![]() ![]() Python, Julia, and Jupyter notebooks will simply wipe out all usage of Mathematica outside of a few esoteric fields. a dead end.Ĭan I publish Wolfram code in Docker Hub and expect it to work (legally)? No.Ĭan I throw some Wolfram code into an Azure Function and have it compute something for me on demand? Nope.Ĭan I embed Wolfram code into a C# app, publish it on GitHub, and have other people be able to use it without forking out $thousands for a Mathematica license? Nope! There is no other use for Wolfram Language scripts outside of Mathematica, which comes with a "license server". Even formerly closed languages have been opened sourced, such as Java and C#. It's one thing to have a proprietary product, but for decades now proprietary languages have been a no-go for practically everyone. The saddest thing about Mathematica is that despite the incredible level of effort invested into it by some of the smartest people on the planet, it will inevitably be relegated to the dustbin of history.Īs a proprietary language and kernel, it can never compete long-term with open source alternatives. But the product - it really should get a lot more kudos and wow factor based on real accomplishments and features that are live, in the real world. This isn't to hide that there are some frustrating things about the language (like, machine learning development has just stopped dead after a couple of really great years of feature dev.why?) and, especially, the organisation and some of its personalities. The front-end is just lightyears in front of Jupyter notebooks in just about every conceivable way. You can get the entire Wolfram Alpha knowledgebase and curated datasets to use in your programs immediately. The integrated libraries are fantastic - especially if you want to chain together different knowledge domains through a consistent interface and syntax. If you enjoy functional programming, the language is super expressive and productive. Unlike ChatGPT's free version (which is basically a giant encyclopedia that cuts off in 2021), Bard will naturally scour Google for answers its training data set isn't privy to.Rather than just bashing Stephen's personality and rehashing Cosma Shalizi's driveby on NKOS, can we try and focus on the technical accomplishment that Mathematica represents? Obviously, Bard would be a pretty shoddy research tool if it couldn't tap into the internet. Bard draws from Google Search, whereas ChatGPT's web browser is powered by Bing So, while GPT can understand and generate a wide range of text for multiple purposes (including content marketing), Bard feels like it was designed primarily to act as a research tool. When I asked ChatGPT to provide me with an outline for a blog post about the crisis surrounding bees, the depth of detail in its output far exceeded Bard's. I found that ChatGPT is also better at brainstorming blog ideas, writing long-form articles or emails, and coming up with content marketing ideas. Which, fine, that's great for someone who's learning the basics, but maybe less great if you just want a working draft right away. Of course, a little prompt engineering might change things, but this gives you a sense of how the two tools operate differently. I'll walk through some of the core differences between ChatGPT and Google Bard in depth in the coming sections, but here's a quick breakdown of how they compare.Īs for the bullet points it lists, it's almost like it wants me to figure out how to write a tweet. Google Bard uses Google's Pathways Language Model (PaLM 2) and can offer responses based on real-time, current events pulled from Google Search-making for a great research tool.ĬhatGPT, on the other hand, uses its Generative Pre-training Transformer 3 ( GPT-3), or GPT-4 for paid subscribers, and while it can draw responses from Bing search, it makes for a better text generator or writing tool. There are a few key differences, though, that boil down to the data sources and models they've been trained on. Google Bard at a glanceĪt a base level, both chatbots use natural language processing, which means users key in a prompt or query, and the chatbots generate a human-like response. ![]() ![]() But there are plenty of other differences that set them apart-and which will dictate how you use each tool. Since the release of Bard, I've been using both tools one as a research tool, the other as a writing assistant. ![]() This is a key difference that Bard, Google's answer to ChatGPT, definitely scores points with-it offers a lot of what ChatGPT does, faster and for free. ![]()
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