We originally invented the concept of “Notebooks” back in 1987, for Version 1.0 of Mathematica. And over the past 36 years, Notebooks have proved to be an incredibly convenient medium in which to do—and publish—work (and indeed, I, for example, have created hundreds of thousands of them). And, yes, eventually the basic concepts of Notebooks […]
How important is the relationship between protein structure and the food we eat?
- Protein structure influences food texture. It can make a food smooth and creamy or crisp and crunchy.
- Protein structure helps determine digestibility. Proteins with looser structures are more readily hydrolyzed into amino acids for easier digestion.
- Protein structure is a factor in whether foods such as peanuts and shellfish cause an allergic reaction.
- Protein structure can make our foods elegant and appetizing.
Prompts are how one channels an LLM to do something. LLMs in a sense always have lots of “latent capability” (e.g. from their training on billions of webpages). But prompts—in a way that’s still scientifically mysterious—are what let one “engineer” what part of that capability to bring out.
Statistics is the mathematical discipline dealing with all stages of data analysis, from question design and data collection to analyzing and presenting results. It is an important field for analyzing and understanding data from scientific research and industry. Data-driven decisions are a critical part of modern business, allowing companies to use data and computational analyses to guide their choices and direction, rather than subjective measures like intuition.
From preparing food to nourish our bodies to finding cures for terminal illnesses, chemistry is a foundational part of our world. As a computational chemist, you may have a lot to learn to master this subject, but fueled by Wolfram’s collection of educational resources, elaborate simulation functions and research projects, you’ll be ready to tackle this exciting science head on.
So far, we mostly think of LLMs as things we interact directly with, say through chat interfaces. But what if we could take LLM functionality and “package it up” so that we can routinely use it as a component inside anything we’re doing? Well, that’s what our new LLMFunction is about.
A few weeks ago, in collaboration with OpenAI, we released the Wolfram plugin for ChatGPT, which lets ChatGPT use Wolfram Language and Wolfram|Alpha as tools, automatically called from within ChatGPT. One can think of this as adding broad “computational superpowers” to ChatGPT, giving access to all the general computational capabilities and computational knowledge in Wolfram […]
"I believe that we do not know anything for certain, but everything probably." —Christiaan HuygensHave you ever wondered how health insurance premiums are calculated or why healthcare is so expensive? Or what led to the financial crisis of 2008? Or whether nuclear power is safe? The answers to these questions require an understanding of probability, which is the best tool that we have for coping with an uncertain world. In fact, an understanding of probability is required for professionals in a large number of fields, including data science, finance, engineering, biology, chemistry, medicine and actuarial science.