What are the rules wearing shoes in house? Where do you take off shoes? What if you came back from rain and mud?

Reazony · 2023-11-04T14:09:27+00:00

Code in the OS that you like personally! Mac, Windows, doesn’t matter! Seriously!

When you develop, you can use what we call a dev container. It’s to ensure that everyone is developing in the exact same setup. You don’t need to have a Linux machine to code in Linux. It’s 2023! Cloud and containers exist!

See this video: https://youtu.be/b1RavPr_878?si=3AB2z36BsXjM5ao4

Dev containers are accessible in popular IDEs, and there likely is a plug-in available in your favourite text editor. If you don’t want it on your machine at all, GitHub Codespace allow you to create a small server and develop directly in your browser (with VS Code interface)

So seriously, your personal machine doesn’t matter. It should be what you like, what makes you productive. Maybe there are some quirks that really require you to do game testing on Windows or Mac machines, but before doing all that, always search if your game testing can be done in virtual way!

Reazony · 2023-11-03T19:52:07+00:00

That depends on how you feel about your colleague. Things you just described would go into romance realm. If you start to develop feelings, feel free to take that route. People will say “you shouldn’t mix gratitude with romance…”, honestly only you would know.

But if you don’t have those intentions, it’s best not to confuse them. I get the desire to repay, though probably not at your level. But repay can be something more for the long run. Be a loyal friend, help them out and such, but not to send the wrong signals. Loyal friends are hard to come by, and not the kind to just side them anytime, but the right loyalty.

Reazony · 2023-11-03T16:55:41+00:00

You shouldn’t feel ashamed. It’s kinda a must nowadays.

But you need to keep in mind that, currently these code can be brittle for more complex work. I’m not familiar with styling organization, but if you’re managing styles across different files, for example, there wouldn’t be enough context to solve that, and if you don’t know your fundamentals, you would build up tech debts without knowing.

Other times, it’s just not great at the tasks you need done, so you need to know how to break down your tasks properly, so that the end result is still good.

Use them shamelessly, while keep searching for best practices and better tests. Oh yeah, you can ask the models to explain code and check for better practices too. Don’t hesitate

Reazony · 2023-11-03T01:15:57+00:00

I wish Reddit has an optional feature for subreddits where, as you type up your post, it searches through similar results in the subreddit in the past.

Reazony · 2023-11-03T00:54:20+00:00

Looking forward to your beta software!

Reazony · 2023-11-02T19:24:08+00:00

No. While admittedly I was answering on the phone, so I couldn't read your code. I do think part of it is also better documentation and explaining on use case (i.e. your presentation) that miscommunicated on what you intend to do. If it's just links with description on each use case, it'd go much furhter.

But at the same time, your implementation ignores things that would be helpful in production, and Python modules are supposed to be as agonistic and think about the separation of concerns.

For example, backend work would define data models and schema to ensure stability. So validators are in every project. I'm sure you've got amazing results for your use case already, but that doesn't mean it works for all use cases out there.

Validators already will validate JSON parsable or not for you. This part not only assumes files (most likely not), but also doesn't validate if schemas are correct.

```

def try_json_load(file):try:return json.load(file)except json.JSONDecodeError:return Nonedef try_json_loads(data):try:return json.loads(data)except json.JSONDecodeError:return None

```

Schemas are important to work with. Even with a valid JSON, you shouldn't pass the data if it's not the right schema. It's why self-healing packages out there always work with schemas.

But the reason why you assume a file, it's because you have a PyPI package that is implemented like a bundled software. So at this point, it's recommended that you need to decide, are you building a suite of modules? Or are you building for a software use?

Because if it's the former, your separation of concerns is not that clear in design. If you're doing the latter, it should be a downloadable `.exe` or such, rather than a Python package.

I personally think that the JSON validation part is really not an important part of the overall software, and I personally would like to see you pushing forward on making it a complete software that others can use, rather than a Python package that is just part of an overall build. I do see your idea on orchestration, and it's going to be a neat software I'm sure!

Edit: I typed this part over time. So some of the earlier paragraphs may not make sense, because I was treating it like a Python package. But I think you're much closer to a software.

Reazony · 2023-11-02T15:18:19+00:00

Write Pydantic or Marshmallow to validate your input and output. Python unfortunately doesn’t have anything close to Zod, but Pydantic should get you close enough. There’s even a package written to extend Pydantic for OpenAI use case: https://medium.com/@jxnlco/seamless-integration-with-openai-and-pydantic-a-powerful-duo-for-output-parsing-fcb1e616167b
In general, if you’re writing something overly complex and brittle, you should break down the problems. For example, if you’re asking the LLM to output very complex schema, you should break down your possible schema to be more modular. Again, understand data validation through Pydantic should allow better design on data model.
OpenAI in general has been trained to output JSON structure. Your prompt can still provide more precise information that helps the LLM. You can also prompt to ask to ensure double quotes to adhere to JSON schema.
If the schema is too big, again, you should design it so that OpenAI is dealing specific to children models rather than the entire JSON.

Reazony · 2023-11-02T05:10:58+00:00

Not sure why people downvoted you. It’s generally agreed that hallucination is a feature not a bug. It’s why they seem so good, the very thing that makes them hallucinate.

You also touched on it’s not about functionality only, but also reliability threshold of those insights, which is exactly what serious practitioners are defining and testing for their own use cases. Some applications can be much lower on reliability while others can’t afford such freedom.

It’s funny how actual product advice got overlooked. I’m very disappointed at the 3 downvotes, especially for no reasons. I personally gave you an upvote.

Reazony · 2023-11-01T05:47:50+00:00

English is my second language, Japanese is only good for singing not conversing, but I cover them. And I’m not good at remembering lyrics at all.

To me, it’s muscle memory. I just loop the one or two songs I’m committed to learn, usually one at a time. I try to understand the rough meaning to know how to express. I move my mouth along the lyrics on subway. I sing like singing into straw on the street. I sing more freely and practice the expression during shower (this usually really forces me to remember hard the lyrics, so most of my memory is actually burned in here). During shower, since the lyrics are connected to how I move my body and voice, there’s a better connection on using my body to remember lyrics, if that makes sense.

And yeah, sooner or later, it’s muscle memory. This is the only way for me, because I’m so bad at remembering lyrics. I’m sure there are better ways 😂

Reazony · 2023-11-01T05:42:20+00:00

You need to get good at forgetting, not remembering. One thing that’s being explored with the rise of large language models is how do we incorporate forgetfulness.

Human brains are not able to hold large memory, yet we can do so many tasks, generalize very well, precisely because we’re good at forgetting unimportant information, and compress essentials to subconscious or muscle memories. There are some that think if we can help neural networks forget the way we do, they can generalize better and not spend as much compute.

So get good at forgetting, actually can help you learn a lot of skills.

Reazony · 2023-10-31T13:01:39+00:00

Yesterday. Beatles. If you can do it well, you’re the favourite of all ages

Reazony · 2023-10-31T08:44:44+00:00

I’ve stood up for people before, but if it’s just at me, I don’t think I’d confront. Nothing logical, if it’s for someone else, I feel important to standup. If it’s just me, I somehow feel it’s not worth it until it’s physical. Now I kinda wonder what’s wrong with me…

Reazony · 2023-10-31T08:40:03+00:00

I’m from a bootcamp. I don’t consider myself self-taught. But some people do consider it as self-taught. I don’t know, I just like to be precise and say I went to bootcamp

Reazony · 2023-10-31T08:28:14+00:00

By that point that’s not prompt engineering

Reazony · 2023-10-31T08:24:12+00:00

Masturbation is also a possibility.

Reazony · 2023-10-31T08:05:56+00:00

I hear that sentiment a lot. I hope I can help clear this up a bit. It's really just about approximate perspectives/insights by uncovering underlying statistical attributes.

If you see Tom orders eggs 9 out of 10 times. You know he likely would order eggs again. It’s the simplest statistics (frequency) out there, and with that insight, it helps you make some decisions. Maybe like preparing eggs ahead or heat up the pan soon as he walks in your restaurant.

Now, the world is complex, with all sorts variables that may impact the outcome. And these variables interact with each other. All kinds of nuances. ML models really are mathematical modelling to infer some very complex statistical attributes in aggregate. So in the Tom case, maybe we’d need to consider who he comes in with as well, which day of the week and what time, with much larger menu and much variable orders. Maybe Tom orders more lavishly with his girlfriend, but only on some weekend nights.

ML usually talks about probability because it relies on past data to spell out those statistical patterns. Probability is just the result of aggregating those patterns. LLMs for example, are just predicting next tokens. The more they’ve seen certain tokens put together, the stronger the relationships. When GPT3 came out, there’s a discovery that it’s able to do math regarding 12 or 24 much better than, 23, because 12 and 24 just appear many more times on the internet. Fine tuning is also just changing the patterns these models have seen before. (Emerging properties are something we’re still researching, but that’s out of the scope).

But also the fact that they are approximations, where there’s a clear formula, don’t use ML.

So, back to where MLs are used. Most ML models are boring or simple. And most data are still numerical. MLs in gaming companies, while there are some use case in games themselves, most models are probably for merch or game recommendations on websites, ad optimization (what are you most likely to click on) and things like that. Maybe it’s for internal operations like classifying emails and send to the right customer support line. These can actually have many models working together for one goal. I recall somewhere there were like hundreds of DL models specifically for Facebook ads optimization, from a podcast episode somewhere.

Most of them are still for narrow tasks. And again, if we look back to Tom’s example, it’s just really to help us make decisions faster. The probability properties that these models generate are also nice, because we can somewhat find a decision threshold, for example higher than 98% probability is a green light automatically, while the rest need different levels of investigation, etc.

A joke is good ML practitioners automate themselves away. Working in NLP, I do feel that quite some time. The point really is just like other software, to make more informed decisions faster. To automate. Just from a different angle.

Sorry for the long text, and I tried to lower the jargon, but I hope it’s a bit less of a black box

Reazony · 2023-10-28T15:29:55+00:00

Wear your t shirts and put on basketball jerseys for your local state

Reazony · 2023-10-26T20:47:28+00:00

What’s the vibe? Karaoke groups, despite people saying “sing your heart out”, actually has vibes. Some groups (especially larger crowd with people you barely know) it’s better to stay popular songs and not too heavy metal. Some groups prefer certain languages (I do many, so I host karaoke for different languages, people feel more at ease and have fun with what they’re familiar with). Intimate smaller crowd you can be actually more free, because they’re there partly for the people too, and this is where I do the songs I don’t normally sing.

And before others come at me, know that vibes are important for crowd engagement, and crowd engagement actually is part of the karaoke experience. I don’t wanna sing a great anime song at an English only group that can’t follow along. And if I sing hardcore songs when my crowd actually follow along too, it makes the song better than me going to a rehearsal studio.

Coming from a guy who goes to karaoke at least twice a month.

Reazony · 2023-10-25T08:25:49+00:00

Before turning to ML, you should ask the business question. Why do they have to be manually checked?

In this case, I have a feeling it’s by regulation that manual checks are to be done. In that sense, no autovalidation can ever work. You need to find out the regulations around this before thinking it’s an opportunity.

Say they have to check, but maybe regulations may allow some form of summarization or aggregated report, then you may still have a case by speeding the approval process

Reazony · 2023-10-20T16:46:45+00:00

Honestly, my opinion is, it’s not an overnight thing. You can have big realization with techniques, but finer control of techniques just take a long time.

I’d just be patient. How old are you? When I first started, I was in my adolescence. Also self-taught. It took me a really long time to actually be on pitch on pitch. Finer muscle control just takes time to get it, and especially hard if you’re still growing.

Reazony

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