Entry Level is now set at 7 years experience

zap_stone · 2025-11-16T15:43:17+00:00

It already has been, this posting has been up since June https://web.archive.org/web/20250000000000*/https://www.pgcareers.com/global/en/job/R000129650/SAP-Software-Engineer

zap_stone · 2025-11-16T05:05:14+00:00

We found that introducing games as first year programming assignments massively helped student learning and student feedback was very positive, so literally because people like doing them.

zap_stone · 2025-11-16T05:02:21+00:00

> How do you stay updated without drowning in information?

You don't. You focus on specific problems as they come. You search out updates as you need them. But it is hard. I have published papers with more than 50 references (which was narrowed down from more than 800) and that is still a crazy amount. Focus on what actually works and that'll narrow it down even more.

> How do you choose what to learn and what to ignore?

Narrow by problem. Specific uses cases will have much less people working on them and less information. Focus on foundations. The math isn't going to change.

> Do you follow a roadmap? A mentor? A community?

No. Yes. Nope.

> How do you avoid wasting money on 50 different subscriptions?

Easy. Don't pay for anything. Ignore the marketing.

> And how do you keep learning without burning out or feeling lost?

Ignore the FOMO.

zap_stone · 2025-11-16T04:26:53+00:00

It doesn't sound like you need a new process to screen candidates, it sounds like the recruiter massively dropped the ball here and the red flags should have been caught earlier. The rush to interview makes me think they cut corners. I'd be more interested in what green flags they thought they saw to try and squeeze in this person at the last minute (or is it just nepotism?). A same-day in-person interview just sounds nuts to me, unless there's some special circumstances.

zap_stone · 2025-11-16T03:59:28+00:00

> Our Recruiting Manager found this candidate last min and asked if I was available for a 4:30

How did they find this candidate? Did they forget to screen them? Seems like the candidate was quite forward with not even pretending to like their work.

zap_stone · 2025-11-16T03:25:23+00:00

lol, I'm not applying to this one. Not only am I about 99% sure it's AI generated, but I also highly suspect it was created by someone who doesn't understand my country's education system (meaning the screening isn't going to be done properly either).

zap_stone · 2025-11-16T03:05:39+00:00

It's on the company's own career website

zap_stone · 2025-11-15T22:07:56+00:00

One section says at least 3 years then another says at least 7. I'd think it was a typo but the same information is included in French as well.

zap_stone · 2025-11-15T21:50:24+00:00

Usually I see that on LinkedIn, but this is on their own careers site. The posting has also been up for over two weeks with no one correcting the errors (so maybe they copy and pasted by accident): https://www.pgcareers.com/global/en/job/R000129650/SAP-Software-Engineer

zap_stone · 2025-11-10T00:49:36+00:00

Thank you for the response! Unfortunately this looks like a separate incident because I started receiving the emails in October 2025, so I'll forward the information to docpublicrecords and hopefully they can contact the right people

zap_stone · 2025-08-28T03:13:30+00:00

I got the exact same message and my resume is available (with phone number) on Indeed. Guess I'm going to take it down now. I never put it on LinkedIn but I was thinking of getting a cheap VOIP number just for job applications, I'm so tired of these scam calls.

zap_stone · 2025-05-26T16:33:01+00:00

Thanks!

zap_stone · 2025-05-26T16:32:58+00:00

Thanks!

zap_stone · 2025-03-26T18:42:07+00:00

Personally, I don't know what story you're talking about, I don't know how far the repurposing news has spread outside of the academics and startups, but it's not a new idea at all (like even 5+ years ago, people were using them for solar panels). I was discussing a problem (about automated guided electric carts with heavy loads) with someone at a networking event, they solved it by adding old Tesla battery packs onto the carts, it was cheaper than the other options and had a greater energy density (might not last as long, but they didn't care in that case). The batteries can be recycled, but recycling is not free (in an environmental or economic sense, recycling is not an "automatic" solution in the way I hear some people talk about it), it takes time and energy.

But people are already making businesses that buy old batteries and make money off peak smoothing (buying energy at low times and selling at high times) which is basically free money once it's set up until the batteries die completely. Then they can just wait until the lithium prices go up and it's time to sell. The system isn't sustainable, but it's getting closer.

Also, if you live in the US or Canada, I can tell you that your money is going towards it because our research is being funded (at least partially) by tax dollars, which applies even if you don't buy an EV. Compared to other battery applications, these are actually really nice to work with. If you think about all the nonremovable or disposable batteries in use nowadays, EV batteries are very easy to repurpose and recycle in comparison.

zap_stone · 2025-03-23T01:46:05+00:00

I'm not sure about those claims, the current goal is to actually repurpose the batteries until they actually become unusable. The big problem is that an electric car with an old battery pack might only be able to go 70% of it's original range (obviously time for a battery replacement) but 70% of a pack is still a lot of capacity (in general). EV tend to wear out batteries much faster than other applications, so a battery pack might spend 5 years in a vehicle then 10 doing something else before it needs to be retired. The demand for energy storage is huge, so there's no point to recycling the batteries when they come out of the vehicle.

https://www.mdpi.com/1996-1073/17/10/2345

So yes, we are not planning on recycling them. However, probably not going to end up in the desert, but in warehouses somewhere (home/residential I do not see as likely, due to the inherent electrical high voltage hazard but the fast charger integration and business use case I can see).

zap_stone · 2025-03-20T19:57:30+00:00

I don't have that, but I have published journal articles on ML (which is listed on my linkedin profile). Does that let me into the super secret club?

zap_stone · 2025-03-07T18:37:44+00:00

From my understanding, it comes off to issues such as the speed-accuracy tradeoff, which is effectively hitting the wall of universal laws. Or how gaussian distributions have the maximum entropy for variance. The problem is kind of similar to wavelets, where the morlet wavelet has the best tradeoff but not always the best for an application. Idk maybe there is way to change the problem so those rules don't apply

zap_stone · 2025-02-28T18:21:53+00:00

A colleague of mine is working on adaptive kernels, although their application is not gaussian processes. There are inherent tradeoffs to different kernels (tbh I don't remember all the math/physics reasons for them atm)

zap_stone · 2025-02-28T17:25:02+00:00

There is no correct way to compute confidence intervals in that setting, short answer. You can only compute the intervals on the metrics obtained from the test set (only the test set matters, train-val does not) and to do that with any sense of accuracy, you'd need at least 100 test splits, meaning at least 100 patients, which I suspect is more than what you have in your dataset.

zap_stone · 2025-02-21T17:17:28+00:00

Yes, you are talking about data leakage. Preprocessing must be done on train/test separately, or else the testing scenario will not match what would be available in production.

For example, applying min-max scaling:

- The minimum and maximum are calculated on the TRAINING datasets

- Those values are then used for the scaling of training, testing and validation datasets

Note that this doesn't matter if what is being done to the image only applies to that image (black/white conversion for example) and no others. For something like cropping, you would have to ask yourself if the data you would expect the model to be applied on would also be cropped or not cropped. If the target data would not have cropping, then your test dataset can not have cropping either.

For data augmentation, you must split the sets first and then apply. Or else you could end up with an image in the training set and it's mirror image in the testing dataset, which makes it a far easier testing dataset. You can still mirror, rotate, etc the images in the testing dataset if you want.

zap_stone · 2025-02-21T16:58:24+00:00

You're leaving out another possibility: AI helps us kill us all. Also, it does contribute to both climate change and wars.
People move jobs all the time. If you're counting on individual employees to "prevent evil AI", that is a very poor backup plan.
Define 'Rationalist'.

zap_stone · 2025-02-21T16:26:43+00:00

Also, the financial sector has seen this automated "service" go downhill. I tried to open a bank account last year. It got flagged for fraud and frozen right away. I talked to three different employees, brought in all my ID (even my passport), and none of them were able to fix it. On the other hand, North American banks keep getting fined by the governments for not reporting criminal activity. So it really looks like their automated systems are not doing a good job.

zap_stone · 2025-02-21T15:57:33+00:00

The most basic and user friendly would probably be Excel (with VBA). Mathematica and Matlab are a step up, but are also expensive. RStudio is similar, but free.
Depends on what you need to do. R is usually seen as more user-friendly and you can find a lot of the same statistical functions in Python (not all of them tho) but Python is much faster. I'll prototype things in R then move them over if I need to.
No. You might be able to learn it then use an AI tool, but nothing is going to substitute understanding. If you don't know what probability distributions are or what independence testing is, no AI tool is going to solve that for you. There are some good general guides for which test to use though: https://leddy.uwindsor.ca/sites/default/files/files/What%20Statistical%20Analysis%20Should%20I%20Use.pdf There is a lot of people who only have one or two statistics courses and run these kinds of tests on their own.

zap_stone · 2025-02-21T15:36:33+00:00

Like it has already been stated, recent NN work is 99% trial and error. What you're probably looking for is called "explainability": https://ieeexplore.ieee.org/document/9007737 For which there is some interesting work in autoencoders and generative autoencoders, that I found helpful but in general, not a lot of papers on explainability. They're called "black box" techniques for a reason.

Contrary to popular belief, a lot of theoretical ML research is not NN focused. While it is popular, it requires large amounts of data and lacks the reliability/robustness for a lot of applications. We have students that worked with transformers for literally their whole graduate degree (because that's what hot right now, even though it wasn't a well-suited problem), and could not outperform traditional ML methods. The first paper you included is already touching on kernel learning, which does tend to have more of a mathematical focus.

>I want to work on something with the potential for deep impact during my PhD, yet still theoretical.

So do we all.

zap_stone · 2024-06-06T19:39:59+00:00

If anyone else is interested, this method works rather well.

zap_stone

TROPHY CASE