you need both for optimal function; that’s the claim i have been making for 30 years. neuro+symbolic. as a point of fact though, most of waymo’s LLM stuff at least as of last summer was still experimental. i am not actually sure how much lift they are getting from LLMs in
MACHINE LEARNING
-
Nous Research Introduces Token Superposition Training for Faster LLM Training
By
–
What if you could train LLMs 2-3x faster without changing the final model at all? Most of that money goes into processing one token at a time, billions of times over. Nous Research published a paper introducing Token Superposition Training. It's a drop-in method that cuts
-
AI’s Third Superpower: From Answers to Actions to Advocacy
By
–
The Third Superpower Of #AI: From Answers To Actions To Advocacy
by Doug Marinaro @Forbes Learn more: https://
bit.ly/3PJtV2i #ArtificialIntelligence #MachineLearning #ML #DL -
The shift from pure LLMs to neurosymbolic AI architectures
By
–
The pure LLM debate – which I had for many years, here and elsewhere – is indeed no longer relevant. Why? Because I won; nobody uses pure LLMs anymore. Nowadays all deployed objects are neurosymbolic, which was exactly the point of my infamous 2022 paper, Deep Learning is
-
NVIDIA-backed sparsity optimization for faster LLM training and inference
By
–
/2 NVIDIA-backed sparsity trick makes LLM training and inference 20% faster on H100s. AI models already do less math than you'd think. Over 95% of neurons stay silent for any given word processed. That's free efficiency, right? Not quite. The problem: GPUs hate irregular work.
-
Top AI Repositories and Tools of the Week
By
–
Top Repo of the Week (May 11 – 17) 1. DeepSeek 4 Flash local inference engine for Metal and CUDA
2. Sparser, Faster, Lighter Transformer Language Models
3. RuView: Turn commodity WiFi signals into real-time spatial intelligence
4. Claude for Legal: A suite of plugins for legal -
AI races: top contenders in models, data centers, chips
By
–
The three AI races and their top contenders:
Models: OpenAI, Anthropic, Google
Data centers: Amazon, Microsoft, Google
Chips: Nvidia, AMD, Google -
Breakthrough in video generation: a new interface to reality
By
–
The breakthrough is not just better video generation. It is a new interface to reality. Instead of being locked into one camera angle, you can: → move across viewpoints
→ inspect scenes from new perspectives
→ revisit the same moment from a different position That means -
RAG with LLM: Creating an AI-Powered File Reader
By
–
RAG with LLM: Creating an AI-Powered File Reader! #BigData #Analytics #DataScience #AI #MachineLearning #NLProc #IoT #IIoT #PyTorch #Python #RStats #TensorFlow #Java #JavaScript #ReactJS #GoLang #CloudComputing #Serverless #DataScientist #Linux #Programming #Coding
-
Training AI on Amazon Reviews with Python for Natural Language Processing
By
–
Training AI on Amazon Electronic Reviews Using #Python for Natural Language! – by – @gp_pulipaka
! JupyterLab/Jupyter Notebook WordNet, Lexical Semantic Relation Analyzer
Thesaurus, 155,000 Words
Synset 115,000, 205,000 word-Sense Pair. NLTK Library, spaCy, TextBlob