cyclecycle

I'm still using gmail in the browser, and still thinking there must be a better way. What is the best pick in 2024 for an Ubuntu user?

I'm tasked with modernizing a legacy Visual Basic desktop application that interfaces with temp/pressure sensors via USB. The current app handles data collection, test management, and cloud uploads. The client wants to improve UI/UX, add features and automation, and ideally make it cross-platform (it's currently windows-only). I do have access to the old source code.

My background is in modern web development (preference for Svelte) and Python. I'm considering these options:

1. Electron: Despite its critics, VSCode's success makes me confident it could work well. However, I haven't found a straightforward Svelte setup. 2. Tauri: Looks promising with Rust backend and SvelteKit frontend support in the docs. I'm new to Rust but willing to learn. 3. Python with Tkinter: Familiar territory, but I'm leaning towards HTML/JS frontends for greater control over aesthetics. Pyinstaller seems viable for distribution though.

Ease of development and distribution are the main considerations. Performance less so as long as it's within reason.

What approach would you recommend? Are there other options I should consider? I'm open to learning new stacks if they offer significant advantages.

What do you think would be the most epic, most special, most interesting or exciting thing that you could possibly happen during your life time?

As a member of an early stage startup, let's say a technical founder, should one be tuned in to social media? What is one leaving on the table one way or the other? What advice would you give for making best use of such tools, and balancing the associated challenges?

Hi HN. Please find herein a brief description of a project I've been working on and why I'm posting.

Problem space: Improve the efficiency with which researchers / students can consume and utilise information from biomedical publications.

Background and use cases: During my time in the biomedical industry, I have been exposed to several cases where the class of tool I'm envisaging would be productive, but have not been able to find a satisfactory solution. Some (abstract) cases: - What are the consequences of modulating a certain biological entity? - What biological changes could cause a certain consequence? - What are the relational paths between process / chemical / outcome A and B, inferrable from published findings?

Solution is a system which: - Automatically compiles relationships between biomedical concepts from publications. - Models as a knowledge graph, allowing traversal queries to form chains of relations (inference). - Is queryable through an interface / API, optimised for the above cases.

Status: I have a relation extraction system that is fit for prototype (built in Python on top of SpaCy) and have experimented with knowledge graph implementation (in GraKn) and am encouraged to continue. Achieved in 3-4 months of part-time effort (relying on previous experience of "text mining" activites on scientific content).

I would like to: - Discuss with anyone interested. - Find potential collaborators for a proof-of-capability system demonstrate to some labs within the next 2-3 months. - Be challenged on the thinking and made aware of related projects (if it exists, sign me up).

Desirable traits in collaborator: - Someone to complement my skills. I.e, foremost they would have strength in front-end development / design. - Scientific background is a plus.

Don't hestitate to hit me up for a chat and more information. Cheers!