After my experience in consulting museums, I found that they spend a lot of money on software, which could potentially be replaced with open source software. Therefore I started an awesome list with FOSS software for museums: https://github.com/smartcompanion-app/awesome-open-source-mu....
i am not sure acctually of the math is acctually that complicated/important. the math around neural networks is calculus/chain rule etc and for model comparison/validation one needs statistics. the required math for e.g. understand transformers is quite accessible.
When reading your comment, it just reminds me on how feature flags can be misused as application configuration/customization. An antipattern i could observe at various organzations already.
For me feature flags go along with trunk based development to enable features in QA settings, but not on PROD yet, for PO/PM testing. Trunk based development allows for fast/easy devops, without complicated branching strategies.
Application configuration is, for me, part of the application and has the business context for customizing the application accordingly. Not sure if there are specific frameworks/tools out there. But one should clearly distinguish these two.
depends, JavaScript in the Browser has many useful things available, which I miss with python, e.g., fetch, which in Python you need a separate package like requests to avoid a clunky API. Java had this issue for long time as well, since Java 11 there is the HttpClient with a convenient API.
This guy is so amazing! With his video and the code base I really have the feeling I understand gradient descent, back propagation, chain rule etc. Reading math only just confuses me, together with the code it makes it so clear! It feels like a lifetime achievement for me :-)
I don't get your point here. User targeted ads are the main business model of the internet? Yes, few days ago it was revealed how billions of user data points could be gathered from Meta [1], did anybody care, outside a small privacy community? So indead these things are not surprising... My thoughts don't go so far to consider the effects on society, idk, do you?
It is no surprise, somehow they need to earn money. It will be interesting though how much the response of the LLM will be adapted. At least legally advertisement need to be marked for users. So either the response of an LLM will be extended with ad content or replaced by ad content.
I use GenAI for text translation, text 2 voice and voice 2 text, there it is extremely useful. For coding I often have the feeling it is useless, but also sometimes it is useful, like most tools...
Somebody scraped the play store and checked the framework, so a list for Android WebView apps, built with capacitor, is here: https://capgo.app/top_capacitor_app/ Maybe an equivalent is there on iOS for the same app...
Thinking without idiology about it, it seems to make sense to have an autonomous agent with a wallet. A requestor could send money (in whatever form) into the wallet of the agent and would buy tokens, processing time or whatever from the agent.
I can recommend Apache Camel (https://camel.apache.org) for similar data integration pipelines and even agentic workflows. There are even visual editors for Camel today, which IMHO make it extremely user friendly to build any kind of pipeline quickly.
Although I didn't collect numbers, but I made a similar experience in my workplace. I assume many people are highly distracted by ads and work efficiency is even reduced. Even many software engineers seem to not be aware of ublock... Would be interesting to know how many students started using an ad blocker at the end of your lecture :)