Great insight into the real applications of LLMs. Also interesting to see that you find the Opus model being more successful for app development. In my experience, a combination of ChatGPT with Anthropic models yields the best results in coding.
Out of curiosity, how useful do you find the thinking mode in Claude Code?
All the tips given in the article are very useful, but for me it was also useful learning how to make different types of jam or cakes helps you understand the amount of sugar and butter used. Replacing store-bought sweets with homemade options gives you a sense of appreciation and a 'ritualistic' aspect when enjoying something sweet, which may reduce how often you indulge in sugary treats.
I found the documentation for networkx much better than the one from igraph[1] (at least the Python version). However, for community detection algorithms graph-tool[2] is better (it also uses a different class of models than the standard in literature)
Interesting, I always thought that research and startups are very similar. Where you have something (product/research-idea) which you think is novel and try to sell it (journals/customers).
The management skills which you potentiated differentiated the success of the two firms. I can see how the lack of this might be wildly spread out in academia.
Most startups need to do a very different type of research than academia. They need to move very fast and test ideas against the market. In my experience, most academic research is moving pretty slowly due to different goals and incentives - and at times it can be a good thing.
How the World Thinks: A Global History of Philosophy - Julian Baggini [1]
The author does an amazing job presenting the different views about the world and some important differences between cultures. If you are like me and haven't interacted that much with other schools of thoughts outside of the Western world, but are interested in learning more about them, you'll enjoy the introductions to Indian thinking as well as Chinese, Islam and some African philosophies. Also, he does a good job of highlighting some of the limitations of each, including Western thought.
If you have knowledge both in biology as a physician and can code, you can also become a bioinformatician, where you can still apply ML. Maybe the difference will be that it will be more on the application side of the ML rather than the theoretical part.
Also, I will be cautious about "... landing a PhD position at a good US school", from my experience and others, I've found out that it's more important to look after a supervisor with whom you can resonate rather than chasing a reputable institution.
It's sort of the problem I'm facing here. Research in machine learning is weak in my country, so I'd probably have to apply elsewhere. Medical research here is very good though, so I would have no problem just staying here as there are multiple good advisors. This is what makes A PhD in machine learning so much more difficult.
My grandparents are in their early 80s or late 70s and aren't very open to learn new technologies.
For the past 7 years they used and iPad (one of the early models 2nd or 3rd generations) and it served them well. I've introduced the the family contacts, put FaceTime and Photo library on the first screen and it seems ok for them. I've also annotated what volume button do and teach them that if they have a problem with it to press the big button (home button).
The only problem with the iPad is that recently there are some connectivity issues (it seems it doesn't always stay connected to Wi-Fi and they don't receive my FaceTime calls). I think this may be due to the old iOS it's using (v10 or v9). So, considering to buy them a newer version.
This is a problem I’ve experienced as well. As apple devices get much older, you run into things like password nags much more frequently. This is extremely off putting for someone who isn’t familiar with tech. Eventually some apps just stop working at all. Then you try to give them a new device, and it’s just similar enough to be extra confusing.
Out of curiosity, how useful do you find the thinking mode in Claude Code?
Good luck with the PDF app!