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@Metacone_agi

EVERYTHING IS REPETITION OF ITs SMALLEST PART https://t.co/1y2mWFVZCF Artificial Intelligence #MTCN #AGI #Game #Token #Nft #Solana #Web3 Discord: https://t.co/S6dUUIqbth

İstanbul Katılım Eylül 2022
120 Takip Edilen146 Takipçiler
Metacone
Metacone@Metacone_agi·
Hello @OpenAI team, We noticed the similarity between our video (youtube.com/watch?v=bK1rwV…) and your video (youtube.com/watch?v=G8sm27…), and we find it quite delightful. It looks like we are both trying to reach a similar point, albeit from different paths( your advanced LLM vs.⚔️ our innovative Metacone). Day by day, you are getting closer to us! 🤓🚀 Thank you for giving us this pleasant coincidence, and we are happy to compete in AGI endeavors. We look forward to seeing more similarities like this! #AI, #AGI, #OpenAI, #chatgpto, #metacone
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Metacone
Metacone@Metacone_agi·
@OpenAI x.com/Metacone_agi/s…
Metacone@Metacone_agi

Hello @OpenAI team, We noticed the similarity between our video (youtube.com/watch?v=bK1rwV…) and your video (youtube.com/watch?v=dVwjog…), and we find it quite delightful. It looks like we are both trying to reach a similar point, albeit from different paths( your advanced LLM vs.⚔️ our innovative Metacone). Day by day, you are getting closer to us! 🤓🚀 Thank you for giving us this pleasant coincidence, and we are happy to compete in AGI endeavors. We look forward to seeing more similarities like this! #AI, #AGI, #OpenAI, #chatgpto, #metacone

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OpenAI
OpenAI@OpenAI·
Fast counting with GPT-4o
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OpenAI
OpenAI@OpenAI·
Say hello to GPT-4o, our new flagship model which can reason across audio, vision, and text in real time: openai.com/index/hello-gp… Text and image input rolling out today in API and ChatGPT with voice and video in the coming weeks.
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Yann LeCun
Yann LeCun@ylecun·
I've made that point before: - LLM: 1E13 tokens x 0.75 word/token x 2 bytes/token = 1E13 bytes. - 4 year old child: 16k wake hours x 3600 s/hour x 1E6 optical nerve fibers x 2 eyes x 10 bytes/s = 1E15 bytes. In 4 years, a child has seen 50 times more data than the biggest LLMs. 1E13 tokens is pretty much all the quality text publicly available on the Internet. It would take 170k years for a human to read (8 h/day, 250 word/minute). Text is simply too low bandwidth and too scarce a modality to learn how the world works. Video is more redundant, but redundancy is precisely what you need for Self-Supervised Learning to work well. Incidentally, 16k hours of video is about 30 minutes of YouTube uploads.
Tom Osman 🐦‍⬛@tomosman

"A 4-year-old child has seen 50x more information than the biggest LLMs that we have." - @ylecun 20mb per second through the optical nerve for 16k wake hours 🤯 LLMs may have consumed all available text, but when it comes to other sensory inputs...they haven't even started.

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Metacone
Metacone@Metacone_agi·
💯 We totally agree and leave our signature. ✍️ Future AI systems need to move beyond the current energy-intensive structures. There's a need for new architectures and objectives for them to be smarter yet controllable. We've developed 'Metacone' to set sail for these new architectures. #Metacone #AGI
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Yann LeCun
Yann LeCun@ylecun·
One thing we know is that if future AI systems are built on the same blueprint as current Auto-Regressive LLMs, they may become highly knowledgeable but they will still be dumb. They will still hallucinate, they will still be difficult to control, and they will still merely regurgitate stuff they've been trained on. MORE IMPORTANTLY, they will still be unable to reason, unable to invent new things, or to plan actions to fulfill objectives. And unless they can be trained from video, they still won't understand the physical world. Future systems will *have* to use a different architecture capable of understanding the world, capable of reasoning, and capable of planning so as to satisfy a set of objectives and guardrails. These objective-driven architectures will be safe and will remain under our control because *we* set their objectives and guardrails and they can't deviate from them. They won't want to dominate us because they won't have any objective that drives them to dominate (unlike many living species, particularly social species like humans). In fact, guardrail objectives will prevent that. They will be smarter than us but will remain under our control. They will make *us* smarter. The idea that smart AI systems will necessarily dominate humans is just wrong. Instead of scaling current systems 100x, which will go nowhere, we need to make these Objective-Driven AI architectures work.
Geoffrey Hinton@geoffreyhinton

New paper: managing-ai-risks.com Companies are planning to train models with 100x more computation than today’s state of the art, within 18 months. No one knows how powerful they will be. And there’s essentially no regulation on what they’ll be able to do with these models.

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Metacone
Metacone@Metacone_agi·
🚀 Our closed beta is live! We're field-testing the Metacone AI algorithm. A unique AI we developed from scratch, ready to learn without prior training – just like a real baby. Our baby is taking its first steps! 🤖💡 #Metacone #ArtificialIntelligence #Innovation #NFT #AGI
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Metacone
Metacone@Metacone_agi·
@Metacone_agi is pushing the boundaries of AI technology! 🔍 Introducing a digital twin that learns and interacts with you personally. With the addition of Metacone Baby NFT and $MTCN token to our ecosystem, we're harnessing the power of NFT technology. Dive into our teach-to-earn model and explore the true potential of AI. 🌐🤖 #AI #Metacone #DigitalFuture
Superteam Turkey@SuperteamTR

Superteam Turkey continues sharing projects, and we have something fantastic to share. 🎉 @SuperteamDAO @Solana Introducing Metacone, the next generation of AI friends! Imagine having a digital twin who is constantly learning from you. Unlike conventional AI, Metacone’s cutting-edge AI algorithm ensures instant, tailored interactions that are aware of your particular needs. 💡 But there is more! The Metacone Baby NFT and $MTCN token have been added to the ecosystem, taking it a step further by integrating NFT technology. Get ready for a teach-to-earn model that rewards you for your participation and an experience like no other. 💪 Follow them as they explore the development of tailored assistance and the potential of AI companions. @Metacone_agi

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Superteam Germany
Superteam Germany@SuperteamDE·
Art 🤝 @solana We've teamed up with @exchgART to showcase an unreal lineup of 32 artists, from local to international talent for the upcoming Berlin @hackerhouses Each day, 8 different artists will have their on work display. Here is a sneak peek of the exhibition👇
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Donny Solana
Donny Solana@DonnySolana·
Unleash the Future: Accelerator Demo Day Brace yourselves for an electrifying lineup of game-changing apps – from the icons you already love to the mind-blowing newcomers you never saw coming. Get ready to be blown away! Aug 25th, 4pm UTC Event Link: lu.ma/7ll1u5j3
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Anatolian Blockchain
Anatolian Blockchain@anatolianchain·
🚀 Get Ready! Time to Meet the Leaders of Blockchain and Crypto World! 🤝 With Anatolian Blockchain Crypto Connect event, the top projects and visionaries from the blockchain and crypto industry are coming together. 🔗🤩 For Detailed Information: anatolianblockchain.com
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Metacone
Metacone@Metacone_agi·
🚀 Yejin Choi'nun konuşmasındaki bulgular gerçekten şaşırtıcı! GPT4 bile 3 basamaklı sayı çarpma konusunda sadece %59 doğrulukla başarılı olabiliyor. Algoritmik zorluklar, Transformer'ların zorlandığı bir alan. Metacone olarak bu konuda fark yaratmak için az veriyle anlama kabiliyeti geliştiren bir algoritmamız geliyor. Geçen seneki videomuzdan örnek,Takipte kalın! 👀 #AGI #Metacone vimeo.com/688768067
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Metacone
Metacone@Metacone_agi·
🚀 Did you hear about Yejin Choi's striking findings? Even GPT4 could only achieve 59% accuracy on 3-digit number multiplication. Algorithmic challenges seem to be a hard area for Transformers. At Metacone, we're about to make a difference with an algorithm that improves understanding with less data. Stay tuned! 👀 #NLP #MetaconeAlgorithms vimeo.com/688768067
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Alex Dimakis
Alex Dimakis@AlexGDimakis·
I was surprised by a talk Yejin Choi (an NLP expert) gave yesterday in Berkeley, on some surprising weaknesses of GPT4: As many humans know, 237*757=179,409 but GPT4 said 179,289. For the easy problem of multiplying two 3 digit numbers, they measured GPT4 accuracy being only 59% accuracy on 3 digit number multiplication. Only 4% on 4 digit number multiplication and zero on 5x5. Adding scratchpad helped GPT4 but only to 92% accuracy on multiplying two 3 digit numbers. Even more surprisingly, finetuning GPT3 on 1.8m examples of 3 digit multiplication still only gives 55 percent test accuracy (in distribution). ¯\_(⊙︿⊙)_/¯ So whats going on? Multiplication is algorithmically very challenging (as are less known algorithmic problems). The authors hypothesize that Transformers have a hard time because they learn linear patterns that they can memorize, maybe compose, but not generally reason with. The paper raises interesting theoretical and practical questions on understanding what Transformers can learn. The paper "Faith and Fate: Limits of Transformers on Compositionality" says: "Our empirical findings suggest that Transformers solve compositional tasks by reducing multi-step compositional reasoning into linearized subgraph matching, without necessarily developing systematic problem solving skills"
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Superteam Turkey
Superteam Turkey@SuperteamTR·
AI ya da Veri Bilimine merakın varsa bu etkinlik senin için! 🤖 #dmgmeets Sen de aynı ilgiyi paylaşanlarla bağlantı kurmak, deneyimlerini paylaşmak ve en son trendlerden haberdar olmak istiyorsan hemen katıl! 👇 🔗kommunity.com/devmultigroup/…
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Metacone
Metacone@Metacone_agi·
"🚀 Falcon is a colossal LLM with 40 billion parameters. It was trained on 1 trillion tokens over two months using 384 GPUs. Never underestimate how much time and resources large LLMs demand! We continue to push the boundaries of technology. #DeepLearning #Metacone #Agi
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Keşfet

@OpenAI @ionet_official @SuperteamTR @ylecun @DonnySolana @HACKERHOUSES @solana @exchgART