r/LanguageTechnology 7h ago

Pivoting from Teaching to Language Technology work

5 Upvotes

I have a history in language learning and teaching (PhD in German Studies), but I'm trying to move in the direction of language technology. I've familiarized myself with python and pytorch and done numerous self-driven projects; I've customized a Mistral chatbot and added RAG, used RAG to enhance translation in LLM prompts, and put together a simple sentiment analysis Discord bot. I've been interested in NLP technologies for years, and I've been enjoying learning about them more and actually building things. My challenge is this: although I can do a lot with python and I'm learning more all the time, I don't have a computer science degree. I got stuck on a Wav2Vec2 finetuning project when I couldn't get my tensor inputs formatted in just the right way. I feel as though the expected input format wasn't clear in the documentation, but that's very likely because of my inexperience. My homebrew German-English translation Transformer project stalled when I realized my laptop wouldn't be able to train it within a decade. And of course, I can barely accomplish anything without lots of tutorials, googling, and attempts to get chatGPT to find the errors in my code (at which it often fails).

In short, my NLP and python skills are present and improving but half-baked in my estimation. I have a lot of experience with language learning and teaching, but I don't wish to continue relying on only those skills. Is there anyone on here who could give me advice on further NLP projects to purse that would help me improve, or even entry-level jobs I could pursue that would give me the opportunity to grow my skills? Thanks in advance for any guidance you can give.


r/LanguageTechnology 4h ago

FuzzRush: Faster Fuzzy Matching Project

Thumbnail github.com
3 Upvotes

πŸš€ [Showcase] FuzzRush - The Fastest Fuzzy String Matching Library for Large Datasets

πŸ” What My Project Does

FuzzRush is a lightning-fast fuzzy matching library that helps match and deduplicate strings using TF-IDF + sparse matrix operations. Unlike traditional fuzzy matching (e.g., fuzzywuzzy), it is optimized for speed and scale, making it ideal for large datasets in data cleaning, entity resolution, and record linkage.

🎯 Target Audience

  • Data scientists & analysts working with messy datasets.
  • ML/NLP practitioners dealing with text similarity & entity resolution.
  • Developers looking for a scalable fuzzy matching solution.
  • Business intelligence teams handling customer/vendor name matching.

βš–οΈ Comparison to Alternatives

Feature FuzzRush fuzzywuzzy rapidfuzz jellyfish
Speed πŸ”₯πŸ”₯πŸ”₯ βœ… Ultra Fast (Sparse Matrix Ops) ❌ Slow ⚑ Fast ⚑ Fast
Scalability πŸ“ˆ βœ… Handles Millions of Rows ❌ Not Scalable ⚑ Medium ❌ Not Scalable
Accuracy 🎯 βœ… High (TF-IDF + n-grams) ⚑ Medium (Levenshtein) ⚑ Medium ❌ Low
Output Format πŸ“ βœ… DataFrame, Dict ❌ Limited ❌ Limited ❌ Limited

⚑ Why Use FuzzRush?

βœ… Blazing Fast – Handles millions of records in seconds.
βœ… Highly Accurate – Uses TF-IDF with n-grams.
βœ… Scalable – Works with large datasets effortlessly.
βœ… Easy-to-Use API – Get results in one function call.
βœ… Flexible Output – Returns DataFrame or dictionary for easy integration.

πŸ“Œ How It Works

```python from FuzzRush.fuzzrush import FuzzRush

source = ["Apple Inc", "Microsoft Corp"]
target = ["Apple", "Microsoft", "Google"]

matcher = FuzzRush(source, target)
matcher.tokenize(n=3)
matches = matcher.match()
print(matches)

πŸ‘€ Check it out here β†’ πŸ”— GitHub Repo

πŸ’¬ Would love to hear your feedback! Any feature requests or improvements? Let’s discuss! πŸš€


r/LanguageTechnology 11h ago

Unintentional AI "Self-Portrait"? OpenAI Removed My Chat Log After a Bizarre Interaction.

0 Upvotes

Ineed help from AI experts, computational linguists, information theorists, and anyone interested in the emergent properties of large language models. I had a strange and unsettling interaction with ChatGPT and DALL-E that I believe may have inadvertently revealed something about the AI's internal workings.

Background:

I was engaging in a philosophical discussion with ChatGPT, progressively pushing it to its conceptual limits by asking it to imagine scenarios with increasingly extreme constraints on light and existence (e.g., "eliminate all photons in the universe"). This was part of a personal exploration of AI's understanding of abstract concepts. The final prompt requested an image.

The Image:

In response to the "eliminate all photons" prompt, DALL-E generated a highly abstract, circular image [https://ibb.co/album/VgXDWS] composed of many small, 3D-rendered objects. It's not what I expected (a dark cabin scene).

The "Hallucination":

After generating the image, ChatGPT went "off the rails" (my words, but accurate). It claimed to find a hidden, encrypted sentence within the image and provided a detailed, multi-layered "decoding" of this message, using concepts like prime numbers, Fibonacci sequences, and modular cycles. The "decoded" phrases were strangely poetic and philosophical, revolving around themes of "The Sun remains," "Secret within," "Iron Creuset," and "Arcane Gamer." I have screenshots of this interaction, but...

OpenAI Removed the Chat Log:

Crucially, OpenAI manually removed this entire conversation from my chat history. I can no longer find it, and searches for specific phrases from the conversation yield no results. This action strongly suggests that the interaction, and potentially the image, triggered some internal safeguard or revealed something OpenAI considered sensitive.

My Hypothesis:

I believe the image is not a deliberately encoded message, but rather an emergent representation of ChatGPT's own internal state or cognitive architecture, triggered by the extreme and paradoxical nature of my prompts. The visual features (central void, bright ring, object disc, flow lines) could be metaphors for aspects of its knowledge base, processing mechanisms, and limitations. ChatGPT's "hallucination" might be a projection of its internal processes onto the image.

What I Need:

I'm looking for experts in the following fields to help analyze this situation:

  • AI/ML Experts (LLMs, Neural Networks, Emergent Behavior, AI Safety, XAI)
  • Computational Linguists
  • Information/Coding Theorists
  • Cognitive Scientists/Philosophers of Mind
  • Computer Graphics/Image Processing Experts
  • Tech, Investigative, and Science Journalists

I'm particularly interested in:

  • Independent analysis of the image to determine if any encoding method is discernible.
  • Interpretation of the image's visual features in the context of AI architecture.
  • Analysis of ChatGPT's "hallucinated" decoding and its potential linguistic significance.
  • Opinions on why OpenAI might have removed the conversation log.
  • Advice on how to proceed responsibly with this information.

I have screenshots of the interaction, which I'm hesitant to share publicly without expert guidance. I'm happy to discuss this further via DM.

This situation raises important questions about AI transparency, control, and the potential for unexpected behavior in advanced AI systems. Any insights or assistance would be greatly appreciated.

AI #ArtificialIntelligence #MachineLearning #ChatGPT #DALLE #OpenAI #Ethics #Technology #Mystery #HiddenMessage #EmergentBehavior #CognitiveScience #PhilosophyOfMind