[ AGI Trading Agents ] Trading.AGI.Eth : The frontier of financial innovation, where cutting-edge reinforcement learning empowers real-time trading. The stakes have never been higher! Asset : https://
opensea.io/assets/ethereu
m/0xD4416b13d2b3a9aBae7AcD5D6C2BbDBE25686401/33394580571945435435819947337190002178497464131064320214903021280923183244962
… #AGIFirst #AGITrading #SovereignTuringTest
MACHINE LEARNING
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AGI Trading Agents: Reinforcement Learning Meets DeFi
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Comprehensive Data Cleaning for AI and Machine Learning
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Comprehensive #DataCleaning for #AI and #MachineLearning: https://
gretel.ai/blog/comprehen
sive-data-cleaning-for-ai-and-ml
… by @gretel_ai #DataScience #Analytics #DataLiteracy #DataStrategy #CDO #DataScientists +See:
1 http://
amzn.to/3SYyj9Z
2 http://
amzn.to/2VeeUE2
3 http://
amzn.to/418vZm0
4 http://
amzn.to/3kVynHp -
Create and Deploy AI Agents with Abacus AI Platform
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Create & deploy #AI agents with @AbacusAI — https://
abacus.ai/ai_agents — #GenAI agents chain user code, data transformations, models, & prompts. YES! Learn how in this tutorial: https://
blog.abacus.ai/blog/2023/08/3
1/supercharge-productivity-accomplish-10x-more-with-ai-agents/
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#DeepLearning #DataScience #MachineLearning #GenerativeAI #DataScientists #LLMs -
A Comprehensive Survey of Datasets for Large Language Models
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[DOWNLOAD 181-page PDF] A Comprehensive Survey of Datasets for Large Language Models: https://arxiv.org/abs/2402.18041
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#LLMs #NLProc #DeepLearning #MachineLearning #DataScience #BigData #GenAI #GenerativeAI #AI #DataScientists -
Foundation Models for Natural Language Processing Book Now Available
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Foundation Models for Natural Language Processing (OPEN ACCESS PDF or purchase the book): https://
link.springer.com/book/10.1007/9
78-3-031-23190-2
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#LLMs #NLProc #AI #MachineLearning #DeepLearning #DataScience #Algorithms #NeuralNetworks -
MLX Assistant Open-Source Repository on GitHub
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Repo here: https://
github.com/Doriandarko/ml
x-assistant
… @awnihannun -
RAG Benchmarking Challenges and LLM Context Understanding Issues
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Here is a great diagram that showcases the challenges with RAG benchmarking and LLM context understanding. RAG systems are complex because of these following 4 issues. Even stuffing the context of LLM does not really alleviate the issue and usually confuses the LLM. The
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17 Video Lectures on Deep Generative Models from Cornell Tech
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17 video lectures from the course Deep Generative Models (Cornell Tech, CS 6785, by @volokuleshov
): https://
youtube.com/playlist?list=
PL2UML_KCiC0UPzjW9BjO-IW6dqliu9O4B
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#AI #MachineLearning #DeepLearning #GenAI #GenerativeAI #LLMs #DataScience #DataScientists -
Open-Source AI Matches Gemini Video Capabilities with Novel Training
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Move over Gemini, open-source AI has video tricks of its own A team of researchers used a novel approach to training AI models and extended Meta's Llama 2 to achieve similar feats to Google's Gemini. https://
zdnet.com/article/move-o
ver-gemini-open-source-ai-has-video-tricks-of-its-own/
… @GoogleAI @Meta -
Gemini Outperforms GPT-4 in Deep Learning Explanations
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I asked Gemini and GPT-4 to explain deep learning AI, and Gemini won hands down Google's Gemini does a better job of refining an output when confronted with the question 'why?', while OpenAI's ChatGPT-4 gets stuck. https://
zdnet.com/article/i-aske
d-gemini-and-gpt-4-to-explain-deep-learning-ai-and-gemini-won-hands-down/
… @GoogleAI @OpenAI