Why You May Not Need Fine-Tuning for Your Use Case!
Author(s): Vaishnavi Seetharama Originally published on Towards AI. In recent years, fine-tuning large language models (LLMs) like GPT-4 or later has become a popular trend among developers, data scientists, and enterprises. The idea of molding a powerful general‑purpose model to your exact …
LAI #80: Why LLMs Fail, Reinforcement Pre-Training, and Local Agents That Listen
Author(s): Towards AI Editorial Team Originally published on Towards AI. Good morning, AI enthusiasts, This week’s issue explores why LLMs fail and what we can actually do about it. We’re starting with a look at their core weaknesses: why they struggle with …
From Pixels to Predictions: Building a Transformer for Images
Author(s): Vicki Y Mu Originally published on Towards AI. Convolutional neural networks have been the driving force behind almost every major breakthrough in computer vision — but what if they’ve been holding us back all along? In 2020, a team of researchers …
TAI #158: The Great Acceleration: AI Revenue, M&A, and Talent Wars Erupt as the Industry Matures
Author(s): Towards AI Editorial Team Originally published on Towards AI. What happened this week in AI by Louie While LLM model releases have slowed down lately, the AI industry’s undercurrents of commercialization and consolidation were taken to the next level this week. …
Beyond RAG: Context Engineering for Smarter AI Systems
Author(s): Vikram Bhat Originally published on Towards AI. How Context Engineering Enhances Retrieval-Augmented Generation (RAG) for Smarter, More Reliable AI Applications. Building a reliable chatbot on top of Large Language Models (LLMs) is far more than just plugging in a model and …
Attention Isn’t All You Need. This Is.
Author(s): Towards AI Editorial Team Originally published on Towards AI. We’ve lived through tech hype before. Cloud, big data, blockchain — each made waves, filled pitch decks, and left us chasing buzzwords. But none of them could draft your code, write your …
LAI #81: Reasoning LLMs, Open-Source ChatGPT Alternatives, and Vector DB Showdowns
Author(s): Towards AI Editorial Team Originally published on Towards AI. Good morning, AI enthusiasts, This week’s issue zooms in on how reasoning has become the next benchmark for LLM progress. From spelling out strawberry to solving logic puzzles, we’re no longer impressed …
Dense Passage Retrieval (2020) and Contriever (2021): The Models That Paved the Way for Future, Smarter LLMs
Author(s): Saif Ali Kheraj Originally published on Towards AI. Dense Passage Retriever (DPR) marked a turning point in open-domain question answering when it launched in 2020. It demonstrated that dense vector representations, learned through deep neural networks, can outperform traditional sparse retrieval …
Implementing Tensor Contractions in Modern C++
Author(s): Luiz doleron | Luiz d’Oleron Originally published on Towards AI. Tensor contractions are of fundamental importance in modern artificial intelligence systems, playing a central role in the computation performed by the underlying linear algebra engines. Despite its relevance, there are only …
Serious about AI? Join us from day one.
Author(s): Towards AI Editorial Team Originally published on Towards AI. Our July Cohort Starts Next Week! AI feels big. Here’s where to start You might not know exactly where to begin with AI, but you know what’s pulling you in. You want …
Building a Vocabulary for NLP in Modern C++
Author(s): Luiz doleron | Luiz d’Oleron Originally published on Towards AI. Building a vocabulary from a mass of text is one of the first steps in every NLP pipeline. This can be easily achieved if the amount of data is small. If …
How to Build Bulletproof Data Pipelines with PySpark That Actually Scale
Author(s): Yuval Mehta Originally published on Towards AI. Photo by Claudio Schwarz on Unsplash We’re past the era when a CSV, a Pandas DataFrame, and a single machine could handle everything you threw at them. Data is heavier now. It arrives fast, …
TAI #159: China’s Open-Model Offensive vs. Meta’s $multi-billion Gamble on AI Talent Acquisition
Author(s): Towards AI Editorial Team Originally published on Towards AI. What happened this week in AI by Louie This week felt like a tale of two AI strategies unfolding in parallel. In China, the open-source movement gained additional momentum as Baidu joined …
LAI #82: MCP, Byte-Level LLMs, Vision Transformers, and the Week Backprop Finally Clicked
Author(s): Towards AI Editorial Team Originally published on Towards AI. Good morning, AI enthusiasts, This week’s issue zooms in on what happens when you go one layer deeper, whether it’s understanding MCP for smarter tool integrations, or hand-coding backprop to finally grasp …
I Ran OpenAI’s New Open Model on My Laptop to Extract Medical Data — Here’s What Happened
Author(s): Marie Humbert-Droz, PhD Originally published on Towards AI. Testing privacy-first healthcare AI with OpenAI’s first open-weight models OpenAI just released its first family of open-weight models, and I couldn’t resist testing them on one of healthcare’s trickiest problems: extracting structured data …
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