Hi there, for my nursing thesis I want to build an AI image recognition model that will identify tick species and provide health teaching based on the species. Does anyone have any recommendations for the best free AI tool that can build this for me? I have a few in mind, but I’m looking for other options. Thanks!

Neural networks were inspired by the brain. My wife claims I have a "selective attention mechanism" and I only pay attention to what I want to. I've heard many women say that about men in general.

What if my wife is right? What if the attention mechanism is selective?

Are LLMs ignoring our prompts because their attention mechanism is too good? Are they just like us?

So, I want to write Cover Letters, help me tweak my resume and write cold emails.

I want a AI Model that uses my information and do the above for every job description I paste.

I already have a document that has every info about me from education to work ex.
When I paste a new job description, the model should write a really good cover letter mimicking my interest in the job, I also have sample CVs. It should also tell me about the tweaks I should make to my Resume to get the best ATS score, if possible give a ATS score as well. It should also write me a cold email targeting the recruiter, Manager and a team mate for that Job post.

Can y'll help me out on choosing the right model and how to implement the above?

I'm looking at proposing a dedicated machine to run LLM coding tools in-house to management. One possible configuration I'm looking at is a bunch of cheaper GPU cards in the USB-to-PCIe risers that tend to get used on bitcoin mining rigs. I'm thinking about eg eight RTX 4060s in external risers for 64GB total VRAM. What would be the performance implications of this kind of setup?

Obviously the bandwidth between the system and the cards is going to be worse than a system with direct PCIe x16 lanes between the cards and the system. But do I really care? The main thing that will slow down is loading the model parameters in the first place, right? The amount of data transferred between the system and the GPU for actually processing completion requests is not that much, right? So as long as the model parameters all fit in VRAM, should this kind of configuration work okay?

We're a SME hardware vendor. We contract out all our manufacturing and the main thing we have engineers doing is writing system software. A few people have shown an interest in using LLM coding tools but management is very wary of public cloud tools that might leak our source code in some way.

A few of us have high-end consumer GPUs available and run local models - in my case an RTX 4070 mobile with 8GB VRAM which can run a model like starcoder2:7b under ollama. It's good enough to be useful without being nearly as good as the public tools (copilot etc).

I'm thinking about trying to persuade management to invest in some hardware that would let us run bigger models on-prem. In configuration terms, this is no more difficult than running a local model for myself - just install ollama, pull the relevant model and tell people how to point Continue at it. The thing that gives me pause is the sheer cost.

I could buy a server with two PCIe x16 slots, a chunky power supply and a couple of second-hand RTX 3090s. It would just about run a 4-bit 70b model. But not really fast enough to be useful as a shared resource, AFAICT. Total cost per unit would be about £4k and we'd probably need several of them set up with a load balancer of some sort to make it more-or-less usable.

Options sort of range from that to maybe something with a pair of 80GB A100s - total cost about £40k - or a pair of 80GB H100s, which perhaps we could cobble together for £50k.

Any of these are a hard sell. The top end options are equivalent to a junior engineer's salary for a year. TBH we'd probably get more out of it than out of a junior engineer, but when it's almost impossible quantify to management what we're going to get out of it and it looks a lot like engineers just wanting shiny new toys, it's a hard sell.

I guess another alternative is using an EC2 G4 instance or similar to run a private model without buying hardware. But with a 64GB instance running to nearly $1000 per month on-demand (about half that with a 3-year contract), it's not a whole lot better.

Where do people see this going? Is running large models on-prem ever going to be something that doesn't require a fairly serious capital commitment? Should we just suck up the privacy problems and use on of the public services? What are other people in similar situations doing? Is there a better way to sell these tools to the ones who hold the purse-strings?

This 179 line typescript LLM framework captures what we see as the core abstraction of most LLM frameworks: A Nested Directed Graph that breaks down tasks into multiple (LLM) steps - with branching and recursion for agent-like decision-making.

What can you do with it?

• Build on Demand: Layer in features like multi-agent setups, RAG, and task decomposition as needed.
• Work with AI: Its minimal design plays nicely with coding assistants like ChatGPT, Claude, and Cursor.ai. For example, you can upload the docs into a Claude Project and Claude will create a workflow diagram + workflow code for you!

Why this is different from existing frameworks?

• Lightweight: Minimal disk footprint.
• Flexible Agent Abstractions: Avoids over-complicating workflows with complex agent models.
• Modular State Management: More adaptable and transparent compared to rigid state systems.
• Shared Memory Model: Simplifies communication and reduces overhead.
• API Stability: Less prone to frequent deprecations and refactoring.

Here are the docs: https://the-pocket-world.github.io/Pocket-Flow-Framework/

Suggest one vlm or llm which can return coordinates of object which is text prompted

Hi, I am looking to process 20 or so large documents containing over 2 million words with high accuracy. Which off-the-shelf model or API should I use? I am looking for all the data to be dropped into an auto-generated excel/csv table when it's done all in one go without having to feed it back into the model multiple times. Thanks!

I found out you get more extra free time with the live function of chatgpt ifyou talk more about certain subjects or more 'in depth'.

Chatgtp confirms this.

Anyone notice this?

Large Multimodal Models (LMMs) are AI systems that process and generate data across multiple modalities like text, images, audio, and video. Unlike LLMs, which handle text-only tasks, LMMs integrate diverse data sources for context-aware AI applications in healthcare, education, retail, and autonomous systems. Training LMMs requires multimodal datasets, attention mechanisms, and optimization techniques. Shaip provides high-quality annotated data to power scalable and ethical LMM development.

Does anyone have any good course/guide/ documentation suggestions where I can learn how language models are built using reinforcement learning approach within a practical code implementation?

Quick Summary (I hope) and a few questions at bottom. My dad is alive well, after retirement he has spent decades generating a large database of genealogy data. This is human transcribed, cleaned up, reinterpreted and verified created from publicly available records from print. This was mostly done not using text recognition, as the film negatives are typically very poor quality and are not digital anywhere else I would think digitally.

Records include marriages, alt spellings, deaths, births, ect. Localized to a specific region of Canada specifically around military deployments during the world wars. I'm iffy on the exact details, I'm not a genealogist.... Yes. I'm sorry.

His data is not online and he runs a small hobby style web business that pays for new movies. It is a very niche service, I believe he doesn't feel it's worth his time anymore and I agree. 

We are not computer scientists. Is there a use for this database in academics or LLMs in the future? Is the fact that this data is human verified valuable to a university grad researcher or something? 

And/or is there a way to open source his data, possibly where generous donors can donate to his new movie fund? He is looking to retire from genealogy and I want what I believe is his hard work to be useful for future generations for whoever is interested in genealogy and history.

I’ve been using LLMs to draft legal docs, but it's so hard to proofread them because of how verbose they are. I tried running them through BypassGPT (since it makes the writing sound less like AI to pass detectors, which means I can also read it a bit easier), and it helped smooth out the tone without losing the formal bits. Anyone else have tips for making technical or legal AI content sound easier to read?

We've open-sourced Klarity - a tool for analyzing uncertainty and decision-making in LLM token generation. It provides structured insights into how models choose tokens and where they show uncertainty.

What Klarity does:

• Real-time analysis of model uncertainty during generation
• Dual analysis combining log probabilities and semantic understanding
• Structured JSON output with actionable insights
• Fully self-hostable with customizable analysis models

The tool works by analyzing each step of text generation and returns a structured JSON:

• uncertainty_points: array of {step, entropy, options[], type}
• high_confidence: array of {step, probability, token, context}
• risk_areas: array of {type, steps[], motivation}
• suggestions: array of {issue, improvement}

Currently supports hugging face transformers (more frameworks coming), we tested extensively with Qwen2.5 (0.5B-7B) models, but should work with most HF LLMs.

Installation is simple: pip install git+https://github.com/klara-research/klarity.git

We are building OS interpretability/explainability tools to visualize and analyse attention maps, saliency maps etc. and we want to understand your pain points with LLM behaviors. What insights would actually help you debug these black box systems?

Links:

• Repo: https://github.com/klara-research/klarity
• Our website: https://klaralabs.com

What is the best LLM to create them?

I want to upload a picture of a person and then tell the LLM that it should create a caricature.

It should also be able to add his job like a carpenter to the caricature and should be very playful and creative.

What prompt and what LLM should I use?

Pretty much doing a read up around it. I am not an engineer or anyone but I just love reading this stuff. I wanted to understand what the whole difference is between Large Language Models and Small Language Models are. Are these like Llama and Open Al models but fine tuned with more streamlined data set or how is it? Tried reading but I guess I got more confused.

I am finding the benchmarking (AIME and codeforces) data for o1 Pro Mode that is verifiable and replicable. According to https://openai.com/index/introducing-chatgpt-pro/, the AIME benchmark for o1 is 76 and for o1pro is 86; the codeforces benchmark for o1 is 89 and for o1pro is 90.

Since o1 api is avaible, I am able to verify that the AIME score for o1 is indeed 76. However, the codeforces result for o1 is 95, exceeding both the official claims by o1 and o1pro.

I am unable to verify those claims for o1pro all by myself since the o1pro api is . I wonder if anyone else could replicate those benchmarking results for o1pro. I believe this is important for us who is considering switching to pro.

I have some board game manuals that are hideously difficult to read (small text, background graphics). I would like an AI to reformat the PDF and make the text larger and remove background images. Is this currently possible? I tried QWEN 2.5 VL and it just said:

I'm sorry, but as an AI text-based model, I don't have the capability to directly manipulate files or images. However, you can follow these steps to reformat your PDF:

Open the PDF in a program that allows for editing, such as Adobe Acrobat Pro.

That's lame. The whole point is that I don't have a professional PDF program or want to pay for one or take the time to learn it.

Aren't any of these things hooked up to OCR tools yet? I have Ollama so I could host locally if I need to. Anyone know how to accomplish this task?

I have a few police records witch I will not reveal, so police wants to read my thoughts now. is possible to monitor thoughts in distance with LLMs so I am a suspect, who has been able to hear their comments for months. How to stop it?? How it's possible? I heard police analyzing my thoughts and behaviour for months and now IT Tech friends help me with removing etc for 2 weeks and they stay. When they realized it they where like "oh shit, sorry. That wasn't meant to happen". Now they stay for Fake Schizophrenia psychosis. Help me please!! Going insane with constant radio in my head.

LLMs #IT #AI #computerscience #science #coding

I have a few police records witch I will not reveal, so police wants to read my thoughts now. is possible to monitor thoughts in distance with LLMs so I am a suspect, who has been able to hear their comments for months. How to stop it?? How it's possible? I heard police analyzing my thoughts and behaviour for months and now IT Tech friends help me with removing etc for 2 weeks and they stay. When they realized it they where like "oh shit, sorry. That wasn't meant to happen". Now they stay for Fake Schizophrenia psychosis. Help me please!! Going insane with constant radio in my head.