autonomoussystem.ai

#Autonomous System AI Meta

#AI in the warehouse

#Mobile robots

#Humanoid robots

#Precision motion control system

#Antagonistic AI system | Behaving in disagreeable, confrontational or challenging ways | Forcing to confront assumptions | Building resilience | Developing healthier boundaries

#Throughput: Tokens per second

#Inference Speed Performance

#Autonomous Industry

#Generative AI Stack

#Generative AI Ecosystem

#Perceptual AI-based systems

#Edge AI-based systems

#AI hardware accelerator

#Latency: Time to first tokens chunk received

#Automated Guided Vehicle (AGV)

#Positioning accuracy

#Roboticist

#Mechatronics

#Natural feature navigation

#Simultaneous Localization and Mapping (SLAM)

#Safety scanner

#Odometry

#Fleet management

#Autonomous Navigation Technology (ANT)

#Vehicle Control

#Kinematic

#Optimized Path

#Obstacle Avoidance

#Mission Control

#GNSS

#Vehicle automation

#Autonomous Mobile Robot (AMR)

#Robotics engineering

#System design

#AMR platform

#Mobile robot

#Precision agriculture

#Environmental sustainability

#Artificial Intelligence for Aviation business

#AI factory

#Dynamic sensing

#Dispatching agile mobile robots equipped with sensors to collect data on site

#Industrial inspection robot

#Measurement sensor

#Navigating facilities built for humans

#Autonomous mobile inspection robot

#Asset-intensive industry

#Determining Jobs to be Done

#Detecting equipment failures

#Visual optical zoom camera

#Directional ultrasonic microphone

#High quality thermal camera

#Gas sensor

#360° Lidar scanner

#Updating 3D models on-demand

#Data contextualization

#AI-based inspection algorithm

#Object recognition

#Depth camera

#Lidar

#Robot control

#Universal Scene Description (OpenUSD)

#Synthetic Data Generation

#Robotics simulation

#Regression Testing

#Changes to prompt

#Retrieval strategy

#Model choice

#Granularity of information

#Annotation Queue

#Template language

#Making informed tradeoffs amongst latency, cost, and quality

#Evaluating response quality

#Multi-actor applications

#In-context (few-shot) learning

#Flow Engineering

#Iterative process

#Vector Retrieval

#Graph-based Metadata Technique

#Vector similarity search

#Robot set-up

#Initial training of robot

#Refresher training of robot

#Field certified robot

#Importing CAD models to perform realistic simulations

#Guiding robot through facilities

#Planning robot mission on-site

#Neural network

#Autonomous robots

#Automatic emergency braking (AEB)

#Warehouse automation

#Internet of Things (IoT)

#Autonomous mobile robots (AMRs)

#Autonomous forklifts

#Additive manufacturing

#Cold spray

#White Hydrogen

#Integrating LTE-M cellular connectivity into EV chargers to enable them to connect to Cloud to respond to dynamic electricity price changes

#Extracting interpretable features from LLMs

#Sparse autoencoder

#Controlling the sparsity level

#Activation shrinkage

#Dead latent

#Scaling laws

#Evaluation metrics

#Mitigating biases in AI systems

#Scaling monosemanticity

#Mixture of Experts (MoE) models in LLMs

#Expert Slimming

#Expert Trimming

#Structured State Space Duality (SSD)

#State Space Model (SSM)

#Transformer Architectur

#Retrieval-Augmented Generation (RAG) | Vector search

#Semantic ranker for search

#Hybrid search with re-ranking | Uutperforming vector search alone, which may struggle to find exact matches for proper names, IDs and numbers | Improving the relevance and accuracy of the AI generated responses

#MLOps platform

#Industrial digitalization

#Autonomous facility

#Reference workflow

#Physically based rendering

#AI robot development

#AI robot deployment

#Digital twin

#Modifying digital design in sensor feedback loop

#Robotics platform

#AI processor

#Building digital twins for real-time simulation of different factory layouts

#AI for manufacturing

#Transformational impact of generative AI and digital twin technologies

#Autonomous technology

#Digital twin of factory

#Virtual plant

#Training robots in virtual environment

#Situating sensors and networked video cameras in matrix to show plant operators right details

#Robot work cell design

#Robotics simulation platform

#Generating physically accurate, photorealistic synthetic data for training computer vision models

#Automatic Optical Inspection

#Autonomy algorithm

#Infrared sensor

#Integrated motion capture system

#Reflective tag

#System generating GPS signals

#Marine Autonomous System (MAS)

#Ocean observation

#Explainable AI (XAI): methods allowing humans to comprehend and trust the results of machine learning algorithms

#AI patents: digital product manufacturing sector accounting for 61.8 percent in China

#Cognitive robotics

#Humans in the loop

#Vision Language Model (VLM)

#Robot workcell

#Industrial robot programming

#Autonomous homing of robots

#Linear actuator | Device converting rotational motion into linear motion

#Disaggregation | Hardware and software components are separated to enhance flexibility and efficiency in network management

#Coherent optical transceiver | Utilizing advanced modulation techniques, including amplitude and phase modulation | Enhancing data transmission over fiber optics | Enabling higher bandwidth and longer reach by employing digital signal processors to manage dispersion and optimize spectral efficiency | Supporing various applications, including Dense Wavelength Division Multiplexing (DWDM), allowing multiple data streams on a single fiber | Essential for modern high-speed networks, facilitating capacities of 100G to 400G and beyond, crucial for data-intensive applications like cloud computing and 5G networks

#YANG (Yet Another Next Generation) data modeling language | Designed for network management | Enables the definition of configuration and state data for network devices | Facilitates automation through protocols like NETCONF, RESTCONF, and gNMI | Human-readable and machine-processable | Simplifies network configuration and management across different vendors | Standardized by IETF | Supports various built-in data types | Allowing for extensibility and compatibility with existing management protocols like SNMP

#3D depth sensing

#Time Of Flght (TOF)

#Active stereo vision

#Reality capture workflows

#Dual polarization

#Prompt adherence

#Vector database

#Learning Management System (LMS)

#Prompt caching | AI reusing of large text across multiple API calls without reprocessing it each time | AI allowing to ask various questions about book while utilizing cached content | AI prompts with many examples | AI repetitive tasks with consistent instructions | AI cache elements: Tools, System messages, Messages, Images | AI conversational agents | AI coding assistants | AI large document processing | AI detailed instruction sets | AI agentic tool use | AI talking to books | AI talking to papers | AI talking to documentation | AI talking to podcast transcript | Python | Curl

#Integrating AI model with organization knowledge

#Scaling expertise across projects

#Scaling expertise across decisions

#Scaling expertise across teams

#AI powered software engineering

#AI powered computer use

#Syncing GitHub repositories with AI model

#Building Information Modeling (BIM) | Creating and managing 3D representations of physical and functional characteristics of buildings and infrastructure projects

#Edge AI

#Large Language Model (LLM)

#Retrieval-Augmented Generation (RAG)

#Conversational AI

#Custom machine learning model

#25 million tokens per second mark

#1 billion tokens per second

#Llama model

#CUDA

#Inference

#API Latency | Time to first token)

#API output speed (output tokens per second)

#Climate reporting requirements | Scope 3 emissions (generated from company supply chain) | Climate statement | Financial opportunities tied to climate change | Financial risks tied to climate change | Climate metrics & targets: emissions from Scope 1 (direct emissions), Scope 2 (indirect emissions from power use), and Scope 3 (everything else, like supply chain emissions) | Governance & risk management: how company is managing climate risks and opportunities) | 2°C scenario | 1.5°C scenario | Risks companies are exposed | Strategy for achieving net-zero emissions | Leadership engagement with climate change issues

#Environmental, Social, and Governance (ESG)

#Agentic AI | Adapting dynamically to its environment | Learning from interactions | Integrating machine learning, reasoning, and workflow optimization | Managing multi-agent orchestration for seamless collaboration

#California wildfire | Challenges | Access roads too steep for fire department equipment | Brush fires | Dangerously strong winds for fire fighting planes | Drone interfering with wildfire response hit plane | Dry conditions fueled fires | Dry vegetation primed to burn | Faults on the power grid | Fires fueled by hurricane-force winds | Fire hydrants gone dry | Fast moving flames | Hilly areas | Increasing fire size, frequency, and susceptibility to beetle outbreaks and drought driven mortality | Keeping native biodiversity | Looting | Low water pressure | Managing forests, woodlands, shrublands, and grasslands for broad ecological and societal benefits | Power shutoffs | Ramping up security in areas that have been evacuated | Recoving the remains of people killed | Retardant drop pointless due to heavy winds | Smoke filled canyons | Santa Ana winds | Time it takes for water-dropping helicopter to arrive | Tree limbs hitting electrical wires | Use of air tankers is costly and increasingly ineffective | Utilities sensor network outdated | Water supply systems not built for wildfires on large scale | Wire fault causes a spark | Wires hitting one another | Assets | California National Guard | Curfews | Evacuation bags | Firefighters | Firefighting helicopter | Fire maps | Evacuation zones | Feeding centers | Heavy-lift helicopter | LiDAR technology to create detailed 3D maps of high-risk areas | LAFD (Los Angeles Fire Department) | Los Angeles County Sheriff Department | Los Angeles County Medical Examiner | National Oceanic and Atmospheric Administration | Recycled water irrigation reservoirs | Satellites for wildfire detection | Sensor network of LAFD | Smoke forecast | Statistics | Beachfront properties destroyed | Death tol | Damage | Economic losses | Expansion of non-native, invasive species | Loss of native vegetation | Structures (home, multifamily residence, outbuilding, vehicle) damaged | California wildfire actions | Animals relocated | Financial recovery programs | Efforts toward wildfire resilience | Evacuation orders | Evacuation warnings | Helicopters dropped water on evacuation routes to help residents escape | Reevaluating wildfire risk management | Schools closed | Schools to be inspected and cleaned outside and in, and their filters must be changed

#Context window | Amount of information LLM can handle in one input/output exchange, with words and concepts represented as numerical tokens, LLM own internal mathematical abstraction of data it was trained on