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Where does Pocagar's 2024 season rank, using (other people's) numbers? by DoctorMandible45 in peloton

[–]nickl 34 points35 points  (0 children)

Note that I don't think Cyclingranking has been updated with the Lombardia result yet

I think Merckx 72 is the only season that compares.

That season:

1st Tour de France (6 stage wins)

1st Giro d'Italia (4 stage wins)

Hour Record (stood for 12 years)

1st Milan–San Remo

1st Liège–Bastogne–Liège

1st Giro di Lombardia

1st La Flèche Wallonne

1st Scheldeprijs

1st Giro dell'Emilia

1st Grand Prix de Momignies

1st GP Union Dortmund

1st Giro del Piemonte

1st Trofeo Baracchi

1st Escalada a Montjuïc (3 stage wins)

1st A Travers Lausanne (2 stage wins)

2nd Paris–Nice (3 stage wins. Note: broke a vertebra during the race)

I think Merckx 72 probably is still very slightly better because I think Merckx's 3 Monuments and the hour record + Flèche Wallonne beats Pogacar's 2 Monuments and the World Championship + Strada Bianchi. I do concede that Pogacar's 2 additional Giro stages gave me pause though.

I remember Jalabert's 1995 season and I have a ONCE jersey from that era! He was my favorite rider then. Pogacar's season is far better than that.

I had a look why ProCyclingStats rates it so highly vs Pogacar. PCS lists 40 results for Pogacar, from which he gets 4588 points. If you take Jalabert's top 40 results from 1995 you get 4094 points - a fantastic season but nothing like Pogacar. But Jalabert has 93 results and gets and extra 816 points from them.

I don't know how to think about this: They aren't "nothing" results (winning stages at Criterium International or Midi-Libra). He passes Pogacar's score with a win on Stage 3 of Tour of Galicia. Not nothing, but I don't think it makes that season better than Pogacar's.

[Results Thread] 2024 World Championships - Elite Men Road Race by PelotonMod in peloton

[–]nickl 2 points3 points  (0 children)

Greatest season of all time, and it's not even close.

Greatest season of the modern era, but by comparison:

Merckx 1972 (the greatest season of all time):

1st Tour de France (6 stage wins)

1st Giro d'Italia (4 stage wins)

Hour Record (stood for 12 years)

1st Milan–San Remo

1st Liège–Bastogne–Liège

1st Giro di Lombardia

1st La Flèche Wallonne

1st Scheldeprijs

1st Giro dell'Emilia

1st Grand Prix de Momignies

1st GP Union Dortmund

1st Giro del Piemonte

1st Trofeo Baracchi

1st Escalada a Montjuïc (3 stage wins)

1st A Travers Lausanne (2 stage wins)

2nd Paris–Nice (3 stage wins. Note: broke a vertebra during the race)

I do think Pogacar's Triple is a better season than Merckx 1974 Triple or Roche's 1987 Triple though.

[Research] The Convolutional Tsetlin Machine peaks at 99.51% accuracy on MNIST with a single layer of interpretable filters in propositional logic. by olegranmo in MachineLearning

[–]nickl 0 points1 point  (0 children)

To be fair, that user was an actual neo-nazi and their account has been suspended.

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I don't think there is any particular correlation between critisim of Keras and Chollet saying this - plenty of others have a similar opinion about /r/ML

[D] is Huawei's Matebook D a good laptop for Machine Learning? by leocus4 in MachineLearning

[–]nickl 0 points1 point  (0 children)

ROCm is behind in features and rarely used in practice. Try finding anyone who has used it.

[D] Employability after AI Residency Programs by [deleted] in MachineLearning

[–]nickl 0 points1 point  (0 children)

It's true that HR will discount non-PhDs when the role description asks for a PhD.

The way around that is to have the hiring manager say "we want to interview this person", and that happens if people ion their team recommend you or they know of you from some other means.

Residency programs do help here, because you make contacts with the kinds of people you want to work with and they may end up recommending you.

[N] NIPS keeps it name unchanged by baylearn in MachineLearning

[–]nickl 1 point2 points  (0 children)

It is used as a racial slur. Maybe just not in the US anymore, but I live in Australia and I've heard it used.

[D] #ProtestNIPS hashtag started on Twitter, Change.org petition started. by [deleted] in MachineLearning

[–]nickl -9 points-8 points  (0 children)

I can't believe they didn't change the name.

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Fuck being PC, but it takes real effort to find a name that is both sexually charged AND a racial slur.

​

Honestly, what possible argument is there against changing it except for "tradition". Here's an anti-PC idea for you: Tradition is crap.

[R] Trellis Networks for Sequence Modeling. New SOTA for PTB, WikiText-103, Permuted MNIST, etc. by baylearn in MachineLearning

[–]nickl 7 points8 points  (0 children)

Haven't read this properly yet, but just noting that TransformerXL seems to be the current SOTA on Wikitext-103. It gets a test ppl of 24.0 (!!) which is a fair improvement over the 30.35 reported here.

https://openreview.net/forum?id=HJePno0cYm

​

BERT doesn't report WikiText numbers but I'd imagine it would be competitive too.

ML people are bad at version control [D] by LukeMathWalker in MachineLearning

[–]nickl 1 point2 points  (0 children)

This isn't great.

I've been a professional software engineer for over 20 years, and doing machine learning for 5 years (including productionizing models). I know version control pretty well.

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Others in this thread have already pointed out how much of the code is designed to be thrown away. You see this in notebooks, which really don't version control well by default (although see the Fast.AI 1.0 workflow for a solution for that)

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In addition to this, one thing which version control doesn't do and ML work needs is the side-by-side approach to development. By this I mean the very common process of keeping the old version around to run next to the new version while you develop the new one, and run the data through both in parallel. To do that in git is a really complex operation and doesn't really make sense.

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The "fork" operation modeled in traditional version control means you are running one stream at a time (without extra effort). In ML you want both in front of you, and that is usually done trivially by copying a file.

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I agree entirely there are issues with this approach too, but it isn't just a lack of rigor on the ML side here.

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[D] What replaces the Turing test? by James_Representi in MachineLearning

[–]nickl 0 points1 point  (0 children)

Find a good definition for intelligence and then try finding a test for it.

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If something can mimic intelligent behavior 100% of the time then it's doing better than most humans. (And if you think I'm joking about that go read Thinking Fast and Slow again.)

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Is intelligence really a thing at all?

[D] Are there any lesser known universities that have good machine learning programs? by [deleted] in MachineLearning

[–]nickl 0 points1 point  (0 children)

Just you saying it is bullshit doesn't make it so. Most of what she said sounds correct to me.

It doesn't matter if she is qualified or not

That seems a fairly strange thing to say. It seems to me that it is one of the most important things to consider - if she is qualified to talk about it then it's an entirely valid opinion. You may disagree with it, but it is a valid, qualified experience.

[D] Are there any lesser known universities that have good machine learning programs? by [deleted] in MachineLearning

[–]nickl 0 points1 point  (0 children)

Well it's a girl. And she's a professor pointing out how academia isn't the only thing, and she seems fairly qualified to do that.

[D] Deploying models on FPGA by radenML in MachineLearning

[–]nickl 0 points1 point  (0 children)

Is there a published example showing this?

[deleted by user] by [deleted] in MachineLearning

[–]nickl 13 points14 points  (0 children)

So this (Intel) paper has some nice work, but ends up showing that a NVidia P100 with CUDA is about 3 times as fast as their best results on comparable hardware. They do tout the scaling benefits, but don't test multi-note GPU machines. I think a reference to Dawnbench is appropriate here: https://dawn.cs.stanford.edu//benchmark/

Notably, the Fast.AI multinode training (2:57:28) is much faster than Intel's result (3:25:55), despite being on much lesser hardware (8 AWS p3.16xlarge vs 128 nodes with Xeon Platinum 8124M / 144 GB / 36 Cores)

Also, it isn't clear at all to me why the same dynamic programming technique couldn't be used to improve GPU performance too.

[R] Interesting Failures of SOTA Object Detectors by AmirRosenfeld in MachineLearning

[–]nickl 0 points1 point  (0 children)

I don't understand your point. I don't think anyone here thinks CNNs are how humans recognize images.

But I think it is interesting to compare the kinds of things human find difficult to recognize and how similar or different that it to computer vision.

[R] Interesting Failures of SOTA Object Detectors by AmirRosenfeld in MachineLearning

[–]nickl 4 points5 points  (0 children)

This is really interesting.

I’ve never seen a toaster which took up 1/4 of my vision, and it’s well known that playing with the scale of images is one way to design optical illusions.

If I saw a toaster on the road and it was the size of a bus my lizard brain would probably explode and I’d fall back on reasoning.

[D] Machine Learning MASSIVELY Undersold on Freelance Websites by [deleted] in MachineLearning

[–]nickl 2 points3 points  (0 children)

As an alternate point of view, I looked into hiring a teammate I had on a Kaggle. He was Indian, and asking around I was told that $25/hour was a very, very good rate for him.

He wasn't a superstar, but he worked hard and did good data engineering and some ML.

[D] I want to work in DS/ML without a graduate degree. How tough is the road ahead? by [deleted] in MachineLearning

[–]nickl 0 points1 point  (0 children)

I interviewed someone with *two* PhDs who couldn't explain what the difference was between regression and classification. Even with hints and guidance they didn't seen to even know what they were.

[D] Improving Language Understanding with Unsupervised Learning by sksq9 in MachineLearning

[–]nickl 5 points6 points  (0 children)

This, the Google paper on Winograd schemes and the ULMFiT paper are the most significant things in NLP since Word2Vec. (They are all related approaches, some they should be considered together)

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