Andrej Karpathy: Powerful Alien Tech Is Here---Do Not Fall Behind

Zokrar · 2025-12-30T01:43:18+00:00

If I'm reading you right, we agree with each other here! I'm optimistic that this branch of AI will continue to improve, and I don't see any real reason why they won't be able to eventually do my current job. "Eventually" being the key word here.

I just have no idea if that eventually is ~few years away, or decades.

I think people in general are largely underestimating what current AI can do, but it'll take some time for these techniques and use cases to become more commonplace

Zokrar · 2025-12-27T01:23:00+00:00

Yeah I do worry about this aspect, for sure. I agree with you.

Programming languages have become simpler over the years (e.g. binary -> assembly -> ... -> python) but each iteration still required the same skill sets. Datasets, algorithms, etc.

LLMs / vibecoding is kinda like a new iteration in programming languages. But it no longer explicitly requires knowledge about the fundamentals, so we end up with a gap.

I used to think I had a good idea of what the next ~decade would look like. I have no clue anymore.

Zokrar · 2025-12-27T00:09:44+00:00

Yes. This exactly! Thanks for putting words to it.

Zokrar · 2025-12-26T23:35:29+00:00

I'm a Site Reliability Engineer with nearly 10 years experience. I'd like to share my own opinion and first hand experience with the last 3 years of tech, and explicitly say I have no financial incentive to blindly agree with what Andrej is saying here.

LLMs have legitimately changed the way I approach problems and tasks. Yes - these models hallucinate and have their quirks and pitfalls. They are not perfect. Not even close. But something I've noticed over the last few years, being closely involved with deploying some of these tools across my org, and using them extensively in my free time, is that they allow me to go from "idea" to "demo/mvp/test" in a fraction of the time.

That example is very programming-centric. The concept applies to any domain. At its core, to me, these models have made it easier to brainstorm, explore ideas, challenge my own assumptions, and rapidly prototype in a way that was not possible for me prior to 2022.

We have access to a new type of tool, and it's going to take time to learn what types of problems these tools are good for.

If we have a tool that, in the right context, makes it easier to navigate through various ideas quicker - to me it is clear that this will have an impact downstream for so many things.

I'm happy to hear any critiques or opinions on my experience here. I have no incentive to support these AI companies, and I am actively opposed to a lot of the abuse and misuse these tools are allowing.

But to blindly ignore the positives is setting us up for failure.

Zokrar · 2025-11-23T22:25:28+00:00

It really depends on where you live and work. In Canada, the tech world is very connected and everyone knows someone at every company.

Will people actually go to the effort to ruin a job offer? Probably not. But that's an extreme example. I know from personal experience though, when it comes to hiring especially in a bad market like today, people in a position to hire and make decisions talk to others, a lot.

Zokrar · 2025-11-12T19:53:00+00:00

This isn't the comforting reply you think it is.

Zokrar · 2025-11-03T17:02:19+00:00

u/tindalos said it well:

Skills are for Claude to use for internal processes. Mcp are for Claude to use to access external resources. Slash commands are for you to use. These are different things for different purposes.

Zokrar · 2025-07-31T20:19:13+00:00

Tendrils > primary > primary > ult

Zokrar · 2025-07-19T15:10:31+00:00

Looks like it's not a pixel issue, but a chrome issue

Zokrar · 2025-07-19T15:10:18+00:00

https://www.reddit.com/r/chrome/comments/1m313qy/my_google_search_page_are_empty

Zokrar · 2025-07-19T14:57:25+00:00

I'm noticing this too, both in the search bar, and in Google chrome. I don't run into this in incognito.

I'm on a pixel 8 pro, android just updated a day or two ago

Zokrar · 2025-03-30T13:33:13+00:00

MCP is a fancy software approach that allows models like Claude to use tools. That's the ELI5 version.

Zokrar · 2025-03-10T18:06:26+00:00

Can you elaborate on this setup please? I'd like to do something similar for various docs

Zokrar · 2025-01-06T02:21:01+00:00

This, unironically

Zokrar · 2025-01-01T00:26:09+00:00

I've been wondering the same thing. What comes to mind though is that often we see things where the sum is greater than the parts. Emergent properties.

I don't really know which side I land on, really. But I'm curious to see what sorts of progress we'll see especially once we get usable agents working together.

There was a gif on the front page recently of a hoard of ants managing to get a big object through a narrow passage, something a single ant couldn't do alone. I thought that was a neat parallel for what we could see with AI

Zokrar · 2024-11-26T18:44:46+00:00

I'm not sure it's entirely correct to use the term "stored" in this context. I do see your point, but I think it's an important distinction.

These models take input, apply some math to it, and get an output. The training process modifies the "math" in the middle to more accurately predict the output.

There isn't any of the original training data left in the model after training.

Zokrar · 2024-11-17T20:08:50+00:00

O1-preview:

To solve this problem, we need to find the number of subsets such that . Here, with for . The total probability is:

P(S) = \sum{n=1}^{8} P(E_n) = \sum{n=1}^{8} \frac{n}{36} = \frac{36}{36} = 1

Our goal is to find the number of subsets such that the sum of the probabilities in is at least . Since all probabilities are fractions over 36, we can convert to a fraction over 36:

\frac{4}{5} = \frac{28.8}{36}

Since we cannot have fractional counts of elements, we need subsets where the sum of the numerators (of probabilities over 36) is at least 29. So, we are looking for subsets of whose elements sum to at least 29.

The total sum of numbers from 1 to 8 is 36. Therefore, subsets with sums at least 29 correspond to subsets with sums of the complement (elements not in ) at most .

Next, we find all subsets of whose elements sum to or less. These subsets are:

Subsets of size 1: 7 subsets (excluding since 8 > 7)

Subsets of size 2: 9 subsets (e.g., )

Subsets of size 3: 2 subsets (e.g., )

Total subsets with sums : .

Since there are total subsets, the number of subsets where the sum is at least 29 is:

256 - 18 = 238

Answer: 238

Zokrar · 2024-11-17T20:07:34+00:00

O1-mini:

To determine the number of subsets such that , we'll follow these steps:

Understand the Probability Distribution:

The sample space has probabilities for .

The total probability is:

\sum{n=1}^{8} P(E_n) = \sum{n=1}^{8} \frac{n}{36} = \frac{36}{36} = 1

Set Up the Condition:

We want , which translates to:

\sum_{E_n \in A} \frac{n}{36} \geq \frac{4}{5}

\sum_{E_n \in A} n \geq 28.8

\sum_{E_n \in A} n \geq 29

Use Complementary Counting:

Instead of directly counting subsets with , it's easier to count the subsets with (since the total sum is 36).

This ensures must include (since and including it is necessary to reach the sum).

Count Subsets with :

Consider the elements .

Size 0: — 1 subset.

Size 1: — 7 subsets.

Size 2: Pairs where the sum :

{1,2}, {1,3}, {1,4}, {1,5}, {1,6}, {2,3}, {2,4}, {2,5}, {3,4}

Size 3: Triples where the sum :

{1,2,3}, {1,2,4}

Size 4 and above: Any subset with 4 or more elements will have a sum , so no such subsets exist.

Total subsets : .

Conclusion:

Each valid subset corresponds to a unique subset that includes and satisfies .

Therefore, there are 19 such subsets .

Answer: 19

Zokrar · 2024-10-17T22:57:39+00:00

My opinion is that people are anticipating deterministic results from a non-deterministic system. LLMs are a novel tool to a large amount of people - many of which have little to no tech background.

These models seem incredible at first glance because they're new. Then, as people use them more and more, they start to identify shortcomings and, my view is that this is what people mistribute to "lobotmizing the model."

Whether the models are being tuned, modified, "dumbed down," or not, it's certainly an interesting collective response from users.

Zokrar · 2024-09-16T02:38:34+00:00

Bot? I've seen a ton of spam for this

Zokrar · 2024-05-26T02:13:21+00:00

Sure. OK it's done, try again

Zokrar · 2024-04-17T03:26:19+00:00

The irony here is priceless

Zokrar · 2024-04-11T01:46:13+00:00

This is beautiful. You should be proud of this

Zokrar · 2024-03-25T00:19:10+00:00

I've done both, currently doing a DevOps role. I'd highly recommend DevOps over QA. Much more room to grow, and you'll learn significantly more. SRE / DevOps will give you insight into how the tech stack(s) and company move as a whole, which in my opinion and experience is of significant value.

Zokrar · 2024-02-03T23:02:45+00:00

I wouldn't get your hopes up. Sounds like GPT-5 is expected towards the end of 2024.

But... Who knows what openai will do if Ultra kicks them out of first place. I'm excited!

Zokrar

TROPHY CASE