Machine Learning Times
EXCLUSIVE HIGHLIGHTS
The AI Paradox: More Humanlike Means Less Autonomous
  Originally published in Forbes The AI executives are at...
How To Overcome The Confidence-Killer That Destroys Most Predictive AI Projects
  Originally published in Forbes When Henry Castellanos first presented...
You Must Address These 4 Concerns To Deploy Predictive AI
 Originally published in Forbes Most predictive AI projects fail to launch into production. The...
Hybrid AI: Industry Event Signals Emerging Hot Trend
 Originally published in Forbes After decades chairing and keynoting myriad...

Left-hand

XGBoost is All You Need, Part 3 – Gradient Boosted Trees

 Originally published on XGBlog, January 30, 2025. This is the third part in the series of blog posts about XGBoost, based on my 2024 GTC presentation you can find Part 1 here, and Part 2 here. Today we want to talk about gradient boosted trees. Even though XGBoost has an option for purely linear boosting, it’s

AI data readiness: C-suite fantasy, big IT problem

 Originally published on CIO, December 12, 2024. Business leaders believe their data is primed for AI, but IT practitioners spend hours every day beating data into shape, only to miss out on automation opportunities. Business leaders may be...

AI Optimism vs. Skepticism: Bridging the Gap Between Hype and Practicality

 Originally published in GenAI: More Than You Asked For, December 15, 2024. This week, Casey Newton published an article where he challenges AI skeptics for minimizing AI. He argues that skepticism concentrates too heavily on present limitations...

How Gen AI and Analytical AI Differ — and When to Use Each

 Originally published in Harvard Business Review, December 13, 2024. Since OpenAI announced ChatGPT in November of 2022, many business executives have focused their attention on generative AI. This relatively new technology set off a frenzy around AI...

Beyond the Hype: The Enduring Value of Predictive AI in a GenAI World

 Originally published in Hackernoon, Nov 18, 2024. Generative AI has revolutionized the tech landscape since OpenAI’s ChatGPT burst onto the scene in late 2022. In response, companies, across sectors, are swiftly pivoting their strategies and redirecting significant...

Chemistry Nobel goes to developers of AlphaFold AI that predicts protein structures

 Originally published in Nature, Oct 9, 2024. This year’s prize celebrates computational tools that have transformed biology and have the potential to revolutionize drug discovery. For the first time — and probably not the last — a...

Generative AI’s Act o1

 Originally published in sequoia, Oct 9, 2024. The Agentic Reasoning Era Begins Two years into the Generative AI revolution, research is progressing the field from “thinking fast”—rapid-fire pre-trained responses—to “thinking slow”— reasoning at inference time. This evolution...

Nvidia improves Meta’s Llama model with new training approach

  Originally published in the-decoder.com, Oct 18, 2024. Nvidia has introduced a new large language model that outperforms others in alignment benchmarks. The company achieved this through a special training procedure combining evaluation and preference models. The...

Generative AI Use Case: Using LLMs to Score Customer Conversations

 Originally published in the Monte Carlo blog, July 15 2024. Despite all the talk about AI replacing humans, Skynet blowing up the sun, and deep-fake celebrities parenting our children, it’s difficult to point to a generative AI...

How to fine-tune: Focus on effective datasets

 Originally published in ai.meta.com/blog, August 7, 2024. This is the third blog post in a series about adapting open source large language models (LLMs). In this post, we explore some rules of thumb for curating a good...

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