An overview of #moneo | RTM System Components for improving Clean-in-place Machine Performance http://
ow.ly/KgBA50M3G1r #sponsored #ifm_iiot #industry40 #iiot #digitaltransformation #GartnerIT
AI
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RTM System Components Enhance Clean-in-place Machine Performance
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Stable Diffusion 2.0 DreamBooth on AutoTrain Now Available
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Have you been a good data scientist this year? Stable Diffusion 2.0 is now available on AutoTrain DreamBooth. Create your own AI-generated images without any code!Check it out here: https://
huggingface.co/spaces/abhishe
k/dreambooth
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The prompt for the image below was inspired by @hardmaru
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YouChat combines ChatGPT and search, useful despite hallucinations
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3. YouChat — http://
You.com ChatGPT + search Not super reliable — hallucinates often in spite of SERP grounding. But when it works, being able to ask conversational questions about recent, technical subjects is just incredible: -
Jasper Chat: Better prose than ChatGPT, but more hallucinations.
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2. Jasper Chat — https://
jasper.ai/chat If you liked my posts on longer-form writing in ChatGPT using conversational feedback, this is what you want. Better prose than ChatGPT, and more imaginative. Fact-check hard, though — it hallucinates more too. -
Reasoning and Pattern Recognition as Transferable Abilities
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Reasoning and pattern recognition are abilities, not problem types. They're what you use to solve problems in different settings, they're not inherent to the problems themselves.
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Recognizing Patterns Through Repeated Problem-Solving Experience
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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.
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Using Shape Equations to Predict Pixel Colors and Solve Problems
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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!)
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Reasoning: Making Sense Beyond Simple Interpolation
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Reasoning is what you use to make sense of things that aren't a simple interpolation of things you've seen before.
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Reasoning versus pattern recognition in novel problem forms
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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…
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Reasoning in Visual Perception: Distinguishing Squares from Circles
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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?