Eric Ness

Dad, husband, programmer, popcorn enthusiast.

Computer Science PhD candidate @AngliaRuskin (Machine Learning, Remote Sensing, Env. Data). bsky: @eric.ness.net

[Eric Ness @ericness]

My nine year old son called me 'Temu Dad's today

[Eric Ness @ericness]

This is a fascinating video. Most people don’t realize this: AI pricing and latency mostly come down to batching. Bigger batches = cheaper tokens but slower responses. Faster modes? You’re literally paying to jump the queue and reduce batching efficiency. https://t.co/8ka2fzuxbw

[Eric Ness @ericness]

This is clever: Sentinel-2 captures RGB bands ~1 second apart. Moving vehicles shift between captures → creating color “smears.” DrishX turns those into vehicle counts, speeds, and trends across the globe. - https://t.co/g8zM3qSc5T

[Ihtesham Ali @ihteshamali]

A mathematician who shared an office with Claude Shannon at Bell Labs gave one lecture in 1986 that explains why some people win Nobel Prizes and other equally smart people spend their whole lives doing forgettable work.

His name was Richard Hamming. He won the Turing Award. He invented error-correcting codes that made modern computing possible. And he spent 30 years at Bell Labs sitting in a cafeteria at lunch watching which scientists became legendary and which ones faded into nothing.

In March 1986, he walked into a Bellcore auditorium in front of 200 researchers and told them exactly what he had seen.

Here's the framework that has been quoted by every serious scientist for the last 40 years.

His opening line landed like a punch. He said most scientists he worked with at Bell Labs were just as smart as the Nobel Prize winners. Just as hardworking. Just as credentialed. And yet at the end of a 40-year career, one group had changed entire fields and the other group was forgotten by the time they retired.

He wanted to know what the difference actually was. And he said it wasn't luck. It wasn't IQ. It was a specific set of habits that almost nobody is willing to follow.

The first habit was the one that hurts the most to hear. He said most scientists deliberately avoid the most important problem in their field because the odds of failure are too high. They pick a safe adjacent problem, solve it cleanly, publish it, and move on. And because they never swing at the hard problem, they never hit it. He said if you do not work on an important problem, it is unlikely you will do important work. That is not a motivational line. That is a logical one.

The second habit was about doors. Literal doors. He noticed that the scientists at Bell Labs who kept their office doors closed got more done in the short term because they had no interruptions. But the scientists who kept their doors open got more done over a career. The open-door scientists were interrupted constantly. They also absorbed every new idea passing through the hallway. Ten years in, they were working on problems the closed-door scientists did not even know existed.

The third habit was inversion. When Bell Labs refused to give him the team of programmers he wanted, Hamming sat with the rejection for weeks. Then he flipped the question. Instead of asking for programmers to write the programs, he asked why machines could not write the programs themselves. That single inversion pushed him into the frontier of computer science. He said the pattern repeats everywhere. What looks like a defect, if you flip it correctly, becomes the exact thing that pushes you ahead of everyone else.

The fourth habit was the one that hit me the hardest. He said knowledge and productivity compound like interest. Someone who works 10 percent harder than you does not produce 10 percent more over a career. They produce twice as much. The gap doesn't add. It multiplies. And it compounds silently for years before anyone notices.

He finished the lecture with a line I have never been able to shake.

He said Pasteur's famous quote is right. Luck favors the prepared mind. But he meant it literally. You don't hope for luck. You engineer the conditions where luck can land on you. Open doors. Important problems. Inverted questions. Compounded hours. Those are not traits. Those are choices you make every single day.

The transcript has been sitting on the University of Virginia's computer science website for almost 30 years. The video is free on YouTube. Stripe Press reprinted the full lectures as a book in 2020 and Bret Victor wrote the foreword.

Hamming died in 1998. He gave his final lecture a few weeks before. He was 82.

The lecture that explains why some careers become legendary and others disappear is still free. Most people who could benefit from it will never open it.

[Eric Ness @ericness]

I built a GitHub issue–centric workflow framework for Claude Code. A GitHub issue # drives everything: plan → audit → execute → review. Fully configurable (TDD, ADR, etc.). At this point, my 9-year-old could probably do most of my job. https://t.co/ShRU6ImGFy

[Eric Ness @ericness]

Growing concern over academic freedom as some college students monitor & report professors for perceived political incorrectness. Texas A&M incidents cited. #AcademicFreedom #News - https://t.co/zszG8yobEh

[Eric Ness @ericness]

Tired of firing up QGIS just to peek at a raster?
viewtif lets you:
• View single-band + RGB GeoTIFFs
• Overlay shapefiles
• Browse NetCDF time steps
• Open HDF/HDF5 + FileGDB rasters
All from the command line.
#GeoSpatial #Python - https://t.co/WlwOvx6JzM

[Eric Ness @ericness]

SWOT captured 65-ft waves during Storm Eddie, the tallest ever measured from orbit. These waves traveled 15,000 miles, carrying the storm’s power across entire oceans. #SWOT #EarthObservation #RemoteSensing #ClimateScience https://t.co/Ros60h4GPo

[Eric Ness @ericness]

Burnscar Detection Pipeline: NASA FIRMS + Sentinel-2 + Google Earth Engine + SQLMesh + DuckDB = open-source system to spot suspicious burn scars & potential arson events. #OSINT #RemoteSensing #FIRMS
Library: https://t.co/Gwq5jFKm44
Writeup: https://t.co/8TAitOkw3u

[Eric Ness @ericness]

So I just implemented a major update to the news clustering algorithm on https://t.co/wYJwlRb9Yj. If anyone is interested, I am also currently supporting a number of new languages.

[Eric Ness @ericness]

Wildfire modeling just got faster. PROPAGATOR uses stochastic cellular automata + rate-of-spread physics to simulate fire behavior in minutes — helping emergency teams make real-time decisions. #GIS #EmergencyManagement #RemoteSensing https://t.co/Fhaia8O6to

[Eric Ness @ericness]

This looks interesting — Lonboard 0.13 just dropped and now supports H3, S2, Geohash, and even A5 layers. Lots of new ways to explore geospatial grids in Python.
#GIS #GeoPython #Lonboard - https://t.co/RNhmp34RFc

[Eric Ness @ericness]

Tired of hunting down shapefiles? The new wkls Python library gives you instant access to 625K global administrative boundaries with clean, chainable syntax — no downloading, no parsing. Just https://t.co/6jPjkY9z12.cityofnewyork.wkt() - https://t.co/BP9fqG8hw4

[Eric Ness @ericness]

SAR satellites don’t need daylight — they image Earth day, night, rain, or clouds. Different radar bands (P, L, S, C, X, Ku, K, Ka) reveal everything from subsurface rivers to cars in a parking lot. Wild tech. #SAR #RemoteSensing #Geospatial - https://t.co/f6uAaVz9NE

[Eric Ness @ericness]

Orbio Earth just open-sourced their full methane detection pipeline—models, tools, synthetic-plume engine & validation notebooks—for Sentinel-2, Landsat 8/9, and EMIT. #Methane #ClimateTech #OpenSource - - https://t.co/jCZW9u8geb

[Eric Ness @ericness]

This is kind of a fabulous song. https://t.co/NQSuMIlsyY

[Eric Ness @ericness]

This is a wonderful 'Introduction to GIS Programming' class online by Dr. Qiusheng Wu - https://t.co/vEo7lZ0ziF

[Eric Ness @ericness]

This is a fairly fabulous paper 'Global mapping of oil palm planting year from 1990 to 2021'. - https://t.co/jlo6OFippM

[Eric Ness @ericness]

Check out the 'C3S global temperature trend monitor' - https://t.co/p2XM8KLOyJ