windsignaling

What? I was around back then. Chrome/Chromium was awesome because we finally had something significantly better than IE.

Looking at the top comment about Google right now. Big difference between "their products/processes suck" vs. "these people and their companies and government are an insidious evil".

Ah, the ol' gaslighting you into thinking you're gaslighting me trick.

I always wonder who these weirdos are that look at commenters' past comments to try and deduce some fact and "win" their argument. More common on Reddit, but still exists here. Basement dweller-level weird either way.

"226 karma in 10 years." - What does that even mean to you? Should I be posting more? Does my behavior not align with your list accepted human behaviors for a non-Chinese?

The ridiculousness of your post shows how far the anti-China bias goes with you people.

There's a search bar at the bottom of the page.

The dishonesty here is coming from you. You're assuming something exists. I'm saying show me. If it's so easy to find, wouldn't it be way easier to simply put this definitive proof in my face instead of this weird roundabout argument you're trying to make?

AI doesn't have a business function...?

I never really understood this sentiment. Some foreign company / government cannot do anything to me. My own government, on the other hand...

There is clearly an anti-China bias here. Show me comments demonstrating the same level of distrust against Google for open-sourcing projects like Tensorflow, Kubernetes, Flutter, Chromium, etc.

How legit is this? In my experience, every time I've updated iOS due to some urgent "security issue", the result was my phone just got a whole lot slower.

I didn't realize these archive links were still working. Ever since the FBI order in November, these links have just been hanging for me. https://downforeveryoneorjustme.com/ had been saying it was down so I just thought it actually was down for everyone, but I continue to see these links posted. Is the site still working for some people?

I'm surprised no one else has commented that a few of the conceptual comments in this article are a bit odd or just wrong.

The final accuracy is 90% because 1 of the 10 observations is on the incorrect side of the decision boundary.

Who is using K-means for classification? If you have labels, then a supervised algorithm seems like a more appropriate choice.

K-means clustering is a recursive algorithm

It is?

If we know that the distributions are Gaussian, which is very frequently the case in machine learning

It is?

we can employ a more powerful algorithm: Expectation Maximization (EM)

K-means is already an instance of the EM algorithm.

On the contrary, I'm confused about why you're confused.

This is a well-known and documented phenomenon - the paradox of choice.

I've been working in machine learning and AI for nearly 20 years and the number of options out there is overwhelming.

I've found many of the tools out there do some things I want, but not others, so even finding the model or platform that does exactly what I want or does it the best is a time-consuming process.

I don't pay money for it?

Not just lately. See /r/politics. Sometime in the last 5-7 years /r/science or /r/technology (or both, I forget because I stopped reading) basically became the science/tech versions of /r/politics.

This is interesting because it shows us how a programmer thinks of a problem vs. how a psychologist or neuroscientist would think of this problem and highlights the lack of "human-ness" in programmer thinking.

I'm no fan of schools forcing STEM students to study boring electives but this is a prime example of why that might be useful.

The entire premise of the post is wrong - average pixel value has nothing to do with how orange the oranges look - it's all about perception.

Here's an example where the same exact color (pixel value) can be perceived as either light or dark depending on the context: http://brainden.com/images/identical-colors-big.jpg

That's what the bag adds - context - but the author hasn't made this connection.

I think you missed the point of that comment. I was responding to the comment saying "Parameter estimation is ML now?"

Neural networks are trained commonly using maximum likelihood estimation, a common parameter estimation technique.

I haven't installed this yet, but does it require camera access? i.e. does it "transform" your own image to the target image while maintaining facial expression, pose, etc.? Based on the animations, I'd assume it doesn't use the camera since there are techniques that can lipsync from audio.

Great course. I highly recommended anyone interested in this topic to check it out on the MIT website, taught by the same authors. They are great lecturers.

Neural networks are not ML now?

You're using the word to define the concept rather than the concept to define the word. Wrong order.

See: "Program".

After spending over a decade in both statistics and machine learning I'd say the only reason there isn't a "broad consensus" is because statisticians like to gate-keep, whether that's linear regression, Monte Carlo methods, or Kalman Filters.

Linear regression appears in pretty much every ML textbook. Can you confidently say, "this model that appears in every ML textbook is the only model in the ML textbook that isn't an ML model"?

Kalman Filters are like a continuous-state HMM. So why are HMMs considered ML and Kalman Filters not considered ML?

IMO it's an ego thing. They spent decades rigorously analyzing everything about linear models and here come these CS cowboys producing amazing results without any of the careful rigor that statisticians normally apply. It's difficult to argue against real results so the inflexible, hard-nosed statisticians just hang on to whatever they can.

Is anyone having trouble downloading their data? Some data, such as "Raw Data", "Imputed Genotype Data R6", and "Phased Genotype Data" need to be requested, but I haven't heard back from them yet.

Would like to download everything first before requesting deletion.

Don't even worry about dating / the apps.

Quite frankly this is the worst advice. As other commenters have noted if you tend to enjoy solo activities or activities that don't naturally involve the types of women you'd like to date, then it's not going to lead to you meeting anyone.

You will eventually meet a partner through these group activities

Ah, the hope and pray method. Doesn't work. And when you do meet a girl you actually like, how do you figure you'll have the social skills to carry yourself through the dating process and developing a relationship? It's just natural? No, it's not.

This also doesn't work if you want to date an abundance of women and it doesn't allow you to meet women when you choose. Ever see a cute girl at the grocery store or at a coffee shop and you wanted to ask her out but you didn't know what to say? No amount of skiing and mountain climbing is going to fix that.

but as the author admits a bit autistic

I don't know why (well, I can guess) it's such a turn-off for people to approach dating systematically. We don't criticize people for practicing math or coding, yet when it comes to social skills, if you're doing anything other than "just being yourself", it's somehow "wrong".

What I meant was, the phrase "inner workings of the processing" doesn't really mean anything at all. i.e. it doesn't convey any useful information about what you're trying to say.

How they interpret one another and respond.

That sounds like it just falls back to "how LLMs work". It's the wrong level of abstraction in this case, because it's one level down from the topic being discussed here.

I think "low-level" is relative to what's being discussed. Low-level for LLMs would have to do with how transformer layers are implemented (self-attention layer, layer norms, etc.) whereas low-level for agents would be the graph structure.

Although I personally don't think the graph implementation for agents is necessarily as established or widely standardized, it's helpful to know about why such an implementation was chosen and how it works.

the inner workings of the processing, probing agents, and getting into the weeds

These feel to me like empty words... "inner workings of the processing"? You can say that about anything.

I'm not a fan of these "gotchas" because they don't test for what we really care about.

Like counting the number of R's in strawberry, many of these are character-counting or character manipulation problems which tokenization is not well-suited for.

I'm sure an engineer could come up with a clever way to train for this, but that seems like optimizing for the wrong thing.

IMO these questions go in the wrong direction. Character permutation is a problem for "Software 1.0", not LLMs. Just as you wouldn't use an LLM to multiply 2 large numbers, you'd use a calculator.

As a website owner and VPN user I see both sides of this.

On one hand, I get the annoying "Verify" box every time I use ChatGPT (and now due its popularity, DeepSeek as well).

On the other hand, without Cloudflare I'd be seeing thousands of junk requests and hacking attempts everyday, people attempting credit card fraud, etc.

I honestly don't know what the solution is.

Always hilarious to see westerners concerned about privacy when it comes to China, yet not concerned at all about their own governments that know far more about you. Do they think some Chinese policeman is going to come to their door? Never heard of Snowden or the five eyes?

That is how most Westerners refer to things from China, or things done or made by Chinese people.

Sadly, that sort of rhetoric is usually used negatively.

If you meet someone really backwards, they'll say anything involving something remotely Asian, "Chinese".

Covered in section 6.2.1.

Still getting the same error I was (and the same error mentioned by parent commenter) when this was first posted.

I'm no fan of the diversity people pushing their beliefs down everyone's throat but this...

Your post seems to say "See? It's not so bad" but you used the tame white example, completely overlooking the "muscular black guy" and the "analytical Chinese guy"...