I can never remember all of these, so here’s a list of key generative AI terms with concise definitions:
Key Generative AI Terms Core AI Concepts Inference – The process of an AI model generating output based on input. Training – Teaching an AI model by adjusting its weights using large datasets. LLM (Large Language Model) – A neural network trained on vast text data to generate human-like language responses.
“How you like them apples?”
The phrase “How do you like them apples?” (or “How you like them apples?”) likely originates from American slang in the early 20th century, though its exact origin is debated. It generally conveys a sense of triumph, challenge, or one-upmanship.
Possible Origins:
World War I Artillery Slang (1910s) - British and American soldiers referred to certain types of grenades or artillery shells as “toffee apples” due to their round shape.
Greeble
“Greeble” refers to small, intricate details added to the surface of an object—often in visual design, 3D modeling, or special effects—to make it look more complex and visually interesting. The term is especially common in sci-fi and fantasy aesthetics, where greebles are used to give spaceships, buildings, or machinery a more detailed, lived-in appearance.
The concept was popularized by artists and model-makers working on Star Wars and other sci-fi films, where adding greebles to models helped create a sense of scale and realism.
The Lights of My Life - Accent lighting and lamps used by one photographer.
How to find waste with the robot
My first law of enterprise AI: if you end up having two robots talk with each other to complete a task, that task was bullshit in the first place, and you should probably eliminate it rather than automate it.
For example, if AI is used in both sides of B2B procurement (enterprise software sales), then much of the process is probably bullshit in the first place. There is so much weird and ancient in procurement, on both sides, that it’s clearly a poorly done process and part of enterprise IT culture.
The Hidden Toll of Meeting Hangovers - Hell is other people: “In our survey, more than 90% of respondents said they experienced meeting hangovers at least occasionally. More than half said these hangovers negatively impacted their workflow or productivity, while 47% reported feeling less engaged with their work. These effects often resulted from rumination, or replaying parts of the meeting in their mind. Nearly half (47%) of respondents noted harmful effects on their interactions with coworkers, such as feeling disconnected from their team or wanting to spend time alone."
A theory of Elons - If you can get away with breaking regulations and laws, you can gain competitive advantage over those who don’t.
Old Media Finally Wakes Up from a Coma - “Hey, guys”-style getting more mainstream. // Also, long form podcasts.
GEN AI: TOO MUCH SPEND, TOO LITTLE BENEFIT? - Goldman (PDF) - ‘We first speak with Daron Acemoglu, Institute Professor at MIT, who’s skeptical. He estimates that only a quarter of AI-exposed tasks will be cost-effective to automate within the next 10 years, implying that AI will impact less than 5% of all tasks. And he doesn’t take much comfort from history that shows technologies improving and becoming less costly over time, arguing that AI model advances likely won’t occur nearly as quickly–or be nearly as impressive–as many believe. He also questions whether AI adoption will create new tasks and products, saying these impacts are “not a law of nature.” So, he forecasts AI will increase US productivity by only 0.5% and GDP growth by only 0.9% cumulatively over the next decade’