sgron

Ticketmaster actually experimented with this https://www.aeaweb.org/articles?id=10.1257/mic.20180230

Eventellect | Hybrid / Onsite / Remote (US – NY, TX, MA only) | Full-time

Eventellect builds algorithmic systems for live event ticketing. We’re on a mission to fix ticketing for fans and teams -- eliminating inefficiencies, replacing opaque pricing, and getting the right tickets directly to the right fans at the right time. We work directly with both sports teams and other major live events, directly shaping revenue, attendance, and fan experience at scale.

We’re hiring for:

Full-Stack Engineers (Senior+) Own and build complete systems. Work on real-time pricing, inventory management, and internal/external tooling. Looking for strong fundamentals, ownership, and good judgment.

Data Platform Engineers (Staff / Principal) Own the data stack and internal data products. Design core data models, pipelines, and standards that support analytics, modeling, and operations. High-impact role with real ownership.

What we’re looking for: Strong builders who thrive in messy real-world problem spaces, take ownership, and ship.

Email me directly at sgrondahl [at] eventellect [dot] com (Subject line should start with "HN")

> what has the war on drugs really ended up accomplishing?

I haven't studied this extensively, and I know that it's widely accepted that the war on drugs was unsuccessful, but I would caution against conflating "it didn't completely solve the problem" with "it had no positive impact at all." As a parent comment mentioned, periods of prohibition are generally associated with lower consumption overall (across both legal and illegal channels).

Do you have a source for that cost attribution? Based on my time there (slightly more recent than yours), that breakdown feels roughly correct. However, I've been trying to find similar information and have found it difficult even for public universities.

Yes, and in other engineering disciplines this level of rigor does exist. https://en.wikipedia.org/wiki/Engineer_in_Training

Fairmarkit | Full-Time | Boston, MA | On-Site or Remote | https://www.fairmarkit.com/careers

Fairmarkit is the intelligent sourcing platform that empowers organizations to more efficiently purchase the goods and services they need. By equipping procurement and supply-chain teams with automation and data, Fairmarkit promotes competitive bidding while reducing manual work within existing processes. Fairmarkit has been recognized with awards by organizations such as Gartner and IDC, and is backed by strategic investors like GGV Capital, Insight Partners, 1984.VC, and Newfund.

Some open engineering roles:

  - Engineering Manager, Integrations
  - Engineering Manager, Machine Learning
  - Senior Machine Learning Engineer
  - Data Engineer

Reach out to "talent AT fairmarkit DOT com" with "Hacker News" in the subject line if you'd like to discuss any of these roles in more detail.

And rowing splits are per 500m, not per km.

Also, from the terms <https://www.charliebitme.com/#/auction-terms>, the buyer doesn't own the media itself, just the NFT...

> “DCF” means the Davies-Carr Family.

> You acknowledge and agree that the DCF (or, as applicable, its licensors) retains ownership of all legal right, title and interest in and to the Media and all intellectual property rights therein. The rights that you have in and to the NFT are as described in this License. The DCF reserves all rights in and to the Media not expressly granted to you in this License.

If you would have opened it, you would have seen that the spreadsheet has exactly what you're asking for... reimbursement rates by DRG/CPT code and insurer. You're right that in many cases the rates paid by different insurers vary significantly.

I believe that was a typo and it's actually around $1k/patient month or closer to $10k/patient year.

Looks like this one is free and also covers a wider breadth of ML topics (though perhaps doesn't cover NNs in as much detail -- I don't have a paid copy of nnfs).

Just did a quick scan and looks pretty good! Would it be possible to add an option for exporting the raw code (maybe broken down by chapter/section) separate from the notebooks? Ideally this would run self-contained without relying on state buildup in the notebooks.

The reference that I posted elsewhere in this thread is pretty thorough: http://web.stanford.edu/~diamondr/jmp_final_all_files.pdf

Sure they can. That there is a natural bound relative to other fundamentals in no way means that the absolute price cannot unboundedly increase. Any in any case, the most thorough spatial equilibrium analysis suggests that there is natural agglomeration of high skill/wage (locally positive feedback). The reference is Diamond (AER 2016), but the working version of her job market paper is a bit more complete: http://web.stanford.edu/~diamondr/jmp_final_all_files.pdf