spitfire

SEEKING CONTRACT WORK - remote, email in profile. Location: West coast, remote only.

I'm a data scientist with more than 15 years experience who has worked with major automakers, shipping companies, and F100 companies, I'm looking for my next project. An ideal fit is a small/medium company with green or brownfield problems that need solving.

I'm skilled at building from 0 to 1, I normally do what is now called data engineer, data scientist, and machine learning engineer as one person. My work usually involves finding non-traditional datasources - Once it was USDA data for rural community demographic enrichment, Several times it was getting hands on with people or equipment. If we work together I'll do what I need to in order to solve the problem.

Technologies/techniques: Machine learning/AI, LLM's/RAG, All the tools surrounding ML and AI, A whole host of others.

Contact me if you have a tough challenge I can gnaw on.

SEEKING CONTRACT WORK - remote, email in profile.

Location: West coast, remote only.

I'm a data scientist with more than 15 years experience who has worked with major automakers, shipping companies, and F100 companies, I'm looking for my next project. An ideal fit is a small/medium company with green or brownfield problems that need solving.

I'm skilled at building from 0 to 1, I normally do what is now called data engineer, data scientist, and machine learning engineer as one person. My work usually involves finding non-traditional datasources - Once it was USDA data for rural community demographic enrichment, Several times it was getting hands on with people or equipment. If we work together I'll do what I need to in order to solve the problem.

Technologies/techniques: Machine learning/AI, LLM's/RAG, All the tools surrounding ML and AI, A whole host of others.

Contact me if you have a tough challenge I can gnaw on.

SEEKING WORK - remote, email in profile.

Location: West coast Canada, remote only.

Techniques: Agentic & Trajectory development, Machine learning/AI, LLM's/RAG, Transformers, GenAI, MCMC, MCTS, Bayesnets, Neural architecture search.

Languages: Python, Postgres, Spark, Bash, Mathematica, Others.

Frameworks: PyData (Pandas, NumPy, scikit-learn), PyTorch, TensorFlow/Keras, PySpark, LangChain, XGBoost, LightGBM, Others.

Tools: AWS, Spark, Gurobi/highs/ortools, Kubernetes, Docker, Linux, Git, Tableau/databricks

I'm a data scientist who has worked with the likes of Porsche and Mulesoft, I'm looking for the next thing.

Some past work:

  - In the wild part failure prediction for automotive parts.
  - Server fleet failure prediction for Mulesoft. Giving a warning to do load shedding.
  - Real-time Vehicle routing, Get a couch from where you are, to where you want it to be.
  - Taxi fleet maintenance optimization and failure prediction for a latam taxi company. Saved entire cars. 
  - Automated sports highlights - Feed in video, get nicely cut highlights of diving catches, touchdowns, etc.
  - Wound identification and mangement - Identify what sort of wound, label and categorize the tissue.
  - Account grading and revenue optimization for ARM. 
  - Maritime anti-piracy - Identifying pirate skiffs, at risk vessels, and routing them aroound danger.

Didn’t Patrick McKenzie (patio11) do this already with appointment reminder?

A soundtrack so good they made three separate soundtracks. The last one was entirely music that wasn’t in the movie.

Fantastic.

The 90s was a time when computers were doubling in speed every 18 months. I remember office 97* being lightning fast on. A 366mhz celeron - a cheap chip in 1998.

You could build fast software today by simply adopting a reference platform, say. A 10 year old 4core system. then measuring performance there. If it lags then do whatever work needs to be done to speed it up.

Personally I think we should all adopt the raspberry pi zero as a reference platform.

Edit: * office 2000 was fast too with 32 megs of ram. Seriously what have we done?

Obsolescence Guaranteed Is a good name for a replica retro computer store.

If I ever retire and run a bar on the beach^w^w^w^w retro computer store, that’s what it’ll be called.

Success is a cruel mistress.

Outsized success a curse.

According to Wikipedia “ JetBrains, initially called IntelliJ Software,[9][10] was founded in 2000 in Prague by three Russian software developers:”

My understanding is that they had the Czech business location with Russian developers so they had a clean public face.

I’d believe you if you insisted on Kiev based too, I don’t know anything first hand.

Oh okay. I thought you had something negative to say about thoughtworks. I’ve known a few people who worked there and thought there was some messy business i didn’t know about.

Jetbrains is Russian. They relocated to Czech to wash their face.

Expand on the a little please. I’d like to know the background.

If cr is old tech any keywords for what is new/current tech?

I’m not sure your second point is true. The vast vast majority of classified information is very boring, or operational like frequencies of radar, etc.

Both sides know the basics, it’s what frequencies the radar comms and aircraft work at that is classified.

There’s very little “OMG this one algorithm changes everything!!”. Unless proven otherwise

I have a copy of the original cognitive radar papers. You can find most of them, the real work is doing a real world implementation.

I’m not aware of any computer science breakthroughs required for the f35.

I expect knowing this new f35 deliveries will have hardware just different enough to need new software.

Move a few flags around in a few registers and for all practical purposes it’s stuck.

Swedish griphen e/d variants use an American engine. Possibly other avionics idk. So those will be grounded after few months into a conflict.

I expect a crash program to reengineer them has already started if only unofficially.

So what (if anything) is taking strangeloops’ place?

I’ll add when I say “learning” I mean memorization. Memorizing on a higher level than facts.

I would love to spend the time and see how altering the query alters the reasoning path. How firm is in the path once it’s chosen?

A high level approach has the possibility to be very computer efficient.

What I further got from this is the models are learning the methods, but not evaluating themselves along the way. They don’t check for errors.

So once they go down a path they can’t properly backtrack.

This feels like the ground truth I’ve experienced in LLMs to date.

It's interesting that you note the unreliability. I always assumed tubes were unreliable, but thought anything solid state (even those card based systems) would be "reliable enough" to start taking for granted.

But then you look at it and think Yeah, obviously they're not going to have MTBF times in the millions. It's going to be hundreds of hours - once a week, or maybe every few weeks between real hard crashes.

How would that change your behaviour.

1963 Jaguar E-Type

Sorry, I should have said “Import more Ukrainians “.

For exactly the reasons you mention. They’ll fit right in.

Import Ukrainians instead?

Planning in the U.S.S.R Problems of theory and Organisation

It is available on annas archive. Along with other similar books (Search: "Planning in the USSR").

LOOK UPON ME AND DESPAIR!

I have the book “planning in the user” somewhere packed away. I remember it speaking about the number of variables and size of the problem in it. Sorry I don’t remember the numbers off the top of my head.

Obviously it didn’t work out though.

The other book worth getting is “red plenty”.

I miss the old internet.

SEEKING WORK - remote, email in profile.

Location: West coast, remote only.

I'm a data scientist who has worked with the likes of Porsche and Mulesoft, I'm looking for the next thing.

An ideal fit would be a small/medium company with hair on fire green or brownfield problems that need solving. I'm currently quite interested in AI, and routing/optimization problems.

Technologies/techniques: Machine learning/AI, LLM's/RAG, Transformers, GenAI, MCMC, MCTS, Bayesnets, Neural architecture search, Python, Pytorch/Tensorflow/Keras, All the tools surrounding ML and AI, A whole host of others.

Some past work:

  - In the wild part failure prediction for Porsche, saving millions.
  - Server fleet failure prediction for Mulesoft. Give a 5 minute warning to do load shedding.
  - LLM system to output human readable flight delay information for well known airline.
  - Real-time Vehicle routing, Get a couch from where you are, to where you want it to be.
  - Goal oriented voice agent in the pre-LLM era. 
  - Taxi fleet maintenance optimization and failure prediction for a latam taxi company. Saved entire cars. 
  - Automated sports highlights - Feed in video, get nicely cut highlights of diving catches, touchdowns, etc.
  - Wound identification and mangement - Identify what sort of wound, label and categorize the tissue.
  - Account grading and revenue optimization for ARM. 
  - Maritime anti-piracy - Identifying pirate skiffs, at risk vessels, and routing them aroound danger.

  - Ads or gambling. I'd rather sleep at night. Thanks.

SEEKING WORK - remote, email in profile.

Location: West coast, remote only.

I'm a data scientist who has worked with the likes of Porsche and Mulesoft, I'm looking for the next thing.

An ideal fit would be a small/medium company with hair on fire green or brownfield problems that need solving. I'm currently quite interested in AI, and routing/optimization problems.

Technologies/techniques: Machine learning/AI, LLM's/RAG, Transformers, GenAI, MCMC, MCTS, Bayesnets, Neural architecture search, Python, Pytorch/Tensorflow/Keras, All the tools surrounding ML and AI, A whole host of others.

Some past work:

  - In the wild part failure prediction for Porsche, saving millions.
  - Server fleet failure prediction for Mulesoft. Give a 5 minute warning to do load shedding.
  - LLM system to output human readable flight delay information for well known airline.
  - Real-time Vehicle routing, Get a couch from where you are, to where you want it to be.
  - Goal oriented voice agent in the pre-LLM era. 
  - Taxi fleet maintenance optimization and failure prediction for a latam taxi company. Saved entire cars. 
  - Automated sports highlights - Feed in video, get nicely cut highlights of diving catches, touchdowns, etc.
  - Wound identification and mangement - Identify what sort of wound, label and categorize the tissue.
  - Account grading and revenue optimization for ARM. 
  - Maritime anti-piracy - Identifying pirate skiffs, at risk vessels, and routing them aroound danger.

  - Ads or gambling. I'd rather sleep at night. Thanks.

Remember kids: Don't burn chrome!

Makers of the 1990's HTML editing software HotDog.

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

Edit: And yes, I saw what you did there.