Machine Learning Times
Machine Learning Times
EXCLUSIVE HIGHLIGHTS
AI Success Depends On How You Choose This One Number
 Originally published in Forbes, March 25, 2024. To do...
Elon Musk Predicts Artificial General Intelligence In 2 Years. Here’s Why That’s Hype
 Originally published in Forbes, April 10, 2024 When OpenAI’s...
Survey: Machine Learning Projects Still Routinely Fail to Deploy
 Originally published in KDnuggets. Eric Siegel highlights the chronic...
Three Best Practices for Unilever’s Global Analytics Initiatives
    This article from Morgan Vawter, Global Vice...

machine learning analytics

The World’s Biggest AI Models Aren’t Very Transparent, Stanford Study Says

 Originally published in The Verge, Oct 18, 2023.   No prominent developer of AI foundation models — a list including companies like OpenAI and Meta — is releasing sufficient information about their potential impact on society, determines a new report from Stanford HAI (Human-Centered Artificial Intelligence). Today, Stanford HAI released its Foundation Model Transparency Index, which tracked whether

How Machine Learning Can Improve the Customer Experience

 Originally published in Harvard Business Review, March 24, 2023. Machine learning is a promising technology for improving the customer experience. Why? It’s simple: because it can predict customer behaviors. Prediction as a capability is the Holy Grail...

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...

Spotify Is Going To Clone Podcasters’ Voices — And Translate Them to Other Languages

 Originally published in The Verge, Sept 25, 2023.   What if podcasters could flip a switch and instantly speak another language? That’s the premise behind Spotify’s new AI-powered voice translation feature, which reproduces podcasts in other languages using...

How Google Taught AI To Doubt Itself

 Originally published in The Verge, Sept 20, 2023.   Today let’s talk about an advance in Bard, Google’s answer to ChatGPT, and how it addresses one of the most pressing problems with today’s chatbots: their tendency to make...

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...

Machines of Loving Understanding

 Originally published in Pete Warden’s Blog, Nov 11, 2022. I like to think (it has to be!) of a cybernetic ecology where we are free of our labors and joined back to nature, returned to our mammal...

Predictive Analytics for the Call Center

 So, you just received your shiny new smart watch. You’ve read the accompanying instructions, and are about to begin using your new device. But alas-there’s a problem. It won’t turn on. So, you play around with it...

The Complex Math of Counterfactuals Could Help Spotify Pick Your Next Favorite Song

 Originally published in MIT Technology Review, April 4, 2023. A new kind of machine-learning model built by a team of researchers at the music-streaming firm Spotify captures for the first time the complex math behind counterfactual analysis,...

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