framebit

GLP-1 and GIP are both hormones the human body makes in the gut. The famous drugs are mimicking those hormones. This is more akin to taking supplemental testosterone than it is to taking Fen-Phen or whatever.

I found the two Sam Quinones books on the US opiate epidemic fascinating.

- Dreamland: The True Tale of America's Opiate Epidemic

- The Least of Us: True Tales of America and Hope in the Time of Fentanyl and Meth

I'm an ML Engineer who's really closer to an MLOps role. I'm weak on ML and strong on data, scaling, cloud stuff, infra as code, making processes not suck, kinda everything _but_ the ML. So take my opinions for what they are worth, and keep in mind that the role of ML Engineering at company A != ML Engineering at company B.

I've described ML Engineering as putting the "science" in Data Science because we help introduce reproducibility. For example, I can take your model training and make it a robust process that happens over a huge amount of data on a daily basis with all the monitoring, logging, and reliability stuff surrounding that.

Some topics I would personally want to see for an ML Engineer on my team (and again, "ML Engineer" has less of a solid definition across the industry than "frontend engineer" or other roles that have been around longer) - Docker: can you containerize your code? Can you interact with a local container? - Model serving: at a basic level, can you wrap an API around a model? There's lots more systems design stuff here if you want to go deeper on model serving platforms. - CI/CD: do you know what Jenkins does? (Or equivalent) Can you talk about a coherent code testing strategy for ML code? How would you deploy a model service using a system like Jenkins? - Cloud stuff: you don't need to be an expert, but can you interact with cloud APIs directly or through Terraform, spin up instances, know the difference between object storage and databases, and do you have some Kubernetes experience (run a pod, get the logs, take some debugging steps when something's wrong). - Modern MLOps: model registry systems like MLFlow, feature stores (DIY preferred but vendors ok) - Scheduling and Pipelining: Airflow, Vertex Pipelines, lots of options here but those are the biggies. Know how to use these for basic data pipelines, model training, service deployment, and why and how you can deploy these via CD - Monitoring: know the difference and have strategies around monitoring systems metrics (cpu usage, etc) and model metrics (data drift, etc)

A lot of this stuff is harder to learn on your own because it often comes up in the context of larger teams and enterprise scale, where monitoring and reliability turn into KPIs that execs look at, but this is, to me, the stuff that defines the difference between a Data Scientists and an ML Engineer.

In some ways I feel lucky that tech was an early career change for me. I was trying to get a career in the arts off the ground, and it was going poorly. I was a recent grad millennial in the economy of the 2008 recession.

The decision to turn my back on what I thought was my passion was a profound spiritual experience. The decision to change came from outside of me. The decision of what path to follow was up to me though.

Tech was hiring and hiring like crazy, and I wasn't going to do an unprofitable degree twice so CS it was. I had a job before I graduated making 4x what my mom was making at her non-profit admin job.

If I hadn't pursued my art career first and had the chance to get deeply disillusioned with it, I would definitely be sitting at my desk trying to write code and thinking "what if... I'm not made for this... there's something else..." The truth is that I'm not cut out for the arts industry. I like stability, I like being salaried, I like having the upper hand in the hiring market (I know Big Tech is doing layoffs, but try spamming applications for a year to everything you can think of until the only place that calls you back is a cashier position at a grocery store. I have skills that are in demand now.) I like work that is decent and stimulating enough but which is definitely not "my passion" because that helps me keep boundaries on it.

I feel for folks who didn't get that chance to try out that other thing, who went straight into this career maybe because they wanted to, maybe because they didn't have the safety net I had that allowed me to do a second degree, maybe because life has held them down and change doesn't feel like an option. I've been out there with my chosen field and gotten burned hard by it so I'm content to stay put. It's definitely one of the cliche sayings about how the lows make the highs much higher.

I have no useful advice for anybody beyond their very early 20s facing this question. I know I would be eaten by this question if I hadn't already gotten my answer at the start.

The connection of lead poisoning and narcissism does seem plausible.

It's also worth noting that, broadly speaking, the parents of Boomers (depending on their age) went through 1 or 2 world wars, the great depression, the spanish flu, etc. and probably didn't come out unscathed. The trauma of the parents is bound to have ripple effects on the mental health of the kids.

There's more than a few stories of dads who went off to war and came back silent, drinking, and traumatized.

I avoided learning anything having to do with front-end for a long time, and I'm just now catching up. I've been doing a course on Responsive Web Design with scrimba.com, and that starts with a really comprehensive overview of CSS basics, including margin collapse, which I'd certainly been frustrated by in the past without having a name for it.

Just a little local perspective on the lines in Georgia. The waits that some folks had to endure in the primaries were a huge problem. Georgia absolutely has history of voter suppression like many post-confederate states, and some seriously shady stuff has gone down in the past.

However, the really long lines yesterday were more attributable to incredible turnout on the first day of early voting, which also happened to be a federal holiday so many people had the spare time to come out and vote. There are new voting systems, new volunteers for whom that was their first day running the polls, and a very motivated electorate.

For comparison, today, two days later, I know of at least two people who were in and out in 15 minutes in some of the same areas that had incredible lines on Monday.

There are legit voter suppression stories of great concern in GA, but I don't think the lines of Oct 12 qualify. I'm totally open to being corrected on this opinion though.

Awesome! Glad to hear it!

Oh wow, I had no idea Scrimba was brand new!

I signed up for the Responsive Web Design course last week and I'm getting a lot out of it. This is actually my first time taking any kind of web course of any type, programming or otherwise.

I work in the data/ml stack, not the web stack, and I've avoided learning anything serious about frontend for _years_. Figured it was about time to fix that so that I can get my personal website to look a little less terrible.

The Scrimba course looked like it would check all my boxes about technical content without forcing me to a timeline or a certificate program or being crazy expensive. I'm not looking for a career change into frontend, I'm just somebody who thrives in a structured learning environment for a new subject area.

I can definitely recommend the lesson + interactive in-browser editor combination. It's a powerful tool for fast, real learning. And I'm very grateful that somebody finally explained CSS margin collapsing to me!

My biggest critique so far is that the preview window for the project doesn't really work in Firefox, but things seem fine in Chrome.

IBM is essentially a consortium of at least 35 different companies masquerading as one. A lot of those companies are doing ridiculous nonsense, but some of them are doing really cutting edge work. IBM Research in particular attracts some top-notch talent.

The Alphasmart! We did typing class with that back in the early 00's. The IR beam to the printer felt like science fiction back in the day.

As of right now looks like AT&T, Verizon, T-Mobile, Sprint, and many others.