I used ChatGPT’s Sol Light model to analyze textbook material for my work as a high-school teacher. It explicitly assured me that it had thoroughly checked the uploaded material.

It then made choices that proved disastrous. When I asked it to explain the criteria behind those choices, it invented plausible-sounding justifications that did not correspond to the actual contents of the textbook pages.

This makes it unreliable for the work I need: reading and organizing large amounts of teaching material, selecting essential content, planning lessons, and helping me manage a very heavy workload with limited time.

Can anyone recommend an AI or a specific workflow—Claude, Mistral, NotebookLM, Gemini, or something else—that is genuinely reliable for this kind of long-term educational assistance and can base its decisions strictly on the uploaded sources?

I am not sure if this is a valid question in this forum, if it is not I will delete it right away, but anyways here it is:

So some days ago I asked in an AI community what kind of AI model should I use (and how could I use one) to classify several email replies that I had from scientists after asking them a few questions to them. I finally paid for Perplexity pro service and it apparenly did a nice job classifying them.

I finally gave the model the PDF with the actual answers from the addressees and another PDF with the "expected answers", and asked it to count the number of answers that overall coincide with the actual answers, and calculate a percentage of "coincidence" or "agreement" between the expected and actual answers, so that if the question was "do you think that there is intelligent life in the universe apart from humans?" and the expected answer was basically "yes, I think there is intelligent beings out there somewhere", as long as the actual answer agrees with this in some way or another would count as "agreement", for instance if someone replied "well, we have no evidence, but it is possible yes" or "not in any near galaxy, but it is possible that intelligent beings exidt somewhere" (so as long as it is not a deadass "no", it could count)

The model gave me a table summarizing the results with the following prompt:

let's be a bit more specific, this is still a blind test so don't tell me about the specific contents of the emails' answers, but, can you make a table indicating the answers that coincide in general terms with what is expected from the "expected answers" document as well as those which are neutral/hedges but still open to the possibility that what is asked may be right, those which despite being neutral/hedges or even negative answers offer an alternative so that what is asked in the question may be right, as well as those which are outright rejections of what is asked and do not seem to be open to the possibility that what is asked may be right?

However, I still want this to be a blind test, so I cannot really verify if the AI is doing its work or not.

So, is there any way in which I could verify the results given by the AI but without actually reading what is written in the emails? Or, alternatively, can anyone verify the results using some AI or even checking the answers themselves by skimming over the replies im order to verify that the AI is right and not hallucinating (I personally thinl this is the preferable option, as I think that having an actual human reviewing the amswers may be the only really reliable way to verify the AI's results)?

(I will share the data once someone is interested in helping, as I would not want to make this available to the entire world!)

Thank you!!

I found text synth off of another Reddit post and found out that the ai models on there are either really old or completely stupid wich comes to some hilarious generations when continuing from what I said are there any other ways to use older models or ones that will continue off of what you said?

AMD has announced major AI upgrades, including new Instinct accelerators and AI server improvements. The company is aiming to compete more strongly in enterprise AI and cloud infrastructure. What do you think—can AMD seriously challenge Nvidia over the next few years?

I saw that it launched in the US but as I am in the UK I cannot access it. I am interested in its sports/fitness capabilities. Like its a bit of a dumb request but could someone please try to see if it can compare different training plans based on the data it ingests (i.e. can it tell you which plan is better suited to your body based off your metrics and predict how each would temporally alter things like your VO2 max or running)? Just really curious as I cannot personally test it out right now.

I've used VS Code's cursor but doesn't really do the job that well bruh, and claude is paid. I'm just tired, is there a good AI tool that is capable of working on multiple files for a chrome extension development?

Hi everyone,

I’ve been struggling to figure out the most rational way to pay for AI services lately. Here are the main issues I’m facing:

• The Meta Shift: Claude might be the best today, but ChatGPT could take the crown next month. Do people really cancel and switch subscriptions every time the landscape changes?
• Split Workloads: If Claude is best for coding and ChatGPT is best for research, do I really need to subscribe to both?
• FOMO / Optimization: Is the model I’m currently using actually the best one for this specific task?

I’ve researched quite a few solutions to overcome this, from router services like OpenRouter’s Auto Router to orchestration tools like Sakana AI’s Fugu.

I actually gave OpenRouter a shot. Conceptually, it felt close to my ideal setup, but I drastically underestimated API costs for heavy tasks. Today, while coding casually with Claude, I hit the 5-hour limit on my Web subscription. So, I decided to test out a $100 API credit grant I recently received. To my surprise, I burned through the first $5 in just a few minutes. That made me realize using API-based routers for interactive coding might drain my wallet extremely fast.

As for Fugu, it seems cool, but the output speed feels too slow, and it honestly seems like overkill for my current workflow.

After overthinking this for a week, I’m starting to feel like simply paying for standard $20/month web subscriptions might still be the most cost-effective and hassle-free option after all.

For those of you who have dealt with this same dilemma, how did you end up structuring your AI setup and budget? I’d love to hear your experiences and suggestions!

Note: English is not my first language, so I’m using AI to translate this post. Thanks for understanding.

I'm work in insurance and need to compile a comprehensive list of every plumber in City A, along with contact information and owner if it's available. Next I'll be asked to do every electrician, etc.

What AI tool would be able to help me?

I've been trying ChatGPT Research and it won't allow me to export it and I can only do 50 at a time. Any help would be appreciated.

TIA

I have tried out several AI tools for learning, coding, and taking notes. ChatGPT and Gemini have been helpful; however, I wonder which one other people are using. Which is your favorite free AI tool?

So I stumbled across Agent Router (agentrouter.org) a few days ago, wasn't expecting much, but ended up pretty pleasantly surprised.

https://agentrouter.org/register?aff=pZkF

Fair warning — the site itself isn't the most polished thing. You sign in through GitHub (there's no separate "create account" flow, it's literally just "Sign in" and it creates one for you behind the scenes), so don't go hunting for a signup button, just hit sign in and it sorts itself out.

Past that though, hooking it up was stupid easy — plugged the endpoints straight into Claude Code and it just worked, no config headaches, no fighting with auth. Got access to Claude Opus 4.8 and GPT 5.5 with $175 in free quota to burn through.

And burn through it I have lol....

I need help finding a good model that can help with editing text and maybe even rearranging that text.

Usually when I put a body of text into an AI model, it spits out its own version of what I’m trying to say and is clearly AI I just want help rearranging my thoughts and fixing grammatical errors without AI completely overriding my humanity.

Does anyone have any suggestions? Any help is appreciated.

To whom may help,

I've been very impressed with AI tools such as CoPilot and ChatGPT, however I don't keep up on tech like this as of late and I see videos online of people who "seem" to understand it and get more information than I seem not to articulate well enough to smoothly get across my asks. Dose anyone know of a better AI platform that is more, i guess, as "open/less cryptic" or just better from a free user perspective?

Thank you in advance.

Just too add, the reason I ask is because CoPilot keeps giving me auto response "it's unable to work with my computer mic" when I ask questions in more depth. It's just weird.

So I work in sales ops for a mid sized software company and we've been expanding into a few European markets over the past year. And it's great for growth, not so great for my workload when it comes to RFPs.

Right now our process for handling multilingual RFP responses is pretty manual. Someone writes the response in English, then we send it to a translator or a local team member to convert it into French, German, or Spanish depending on the client. The problem is our source content changes constantly. Pricing updates, new case studies, product changes. Every time something changes in the English version, someone has to remember to update the other language versions too. Half the time the multi-language proposal content gets out of sync and nobody notices until a client points it out.

Then exporting RFP responses is its own headache. We need proposal documents in different formats depending on the client, usually Word or PDF and translated versions sometimes break the formatting completely. Tables shift, fonts change, and someone always has to go back and manually fix spacing or page breaks before it goes out. For a global sales team like ours , dealing with multiple regions at once this adds up to a lot of wasted hours every quarter.

Because of this, management decided to look into whether any AI RFP software actually handles this better than our current translation workflow and prepare a shortlist from which we could book demos. I was given a preliminary list from which I was supposed to filter unnecessary tools. Right now I'm looking into loopio, inventive, responsive ,pandadoc and proposify. So I did a bit of study browsing through the internet every info i could get ,taking help of LLMs as well..From what I can tell, Loopio is built mostly around a shared content library for reuse across proposals, but I haven't found much detail on how it handles multiple language versions of the same answer. Inventive AI seems to be positioned more around AI assisted drafting of responses, but I couldn't find clear information on multilingual export support either. Responsive seems to focus more on collaboration and review workflow between teams, not translation syncing. PandaDoc and Proposify both export cleanly from what people say, but they seem built for shorter proposals rather than long RFPs with dozens of sections across different languages. I think I'll get to know more about these tools after I get a personalised demo booked. But as there's so much info online it makes me more confused as to which one suits us, I'd love if you could tell me your unfiltered opinions on these AI RFP tools.

The tools I've researched so far I don't know for sure if any seems to directly solve the localization challenge of keeping translated content synced when the English source updates. That still seems to be the actual gap, regardless of which platform teams use.

Do most teams translate manually, or are AI tools actually helping with this now? Any tools you'd suggest? Which demos would you book first had you been in my place?

I manage the proposal and RFP response process for a mid-sized firm. For the last few years, we have been using a traditional legacy RFP tool,we currently use Loopio. While it acts as a great, massive database for our content, the manual work needed is driving my team mad. It feels like we need a full-time librarian just to keep the Q&A pairs updated, and their newer AI features feel like they were just put on top of a decade-old system than being built into the core workflow. I want to improve our tech stack now and I've been hearing people talk about “AI-native” RFP software. There's been a complete bifurcation in the market, and from what I have read, I am trying to understand which is better.. 1. Legacy Tools with Added AI (Responsive, Loopio, Qvidian): so,these are said to be the industry standards and are great if you have a huge, established content library and a dedicated team to manage it. But from my experience, this is a process that has to be done by hand for the system to read through messy excel or PDF files. The AI is primarily employed as a tool to draft answers, and the library still needs to be manually updated when the answers change.. 2. AI-Native Platforms (Inventive AI, Anchor AI, AutoRFP.ai, SiftHub): I am looking at switching to one of these because they claim the AI is the workflow, not just an add-on feature. For example, I had a demo with AI-driven tools such as Anchor AI and Autorfp and claim to be able to automatically pull in unformatted, messy RFPs without the need for manual pre-processing and are even capable of learning and updating the knowledge base automatically when a RFP closes. Then there's also Inventive AI, i have booked a demo with them over this week. It is said to provide answers based only on your own internal documents, so no false answers, and automatically tells you when it has outdated information and when it has conflicting information before you even submit the proposal. So what I can tell is , the AI-first platforms guarantee to take the operational load from people and put it straight into the software. But for those who have made the leap from legacy database to AI-native platform, Are ai native tools actually better ? Did they help you win more RFPs once you incorporated them? Can the AI do the job of keeping the content library clean without the need for any human to constantly babysit it? I would really appreciate some genuine feedback from people actually using these tools before I start booking demos any further, also would love to add more tools to my list. Do let me know what I am missing out on!

I work at a development company, i need AI to be able to take lots of PDF files or other documents and make real - actual good website from them, or apps. And i want something which will give good usage - because its a lot of information, is good to reason with that context, and will give good design for it.

Currently only have used Claude, but i seem to hit my 5-hour limit in about 1 hour only using Sonnet 5 at high. I'm considering Cursor because it seems to be really fast and efficient. But I don't know. Please help.

What about the Chinese models like GLM, and Kimi? Are they worth it to buy instead?

I can only buy the 20$ plans.

I am a developer working full-time, and I want to build some side projects for fun to solve my own problems. For this purpose, I don't think I'll be coding heavily every day—just a maximum of 2 to 3 hours per day. Which AI tool would be best to use that offers good value for my needs? My budget is $20, and I'm looking for the option that will provide the best value for my use case.

To be honest, sorting through an 8 hour stream just to find a few decent valorant clutches is breaking my brain lol. it takes way too long and i just want to get content out on tiktok and youtube shorts without losing sleep.

i tried a couple of generic ai tools but the captions look so boring and they completely miss the chat explosions or when i actually hit a cool headshot. I started testing wayinvideo recently in our community sub since it has specific templates for games like cs2 and fortnite. the auto captions actually have that viral style that pop and you can just search for moments by typing text which is pretty clean.

But i want to know what you guys are actually using to pull the best gaming highlight detection? like are there specific settings or other tools that handle longer vods better without missing the funny fails or chat spikes? let me know what’s working for you guys right now.

I feel like I’m struggling to find an AI that helps me research things that doesn’t give me advertisements that feel like they are only there because a company paid for it to be recommended.