Machine Learning Times
Machine Learning Times
EXCLUSIVE HIGHLIGHTS
Three Best Practices for Unilever’s Global Analytics Initiatives
    This article from Morgan Vawter, Global Vice...
Getting Machine Learning Projects from Idea to Execution
 Originally published in Harvard Business Review Machine learning might...
Eric Siegel on Bloomberg Businessweek
  Listen to Eric Siegel, former Columbia University Professor,...
Effective Machine Learning Needs Leadership — Not AI Hype
 Originally published in BigThink, Feb 12, 2024.  Excerpted from The...

LLM

New Theory Suggests Chatbots Can Understand Text

 Originally published in Quanta Magazine, Jan 22, 2024.  Artificial intelligence seems more powerful than ever, with chatbots like Bard and ChatGPT capable of producing uncannily humanlike text. But for all their talents, these bots still leave researchers wondering: Do such models actually understand what they are saying? “Clearly, some people believe they do,” said the AI

2024 Data Engineering Trends

 Originally published in Kestra, Jan 24, 2024. Doing More with Less The tech industry in 2024 is under pressure to optimize resources. Technology and data leaders are asked to integrate more data to support new AI-driven features...

Google DeepMind Used A Large Language Model to Solve An Unsolved Math Problem

 Originally published in MIT Technology Review, Dec 14, 2023. Google DeepMind has used a large language model to crack a famous unsolved problem in pure mathematics. In a paper published in Nature today, the researchers say it is...

Peak Data

 Originally published in East Wind, Oct 25, 2023. I’m probably not the first person to write about the insane leverage that LLMs confer to engineers, but Stack Overflow’s 28% layoff really got me thinking about the future of human-generated data,...

How to Build An Enterprise LLM Application: Lessons From GitHub Copilot

 Originally published in The GitHub Blog, Sept 6, 2023.  It took us three years to develop GitHub Copilot before we officially launched it to the general public. To go from idea to production, we followed three stages—find...

How To Make History With LLMs & Other Generative Models

 Originally published in Leigh Marie’s Newsletter, Sept 21, 2023.   Or, I’m getting tired of market maps and am ready for some hotter takes. It’s been well over a year since I published my overview of large language models,...

Medusa: Simple Framework for Accelerating LLM Generation with Multiple Decoding Heads

 Originally published in together.ai, Sept 11, 2023. Large Language Models (LLMs) have changed the world. However, generating text with them can be slow and expensive. While methods like speculative decoding have been proposed to accelerate the generation...

Can LLMs Learn From a Single Example?

 Originally published in Fast.AI, Sept 4, 2023. We’ve noticed an unusual training pattern in fine-tuning LLMs. At first we thought it’s a bug, but now we think it shows LLMs can learn effectively from a single example....

Meta Launches Own AI Code-Writing Tool: Code Llama

 Originally posted in The Verge, Aug 24, 2023. Meta said Code Llama will make it easier to finish code. Meta has released a tool called Code Llama, built on top of its Llama 2 large language model, to generate...

Productizing Large Language Models

 Originally posted on Replit.com, Sept 21, 2022.  Large Language Models (LLMs) are known for their near-magical ability to learn from very few examples — as little as zero — to create language wonders. LLMs can chat, write...