But if you're given a similar problem again and again… then you'll start noticing patterns. Maybe you'll become able to make a pretty good guess just from the look & feel of the drawers. Despite the strange format, the problem will become just another pattern recognition task.
RESEARCH
-
Using Shape Equations to Predict Pixel Colors and Solve Problems
By
–
You're going to have to use the shape equations to make predictions about the color of certain pixel coordinates, find discriminative ones, and fetch the corresponding cubes from the drawers to make a conclusion. (One of several possible methods you could come up with!)
-
Reasoning: Making Sense Beyond Simple Interpolation
By
–
Reasoning is what you use to make sense of things that aren't a simple interpolation of things you've seen before.
-
Reasoning versus pattern recognition in novel problem forms
By
–
You'd have to use reasoning if the problem comes in a form that you've never seen before, that renders your pattern recognition ability ineffective. Let's say the task specification comes in the form of shape equations in the 2D plane, and your images come in the form of…
-
Reasoning in Visual Perception: Distinguishing Squares from Circles
By
–
The former sounds perhaps stranger, so here's an example. Let's say you have to tell whether a given image contains a square or a circle — a canonical perception problem. Sounds easy enough if you have a well-trained visual system, right? How would reasoning come into play?
-
Perception vs Reasoning: Data Volume Determines Problem-Solving Approach
By
–
Any task, even those canonically considered to be perception problems, can be solved with reasoning (if working with very little data). Inversely any task, even those canonically considered to be reasoning problems, can be solved with pattern recognition (given sufficient data).
-
Clarifying AI Text Prediction Beyond Simple Pattern Matching
By
–
Somebody needs to explain this to the people who are like "It's safe to predict human text – all the AI is doing is predicting what humans say, not [various aspects of thinking that humans do while they themselves decide what to say, which is what the AI is predicting]."
-
Digital Transformation Framework with Key Sub-Dimensions Overview
By
–
Digital Transformation Framework with Sub-Dimensions @ResearchGate https://
researchgate.net/figure/Digital
-Transformation-Framework-with-Sub-Dimensions_fig1_337167323
…
Via @ingliguori #DigitalTransformation #Cloud #MachineLearning #BigData #ArtificialIntelligence #cybersecurity #Blockchain #DX #Analytics #AI #IIoT #DataScience #IoT #IoTPL #digitaltwin -
Claim of ChatGPT political shift criticized for weak evidence
By
–
There's a popular thread claiming ChatGPT's political opinions shifted centrist after its Dec. 15 update. Evidence given for this is weak (4 online political tests given only once in each period), and the prompting method inappropriately forces in-test consistency of answers:
-
Galactica less popular, more hallucinatory than ChatGPT
By
–
Less, I think. Galactica didn't land with the consumer-facing splash that ChatGPT did. I only used it briefly, but it was also more hallucinatory, e.g. never refusing absurd requests. I think hallucination can be worse when infrequent, because we trust the model more.