When (Not) to XGBoost
AIM Research
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Oliver Molander , a serial entrepreneur and investor, recently shared his interaction with a VC who claimed to be an ‘AI-first investor’.??
“What’s your thoughts on XGBoost 2,” he asked. The VC replied, “I’ve never heard of that LLM.”?
Many individuals—not only VCs—suddenly labelled themselves AI experts in the post-ChatGPT era. “If you had asked them what an LLM was before 2022, many probably would have answered that it's a law degree,” quipped Molander. He acknowledged that though LLMs brought AI to the mainstream, “the truth is that AI is much more than just LLMs”.?
Citing XGBoost , he said that it is one of the most successful implementations of GBT (aka gradient-boosted trees), a class of machine learning algorithms that combine a decision tree ‘basic learner’ with the ensemble technique called boosting. “When it comes to predictive tabular data use cases, XGBoost is the true workhorse,” he added.
Further, he said that XGBoost is both an algorithm and a library, which was started by a research project by Tianqi Chen in 2014. “For years, XGBoost has been the key component of almost all winning Kaggle solutions, as well as many important real-world applications. The library is now in version 2.0, and supported on almost every computing platform and environment,” said Molander.
Read the full story here .??
ChatGPT for Protein
NVIDIA chief Jensen Huang last year spoke about how he used ChatGPT to understand the use of generative AI to solve real-world problems such as dissolving plastics, reducing carbon emissions and more. Little did we know that a European AI startup was doing something similar, leveraging LLMs for DNA and protein sequences.?
Read the full story here .?
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