hellodanylo

If need anything more complicated than simple $var substitution, it's time to use a general purpose scripting language with appropriate libraries to generate your data structure. A half-baked template DSL will never work.

Why not buy a giant display panel and connect it to a computer that you fully control?

I don't seem to understand where OpenAI's market segment ends and Azure's begins.

> I question just how much productivity you've gained.

Me too. It's an empirical question to be answered by those who will dare to try.

> It's kinda like self-driving cars

Strong disagree. Yes, neural nets are blackboxes, but the generated code can be idiomatic, modular, easy to inspect with a debugger, etc.

> more formally specify the problem that an LLM is being asked to solve.

That would be a great direction to explore.

This should give a second life to Test-Driven Development.

One of the under-appreciated wisdoms of TDD is that there is a complexity asymmetry in many problems between finding a solution and (fully or partially) verifying it. Examples of asymmetric problems: inverting matrices, sorting an array, computing a function's gradient, compressing a byte stream, etc.

Human writes the easier part -- the test suite, the language model writes the harder part -- the solution. This can be a net gain in productivity.

There is a major flaw in placement of the EC2 instance in this diagram.

Each EC2 instance has 1 or more Network Interfaces, where each Network Interface resides in 1 subnet and can have multiple public and private IP addresses. The diagram currently suggests that an EC2 instance is located in a single subnet — it’s not. Each Network Interface connected to an EC2 instance is only required to be in the same Availability Zone where the instance was launched.

I would rephrase this concern as "dconf is not a stable API" rather than "you are not supposed to do this". It's my computer, I am supposed to do whatever I want, but using unstable API comes with costs that should be understood.

There is also ECR Public Gallery, which mirrors many public images from DockerHub. https://gallery.ecr.aws

I find SQL very hard to use when the data schema and/or transformation graph needs to be dynamic (e.g. depends on the data itself). It's hard to make SQL dynamic even at build time -- Jinja+SQL is one of the worst development experiences I have ever had.

Yeah, I am also struggling to interpret the metrics in this post positively.

The 50% success rate is also best out of 3200 completions. For best out of 1 completion, the success rate is in low single digits.

I think the lesson here is that these models bring a lot more value when: 1. you have unit tests, 2. can afford compute/time to let the model try many solutions, 3. have enough isolation to run unverified code.

> I'm sure the recovery process is not as easy.

A lot of services offer one-time backup codes and connecting multiple 2FA devices. Making Yubikey a single point of failure is certainly a bad idea.

> Authenticators are fine, except if you lose a couple of smartphones too close together, or you need a team to access one account.

When you enable TOTP with a service, you can extract the TOTP secret and do all of the above with it -- backup to storage, copy to new devices, distribute to multiple people, etc.

In my recent job, I committed Jupyter notebooks to Git, and they tend to be giant JSON files. I had 10x SLOC of anyone who did not commit Jupyter notebooks.

If you had 3 days to find bottom 50% of devs to be fired, what would be your heuristic?

Sorry, you are right. I need another coffee today.

[retracted]

I have been working on an iOS/MacOS app that reminds me to stand up and/or take breaks at certain intervals. It's using the iPhone's camera and local computer vision to collect ground truth.

Drop me an email at "hello at danylo dot me", if you would like to beta test with me. Or watch an informal demo here: https://www.youtube.com/watch?v=zvzHrwjU9TU

A lot of concerns are focusing on (person) -> (tiktok) -> (CCP) data flow. What about the reverse information flow?

A foreign political party tuning the algorithm to affect public opinions? I think this is even more impactful than data snooping. It's also a lot harder to detect and prevent.

What if US government makes a (secret) deal with China to get data from them? It might seem unlikely today, but politics can change any time. Data markets can be fairly efficient. Once someone has your data, they can always (re)sell it to the highest bidder.

They use various clustering algorithms and heuristics, but it's true that it only gives a lower bound at best.

For example: https://youtu.be/D_Eqz8_Jm2E

I keep getting tricked by ML referring to either the programming language or the subfield of AI.

Do users have incentive to document and share the connections, other than helping the community's long term goal?

Absence of such incentive appears to be the reason that open-source software is not always perfectly connectable -- few people have a significant incentive to ensure this design goal.

I think JIT and custom code is the same requirement in this discussion. In Chrome's case, the V8 engine is a JIT compiler from JS to ARM instructions. The code of V8 can be vetted during the review process, but the ARM instructions that it will generate (just in time) can not.

> 3.3.2 An Application may not download or install executable code. Interpreted code may only be used in an Application if all scripts, code and interpreters are packaged in the Application and not downloaded. The only exception to the foregoing is scripts and code downloaded and run by Apple's built-in WebKit framework.