tictacttoe

Usually the subtext is that they’ve created a promotion process which is onerous, they are under paying you market rate, and/or management doesn’t want to make hard decisions or uphold their side of the bargain. The last thing I want to do as an IC after I’ve crawled through glass for several years to accomplish something Herculean is draft documents that defend my accomplishments from bureaucrats.

When I hear comments like that, I raise my eyebrows because it’s almost tempting me to apply elsewhere. I don’t know why, when presented with mountains of evidence, managers can’t just make a reasoned judgment call and grant promotions when appropriate, unassisted.

Any recommendations for acquiring the place website URL through an API or ethically scraping it at scale? I’m specifically wondering about options that wouldn’t involve Google Places.

But at least in science roles it hasn’t happened yet. Rather, I keep seeing instances of bogus scientific conclusions which waste money for years before they are corrected.

Being systematic, reproducible, and thorough is difficult, but it’s the only way to do science.

Yes, Google and Meta (the parent company of Facebook) do allow businesses to upload customer email addresses and phone numbers for advertising purposes, under specific conditions. This process is part of what's known as "Custom Audiences."

1. *Google Customer Match:* Google allows businesses to upload a list of email addresses through their Google Ads service. This feature, known as Customer Match, lets advertisers target or retarget their advertisements to these customers across Google products like Search, Shopping, YouTube, and Gmail. Businesses must comply with Google's policies and data protection laws.

2. *Meta Custom Audiences:* Similarly, Meta (Facebook) offers a feature called Custom Audiences, where businesses can upload lists of emails or phone numbers. These are then used to match users on Facebook, Instagram, and other platforms in Meta's network for targeted advertising. The data is hashed to protect user privacy, and the businesses must have the right to use this data.

Both companies emphasize privacy and the necessity for businesses to have obtained the data lawfully and with the user's consent. Users also have tools at their disposal to control their ad preferences and understand why they are seeing certain ads. It's a balance between effective targeted advertising and user privacy, governed by both internal policies and external regulations like GDPR and CCPA.

Google and Meta are building social graphs across this uploaded information.

I’ve been banging my head against the internet looking for something and have come up mostly empty handed. I don’t really want a toaster oven either. The dualit classic is close to what I want, but it sounds like it doesn’t toast that evenly which seems crazy to me given its price point.

Does anyone else feel like there’s a significant gap in the market when it comes to well-engineered minimalistic toasters?

However, if the market pulls back X% on compensation, but Amazon pulls back Y% with Y > X, people are going to leave… and not the ones you want to leave.

I use a credit union for checking. I'm currently planning to open up a second checking account with the same credit union to split my income stream into fixed and variable expenses as some have mentioned here.

General idea is as follows:

1) Deposit income check each month into checking account #1. Draw from this account for monthly and yearly expenses. Add some buffer so as not to over draw.

2) Initiate an auto-transfer from checking account #1 to checking account #2 after check is deposited each month. Work within the budget set by checking account #2 for variable expenses.

Why use a credit union? A for-profit bank does not share the same incentives as their clientele. If they can separate you from your money, they will. I'm generally wary of any industry that is rewarded financially for stealthily screwing their customers, e.g. insurance industry. Credit unions are also known for having very reasonable loan terms.

Why two checking accounts? It's nice to know what I'm spending each month on stuff like gym membership, streaming music, cellphone bill etc, versus things like coffee and dining out.

Investing setup

I'm young. I'm willing to incur risk for better long term returns (on average). I also recognize that I am not Rentec. If I were to outperform the S&P500 picking stocks, it would be almost entirely due to random chance.

I keep enough money in checking to survive an emergency that requires immediate access to funds. Everything else that I earn above what I need for the month goes straight into an S&P500 index fund. Both Vanguard and Fidelity are essentially fungible.

I'm open to others convincing me that this is a stupid strategy. It is entirely possible the S&P500 tanks, and I lose a large fraction of my money. Few counter points though. First, it is by definition a diversified portfolio of stocks. Second, it has performed very well historically. Third, it has enough people invested in it that it couldn't just "go away" without serious repercussions for the US and the world.

Perhaps the largest concern, is that there is way more wealth in the S&P than there are people actually trading it on a day by day basis. If there was a flash crash, there simply wouldn't be enough people on the buy side of the equation to drink from the firehose of people selling. This is really beyond my depth though so I'll stop here.

Other principles

I'm trying to avoid debt like the plague. Mostly for my mental health; I know it can be important to your credit score to carry some continual debt. Be wary what you sign up for (college, grad school, etc).

Keep in mind though, you always want to maximize your net effective interest rate. If your student loan rate is 4%, consider paying the minimum on your student loans and put the difference (what you would have paid) into the stock market. Only do this if you can automate the process as you will be inclined to spend the money and not save it.

Now, I’ve probably taken 100+ math exams in my life and I’d be happy to provide data from any one of them. Why trump all that data with 15 questions? Viewing the application process as a pure machine learning problem, their decision seems crazy.

The reason it carries value is the skills are difficult to acquire. I think the recent decline in interest reflects the rise of new data science candidates that are taking the path of least resistance to a career in data science. Rather than pursuing problem solving, people are pursuing "data science" which is a nebulous term in and of itself.

However, constructing and sampling the Bayesian posterior using MCMC methods has several advantages. Sometimes you can have a local minimum which is essentially flat, so the optimal hyperparameter is unstable. You'll see this in the posterior distribution. Or you could have two parameters which are correlated so it's their sum that's constrained not their individual values. All this information provides important context when understanding your model's uncertainty.

People need to address the issue at each stage of the pipeline. I would argue that early stage imbalances are even more important than late stage imbalances (post-graduate) because upstream imbalances necessarily propagate downstream but not vice versa.

The predominant issue is that physics codes are typically written by PhD candidates, often with little to no programming experience. The projects can span 3-5 years and continue existing in the physics ecosystem for decades. Good programming practices are seldom employed, and the codes become these massive patchwork ships, leaking everywhere with holes plugged by spaghetti code.

The issue is not that the students aren't smart enough to learn good programming practices, it's that the advisers are not patient enough to wait for documentation, unit tests and so forth. They view good practices as wasted time, after all it's "physics not computer science".

Unfortunately, the path of least resistance is actually to adopt unit tests, write code documentation and generally employ industry programming practices, it's just that this path has a barrier to entry and the benefits are not immediately apparent to older academics who have fallen out of the loop.

The end result is quite sad; students with advanced programming skills are chronically under appreciated in the field. Professors will happily bring them on board as post docs to develop their simulations, but they balk at giving them jobs based on their computational skill set. It is thus no surprise why the computational talent leaves physics and takes careers in the private sector where the union of math skills and programming is in high demand.

To be honest, I've been extremely disappointed by the scientific process in high-energy particle physics. People are so tethered to their theory convictions, that they accept derivations as physical realities and dismiss the importance of experimental validation. The old farts in the field are also completely averse to computational/numerical methods and dismiss the importance of production quality code development.

So while I embrace the sentiment that 'math is the essential language of physics', if you can't embed the mathematics into a simulation which describes reality, then what are you doing as a scientist?