AI in Business Across Industries
#AI #AIio #AIInnovation #ML #DataScience #Futureofwork @lexfridman @sama @kaifulee @ID_AA_Carmack @karpathy @2morrowknight @ylecun
MACHINE LEARNING
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AI in Business Across Industries
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Energy-Based Transformers: Scalable Learning and Reasoning Architecture
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Energy-Based Transformers are Scalable Learners and Thinkers Gladstone et al.: https://
arxiv.org/abs/2507.02092 #ArtificialIntelligence #DeepLearning #MachineLearning -
Goodside critiques a lucky guess about a famous illusion image
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I’d call that a lucky guess, given: – You told it it was a famous image
– It took 3 sequential (vs. independent) tries
– It’s not describing the illusion well at all
– It says the image includes her “upper body” which isn’t true -
Fractured Entangled Representation Hypothesis Challenges Deep Learning Optimism
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Questioning Representational Optimism in Deep Learning: The Fractured Entangled Representation Hypothesis Akarsh Kumar, Jeff Clune, Joel Lehman, Kenneth O. Stanley : https://
arxiv.org/abs/2505.11581 #ArtificialIntelligence #EvolutionaryComputing #NeuralComputing -
Fractured Entangled Representation Hypothesis Challenges Deep Learning Optimism
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Questioning Representational Optimism in Deep Learning: The Fractured Entangled Representation Hypothesis Akarsh Kumar, Jeff Clune, Joel Lehman, Kenneth O. Stanley : https://
arxiv.org/abs/2505.11581 #ArtificialIntelligence #EvolutionaryComputing #NeuralComputing -
AI For Manufacturers In 2024: Separating Hype From Reality
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AI For Manufacturers In 2024: Hype Vs. Reality
#AI #AIio #AIInnovation #ML #DataScience #Futureofwork @HaroldSinnott @fogoros @iainljbrown @NandoDF @katecrawford @drhassanrashidi @YuHelenYu http://
ow.ly/kNMa30sNAOm -
AI for Scientific Research: Comprehensive Survey Overview
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AI4Research: A Survey of Artificial Intelligence for Scientific Research Chen et al.: https://
arxiv.org/abs/2507.01903 #ArtificialIntelligence #DeepLearning #MachineLearning -
AI for Scientific Research: Comprehensive Survey Overview
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AI4Research: A Survey of Artificial Intelligence for Scientific Research Chen et al.: https://
arxiv.org/abs/2507.01903 #ArtificialIntelligence #DeepLearning #MachineLearning -
Free Deep Learning Book: Complete Guide from Math to LLMs
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A fantastic, visually stunning intro to deep learning. This free book covers: – Maths for ML
– Datasets & Losses
– Linear Models
– Fully Connected Models
– CNNs for Images & Beyond
– Transformers & LLMs
– Graph Models Highly recommended! -
Building on LLMs: RAG, Fine-tuning, Personalization Essentials
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How to Really Build on Top of LLMs (full training session) Personalization, databases, retrieval (RAG, CAG), frameworks, fine-tuning… We will discuss… Some theory for the essentials
LLM limitations
Context window
Knowledge issues
Embeddings + encoders
Long context
RAG
Data,