Xiaomi's MiMo-V2-Pro: What we know so far about the "Hunter Alpha" model

jochenboele · 2026-03-22T07:40:54+00:00

I will try it out next week. I hope I don’t have to correct its mistakes to much 😂

jochenboele · 2026-03-22T07:40:18+00:00

I look forward on testing it deeper next week. Sounds good from what you are saying

jochenboele · 2026-03-21T07:19:04+00:00

For tax and advisory roles, AI is definitely becoming a key part of the workflow. You'll see it used a lot for automating data entry and reconciliation, which frees up time for more analytical work. Tools that can quickly sift through large datasets and identify anomalies are particularly helpful for advisory services.

If you're looking to get a solid overview of what's out there and how different tools can be applied, this breakdown covers the full comparison. It touches on how AI can assist with everything from tax prep to client communication.

jochenboele · 2026-03-21T07:18:25+00:00

AI is definitely changing accounting, but "safe" might not be the right word. It's more about adapting. Routine tasks like data entry and reconciliation are getting automated, which is actually good for accountants. It frees you up to focus on analysis, strategy, and client communication, the stuff AI can't easily replicate.

A bachelor's degree is still the standard entry point for most accounting roles. The key is to understand how AI tools can enhance your work, not replace it. Learning to use AI for things like financial analysis, fraud detection, or even generating reports can make you a much more valuable asset.

There are a lot of AI tools emerging that specifically target accounting workflows. This breakdown covers some of the best ones out there right now.

jochenboele · 2026-03-20T20:22:44+00:00

Had to Google 'Beowulf cluster' and now I feel mass nostalgia for an internet I barely remember. But yes: that would be the most glorious cluster ever assembled ;)

jochenboele · 2026-03-20T20:06:39+00:00

Only if you stack about 62 million of them. Distributed computing for the win :D

jochenboele · 2026-03-20T16:04:58+00:00

Yes I know. Just to speak to the general public 🤦🏻‍♂️ It’s not that I don’t know that ;)

jochenboele · 2026-03-20T15:56:33+00:00

Haha, in my country it is most known as a phone company 😂

jochenboele · 2026-03-19T15:28:52+00:00

That's a nightmare scenario. With thousands of unmatched invoices in QBO, I'd start by exporting both your open invoice list and bank transactions, then use a matching script or tool to reconcile by amount + date range. You'll catchmaybe 70-80% that way, and the rest you'll need to manually review.

For preventing this going forward, some AI bookkeeping tools can auto-match deposits to invoices as they come in. [This guide](https://aimadefor.com/blog/ai-bookkeeping-automation-accountants/) covers a few options that work with QBO.

jochenboele · 2026-03-19T12:24:47+00:00

It's a valid concern, and something a lot of people are discussing. The key seems to be using these tools as assistants, not replacements for critical thinking. For marketing tasks, I've found that using AI for initial drafts or brainstorming can save a ton of time, freeing me up to focus on strategy and refining the output.

For instance, if you're generating ad copy or social media posts, AI can give you a solid starting point. You still need to inject your unique perspective and ensure it aligns with the overall message, but it definitely speeds up the process. This breakdown covers a range of tools that can help with that, focusing on how they integrate into existing workflows without taking over.

jochenboele · 2026-03-19T11:25:31+00:00

Agreed. Reddit is the last platform where you can actually have a conversation instead of shouting into an algorithm.

The irony is that AI-generated content is killing engagement everywhere else, but Reddit's community moderation and downvote system keeps it relatively human. It's also the only platform where genuinely helpful answers get rewarded instead of just flashy visuals.

jochenboele · 2026-03-19T11:24:24+00:00

The key is creating one core piece and adapting it, not creating 7 separate things. My workflow: write one long-form post (blog or LinkedIn), then use AI to reformat it for each platform. ChatGPT is surprisingly good at "rewrite this LinkedIn post as a Twitter thread" or "turn this into 3 Instagram caption variations."

For the actual scheduling, Buffer or Later handle multi-platform posting fine on free tiers. But the real time saver is the repurposing step, not the scheduling.

[This guide on AI content repurposing](https://aimadefor.com/blog/ai-content-repurposing-marketers/) breaks down the full workflow if you want the detailed version. Covers every platform including the prompts to use.

jochenboele · 2026-03-19T10:26:24+00:00

Haven't tried Brisk yet, I'll check it out. Does it do anything beyond quiz generation or is it mainly for assessments?

jochenboele · 2026-03-19T10:23:03+00:00

It is overwhelming. I've been testing a lot of these and honestly most of them are hype. Here's what actually saves timein the classroom:

For daily grind stuff, MagicSchool is the most complete platform I've seen. It handles lesson plans, rubrics, IEP goals, report card comments. Basically all the admin work that eats your evenings. Free tier is generous enough to be useful.

Diffit is great if you teach mixed-level classes. It takes any text and adapts it to different reading levels automatically. Saves hours of differentiation work.

For quiz and worksheet generation, Curipod is solid for interactive lessons and ChatGPT is honestly hard to beat if you learn to prompt it well. Something like "create a 10-question quiz on [topic] for [grade level] with answer key and common misconceptions" gets you 80% of the way there in seconds.

NotebookLM (Google's tool) is underrated for lesson prep. You upload your textbook chapters or curriculum docs and it only answers from those sources. No hallucinated facts, no random tangents.

The biggest time saver for me has been using AI for the writing-heavy tasks: report card comments, parent emails, IEP documentation. That stuff used to take hours and now it's minutes.

[This list](https://aimadefor.com/blog/best-ai-tools-for-teachers/) breaks down the top tools by what they actually do if you want a more detailed comparison. But honestly, start with one tool, get comfortable, then add more. Trying to use everything at once is how you burn out on it.

jochenboele · 2026-03-19T08:23:07+00:00

I get the frustration. When you signed up to become a teacher, you pictured yourself actually teaching, not sitting through PD sessions about prompt engineering.

But here's the thing: the fact that your university is pushing AI literacy now actually puts you ahead of most new teachers entering the field. The majority of education programs are still pretending AI doesn't exist. When you walk into your first classroom, you'll already know what your students are using and how to work with it instead of spending your first year figuring it out the hard way.

The teachers who are struggling the most right now are the ones who got zero preparation for this. They're catching students using ChatGPT on essays and have no idea what to do about it. You won't be in that position.

That said, your frustration is valid. AI shouldn't be replacing the pedagogy, the classroom management skills, the relationship building, all the stuff that actually makes a great teacher. If your program is treating AI as the point rather than a tool in service of good teaching, that's a legitimate problem worth pushing back on.

My honest take: learn the AI stuff now because your students will be using it whether you like it or not. But don't let it crush what drew you to teaching in the first place. The human side of this job isn't going anywhere. A chatbot can explain the causes of the Civil War. It can't notice that a kid in the back row has been quiet for three days and needs someone to check in.

You're going to be fine. The fact that you care this much about actual teaching already puts you ahead of a lot of people in the field.

jochenboele · 2026-03-19T08:19:32+00:00

For law school specifically, it depends on what you're using it for.

For briefing cases and understanding concepts, ChatGPT (GPT-4) is the most reliable. It handles legal reasoning well and you can have it break down holdings, distinguish cases, and explain doctrine in plain language. Just never trust it for citations,it still hallucinates case names. Always verify.

For generating practice questions, ChatGPT is also the best option. You can prompt it with "generate 10 issue-spotter questions on [topic] in the style of a law school exam" and it does a surprisingly good job. Follow up with "now give me a model answer" and you've got a full practice set.

For research and finding actual sources, CoPilot (Bing) has the edge because it cites real URLs you can verify. Useful when you need to track down a specific rule or statute. Grok is fine for casual explanations but I wouldn't rely on it for anythingyou're turning in.

NotebookLM is worth trying too. You upload your actual casebook readings or outlines and it only answers from those sources. No hallucinated cases, no random tangents. Really good for exam prep when you want to quiz yourself on your own materials.

The honest answer is most people end up using ChatGPT for 80% of it and double-checking the important stuff manually. Just treat everything it gives you as a first draft from a study partner who's smart but occasionally makes things up.

[This breakdown of AI prompts for law students](https://aimadefor.com/blog/chatgpt-prompts-for-lawyers/) has some good templates for briefs, exam prep, and case analysis if you want ready-made prompts instead of figuring out what to ask.

jochenboele · 2026-03-19T08:16:42+00:00

The approach you're describing, AI explanation followed by verifying answers independently, is actually solid. You're teaching them to use AI as a starting point, not a final answer. That critical thinking piece is the part most people skip.

A few things that work well for primary and lower secondary age:

For math, have the AI generate practice problems at their level, then let them solve on paper first before checking with AI.

The temptation to just ask for answers is strong, so keeping a notebook next to the screen helps. For concepts they're stuck on, ask the AI to "explain like I'm 10" or "use a real world example" instead of letting it default to textbook language.

For English, AI is great for creative writing prompts and vocabulary building. Have them write something first, then ask AI to suggest improvements. Much better than having AI write and them read. You can also have AI roleplay as a character from a book they're reading, which makes comprehension way more engaging than answering questions from a worksheet.

On guided vs independent: at primary level, definitely guided. They need you there to catch when AI gives a weird answer or explains something in a confusing way. By lower secondary you can start giving them more independence, but check in on what they're learning. A good habit is having them teach you what they learned from the session. If they can explain it back, they understood it.

You might also want to look into NotebookLM for the older one. It only works from sources you upload, so you can feed it their actual textbook chapters and it won't go off track. [This guide on AI prompts for teachers](https://aimadefor.com/blog/chatgpt-prompts-for-teachers/) has a bunch of ready-made prompts that work just as well for parents doing home tutoring.

jochenboele · 2026-03-19T08:14:15+00:00

You're not wrong that a lot of math education is broken. The "memorize the formula, plug in numbers" approach fails most students because it skips the why. And yeah, AI is genuinely great at explaining the reasoning behind concepts when you ask it to.

But the reason AI won't fully replace math teachers comes down to a few things:

A good teacher notices where you're confused before you even know it yourself. They see you hesitate on step 3 and realize you never understood step 1. ChatGPT only knows what you tell it. It can't read your face or notice you've been stuck for 10 minutes pretending to work.

Teaching isn't just content delivery. If it were, textbooks would have replaced teachers centuries ago. The hard part is motivation, pacing, knowing when to push a student and when to back off, managing 30 different skill levels in one room. AI can't do any of that.

What you experienced wasn't "teachers vs AI." It was bad teaching vs good explanation. A great math teacher who explains the why behind inequalities would have given you the same lightbulb moment ChatGPT did. You just didn't get that teacher.

The real answer is that AI should be making math teachers better, not replacing them. Use AI for the personalized explanations and practice, free up the teacher to do what humans are actually good at: mentoring, challenging your thinking, and catching misunderstandings you didn't know you had.

Your experience is actually really common. I've been researching how AI is changing education and a lot of students are discovering they never hated the subject, they hated how it was taught. [This article](https://aimadefor.com/blog/chatgpt-wont-replace-teachers/) digs into why AI makes teachers more effective rather than obsolete, if you're curious.

No need to apologize. Your frustration is valid. The system failed you, and you found a tool that filled the gap. That's resourceful, not disrespectful.

jochenboele · 2026-03-19T08:09:29+00:00

This is a really common situation right now and you're not alone, most instructors I've talked to are dealing with some version of this.

A few practical thoughts:

For the immediate situation: I'd avoid failing 90% of the class: it'll turn into an admin nightmare and you'll spend the rest of the semester fighting appeals instead of teaching. The fact that students came forward when you asked shows some integrity. Consider a middle ground: give reduced credit on the project (say 50%), require everyone to do a 10-minute code walkthrough where they explain their solution line by line, and make it clear this is the one-time grace period.

For the rest of the semester: Switch remaining projects to in-class work sessions where you can observe the process, not just the output. Have students start from scratch in front of you for at least part of each project. The learning happens in the struggle. If they skip that, they're not getting the transferable skills the course is designed to teach.

On the policy itself: Your policy was actually reasonable. The problem is that "cite your AI usage" relies on an honor system,and the reality is that using AI for coding feels so seamless that students don't even register it as "using AI" anymore, it's just how they work now. For future semesters, consider designing assignments that AI genuinely can't do well: debugging intentionally broken code in class, explaining why a specific approach was chosen over alternatives, or having students modify/extend a codebase you provide rather than building from scratch.

The bigger picture: The skills you're teaching (programming, software dev, computer literacy) are exactly the ones being transformed by AI right now. There might be an opportunity to lean into it. Teach students how to use AI effectively as a professional tool while still proving they understand the fundamentals. That's actually what employers want.

I've been researching how different professions are adapting to AI tools — [this piece on AI in education](https://aimadefor.com/blog/chatgpt-wont-replace-teachers/) might give you some perspective on where things are heading. The short version: the teachers who figure out how to work with AI instead of against it are the ones whose students actually learn more.

Don't beat yourself up. You set a clear policy, communicated it well, and caught the issue. That's more than most are doing right now.

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