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157 karma · joined May 10, 2016
remote: Repository not found. fatal: repository 'https://github.com/frigadehq/homebrew-tap/' not found
Yes, assuming its the first time you've interacted with an API endpoint and don't have cached payment requirements.
>Is there a reason why you wouldn’t pay ahead of time? I just understand why you couldn’t buy a few dozen/hundred/thousand dollars worth of credits, and wait until it runs low.
This would require manually integrating each vendor, which is totally valid if your agent performs a lot of a single type of task, but we suspect over time there will be huge value in agents being able to dynamically select tools / apis they want to use to accomplish their tasks, and dynamically pay for what they use
This depends on the implementation on the underlying network, but basically the spending signs an authorization for transfer, and the merchant either settles that onchain themselves or delegates to what is called a facilitator that settles on their behalf. On EVM chains for the exact payment scheme this leverages EIP-3009 signatures
If you're at a giant company, the answer is likely no, there's enough politicing and paperwork where the highest impact thing to be done by a manager is likely not coding.
If you're at a startup / smaller more nimble org in a big company, the answer is likely yes, if you've gotten to the point where you're a manager, in theory you're a very good engineer and you should spend your time coding, but on things that aren't on critical path. Bug backlog, experimental things with no hard deadlines, proof of concepts, all of these are valuable things. Leading from the front is also just generally good with smaller groups.
Also under discussed by people having these debates (typically managers), is not acknowledging how bad most managers are at coding, especially if their job hasn't required them to code in a while. I see all the time that managers look for any excuse not to code, because it would reveal to their team that they're at best an L4 level coder after being in management for 5-10 years.
About Zora: * Zora is a decentralized market protocol for NFTs * Globally distributed team, remote first but with an NYC office * Focused on creators and artists * Great comp and equity * Amazing entrypoint for people who want to get in to crypto, no crypto / web3 experience required, Zora is a crypto native company!
About you: * Terraform / infra wizard * Enjoy startup vibes * Comfortable with AWS, Datadog, GCP * If you've got experience with data thats amazing * Interested in crypto / NFTs / Web3
Shoot me an email! erik @ zora.co
Models:
- Models are structured as python packages, each model inherits a base class
- base class has define how to train, and how to predict (as well as a few other more specific things)
- ML engineer can override model serialization methods, default is just pickle
Infra:
- Code is checked in to github, Docker container built each merge into master
- Use Sagemaker BYO container to train models, each job gets a job_id that represents the state produced by that job (code + data used)
Inference / deployment:
- Deploy model as http endpoints (SageMaker or internal) using job_id
- Have a service that centralizes all score requests, finds correct current endpoint for a model, emits score events to kinesis, track health of model endpoints
- A/B test either in scoring service or in product depending on requirements
- deploy prediction jobs using a job_id and a data source (usually sql) that can be configured to output data to S3 or our data warehouse
So far this has been pretty solid for us. The tradeoff has been theres a step between notebook and production for ML engineers which can slow them down, but it forces code review and increases the number of tests checked in.
I also just really like Chris' work and trust him to make the right calls until proven otherwise.