From the Leanpub Blog: Leanpub Course LAUNCH The Hundred-Page Language Models Course by Andriy Burkov

From the Leanpub Blog: Leanpub Course LAUNCH The Hundred-Page Language Models Course by Andriy Burkov
Leanpub Course LAUNCH The Hundred-Page Language Models Course: Hands-on with PyTorch by Andriy Burkov
Watch here: https://youtu.be/r2EEBL59tLI
Course Link: https://leanpub.com/c/theLMcourse
From the Leanpub Blog: The Leanpub Podcast Feat. Andriy Burkov, Author of The Hundred-Page Language Models Book and The Hundred-Page Language Models Course
Course Link: https://leanpub.com/c/theLMcourse
Book Link: https://leanpub.com/theLMbook
NEW! A Leanpub Podcast Interview Feat. Andriy Burkov, Author of The Hundred-Page Language Models Book and The Hundred-Page Language Models Course
Watch here: https://youtu.be/oeNHnO4E0RU
Mastering Modern Time Series Forecasting by Valery Manokhin is on sale on Leanpub! Its suggested price is $49.95; get it for $40.46 with this coupon: https://leanpub.com/sh/62tDVB9r #ComputerScience #MachineLearning #Mathematics #Python #DataScience #DeepLearning #Education
Large language models lack true reasoning capabilities, researchers argue: Large language models function through sophisticated retrieval rather than genuine reasoning, according to research published across multiple studies in 2025. https://ppc.land/large-language-models-lack-true-reasoning-capabilities-researchers-argue/ #AI #ArtificialIntelligence #MachineLearning #LanguageModels #DeepLearning
Large language models lack true reasoning capabilities, researchers argue https://ppc.land/large-language-models-lack-true-reasoning-capabilities-researchers-argue/ #AI #ArtificialIntelligence #MachineLearning #LanguageModels #DeepLearning
ARC-3, a sneak peek at the next-gen, interactive reasoning benchmark designed to illuminate the capability gap between today's AI and tomorrow's AGI.
Play First 3 Games
https://three.arcprize.org/
As with previous ARC tests, the actual games used for testing AI are kept secret. AI algorithms must learn the games on the spot.
There are no instructions. You must play the game to discover controls, rules, and goal.
Interactive Reasoning Benchmarks (IRBs) test for a broad scope of capabilities:
• Exploration
• Percept -> Plan → Action
• Memory
• Goal Acquisition
• Alignment
Game Design Constraints
• Easy for humans (can pick it up in <1 min of game play)
• Core Knowledge Priors (no language, trivia, cultural symbols)
• Should require no instructions to play
• Should be fun for humans and playable in 5-10 minutes
• Innovative and novel game mechanics encouraged (Hidden state, theory of mind, long term planning, navigating other agents, etc.)
Does AI Aid Rare Bone Fracture Detection in Children? https://www.byteseu.com/1205181/ #AI #ArtificialIntelligence #ArtificialNeuralNetworks #child #childhood #Children #DeepLearning #fractures #kids #MachineLearning #MLNaturalLanguageProcessing #NPL #OsteogenesisImperfecta;OsteogenesisImperfecta(OI) #Pediatrics #UK #UKSiteContent;UnitedKingdomSiteContent #UnitedKingdom
Recent @DSLC club meetings:
An Introduction to Statistical Learning with Applications in Python: Deep Learning https://youtu.be/ZA99FHf08DQ #PyData #DeepLearning #AI
Analyzing Baseball Data with R (3e): Making a Scientific Presentation using Quarto https://youtu.be/UNR0E5K5IhA #RStats #SportsAnalytics
Visit https://dslc.video for hours of new #DataScience videos every week!
Finished reading the early-access version of Deep Learning with Python (3rd edition), by @fchollet and Matthew Watson. It's very good! Emphasis on concepts and Keras implementation rather than math.
Pre #2020: #Factorizing Tools
These #AI wre #DeepLearning breakthroughs. #Word2Vec, #DeepDream and #AlphaGo solved novel, previously unsolvable, problems.
If you weren't in the field, you might not think these were AI, and #GPT 2 might have surprised you.
I'm spending some time with the history of #deeplearning and pretrained networks. It seems the Restricted Boltzmann Machines (RBMs) played a key role nearly 2 decades ago. Guess what, RBMs are the binary analog of factor analysis that was invented by Spearman in *1904*.
#AI
https://www.europesays.com/uk/263330/ Top AI medical scientists Roland Eils and Irina Lehmann leave Germany for China #AI #AIInMedicine #ArtificialIntelligence #Berlin #BIH #CharitéUniversityOfMedicine #China #Chinese #ComputationalBiologist #Covid19Pandemic #DeepLearning #Eils #Epigenetics #EU #Europe #FudanUniversity #german #Germany #IntelligentMedicine #IrinaLehmann #LargeLanguageModel #LLM #MedicalAI #MolecularEpidemiology #Research #Science #Shanghai #SmartMedicine #UniversityOfHeidelberg
Gary Marcus is onto something in here. Maybe true AGI is not so impossible to reach after all. Just probably not in the near future but likely within 20 years.
"For all the efforts that OpenAI and other leaders of deep learning, such as Geoffrey Hinton and Yann LeCun, have put into running neurosymbolic AI, and me personally, down over the last decade, the cutting edge is finally, if quietly and without public acknowledgement, tilting towards neurosymbolic AI.
This essay explains what neurosymbolic AI is, why you should believe it, how deep learning advocates long fought against it, and how in 2025, OpenAI and xAI have accidentally vindicated it.
And it is about why, in 2025, neurosymbolic AI has emerged as the team to beat.
It is also an essay about sociology.
The essential premise of neurosymbolic AI is this: the two most common approaches to AI, neural networks and classical symbolic AI, have complementary strengths and weaknesses. Neural networks are good at learning but weak at generalization; symbolic systems are good at generalization, but not at learning."
https://garymarcus.substack.com/p/how-o3-and-grok-4-accidentally-vindicated
New in #eLife: #CellSeg3D introduces #WNet3D, a self-supervised 3D #segmentation method for #microscopy data — no labels needed. Claims to outperform #Cellpose/#StarDist on 4 datasets. Includes #opensource plugin (#Napari) + full 3D annotated #cortex dataset. Will test it later.
Forschung trifft Zollstock: Ein Team der Universität Basel zeigt mit einem mechanischen Modell, wie sich Datenseparation in tiefen neuronalen Netzwerken optimieren lässt – und das mit erstaunlicher Präzision. #KI #DeepLearning
https://nachrichten.idw-online.de/2025/07/11/was-ein-zollstock-ueber-neuronale-netzwerke-verraet
Recent @DSLC club meetings:
An Introduction to Statistical Learning with Applications in Python: Support Vector Machines https://youtu.be/oGLllT7LpRk #PyData #DeepLearning #AI
Analyzing Baseball Data with R (3e): Working with Large Data https://youtu.be/FqPuS102EDQ #RStats #SportsAnalytics
Analyzing Baseball Data with R (3e): Home Run Hitting https://youtu.be/7d2MZp-gEt4 #RStats #SportsAnalytics
Visit https://dslc.video for hours of new #DataScience videos every week!
Recent @DSLC club meetings:
Outstanding Shiny UI: Adding more interactivity https://youtu.be/62RpcLDFU1M #RStats #RShiny
pharmaverse Examples: BDS ppt + start of the example https://youtu.be/WT90o2FjHgo #RStats #pharma #pharmaverse
An Introduction to Statistical Learning with Applications in Python: Support Vector Machines https://youtu.be/Ikn4q7di0LU #PyData #DeepLearning #AI
Visit https://dslc.video for hours of new #DataScience videos every week!
CT-Aufnahmen des Thorax sind essenziell für die frühe #Diagnostik und Kontrolle von Lungenerkrankungen wie Bronchialkarzinomen. Doch der Vergleich mit Voraufnahmen ist zeitaufwendig und fehleranfällig.
Die #DeepLearning-Software aus dem Projekt SPIRABENE des Fraunhofer MEVIS erkennt Veränderungen von Lungentumoren deutlich schneller und präziser. Dank der Software findet das Fachpersonal 11% mehr Tumore in einem Zehntel der Zeit!
Lies mehr: https://s.fhg.de/WfUn