thegginthesky

This is not the point. The point is you misquoted the article without understanding the full context, and was corrected. The parents weren't judgmental of an online life, they were just unaware. Matter of fact, on the documentary from one of the replies, it felt that they were glad their son had good friends who really cared about him.

I'm a similar position as you in terms of job, salary and balance.

But this is my 5th job out of college and the longest I've been in a single job. When I hit my 4year mark, I started to think that the grass is greener on the other side and looked for opportunities here and there.

A few years in and I didn't find the right place that would make me jump ship. I have high standards and I can spot redflags based on past experiences in jobs in multiple countries.

I also found out that after I got older and accrue more responsibilities outside work, my job became a much smaller focal point of my life.

I'd rather be employed in an okay place, being paid a competitive enough salary (75% in the curve), and have opportunity to learn new things in the job and out, even if I don't love the field. As opposed to try a new job and risk being put in a toxic work environment and lose the balance I have now.

If you are not growing as an engineer, going to a new job might not help you and could be detrimental. It's much better to learn new things while you have the time to do so. Find an area you want to learn more, try new projects or courses, and have fun at your own pace.

No problem! I have most of the code in very small functions that I'd be willing to contribute.

At my company we have very time sensitive AB tests that we have to run with very few data points (at most 20 conversions per week, after 1000 or so failures).

We found out that using Bayesian A/B testing was excellent for our needs as it could be run with fewer data points than regular AB for the sort of conversion changes we aim for. It gives a probability of group B converting better than A, and we can run checks to see if we should stop the test.

Regular ABs would take too long and the significance of the test wouldnt make much sense because after a few weeks we would be comparing apples to oranges.

Great package! I'll test it out on my free time.

I'm wondering if you'd like to accept a contribution for Bayesian AB Testing, based on this whitepaper[0] and developed in Numpy.

If so, we can chat at my email gbenatt92 at zohomail dot com, or I can open a draft PR to discuss the code and paper.

[0]https://vwo.com/downloads/VWO_SmartStats_technical_whitepape...

I stand corrected! It was my impression that many methods used in ML such as Support Vector Machines, Decision Trees, Random Forests, Boosting, Bagging and so on have very deep roots in Frequentist Methods, although current CS implementations lean heavily on optimizations such as Gradient Descent.

Giving a cursory look into Bishop's book I see that I am wrong, as there's deep root in Bayesian Inference as well.

On another note, I find it very interesting that there's not a bigger emphasis on using the correct distributions in ML models, as the methods are much more concerned in optimizing objective functions.

Most models are derived of Machine Learning principles that are a mix of classic probability theory, Frequentist and Bayesian statistics and lots of Computer Science fundamentals. But there have been advancements in Bayesian Inference and Bayesian Deep Learning, you should check the work of frameworks like Pyro (built on top of PyTorch)

Edit: corrected my sentence, but see 0xdde reply for better info.

Frequentist and Bayesian are correct if both have scientific rigor in their research and methodology. Both can be wrong if the research is whack or sloppy.

It's because practicioners of one says that the other camp is wrong and question each other's methodologies. And in academia, questioning one's methodology is akin to saying one is dumb.

To understand both camps I summarize like this.

Frequentist statistics has very sound theory but is misapplied by using many heuristics, rule of thumbs and prepared tables. It's very easy to use any method and hack the p-value away to get statistically significant results.

Bayesian statistics has an interesting premise and inference methods, but until recently with the advancements of computing power, it was near impossible to do simulations to validate the complex distributions used, the goodness of fit and so on. And even in the current year, some bayesian statisticians don't question the priors and iterate on their research.

I recommend using methods both whenever it's convenient and fits the problem at hand.

I miss the college days where professors would argue endlessly on Bayesian vs Frequentist.

The article is very well succinct and even explains why even my Bayesian professors had different approaches to research and analysis. I never knew about the third camp, Pragmatic Bayes, but definitely is in line with a professor's research that was very through on probability fit and the many iteration to get the prior and joint PDF just right.

Andrew Gelman has a very cool talk "Andrew Gelman - Bayes, statistics, and reproducibility (Rutgers, Foundations of Probability)", which I highly recommend for many Data Scientists

Hey Peter, I'm a foreigner residing abroad with an american spouse of 10 years and we have kids holding American Passports. I'm currently working as a contractor for a company in the US, but I'm thinking of moving to the US and applying for the IR1 visa due to family reasons. I am the primary earner of the household.

What are my limitations in this case? Can I keep the contract I'm currently in while the visa process chugs along? What about proof of income?

That is a much lesser punishment than what the US is doing in this thread. A fine that is a small but non-insignficant percentage of annual revenue is a measured response when you want to punish bad behavior but allow businesses to still operate within the jurisdiction.

Restricting business operation altogether is a response a country gives when they see the other party as extremely adversarial, which is a few orders of magnitude above what EU fines are to Big Tech.

Big difference

I know someone who works on this in Meta. His resume is computer science heavy, with a masters in Machine Learning. On the previous experience side, before getting into Meta, he had about a decade working as a Software Engineer with Machine Learning system in multiple languages, such as Go, C++ and Python.

To get the job he applied for a spot I'm Software Engineer applied in Machine Learning, he went through the multiple step interview process, and then when he got the job he did a few weeks of training and interviewing teams. One of the teams in charge of optimizing ML code in Meta picked him up and now he works there.

Because of Meta's scale, optimizing code that saves a few ms or watts is a huge impact in the bottom line.

In sum:

- Get a formal education in the area - Get work experience somewhere - Apply for a big tech job in Software Engineer applied with ML - Hope they hire you and have a spot in one of the teams in charge of optimizing stuff

I won't be defending Nintendo because their issue with joy-stick drifting, their unwillingness to fix their design flaw, and their constant efforts to stop video game preservation really pisses me off.

But emulators are hit or miss, specially if you aren't tech-savvy enough to fix specific problems, and depends on the people's preferences:

- they need to install and configure an emulator, which isn't fool proof

- go through the hoops of downloading ROMs from sometimes sketchy sources

- configuring each game to work well

- self troubleshooting any issues they might have with some games

- not wanting to play their games online (which in Nintendo's case the online experience is truly lacking)

- not have any moral issues with piracy for games that are currently selling in both physical and digital format and are widely available

Nintendo's Switch is due for a very necessary upgrade, but the console is still widely available, very convenient with minimal setup and troubleshooting, and very plug and play. With the added benefit that you get to support developers to continue making the games.

Freight broker that wanted to use technology to automate the work of finding trucks, managing the communication between truck, shipper and facilities, and auditing the job of moving the load.

But the job is very high revenue (thousands of dollars per cargo depending on the distance) but low profit (5%-10%) in these times.

Like the sibling comment has said.

But what we saw during the peak was crazy, and some investors and execs thought it would last.

At least in regards to what pertains FTL freight, we saw a drop of tougjly 50% in volumes as consumer spending is down when compared to pandemic height. I am pretry sure there will be a seasonal trend upwards, but no where in the way it was before.

If you are in the industry, you can easily check how much cargo is moving around. Maybe by November-December it will be less than a 50% drop, but expect it to return by kid January-February.

I work for one of their competitors and I can empathize with them. My thoughts goes to all the employees and their families.

The Freight business is collapsing after an unrealistic high during the pandemic. Since April 2022, revenue per load has decreased to about 70%, this means less ways to generate a profit under the same headcount.

We also saw a decrease in volume as companies overstocked and consumer spending has shrunk to less than 50% of what it used to be. Just add it all up and you see why so many companies are collapsing, carriers and brokers alike.

Though market.

Process, git and S3.

We trained the whole team to:

- version the analysis/code with git - save the data to the bucket s3://<project_name>/<commit_id> - we wrote a small code to get the commit id to build this path and use boto3 to both access it and save it

We normally work with zipped parquet files and model binnaries and we try to keep them together in the path mentioned

It's super easy and simple, very little dependencies, and allow for rerunning the code with the data. If someone deviates from this standard, we will always request a change to keep it tidy.

Keeping track of data is the same with keeping a clean git tree, it requires practice, a standard, and constant supervision from all.

This saved my butt a many times, such as when I had to rerun an analysis done over a year ago, or take over for a colleague that got sick.

The point isn't paying to publish apps, the point is that you can't hack into it if this is anything like iOS.

If this runs a version of iOS, we can't access the code that is running in it, we can't open a terminal, we can't use our programing language of choice. We can't use the actual device for building anything hacker related by itself.

We can make apps for it using an actual PC made for building, but only if it runs MacOS, ans using their proprietary language. The actual device is far from a hackers dream or plaything if its as locked up as the iPhone. But very cool device though, hopefully it brings VR into Mainstram outside of gaming

Not my first on site either, but normally I'd just need to go through a phone screen and a tech test to secure an onsite, not many hours of interviewing. Plus, I just listened to what the recruiter told me through the phone and confirmed through the email.

Why would I think I'd need to go over another round of interviews after spending over 4 hours interviewing remotely, plus interviewing with engineers, to do it all over again?

I'll tell you a personal anecdote about Shopify and why I dislike the company.

Back in 2019, I was contacted by Shopify for a job opportunity. After acing multiple remote interviews, their recruiter couldn't contain their excitement. They promised me an onsite interview to simply meet the team and potentially secure an offer.

Imagine my surprise when, after enduring a 15-hour economy class flight with barely any time to recover, I received a call from the recruiter. They casually informed me that the team had decided to put me through five grueling back-to-back interviews, including a whiteboard session and a pair programming assignment. Despite my lack of a laptop, they assured me one would be provided.

What followed was an unmitigated disaster. The first interview bombarded me with ecommerce questions, completely unrelated to my field of expertise. The pair programming session was a nightmare, as I was handed a barely functional laptop that delayed the start by 20 minutes, and then given just 30 minutes to complete the task without any assistance.

Bear in mind, I was already physically and mentally drained from the arduous journey.

While the remaining interviews were passable, they were nothing to brag about. After being sent home with the promise of a call, I received a cold rejection a week later, citing a lack of experience based on the onsite interviews.

Looking back, I'm grateful I didn't sacrifice everything for a company with a track record of questionable practices and frequent layoffs.

I'd love to be able to ask questions about technical documentation, code bases, contract PDFs and so on, without having to worry to send my data unprotected to another company that doesn't have a Enterprise contract or can assure us of SOC 2 compliance.

If the AI can interpret what I mean, find the file, link me to the sources and distill the information and context, it will be major productivity boom.

No joke at all. I personally know people that rode this last hiring bubble very stellar and got from analyst to manager in just 2 years, while raising their salary over 300% upwards because of strategic company hopping.

Some of them did get fire and are having trouble finding a job that paid as well as the last one.

It was a risk they were willing to take and I believe in some cases it paid off.

I have yet to see a country where licensing equates to high quality in all the services. The examples I've used might not work in some places, but people find flaws in licensing systems all the time.

Sometimes licensing is so strict that things get done anyways ignoring license requirements because there is way more demand for some services than the supply of licensed professionals. In such cases, there are so many people violating regulation that policing becomes ineffective. It's the case with some Latin American countries.

And then you get to the problem that the license is ineffective and doesn't add to anything.

There's no perfect system to uphold quality of labor across a profession, we pick our poison and deal with it.

Renting might be stable but it's very dependant on whoever owns the house and what type of regulations and protections your government has in place. Owning a home (house/apartment/land/etc) gives you more rights over where you live and more stability in most countries.

I've seen rents go up with inflation where inflation grows at 25% yoy, and I've seen people kicked out of an apartment 3 months after moving in because the owner found a buyer with a good deal.

But I agree with you, single family housing is the goal for some cultures and generations, and it was carefully crafted by governmental policy, propaganda, marketing and third party interests. We are now seeing the consequences of such.

Yet, not all people have that goal, but a lot are content to just owning a place to live even with relatives, a community or others.

I feel it's hard to not wanting to own something if it grants more rights and protections against injustices. In the countries I've lived, having a property deed of any sorts with your name on it makes your life so much better and stress free.

Truth to be told, Engineering license requirements have a bigger effect in gate keeping the profession and keep supply restricted, much like any other regulated profession. Gate keeping has some benefits, but is easily circumvented by bad actors all the time, such as all the sham degrees that just churn out the bare minimum to pass licensing tests.

If all the licensing to architects, doctors, engineers, lawyers, and so on, really had a big impact on quality, the world we live in would be very different and better. But that doesn't happen because licensing a profession only works if quality is upheld on all steps of the professional education chain.

A lot of software companies circumvent all of these downsides of bad quality in education by raising the bar on the hiring pipeline with a bunch of tests and so on. Does it always work? No, just like licensing doesn't. But at least it keep la the profession accessible to those who are willing to study algorithms, data structures and so on.

There's no perfect system in our world, but I am glad we don't have license requirements to develop software. I am a statistician that became a dev through self studying, training and learning on the job, and I also know many others (even real engineers) that turned to this profession without graduating in the field and contribute a ton with their specific background knowledge.

Should everyone be called engineers? Probably not as it will elude to licensing the profession, but not calling yourself one decreases chances of finding another job dramatically.

A true tragedy tbh, I'd rather if everyone called themselves devs, scientists or something less loaded than engineer.

The real problem is that Google holds an effective monopoly in search, so any digital marketer worth a salt will optimize the crap out of their blogs and pages to get higher and higher rank within Google alone. This will, in turn, lead to what we see today: a race to the bottom in terms of quality to get the best SEO results.

I've found that a mix of search engines give me the best results, I'm trying my best to incentivize competition. If I want super local results anywhere outside the US, I'll use Google+uBlock because that's what it works, but everything else I use Kagi or DDG.

I really like your heuristic, and I'll add to your list of examples where one could work

- Any tech company where the Stats/ML model is one of THE products and differentiators. You'll need to cut through a lot of buzz word and sales-speak to find the good ones.

- Banks and other financial institutions where making uneducated guess is a big no-no when it comes risk, pricing and anything related to financial products. Your example of Credit Risk Modeling is a classic example and very interesting problem.

- As much as consultancy gets a bad rep due to some shady practice from big players, there exists a solid demand for professionals that know Statistics in the Large Construction Projects space. Let's say modeling demand and return financial for a project, proving environmental impact, preparing/implementing/analyzing unbiased surveys in the area, and so on.

- Government agencies where data is one of the Key Outputs. Such as the Census, Bureau of Labor Statistics, CDC, and so many others.

As you said, sometimes it will mean a pay cut, especially if you want to remain in the technical work and not deal with the business and managerial side of things. But there's solid demand.

No, but a CEO can slash his own pay to reflect the current situation. For example, when the WiiU was a flop, Nintendo's CEO personally decided to take a paycut of about 50%[0]

I believe this should be the standard for any CEO who wants to say they take accountability.

[0] https://www.bbc.com/news/business-25941070

I love the Botanical Garden, it's my favorite place in Rio and truly underrated. The biodiversity is amazing, great spot for picnics with the kids, photos and so on. Plus it's super cheap and the staff is very welcoming.

I highly recommend their orchids exhibition, which contains 630 unique orchids.

I've worked on 2 companies where I was in a team of 4/5 devs + 1 SRE in charge of the infra. In both cases, once the SRE guy created the appropriate terraform modules and CI template, he had to move on to a new team because there was literally no work left for him to do. Once things are infra as a code and the happy path is defined and implemented as a process, we rarely lost time thinking about infrastructure. Or anything.

The system needs permission for AWS S3? Here is the component. Does it need to setup secrets? Here is the component. Does it needs to be in the same VPC as a Redshift cluster, or whatnot? There's a component for that. Do you need a SQS/RDS/Redis service? You get it.

K8s, terraform and Atlantis have been such huge enablers I cannot overstate. Everything is so nimble and cheaply setup that our current infra bill is about 500USD/month to generate over 100k MRR for the company.

And better yet, we rarely ever think of our infra unless we want to do something brand new (such as testing Sagemaker), or there's unexpected traffic above our current scaling limits (about once a year). Plus, if we need to fix anything infra related there's an internal cookbook for that.

I also feel I have acquired useful skills by learning all of this.