RomainB

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RomainB

@Rom1Bat

Building abundance

sf Katılım Aralık 2024
217 Takip Edilen65 Takipçiler
Lachlan Phillips exo/acc 👾
Let's do a basic thought experiment. Let's slow down our LLM. One layer per minute. One layer per hour. Run one layer of an LLM. Just one. Write the numbers down and post them to Tokyo. Run the next layer. Write them down and post them to Milan. After 100 or so rounds of basic matrix multiplication, scattered across 100 different computers, we finally get one token. Do it again for the next token. And the next. Thousands of rounds of arithmetic, posted between cities by hand, to produce a sentence. At no point in this process has any machine had any awareness of any meaning. Each step is just numbers going into numbers. The meaning only emerges upon observation. We happen to like the results, so we infer meaning. Where's the consciousness? In the pencil? The postman? If you cannot justify consciousness in such a situation then "complex behaviour" is a totally invalid metric for evaluating consciousness. You're just stunned that the eyes of the painting follow you around the room.
Lachlan Phillips exo/acc 👾 tweet media
Eliezer Yudkowsky@allTheYud

Simple way to see this is wrong: If you view a system as having inputs (like hearing something) and outputs (like saying something) then you can divide system properties by whether or not they affect I/O. Claude's weights somewhere storing "Paris is in France" affect I/O if you ask a question about Paris. The exact mass of the power supply to the GPU rack for that Claude instance doesn't affect I/O. That Claude instance being made out of silicon instead of carbon, or electricity in wires instead of water in pipes, doesn't affect I/O given a fixed algorithm above the wires or pipes. Nothing Claude can internally do will make anything get damp inside, if it's running on electricity. Nothing about "electricity vs water" can affect Claude's output for the same reason. It always answers the same way about France. Nothing Claude can internally compute will let it notice whether it's made of electricity or water flowing through pipes. When someone says "a simulated storm can't get anything wet", they are unwittingly pointing to the difference between the physical layer and the informational/functional layer. Things that the computer physics affect without affecting output; things that affect the output without depending on the exact computer-physics. The material it's made of doesn't affect the output. The output can't see the material because no algorithm can be made to depend on the choice of material. You can always run the same algorithm on different material, so you can't make the algorithm depend on that, so the output can't depend on that. By reflecting on your awareness of your own awareness, the fact of your own consciousness can make you say "I think therefore I am." Among the things you do know about consciousness is that it is, among other things, the cause of you saying those words. You saying those words can only depend on neurons firing or not firing, not on whether the same patterns of cause and effect were built on tiny trained squirrels running memos around your brain. You couldn't notice that part from inside. It would not affect your consciousness. That's why humans had to discover neurobiology with microscopes instead of introspection. Consciousness is in the class of things that can affect your behavior and can't depend on underlying physics, not in the class of direct properties of underlying physics that can't affect your behavior. A simulated rainstorm can't get anything wet. Running on electricity versus water can't change how you say "I think therefore I am." And that's it. QED.

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RomainB
RomainB@Rom1Bat·
few people do understand what an exponential is.
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RomainB
RomainB@Rom1Bat·
@noahlofq it makes so much sense: what is encoded in you DNA and allows you animals and humans to learn so fast isn't based on real data.
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Stefano Ermon
Stefano Ermon@StefanoErmon·
Mercury 2 is live 🚀🚀 The world’s first reasoning diffusion LLM, delivering 5x faster performance than leading speed-optimized LLMs. Watching the team turn years of research into a real product never gets old, and I’m incredibly proud of what we’ve built. We’re just getting started on what diffusion can do for language.
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Luiza Jarovsky, PhD
Luiza Jarovsky, PhD@LuizaJarovsky·
Why do so many in AI flirt with science-fiction-like AI governance approaches? No, an AI model does not have a soul No, an AI model does not have feelings No, an AI model is not alive These are nice topics for books, movies, and philosophy... NOT for serious policymaking.
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RomainB
RomainB@Rom1Bat·
@AJButton2 "Solid proof that AI does not retain memory and experience like a human brain does, only summoning and interacting with data when explicitly instructed to do so by a human" ahahahahaha what a strawman
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A.J. Button
A.J. Button@AJButton2·
The sheer ARROGANCE of these AI hypesters is unbelievable! In recent months we've seen: 🫢 MOUNTAINS of testimony from real world users confirming that they spend most of their work day fixing AI's errors. 😮 AI developers like Ujjwal Chadha confirming that AI does not "think" 😱 Solid proof that AI does not retain memory and experience like a human brain does, only summoning and interacting with data when explicitly instructed to do so by a human Yet still these religious fundamentalists maintain their superstition that AI is "sentient!"
HealthRanger@HealthRanger

AI denialists are sure sounding a lot like Flat Earthers right now. "AI isn't intelligent." "It's a prediction machine." Yet I can give an AI engine 100,000 lines of code and ask it to tell me what that code does. In plain English, it describes all the functionality of the code that it has NEVER seen before. That's not prediction. That's intelligence.

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NZ ☄️
NZ ☄️@CodeByNZ·
LLMs don’t think. They don’t reason the way humans do. They predict the next token based on probability distributions learned from massive datasets. What feels like reasoning is statistical pattern completion at scale. The magic isn’t intelligence, it’s compression. They’ve compressed patterns from millions of documents into weights. That’s powerful. But it’s not consciousness.
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RomainB
RomainB@Rom1Bat·
@cannibality are you certain you are much different from what you just described?
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emmy rākete 🇵🇸
emmy rākete 🇵🇸@cannibality·
LLMs are methodologically incapable of reasoning, that's like their defining characteristic! All they do is correlate statistically-probable strings of texts, they are categorically incapable of reasoning about information!
Cheng Lou@_chenglou

Stupidly late realization on why LLMs are so good at reasoning: human’s reasoning capability is bottlenecked by language! It’s not that languages are good at reasoning; reasoning ended up being defined by language first and foremost. The medium truly shapes the message

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RomainB
RomainB@Rom1Bat·
@TrueAIHound you are right, but it's not what Dario is saying here. He is talking about before training. ~Just random weights. when deployed those are indeed, not random weights
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AGIHound
AGIHound@TrueAIHound·
According to Amodei, LLM models start from scratch (blank slates) with random weights. Dude, please. 🙄 No they don't. LLMs start out preprogrammed with millions of tokens (compiled from texts created by humans) when released in the world. Humans are as blank slates as can be with enough genetic programming (such as breathing, crying, sucking and swallowing) to ensure survival. Evolution did not pretrain the human brain to learn how to read, ride a bicycle and program computers. We learn almost everything from scratch, including eye-tracking, reaching, grasping, walking, running, etc. Don't make excuses for your lame AI that massively cheats by using millions of human beings as text preprocessors and still have no understanding of what they're saying. Unless your AI can use its sensors and effectors to learn everything in the real world, it's not intelligent. It's just computer automation. 🤦‍♂️
vitrupo@vitrupo

Dario Amodei says pre-training sits somewhere between learning and evolution. Humans inherit priors shaped over millions of years. LLMs start as random weights and distill trillions of tokens into those priors. We describe them using human learning metaphors. But the analogy only goes so far.

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RomainB
RomainB@Rom1Bat·
@Dimillian slopen ai is paying a lot of people on that app
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Thomas Ricouard
Thomas Ricouard@Dimillian·
Codex 5.3 on the Pro plan just smoke whatever slopus 4.Idk is trying to be.
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RomainB
RomainB@Rom1Bat·
ok now we need Claude opus 5.
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Wiebe de Jager
Wiebe de Jager@wdejager·
@auterion Unless someone switches on the radio jamming equipment. How will the drones coordinate their actions then?
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Auterion
Auterion@auterion·
This is the end of the one-pilot, one-drone era. War fighters can now manage multiple vehicles and complex operations. Operators define the mission. Autonomous systems coordinate the execution in real time. Simpler, faster, scalable. #swarmsnotdrones
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RomainB
RomainB@Rom1Bat·
@simonw probably generated by gpt 5.2 Also yes, why do you only get 32k context on plus is really not cool..
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Simon Willison
Simon Willison@simonw·
Anyone else confused by the new ChatGPT plan comparison grid? Here's an annotated screenshot:
Simon Willison tweet media
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RomainB
RomainB@Rom1Bat·
@qtnx_ are you mainly using mistral models?
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Q@qtnx_·
deeply grateful for agentic harnesses; around june-july i started getting daily horrible wrist pains after a day of work now that i write 90% less since i can tell an ai exactly how to write something, the pain is gone
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RomainB
RomainB@Rom1Bat·
@cloneofsimo + sell the data to labs I want to do this can we team up?
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Simo Ryu
Simo Ryu@cloneofsimo·
Trazillion dollar idea. Make a game engine, a decent one, that supports basic stuff, but that could be heavily extended and modified. But make it unconventionally console / test driven, make it easily verifiable. Then, make a lot of toy game with it. Get lot of instructions, Train (fine-tune) an LLM on it. Sell the LLM & game engine as a paired product. Train on the user-generated games. SFT. RLVR. I would do this if I didnt have a job
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RomainB
RomainB@Rom1Bat·
hey @AnthropicAI, Claude Code is great, but why can't it output accents? like even when required to do it into and docx it just doesn't output the accent, and gets pretty r about it
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RomainB
RomainB@Rom1Bat·
even oai has to focus. why don't you focus?
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