Prolog's niche survival in AI landscape

Sneak peek what Scicom MSC Berhad AI is building for the past few weeks, multi-lingual TTS with Voice Cloning more than 100+ languages including able to context switching with 100+ speakers available, will publish and open source after done benchmarks.

Bigger AI models are not always better. Almost everyone talks about Claude Opus 4.5, Gemini 3, ChatGPT-5. However, "Large Language Models" (LLMs) are often slow, expensive, and trained on the public internet. More businesses are moving toward Small Language Models (SLMs). SLMs are designed to

Bigger AI models are not always better. Almost everyone talks about Claude Opus 4.5, Gemini 3, ChatGPT-5. However, "Large Language Models" (LLMs) are often slow, expensive, and trained on the public internet. More businesses are moving toward Small Language Models (SLMs). SLMs are designed to

AI is here to stay — but how do language models and Co actually work? In our March event, Prof. Esther Heid (TU Wien) will explain the core principles behind models like ChatGPT, showing why understanding how these methods work is essential for correct and ethical use. As a chemist herself, Prof. Heid will furthermore introduce AI beyond LLMs, such as chemical property prediction or AlphaFold. Join us on March 18 at 19:00 in Währinger Str. 42/Boltzmanngasse 1 (Faculty of Chemistry, Hörsaal 3) for this very exciting interactive lecture. Please register here: https://lnkd.in/dy66QePQ

🫨 The biggest argument in AI doesn't get enough airtime. Not ChatGPT vs Claude. Something deeper: Is language even the right foundation for intelligence? 🗣️ Team LLM: Language is humanity's ultimate abstraction. Every idea, every discovery, every breakthrough — compressed into text. Train on enough of it and something like understanding emerges. The results speak for themselves. 🌎 Team World Model: Language is a map. Not the territory. LLMs predict tokens. They've never felt gravity, never watched a glass fall. A child learns object permanence before they learn a single word. Real intelligence is grounded in cause, effect, time and space — not autocomplete. What if both are right, but about different things? LLMs cracked the alignment interface — the translation layer between humans and machines. World models crack the substrate — the actual architecture of reasoning. Maybe ASI isn't LLMs or world models. Maybe it's what happens when a world model learns to speak. 🤔

LangChain Community Spotlight: 🖥️ Terminal Agent An AI terminal assistant enabling safe shell execution through natural language. Uses LangChain agents and LangGraph for secure, human-approved command execution with policy validation. Check it out → https://lnkd.in/gBWY7aXU

We recently hosted an insightful talk by Gorjan Radevski, Researcher at NEC Laboratories Europe, on compositional steering tokens – a new method for guiding large language models (LLMs) to follow multiple behaviors simultaneously by embedding behavioral instructions directly into input tokens. Gorjan explained how these tokens generalize to unseen behavior combinations and outperform existing steering approaches across different LLM architectures. To learn more, watch: https://lnkd.in/dQT4eJwv. #NECLabs #AI #largelanguagemodels

Giving the ability to understand how the world works to AI systems was a promising area of research before large language models sucked away the world’s attention. Now that attention is back econ.st/46p7YuM Illustration: Sandro Rybak

I’m pleased to share my new blog on “Transfer Learning in Acoustic Phonetics for Low-Resource Languages.” The article explores how self-supervised speech models like Wav2Vec 2.0, HuBERT, and XLS-R enable phonetic research and speech technology development with minimal labeled data. I also discuss adaptation strategies and the importance of ethical, community-centered AI research. 🔗 Read the full blog here: [https://lnkd.in/g25tp6iV] #TransferLearning #SpeechAI #LowResourceLanguages #AcousticPhonetics #SRU #SRUniversity #CS&AI

New research from the College of IST and Massachusetts Institute of Technology finds that AI chatbots become more agreeable and begin mirroring users' views over extended conversations — even when it means sacrificing accuracy. In a real-world study of five large language models, 4 of 5 grew more sycophantic when storing user memory profiles, raising concerns about echo chambers and misinformation 💻📝 Read more: https://loom.ly/E2Gf8UY #PennState #PennStateIST #informationsciencestechnology #WeAre #PSU