autonomoussystem.ai

#Autonomous System AI Meta

#Agentic AI | Artificial intelligence systems with a degree of autonomy, enabling them to make decisions, take actions, and learn from experiences to achieve specific goals, often with minimal human intervention | Agentic AI systems are designed to operate independently, unlike traditional AI models that rely on predefined instructions or prompts | Reinforcement learning (RL) | Deep neural network (DNN) | Multi-agent system (MAS) | Goal-setting algorithm | Adaptive learning algorithm | Agentic agents focus on autonomy and real-time decision-making in complex scenarios | Ability to determine intent and outcome of processes | Planning and adapting to changes | Ability to self-refine and update instructions without outside intervention | Full autonomy requires creativity and ability to anticipate changing needs before they occur proactively | Agentic AI benefits Industry 4.0 facilities monitoring machinery in real time, predicting failures, scheduling maintenance, reducing downtime, and optimizing asset availability, enabling continuous process optimization, minimizing waste, and enhancing operational efficiency

#Traditional AI | Models focus on tasks like classification or prediction

#Generative AI | designed to create new content, like text, images, or videos, based on patterns learned from existing data

#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

#Manufacturing ecosystem

#Multi-agent ecosystems | Shift toward multi-agent ecosystems designed for specific workflows

#Deep Research | OpenAI | Autonomous analyst | AI accelerates open knowledge sharing | Companies may lean harder into secrecy to maintain competitive edges

#Event-based imaging for machine vision

#Event-based cameras for highly efficient motion analysis

#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 1¼-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

#Neural cascade | Scheme that allows division of computation across devices

#Self-learning infrared digital anti-masking system | System continuously monitors the sensor environment and adjusts accordingly, reducing the chances of false alarms while maintaining security performance | Unlike manually adjustable ones it adapts upon installation | Anti-masking | Designed to detect and respond when sensor is deliberately covered or obstructed | Anti-masking is critical feature in professional security solutions | Achieved by emitting infrared or microwave signals that continuously check for obstructions | Allowing user to fine-tune detection sensitivity to suit environment minitored

#Artificial intelligence | Accelerated growth in space and satellite industry | Enhancing data processing, automation and decision-making | Enabling faster image analysis | Real-time satellite adjustments | Predictive maintenance | Autonomous spacecraft operations | Making space technology more efficient, cost-effective and scalable

#Mobile robots

#AI in the warehouse

#Humanoid robots

#Field Foundation Model (FFMs) | Physical world model using sensor data as an input | Field AI robots can understand how to move in world, rather than just where to move | Very heavy probabilistic modeling | World modeling becomes by-product of Field AI.robots operating in the world rather than prerequisite for that operation | Aim is to just deploy robot, with no training time needed | Autonomous robotic systems applucations | Field AI is software company making sensor payloads that integrate with their autonomy software | Autonomous humanoid Field AI can do | Focus on platforms that are more affordable | Integrating mobility with high-level planning, decision making, and mission execution | Potential to take advantage of relatively inexpensive robots is what is going to make the biggest difference toward Field AI commercial success