Will new developers know/understand what they don't know, or will the new state of things simply become normalized?

Will the SEC decide to?

It's about a company that makes sausage that discovers their meat supply is full of sawdust and rat feces. They decide to sell off all their inventory, and crash the market, before their competitors do.

https://en.wikipedia.org/wiki/Sparse_distributed_memory

https://512pixels.net/2024/03/apple-jonathan-modular-concept...

Is HN run on eventual consistency? My numbers don't match yours.

I'm a data scientist with over 20 years of experience specializing in solving hair on fire problems. I thrive on gnarly problems AI can't complete even if walked through the problem step-by-step. Often it involves getting hands on or talking with staff to find the data that's really needed.

My past work includes:

   - Saving a German automaker from lemon law recalls.
   - Helping a major cloud vendor predict server failures to enable load shedding.
   - Real-time on demand routing logistics work .
   - Airline flight delay forecasting.
   - Oil & Gas forecasting.
   - Shipping piracy risk.
   - Wound identification and classification.
   - Revenue optimization, persona identification and dynamic "risk-on/risk-off" risk management for ARM.

Things I'm unwilling to work on:

   - Gambling.
   - Ads/Surveillance.
   - Payday loans/rent-to-own.

I'm a data scientist with over 20 years of experience specializing in consulting and fractional leadership. I do the data science that AI's can't do. I thrive on gnarly problems where standard off-the-shelf solutions fall short, and recently where Ai just can't complete the task even if walked through the problem. My track record includes saving a German automaker from lemon law recalls and helping a major cloud vendor predict server failures to enable load shedding.

I've tackled a wide range of challenges across various industries, including oil reservoir and well engineering forecasting, automotive part failure prediction, and shipping piracy risk to route ships away from danger. My technical work extends to realtime routing (CVRP-PD-TW) for on-demand delivery, legal entity and contract term extraction, and wound identification with tissue classification. I also work with the current wave of LLMs and agents, and make them do magic.

I've worked with the standard stacks you’d expect: Python, PyTorch, Spark/Ray, AWS, Agentic engineering, etc. But I believe the solution must be driven by the problem, not the tools. I bring years of experience helping companies plan, prototype, and productionize sane data science solutions.

Please reach out if you have a difficult problem to solve. I do love stuff in physical meat-space.

NB: Please do not contact me if you are working on ads, gambling, or "enshittification". I prefer to sleep at night.

Keep the interpreters surface area as small as possible. Do some work to make sure you can accelerate numeric, and JIT/compile functions down to something as close to native as you can.

Wolfram, and Taliesin Beynon have both said Wolfram were working internally to get a JIT working in the interpreter loop. Keep the core small, and do that now while it's easy.

Also, it's just easier to write in Mathematica. It's probably 10x smaller than the rust code:

    f[x_Integer]:=13*x;
    f::help:="Multiplies x by 13, in case you needed an easy function for that."

There is an architectural flaw in Woxi that will sink it hard. Looking through the codebase things like polynomials are implemented in the rust code, not in woxilang. This will kill you long term.

The right approach is to have a tiny core interpreter, maybe go to JIT at some point if you can figure that out. Then implement all the functionality in woxilang itself. That means addition and subtraction, calculus, etc are term rewriting rules written in woxilang, not rust code.

This frees you up in the interpreter. Any improvements you make there will immediately show up over the entire language. It's also a better language to implement symbolic math in than rust.

It also means contributors only need to know one language: woxilang. No need to split between rust and woxilang.

Edit: picture is from a Vienna meet up. Not OpenAI.

They're probably just busy.

Is that true? I remember sgi had a shader library for modeling light aimed at the automotive market. All the demos and examples were showing off car paint colours in different environments.