Readit NewsKydlaw commented on Why we chose LangGraph to build our coding agent qodo.ai/blog/why-we-chose... · Posted by u/timbilt
We explored LangGraph last November and were pleasantly surprised by the difference with LangChain. The framework had much more care put in it. It was much easier to iterate and the final solutions felt less brittle.
BUt the pricing model and deployment story felt odd. The business model around LangGraph reminded us of Next.js/Vercel, with a solid vendor lock-in and every cent squeezed out of the solution. The lack of clarity on that front made us go with Pydantic AI.
Kydlaw commented on Notebooks as reusable Python programs marimo.io/blog/python-not... · Posted by u/akshayka
I discovered Marimo a couple weeks/months ago here iirc. This really lands on a sweet spot for me for data exploration. For me the features that really nails it are the easy imports from other modules, the integrated UI components, and the app mode.
Being able to build model/simulations easily and being able to share them with others, who can then even interact with the results, as truly motivated me to try more stuff and build more. I've been deploying more and more of these apps as PoCs to prospects and people really like them as well.
Big thanks to the team!
In the list that you filtered and hand picked yourself there is literally "War crimes committed in Serbia". The article linked is mentioning a researcher that spoke badly about the US president.
Help me understand how these two things are on same level, please?
Kydlaw commented on Building Effective "Agents" anthropic.com/research/bu... · Posted by u/jascha_eng
I put the agents in quotes because anthropic actually talks more about what they call "workflows". And imo this is where the real value of LLMs currently lies, workflow automation.
They also say that using LangChain and other frameworks is mostly unnecessary and does more harm than good. They instead argue to use some simple patterns, directly on the API level. Not dis-similar to the old-school Gang of Four software engineering patterns.
Really like this post as a guidance for how to actually build useful tools with LLMs. Keep it simple, stupid.
In fact they are mentioning LangGraph (the agent framework from the LangChain company). Imo LangGraph is a much more thoughtful and better built piece of software than the LangChain framework.
As I said, they already mention LangGraph in the article, so the Anthropic's conclusions still hold (i.e. KISS).
But this thread is going in the wrong direction when talking about LangChain
Kydlaw commented on Kowloon Walled City: Heterotopia in a Space of Disappearance (2013) mascontext.com/issues/tra... · Posted by u/hyperific
I am adding a blog post, shared on HN a couple months ago, that show an architectural cross section of the city.
https://cohost.org/belarius/post/6677850-architectural-cross
(I am not the author of the blog, nor the original poster, but I just want to share the link because I found this incredibly cool)
The title made me click, and the content was enjoyable. But I still don't think clickbait like this should be present in scientific papers.
It's something about how scientific papers are not "for pleasure", they're informational tools. An easter egg in a game is cool right, but an easter egg in a graphics driver? That's the distinction I'm making here.
I am so puzzled by this attitude. People are free to make any distinction they want, the way they want, but the representation you have of a scientific literature is erroneous.
Scientific articles are informational tools that report results of experiments and nothing more. If the results are interesting to the peers, they are published. By they are not world's laws made paper unless sufficient replications are made. This means that each article need to be read with the context of the literature in mind and with a critical eye. Each are a single point of evidence to a phenomena.
Hence, there are subjective informational tools, written toward a specific audience (the experts of the domains) to inform of a specific result in a specific case.
On top of that, their are specific journal/issues where these types submissions are allowed. Don't read these submissions if you are looking for serious "information tools"
Scientific literature must be handled the same way as legal literature. If you are not a law expert, you ask a lawyer. If you think you are a legal expert when you are not, surprising consequences may arise.
In universities, they are classes dedicated to handling the scientific literature. They are provided for a reason.
So please, don't use cat's physic for liquid simulation in game engine... or please do?
Any modern tips / life hacks for this situation?
They are a little more focus on scientific computing than uv, which is more general. They might be a better option in your case.