Month in 4 Papers (April 2026)
Author(s): Ala Falaki, PhD Originally published on Towards AI. Month in 4 Papers (April 2026) This series of posts is designed to bring you the newest findings and developments in the NLP field. I’ll delve into four significant research papers each month, …
GPT-4 Has 1.8 Trillion Parameters. It Uses 2% of Them Per Token.
Author(s): DrSwarnenduAI Originally published on Towards AI. GPT-4 Has 1.8 Trillion Parameters. It Uses 2% of Them Per Token. DeepSeek-R1: 671 billion parameters. 37 billion active per token. DeepSeek-R1: 671 billion parameters. 37 billion active per token.The article discusses various machine learning …
From Notebook to Production: Running ML in the Real World (Part 4)
Author(s): Raj kumar Originally published on Towards AI. Part 4 of a 4-part series: From Data to Decisions Most machine learning projects look successful right up to the moment they are deployed. The notebook runs. The metrics look good. Stakeholders sign off. …
LAI #122: Word Embeddings Started in 1948, Not With Word2Vec
Author(s): Towards AI Editorial Team Originally published on Towards AI. Good morning, AI enthusiasts! This week, we’re covering what happens when AI labs sit across the table from governments, why most AI-generated writing still sounds the same (and how to fix it), …
40 Generative AI Interview Questions That Actually Get Asked in 2026 (With Answers)
Author(s): Darshandagaa Originally published on Towards AI. A practitioner’s guide to cracking senior GenAI/LLM engineering roles — from RAG pipelines to multi-agent orchestration I’ve been in AI/ML for eight years. In the last two, almost every interview I’ve sat in — whether …
TAI #199: Gemma 4 Brings a Credible US Open-Weight Contender Back to the Table
Author(s): Towards AI Editorial Team Originally published on Towards AI. What happened this week in AI by Louie This week, Google DeepMind released Gemma 4, and I think this is the most consequential US open-weight release in quite a while. China has …
Calling the Anthropic API: 4 Lines to Your First LLM Response
Author(s): Nagaraj Originally published on Towards AI. No boilerplate here. No DI container, nothing-no middleware whatsoever. Just results I have dedicated several months to developing artificial intelligence backends using C# which includes building Semantic Kernel and HttpClient and custom middleware and dependency …
Reliable Agentic Development on a €40 Budget: Dependency-Aware Orchestration for Claude, Codex, and Human-in-the-Loop
Author(s): Akash Acharya Originally published on Towards AI. Most agentic coding demos show the happy path: AI gets task, AI writes code, done. What they don’t show is who decides what the tasks are. Or what happens when a task is marked …
TAI #195: GPT-5.4 and the Arrival of AI Self-Improvement?
Author(s): Towards AI Editorial Team Originally published on Towards AI. What happened this week in AI by Louie Two stories dominated this week that look unrelated but tell the same story. On Wednesday, OpenAI released GPT-5.4, its most work-oriented frontier model to …
Part 4: Data Manipulation in Data Cleaning
Author(s): Raj kumar Originally published on Towards AI. There is an assumption many teams carry without fully examining it. Data cleaning feels responsible.It feels corrective.It feels like a necessary step to improve data quality before analysis or machine learning begins. But data …
Recent Posts
