#Deep LearnIng Inference Application Meta
#Convolutional Neural Network
#Artificial Intelligence
#Machine Learning
#Artificial Neural Network
#Image Analysis
#Shift Invariant Neural Network
#Shared Weight Architecture
#Convolutional Kernel
#Filters
#Feature Map
#Image Recognition
#Video Recognition
#Remommender System
#Image Classification
#Image Segmentation
#Media Image Analysis
#Natural Language Processing
#Brain Computer Interface
#Financial Time Series
#Multilayer Perceptron
#Fully Connected Networks
#One Neuron Connected To All Layers In The Next Layer
#Over Fitting Data
#Penalizing Parameters
#Weight Decay
#Skipped Connections
#Hierarchical Pattern Of Data
#Biological Process
#Animal Visual Cortex
#Cortical Neuron
#Receptive Field
#Perceptual AI
#Edge AI
#Token
#Fine-tuning
#AI model
#Tokenization
#Speech to text
#Text classification
#Sentiment
#Semantic similarity
#Semantic search
#Part of Speech tagging
#Named Entity Recognition
#Intent classification | Intent detection | Intent recognition
#Summarization
#Code Generation
#Training Convolutional Neural Networks (CNN)
#Error surface learning
#Gradient-based learning
#Hyperparameters
#Loss Functions
#Text-to-image diffusion model
#Idiosyncratic prompt
#Prompt alignment
#Direct reward fine-tuning (DRaFT)
#Differentiable reward function
#Complex prompt
#DRaFT method
#DRaFT+ algorithm
#Custom generative AI
#Training
#Layer and tensor fusion
#Retrieval-augmented generation
#Guardrailing
#Data curation
#Pretrained model
#Reinforcement learning from human feedback (RLHF)
#Large language model (LLM)
#Generative text-to-image
#Reinforcement learning (RL)
#Prompt domain
#Backpropagating differentiable reward through diffusion process
#Over-optimization
#Mode collapse
#Script
#Deep learning algorithm
#Model alignment
#Workflows for GenAI models
#Deep generative learning
#Weakly supervised learning
#Neural network
#Prompt engineering
#Quantization
#Vision-Language Model (VLM)
#Deep neural network
#Vectorized neural network
#Deep-learning framework
#Pre-training method
#Fine-tuning method
#Fine-tuning 2D model on 3D scans
#SLice Integration by Vision Transformer (SLIViT)
#Downstream learning
#4D deep learning model
#A-list celebrity home protector | Burglaries targeting high-end items | Burglary report on Lime Orchard Road | Burglar had smashed glass door of residence | Ransacked home and fled | Couple were not home at the time | Unknown whether any items were taken | Lime Orchard Road is within Hidden Valley gated community of Los Angeles in Beverly Hills | Penelope Cruz, Cameron Diaz, Jennifer Lawrence, Adele and Katy Perry have purchased homes there, in addition to Kidman and Urban | Kidman and Urban bought their home for $4.7 million in 2008 | 4,100-square-foot, five-bedroom home built in 1965 and sits on 1ΒΌ-acre lot | Property large windows have views of the canyons | Theirs is one of several celebrity properties burglarized in Los Angeles and across country recently | Connected to South American organized-theft rings
#Professional athlete home protector | South American crime rings | Targeting wealthy Southern California neighborhoods for sophisticated home burglaries | Behind burglaries at homes of professional athletes and celebrities | Theft groups conduct extensive research before plotting burglaries | Monitoring target whereabouts and weekly routines via social media | Tracking travel and schedules | Conducting physical surveillance at homes | Attacks staged while targets and their families are away | Robbers aware of where valuables are stored in homes prior to staging break-ins | Burglaries conducted in short amount of time | Bypass alarm systems | Use Wi-Fi jammers to block Wi-Fi connections | Disable devices | Cover security cameras | Obfuscate identities
#27B parameter model | Google Gemma 2 | High-performing lightweight language model | Designed for efficiency and versatility | Part of Gemma family | Available in three sizes: 2B, 9B, and 27B parameters | 27B variant trained on 13 trillion tokens (web documents, code, and mathematics | Excels in text generation, summarization, reasoning