To the CSE community: We are excited to introduce you to the newest member of our department -SmartWheels-, a miniature robotic vehicle! Our robotic vehicle is outfitted with the most advanced sensor technology, including LiDAR, radar, and cameras, enabling it to perceive its surroundings in real-time and make intelligent decisions based on its surroundings. It is also powered by cutting-edge AI algorithms that enable it to learn from its experiences and enhance its performance continuously. This platform will host numerous master's theses and graduation projects. We appreciate you taking the time to learn about our latest innovation.

"Without understanding the cause and effect of interactions within the world, no AI model, algorithm, technique, application, or technology is real and true", be it: Natural language generation converting structured data into the native language; Speech recognition converting human speech into a useful and understandable format by computers; Virtual agents, computer applications that interact with humans to answer their queries, from Google Assistant to the Watson; Biometrics, to identify individuals based on their biological characteristics or behaviors, with fingerprints and faces, hand veins, irises, or voices biometric modalities; Decision management systems for data conversion and interpretation into predictive models; Machine learning empowering machine to make sense from data sets without being actually programmed, to make informed decisions with data analytics and statistical models; Robotic process automation configuring a robot (software application) to interpret, communicate and analyze data; Peer-to-peer network connecting between different systems and computers for data sharing without the data transmitting via server; Deep learning platforms based on ANNs teaching computers and machines to learn by example just the way humans do; Generative AI (GANs, Transformers, Autoencoders) referring to unsupervised and semi-supervised machine learning algorithms that enable computers to use existing content like text, audio and video files, images, or code to create new possible content as completely original artifacts. It leverages AI and ML algorithms to generate artificial content such as text, images, audio and video content based on its training data to trick the user into believing the content is real, facing legal challenges concerning data privacy; Generative AI models with image generation algorithms generating photographs of human faces, objects and scenes, image-to-image conversion, text-to-image translation, film restoration, semantic-image-to-photo translation, face frontal view generation, photos to emojis, face aging, media and entertainment: deep fake technology; AI optimized hardware support artificial intelligence models, as #neuralnetworks, #deeplearning, and #computervision, including CPUs, GPUs, TPUs, OPUs to handle scalable workloads, special purpose built-in silicon for neural networks, neuromorphic chips, etc.; Real AI is NOT about representing computational models of intelligence, described as structures, models, and operational functions that can be programmed for problem-solving, inferences, language processing, etc. Real AI is about the computational models of reality and mentality, described as causal structures, models, and operational functions that can be programmed for problem-solving and inferences for a wide range of goals in a wide range of environments.

Real AI is not data engineering or coding and software engineering skills, in big data tools or developer's skills in Python, R, Java, MATLAB, C or any other programming language desired, combined with machine learning skills. Keep a big view of Real AI as growing via three human intelligence faking levels to the Trans-AI: Artificial Narrow Intelligence (ANI)/ML/DLNNs; Artificial General Intelligence (AGI)/Human-Level AI; Artificial Super Intelligence (ASI); Trans-AI, Real and True AI, Meta-AI, Causal Machine Intelligence and Learning Man-Machine Hyperintelligence, the most disruptive integrative general-purpose technology.

AI Researcher, Cognitive Technologist Inventor - AI Thinking, Think Chain Innovator - AIOT, XAI, Autonomous Cars, IIOT Founder Fisheyebox Spatial Computing Savant, Transformative Leader, Industry X.0 Practitioner BCI capture a user's brain activity and translate it into commands for an external application. What types of brain's signal BCI is acquiring? The system can use any brain's electrical signals measured by applications on the scalp, on the cortical surface, or in the cortex to control external application. The most researched signals are: Electrical and magnetic signals of brain's activity captured by the intracortical electrode array, electrocorticography (ECoG), electroencephalography (EEG), magnetoencephalography (MEG) techniques. Metabolic signals measuring blood flow in the brain acquired by functional magnetic resonance imaging (fMRI) or functional near-infrared imaging (fNIRS) techniques.

Glancing at Barcelona's still-unfinished Sagrada Família Roman Catholic basilica, with its famous sandcastle-like exterior, it is easy to get the wrong idea about its architect, Antoni Gaudí, as a carefree, loosey-goosey artist. The whimsical exterior hides a geometrically sophisticated, structurally advanced design--a big part of the reason this grand basilica, begun in 1882, has taken so many decades to build, remaining the world's longest-running ongoing architectural project. This complexity required an utterly different approach to modeling than what architects had typically deployed. Instead of using two-dimensional drawings to guide builders, Gaudí relied heavily on large, high-fidelity plaster models--models that needed to be reverse engineered and rebuilt after extensive damage during the Spanish Civil War. In a separate project, Gaudí pioneered the use of hanging-chain models that enable changes in real time; though he did not use these interactive models on the Sagrada Família, they guided his thinking and prefigured the so-called parametric design software that has been instrumental to the acceleration of the project's pace in recent years.

𝐇𝐈𝐑𝐈𝐍𝐆 𝐀𝐋𝐄𝐑𝐓 (𝐍𝐨 𝐑𝐞𝐜𝐫𝐮𝐢𝐭𝐞𝐫𝐬 𝐏𝐥𝐞𝐚𝐬𝐞) Hiring Research Engineers in the domain of Computer Vision, 3D Geometry and Machine ...

AI Researcher, Cognitive Technologist Inventor - AI Thinking, Think Chain Innovator - AIOT, XAI, Autonomous Cars, IIOT Founder Fisheyebox Spatial Computing Savant, Transformative Leader, Industry X.0 Practitioner A better way to build #machinelearning - why you should be using ActiveLearning? You spend less time and money on labelling data: Active learning has been shown to deliver large savings in data labelling across a wide range of tasks and data sets ranging from #computervision to #NLP. Since data labelling is one of the most expensive parts of training modern machine learning models this should be enough justification on its own. You get faster feedback on model performance: Usually people label their data before they train any models or get any feedback. Often, it takes days or weeks of iterating on #annotation guidelines and re-labelling only to discover that model performance falls far short of what is needed, or different labelled data is required.

Global AI in Computer Vision- Significantly Growing with Emerging Trends The major driving factor behind the growth of computer vision is the huge amount of data generated in day to day life. The accuracy rates of object detection have been increasing with an increase in new hardware and algorithms in computer vision. From 50% accuracy to 99%, computers are reacting more quickly than humans to visual inputs. Features like Topology for Custom-tailored eyewear, MTailor for making custom fitted pants and shirts, Pottery Barn for virtual look of new furniture at homes with 3D models, self-driving vehicles, and cashier less supermarkets - all are a result of computer vision Know more @ https://lnkd.in/gj72e9J

GlobalData research has found the top artificial intelligence influencers based on their performance and engagement online. Using research from GlobalData's Influencer platform, Verdict has named twelve of the most influential people in artificial intelligence on Twitter during Q1 2020. Ronald van Loon is a recognised thought leader and a top technology influencer. As director of Advertisement, the influencer provides insights and secures analytics data quality, among other responsibilities. He also serves on the Advisory Board of the wefox Group, a Europe-based insurtech start-up.

Are you sure you want to view these Tweets? World's First'Living Machine' Created Using Frog Cells and #Artificial ntelligence. The Tembé tribe from the central #Amazon is collaborating with Rainforest Connection, an environmental nonprofit, to use old cell #phones hidden in #trees and #TensorFlow to listen for sounds of illegal logging. This #AI-powered app makes learning #math as simple as clicking a photo. What is the triplet loss?