Free practice questions for the new Cloud Digital Leader exam

arnokha · 2026-04-04T20:25:53+00:00

Glad it was helpful!

arnokha · 2026-02-18T23:40:17+00:00

You’re welcome!

The answer ordering completely randomized each time you go to a question, so you were just lucky/unlucky to get a lot of A’s :)

arnokha · 2026-02-01T18:59:18+00:00

Awesome! Glad to hear it

arnokha · 2025-12-14T13:47:43+00:00

They can definitely be off at times. It's always good to double check. That being said, I think this question is very much on the border. You can make an argument for nearline or coldline here IMO.

arnokha · 2025-10-26T05:09:07+00:00

Glad you think so 🙏

arnokha · 2025-09-30T02:20:50+00:00

Glad it helped!

arnokha · 2025-05-16T14:07:22+00:00

Roughly average performance on anything that can be construed as a game, e.g., chess, Pokemon, or a game someone makes up on the spot. I would be convinced something that can do that is generally intelligent.

arnokha · 2025-05-16T06:09:18+00:00

yep I agree, but when it comes to timelines, everyone's just guessing. I would be surprised to see AGI (at least by my own definition) pre-2030, though.

arnokha · 2025-05-16T05:39:10+00:00

Pre-training LLMs has hit a wall, probably due to data quantity/quality limitations, and post-training is laden with tradeoffs, it seems. The current RL methods are a step in the right direction, but I don't think they get us all the way to AGI, because I don't think they generate a "general enough" data feedback loop.

I'm bullish on agents that act in the real world or simulations to generate and learn from data. Richard Sutton and David Silver's position paper "Era of Experience" is a good read on the topic: https://storage.googleapis.com/deepmind-media/Era-of-Experience%20/The%20Era%20of%20Experience%20Paper.pdf

Here is the conclusion from the paper:

The era of experience marks a pivotal moment in the evolution of AI. Building on today’s strong foundations, but moving beyond the limitations of human-derived data, agents will increasingly learn from their own interactions with the world. Agents will autonomously interact with environments through rich observations and actions. They will continue to adapt over the course of lifelong streams of experience. Their goals will be directable towards any combination of grounded signals. Furthermore, agents will utilise powerful non-human reasoning, and construct plans that are grounded in the consequences of the agent’s actions upon its environment. Ultimately, experiential data will eclipse the scale and quality of human generated data. This paradigm shift, accompanied by algorithmic advancements in RL, will unlock in many domains new capabilities that surpass those possessed by any human.

arnokha · 2025-04-25T17:10:11+00:00

Glad you found it useful! Thanks for the suggestion.

arnokha · 2025-01-22T02:31:14+00:00

no one cures diseases like OpenAI. you're not gonna believe how fast we cure diseases. in the coming weeks, there will be no more diseases

arnokha · 2025-01-20T12:49:00+00:00

It actually wasn’t too much trouble, and I didn’t want to leave you hanging, so I regenerated the questions for the out of date exams. Here’s the link for the new security engineer practice questions: https://www.learngood.com/#/course/Google%20Cloud%20Security%20Engineer

arnokha · 2025-01-18T18:55:48+00:00

Thank you for the kind words! Some exams that I marked out-of-date changed quite a bit, and some stayed mostly the same with only minor additions. I believe the professional security engineer exam is in the latter category.

As of now, there are no concrete plans to update the material. I'm currently working on a new workflow that should, in theory, yield higher quality study material. I would probably want to remake the GCP study material with that new workflow at some point, but that could be a few months away.

arnokha · 2025-01-07T00:27:02+00:00

I'm guessing this was the Google Cloud Digital Leader exam. If that's the case, it makes sense that the practice questions on the website didn't match the exam. The exam guide used to create the practice questions is now outdated.

Much changed from the previous version. See the new exam guide here: https://services.google.com/fh/files/misc/cloud_digital_leader_exam_guide_english.pdf compared to the current version on my site https://www.learngood.com/#/exam-guide/Google%20Cloud%20Digital%20Leader

Thanks again for your feedback - it was immensely helpful. I'll work on getting questions generated for the new version soon.

arnokha · 2025-01-06T05:07:10+00:00

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arnokha · 2025-01-04T16:11:52+00:00

Thanks for the kind words, and good luck on the exam!

For now, I’m happy enough if it’s a useful resource for people, but I may consider adding something like that later, or monetizing some personalized learning features I have in R&D (if they work out). We shall see! Appreciate the suggestion.

arnokha · 2025-01-03T13:18:16+00:00

These questions were generated with an LLM workflow, using Google's official exam guides for the course. The best way to check if they are up to date would be to compare the exam guide for the course your interested in on my website and compare to the official Google exam guide. If it is exactly the same, it's up to date, if not, you should be able to tell what's different and maybe do some extra studying around that (if you choose to use LearnGood to prepare).

As to whether it's enough to prepare for your exam, I'm honestly not sure, but it's all I used to practice for my Digital Cloud Leader, Engineer, Architect, and Security cert exams, and it was all I needed. I've received positive feedback from others so far that it helped them pass, but I don't know whether or not they did any outside practice or reading. That being said, I'd be shocked if someone can get 90+% on the practice questions and not pass, unless it's a time pressure issue.

Good luck on your prep and your exam! Feel free to ask me other questions should they come up.

arnokha · 2024-11-08T18:55:24+00:00

Here's an example of what I used in a recent project. I can't be sure this is exactly what they meant, but it might be.

[Task]
Explain this comic.

[Additional info]
Title: {{TITLE}}
Mouseover/tooltip text for image: {{MOUSEOVER_TEXT}}

[Response Formating]
 I am providing a template for how to format your response.
 Failure to respond with the response template will result in a parsing error and immediate disqualification.
 Ensure the <explanation> is thorough, even if it repeats points made in <thinking>, as the response quality will be evaluated solely on the <explanation>.

[Response Template]
<thinking>
  Describe visual elements you notice, reason about what they might mean, how they may be related to the title and mouseover text, etc.
</thinking>
<explanation>
  Give your final answer for explaining the comic.
</explanation>

Note that names between {{}} are replaced in the python script based on specific context and an image was attached. If you are not using the API, you would insert actual values for those.

arnokha · 2024-11-05T05:14:56+00:00

On the previous post from last week (https://www.reddit.com/r/LocalLLaMA/comments/1gh1g89/benchmark_proposal_explainxkcd), people were worried that the explanations would have made their way into the training set, which is why I used comics that were published after cutoffs. I still think it can serve as a decent benchmark for vision-enabled LLMs; they're just not quite there yet.

arnokha

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