antirez

It is months that I find subtle bugs far more complicated than the most immediately findable issues in the report. Together with the rest of the world. So there must be something wrong with their AI usage.

Imagine asking for a review before checking with the brutally powerful agents we have today all the low hanging fruits. And, at the point we are, you can likely go at incredible levels of automated bugs seeking and do the whole test in house.

"Why you bother about local AI? LOL with the $ you spend for <insert hardware here> you can buy 5 years of 20x account". Yeah. 5 years where you are told what you can do.

Thanks, I believe the hate is also linked to my AI-positiveness... Funny enough GPT 6 Astra can easily produce a TLA+ model that can be verified under very real-world system model assumptions on the safety of RedLock, which is a paradox to the arguments I see in this thread and to the AI-rage.

Redis remained useful for 10+ years because of the design choices that were made, actually. Many other systems/companies failed since the idea, back then, was that a system needed to be linearizable or could not be useful at all. So what you point as a limit of my work was one of the better things I did in my career.

I hope he didn't really say this: it is an incredibly basic take. More or less like atomic bomb is hardware, it can be controlled.

Fun fact: in the 60s Italy was after the US and UK the county with the most advanced nuclear energy plants. These days still North Italy produces key parts of nuclear reactors in other countries.

Because of masked attention in LLMs, if you put the options before the body (the email to analyze), the transformer already knows what it needs to look for, and can use more tokens to create state to address that specific task (BERT has no mask in the attention, so tokens attend also to next tokens). You could also do a few examples in the system prompt to improve calibration.

Another trick that works is to repeat the question two times: "I'm repeating the task and labels for clarity: ..."

Anthropic is incredibly good at avoiding all the useless AI risks, while not doing anything serious about the real risks (that is: uncontrolled growth). I'm as pro-AI as I think that eventually it will remove suffering from humans, and will allow us to prosper more and help us with tons of problems we created. However the problem is not job loss or minors using AI (minors are fucked because of cell phones and social networks), the problem is avoiding extinction. For this position I was accused of AI psychosis multiple times, but I'm in good company (Hinton, for instance), so I bet some comment that trivializes this issue will surely reply to this one, but at this point it is important to see what everyone really believes. Anthropic only touches the surface of AI security, consistently.

That's perfectly wrong. Since strong coding AI, people venture into huge rewrites and other big changes that automatically make sense but otherwise would not.

Sol for low level programming is consistently better, can work alone for more time, and is faster. If you think Fable is so superior, you need to work with Sol ways more.

Yes. The article says that you need to read a lot to write well. You actually need to write a lot, and to read carefully, high quality, and potentially low quantity too (to use more time to write).

This is simply not true, even if it is commonly repeated among the folks that usually don't really write. Like how reading every source code that comes handy will not turn yourself into a great programmer, to be a good writer you need to: 1. Read selected books, and re-read good books more often then reading new stuff, to understand why they are good. 2. Read, from time to time, some bad book, and understand why it is bad. 3. And obviously you need to write a lot to become good at writing. And writing, in order to improve, is writing remembering, at the same time, the vibrations of the good authors you loved, and especially making the act of choosing of every word you put in the blank page, one after the other.

We need companies able to reimagine the devices we use every day in a more sharp way.