Training a Tokenizer for Llama Model
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Discipline Expert: The Tiny Habit That Finally Makes You Lose Weight! The 2-Minute Trick!
Ready to make habits that stick in 2026? Atomic Habits author JAMES CLEAR reveals the science behind building lasting habits, breaking bad ones, and how 1% improvements transform your entire life! James Clear is a #1 international bestselling author and habit formation expert, best known for his book “Atomic Habits”, which sold over 25 million copies worldwide. He writes the ‘3-2-1 Newsletter’ (read by millions weekly) and recently published ‘The Atomic Habits Workbook’. He explains: ◼️The 2-minute trick […]
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Interview: From CUDA to Tile-Based Programming: NVIDIA’s Stephen Jones on Building the Future of AI
As AI models grow in complexity and hardware evolves to meet the demand, the software layer connecting the two must also adapt. We recently sat down with Stephen Jones, a Distinguished Engineer at NVIDIA and one of the original architects of CUDA. Jones, whose background spans from fluid mechanics to aerospace engineering, offered deep insights into NVIDIA’s latest software innovations, including the shift toward tile-based programming, the introduction of “Green Contexts,” and how AI is rewriting the rules […]
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Google launches managed MCP servers that let AI agents simply plug into its tools
Google is rolling out managed MCP servers to make its services “agent-ready by design,” starting with Maps and BigQuery, aiming to simplify messy integrations and help AI agents use real tools.
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Language Models: A 75-Year Journey That Didn’t Start With Transformers
Introduction Language models have existed for decades — long before today’s so-called “LLMs.” In the 1990s, IBM’s alignment models and smoothed n-gram systems trained on hundreds of millions of words set performance records. By the 2000s, the internet’s growth enabled “web as corpus” datasets, pushing statistical models to dominate natural language processing (NLP). Yet, many believe language modelling began in 2017 with Google’s Transformer architecture and BERT. In reality, Transformers revolutionized scalability but were just one step in a much […]
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How to design LLMs that don’t need prompt engineering
Standard LLMs rely on prompt engineering to fix problems (hallucinations, poor response, missing information) that come from issues in the backend architecture. If the backend (corpus processing) is properly built from the ground up, it is possible to offer a full, comprehensive answer to a meaningful prompt, without the need for multiple prompts, rewording your query, having to go through a chat session, or prompt engineering. In this article, I explain how to do it, focusing on enterprise […]
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Harness hits $5.5B valuation with $240M raise to automate AI’s ‘after-code’ gap
Goldman Sachs has led Harness’s Series E round, with participation from IVP, Menlo Ventures, and Unusual Ventures.
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New research from Google Workspace reveals how young leaders are using AI at work.
Google Workspace has released findings from our second survey that looks at how people aged 22-39 are using AI at work. Commissioned by Workspace in partnership with the…
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Open borders are incompatible with the welfare state
I’ve seen a lot of people talking about opening the borders, and that would be fine if all those Democrat states didn’t exist. Until anarcho-capitalism is implemented, it’s better to keep the borders closed. submitted by /u/AmirSuS123 [link] [comments]
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Don’t Build an ML Portfolio Without These Projects
What recruiters are looking for in machine learning portfolios The post Don’t Build an ML Portfolio Without These Projects appeared first on Towards Data Science.
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