npalli

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8 日前議論

Rewrite in C is the new Rewrite in Rust.

4 か月前議論

So, and iPad with an attached keyboard.

5 か月前議論

If it is this easy, surely the trend is Rust output being an intermediate pass of the LLM super compiler. A security subset if you will (like other kinds of optimization), it will move from Rust specs to some deeper level of analysis and output the final executable. Some brave souls will read the intermediate Rust output (just like people used to read the assembler output from compilers) but the LLM super compiler will just translate a detailed English like spec into final executables.

6 か月前議論

Good. How does it compare to cuOPT which seems to be 10-5000x faster than existing solvers for Vehicle routing if you believe the marketing.

6 か月前議論

Not Rust because you won't find anyone to maintain code. Rust is only for rewriting existing code in other language not maintaining it. C++ perhaps because of number of people who already know it, but only for performance sensitive areas. Also, lot of training data. Other than that, usual suspects, Java/C# for enterprise and node/Python for web/DS.

6 か月前議論

LOL, the blog gives a lot of detailed reasons, even summarizes it [1] and but some random stranger gives an outdated opinion from the '90s, which is not even wrong just plain humorous. If slave labor, how come everything else is also not so cheap.

   [1] Virtually all the major mechanisms that can drive efficiency improvements — improving technology and overlapping S-curves, economies of scale (including geometric scaling effects), eliminating process steps, reducing variability and improving yield, advancing towards continuous process manufacturing — are on display here

6 か月前議論

Andy is probably the only person who adores Larry Ellison (Oracle) unironically.

6 か月前議論

Seems like a bug, it's pulling in all the jobs that have either vision or pro in their text (which is probably everything). Need to put "vision pro" to filter and even select the product (Apple Vision Pro) to get about 74 jobs.

6 か月前議論

This is a good resource, however for about 99.99% of people, you are most likely to just use a foundation model like ChatGPT, Claude, Gemini etc. so this knowledge/training will get you neither here or there. I would suggest you look into another Karpathy's video -- Deep Dive into LLMs like ChatGPT.

https://www.youtube.com/watch?v=7xTGNNLPyMI

6 か月前議論

LOL, this is the list to keep in your head for this so called "manual". Best of luck of those who will work through this. BTW, Karpathy made that comment in 2025 not 2024.

  Morphability - natural language as morphable code
  Abstraction - tasks become reusable commands
  Recursion - stack abstractions for leverage
  Internal Consistency - prevent system drift
  Reproducibility - crash-resilient design
  Morphic Complexity - recognize over-engineering
  E2E Autonomy - measure actual capabilities
  Token Efficiency - maximize work per token
  Mutation & Exploration - controlled self-improvement

6 か月前議論

Seems you are paying the Dell tax of 15%. The same setup is $4K from NVidia, Lenovo and $3K for 1TB at Asus.

https://www.dell.com/en-us/shop/desktop-computers/dell-pro-m...

6 か月前議論

You just need to master one package managed in depth and you will get what you really want with Modern C++.

6 か月前議論

Just like San Francisco and Dallas/Texas (from his article) are very different in the US, we should expect lot of differences in Europe (as others mentioned, he clubs UK with EU). Housing is a general problem for all major cities though, not sure why you think it is unique to London in the whole continent. Stockholm, Paris, Dublin, Lisbon to name a few, are pretty bad for housing in their own unique ways. Certainly shouldn't be "breaking your brain".

6 か月前議論

Great summary of the year in LLMs. Is there a predictions (for 2026) blogpost as well?

7 か月前議論

Seems very detailed and comprehensive. Did I miss it, but was there a performance comparison to the PyTorch version at the top?

7 か月前議論

Three things:

1. The Rise: 2005 - 2010 Google hired Guido van Rossum in 2005 (stayed on for seven years) and gave corporate blessing that made everyone comfortable with moving from Perl to Python. It was seen as the language of scientists and smart people so a lot of people working in misc. languages like Fortran, MATLAB, Perl moved here. To remove the speed issue the official Google mantra was "Python where we can, C++ where we must". AI heavy weights like Peter Norvig (I think he was the chief AI scientist at one point and co-author of the famous AIMA book), promoted Python to be an acceptable Lisp.

2. Near Death: 2010-2015 Python almost died due to self inflicted wound from the 2 -> 3 transition and there was a good chance it would have gone nowhere like many languages before. Guido also moved away from Google and Google seemed to have shifted it's attention to Golang (apart from the standard C++ and Java). BTW, Python's dominance was not seen positively within Google hence they stopped actively promoting it. For ex. a leaked transcript from Eric Schimdt had him saying this

   So another definition would be language to Python, a programming language I never wanted to see survive and everything in AI is being done in Python.

https://gist.github.com/sleaze/bf74291b4072abadb0b4109da3da2...

3. Resurrection: 2015-Now Data science and ML took off and Python was right there thanks to the initial sponsorship from Google and ecosystem of scientists and engineers who were familiar (including working in the two-language mode). There was no language that could rival at this point.

Most of the syntax, power considerations etc.. are side shows as most scripting languages just tap into very powerful libraries written in c/c++/fortran or wrappers around shell. Doubt that distinguishes Python to the point where it has become so dominant.

7 か月前議論

Confluent was trading at less than 50% of its IPO price when IBM made the offer. The stock and the company has been going sideways for several years now, keeps growing revenues but loses even more as most of it is in Sales and Marketing. In which world is this seen as some sort of extraordinary company that will get sabotaged by IBM. Seems Confluent management knows the writing on the wall, IBM will clean up (fire a bunch of sales and management guys) and make this a workable business. It will seem brutal for some Confluent guys but that's because their business is broken; and only someone from outside can come in and fix it as the current senior management cannot.

IBM has been around for over a hundred years, maybe they know a thing or two about running a software business :-)

7 か月前議論

[flagged]

8 か月前議論

Kind of strange take as though unique to software. Every sector that is large has issues since ambitious projects stretch what can be done by the current management and organizational practices. All software articles like these hark back to some mythical world smaller in scope/ambition/requirements. Humanity moves forward

* Construction and Engineering -- Massive cost overruns and schedule delays on large infrastructure projects (e.g., public transit systems, bridges)

* Military and Government -- Defense acquisition programs notorious for massive cost increases and years-long delays, where complex requirements and bureaucratic processes create an environment ripe for failure.

* Healthcare -- Hospital system implementations or large research projects that exceed budgets and fail to deliver intended efficiencies, often due to resistance to change and poor executive oversight.

8 か月前議論

Python is nothing without it’s batteries.