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@RushHourPhD

参加日 Temmuz 2018
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Prof. Stefan Rahmstorf 🌏 🦣
Re climate change, many here repeat all the old climate myths… Warming caused by urban heat island effect. Global confused with Greenland temperatures. Or tell me (paleoclimate expert) that climate always changed. Hey, we know it all, you find all here: skepticalscience.com
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ViralRush ⚡
ViralRush ⚡@ViralRushX·
Focus on the black cross and the red dots will appear to follow waves even though they move straight.
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The Scientific Lens
The Scientific Lens@LensScientific·
Start several metronomes out of sync on a movable base, and watch what happens. Through tiny vibrations transmitted across the platform, they slowly adjust to each other and end up ticking in perfect unison. Source: UCLA Physics & Astronomy
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Nav Toor
Nav Toor@heynavtoor·
🚨BREAKING: OpenAI published a paper proving that ChatGPT will always make things up. Not sometimes. Not until the next update. Always. They proved it with math. Even with perfect training data and unlimited computing power, AI models will still confidently tell you things that are completely false. This isn't a bug they're working on. It's baked into how these systems work at a fundamental level. And their own numbers are brutal. OpenAI's o1 reasoning model hallucinates 16% of the time. Their newer o3 model? 33%. Their newest o4-mini? 48%. Nearly half of what their most recent model tells you could be fabricated. The "smarter" models are actually getting worse at telling the truth. Here's why it can't be fixed. Language models work by predicting the next word based on probability. When they hit something uncertain, they don't pause. They don't flag it. They guess. And they guess with complete confidence, because that's exactly what they were trained to do. The researchers looked at the 10 biggest AI benchmarks used to measure how good these models are. 9 out of 10 give the same score for saying "I don't know" as for giving a completely wrong answer: zero points. The entire testing system literally punishes honesty and rewards guessing. So the AI learned the optimal strategy: always guess. Never admit uncertainty. Sound confident even when you're making it up. OpenAI's proposed fix? Have ChatGPT say "I don't know" when it's unsure. Their own math shows this would mean roughly 30% of your questions get no answer. Imagine asking ChatGPT something three times out of ten and getting "I'm not confident enough to respond." Users would leave overnight. So the fix exists, but it would kill the product. This isn't just OpenAI's problem. DeepMind and Tsinghua University independently reached the same conclusion. Three of the world's top AI labs, working separately, all agree: this is permanent. Every time ChatGPT gives you an answer, ask yourself: is this real, or is it just a confident guess?
Nav Toor tweet media
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nature
nature@Nature·
Earth is now warming at a rate of around 0.35 ºC per decade, fresh analysis finds. go.nature.com/4aV6Gu8
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Vintage Maps
Vintage Maps@vintagemapstore·
Hours of daylight throughout the year.
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Zeke Hausfather
Zeke Hausfather@hausfath·
As a bit of background, I've been working with these tools since late 2022, and seen firsthand how they have dramatically improved over time. I’ve also worked with frontier AI labs to evaluate how well LLMs answer climate questions, and to help enable AI tools to support scientific collaboration. theclimatebrink.com/p/the-ai-augme…
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Eli Rabett
Eli Rabett@EthonRaptor·
Done previously
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Zeke Hausfather
Zeke Hausfather@hausfath·
@atrembath @RogerPielkeJr That’s nonsense, as water vapor is a feedback in the climate system rather than a forcing (with the exception of stratospheric water vapor from CH4 oxidation, which is generally accounted for as part of CH4 indirect forcing).
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