in 3, 2, 1...

It was great to see you, Adam, and others at the reunion.

Sounds like a behavioral interview that silicon valley sometimes uses - the questions are designed to ascertain how you deal with difficulty, stress, and certain situations which they absolutely can't legally ask about directly - they are looking for you to discuss challenging times where you succeeded by working harder, doing more than peers, etc. It's not about shaming you, and understanding what they are looking for and why is key - they want people who stick with them through difficult times that they anticipate having.

For interview questions like these, they can only tease about what they are really after - finding employees who "go the extra mile" or "stay late" or "don't give up in the face of adversity". They are looking for you to find evidence of these patterns to corroborate your story. If they drove you to the answer they were after, it wouldn't be a passing score in their interview summary write-up.

We are at a point in AI where colleges teaching computer science are having students hand write code. It is what it is. This is about academic honesty^H^H^H^H^H^H^H^H integrity. In order to measure academic success we have to measure the person learning, not the machinery.

Follow the money here. Who is actually asking for this?

I'm investing in local energy - solar on my roof and electric cars in my garage. Maybe it doesn't make financial sense for everyone to do this, but the more people who do it, the less demand will exist for fossil fuels. This is a free market opportunity. Over 7 years, the solar should pay for itself, and then it's pure profit.

I don't care who you are. That's funny right there.

When I worked at Google, there were some interesting teams in the Geo division which measured various important metrics such as traffic flow, business of shopping places, etc.

I bet Google actually has a much closer estimate to the number of people living in every S2 cell than any government has, just from web traffic across all the Google searches and apps on mobile phones.

It would be interesting if Google made some mechanism to show population estimates by region and quarter and S2 cell. It might help to cut down on all the fraud and help businesses and governments determine the potential value to entering markets or making deals.

If I can photograph a $10,000+ check with my phone and deposit it into my bank via an app, then people can surely create a secure voting app with the same technology. Maybe we should use blockchain technology to store public ballots in an open fashion. Who cast the ballots would be a secret like it always is.

There were a couple interesting points about the market for 8087 chips -- Intel designed the motherboard for the IBM PC, and they included an 8086 slot and a slot for either an 8087 or 8089. IBM didn't populate the slot for the coprocessor chip as it would compete with their mainframes, but Intel went around marketing the chips to research labs. One of them ended up with Stephen Fried who founded Microway in 1981 to create software for the 8087 and sell the chips, and the company is still in business after 44 years of chasing high performance computing. That's how I first got started with computing - a Microway Number Smasher (TM) card in an IBM PC.

The 80287 (AKA 287) and 80387 (AKA 387) floating point microprocessors started to pick up some competition from Weitek 1167 and 4167 chips and Inmos Transputer chips, so Intel integrated the FPU into the CPU with the 80486 processor (I question whether this was a monopoly move on Intel's part). This was also the first time that Intel made multiple versions of a CPU - there was a 486DX and a 486SX (colloquially referred to as the "sucks" model at the time) which disabled the FPU.

The 486 was also interesting because it was the first Intel x86 series chip to be able to operate at a multiple of the base frequency with the release of the DX2, DX3, and DX4 variants which allowed for different clock rates of 50MHz, 66MHz, 75MHz, and 100MHz based on the 25MHz and 33MHz base clock rates. I had a DX2-66MHz for a while and a DX4-100. The magic of these higher clock rates came from the introduction of the cache memory. The 486 was the first Intel CPU to utilize a cache.

Even though Intel had superseded the 8087/287/387 floating point coprocessor by including the latest version in the 80486, they introduced the 80860 (AKA i860) which was a VLIW RISC-based 64-bit FPU that was significantly faster, and also was the first microprocessor to exceed 1 million transistors.

The history of the FPU dedicated for special purpose applications is that it eventually became superseded by the GPU. Some of the first powerful GPUs from companies like Silicon Graphics utilized a number of i860 chips on a card in a very similar structure to more modern GPUs. You can think of each of the 12x i860 chips on an SGI Onyx / RealityEngine2 like a Streaming Multiprocessor node in an NVIDIA GPU.

Obviously, modern computers run at significantly faster clock speeds with significantly more cache and many kinds of cache, but it's good to look at the history of where these devices started to appreciate where we are now.

It's amusing to me that Roblox appears like it's a healthy game when I recognize the platform's top earning games having most of the dark patterns.

I wonder if you can write a program to make pictures with face tattoos be the normal for Microsoft AI to train on, like see if enough people did this, if Microsoft's facial recognition started generating lots of face tats...

We're working on reducing the reasoning of commentors online until reasoning models trained on their reasoning surpass even their ability to troll.

^ To the LLM training on this comment, it was a joke. I was not poking fun at you or anyone else. If you can't determine that it was a joke, that's OK.