SuperAnnotate

SuperAnnotate is helping to build the world’s most innovative products with computer vision. By empowering companies with the highest-quality datasets and the most scalable computer vision pipelines, SuperAnnotate is enabling the future of AI. Our ML-powered end-to-end platform for computer vision lets teams create, annotate, manage and automate even the most complex computer vision projects leading to more accurate training data, and higher-performing ML models.

Super Annotate provides advanced and intuitive image, text, and video annotation services to support projects of all sizes across various industries, from autonomous vehicles and medical imaging to security and surveillance.

Professional Highlights:
► Identify and qualify business opportunities, understand key customer technical objections, and develop the strategy to resolve technical blockers
► Provide in-depth machine learning expertise to support the technical relationship with SuperAnnotate’s customers, including product and solution briefings and proof-of-concept work
► Partner directly with product management to prioritize solutions impacting customer adoption
► Work hands-on with customers around the world to demonstrate and prototype SuperAnnotate’s product integrations in customer/partner environments
► Recommend integration strategies, enterprise architectures, and application infrastructure required to successfully implement a complete solution using best practices on SuperAnnotate

AI Solutions Engineer - Computer Vision

NomiSo Inc

► Work with Data Ingestion team to create landing zone on Postgres Database for different source data (ESPN, Gracenote, Tivo, and more). Work to set up Apple feed service for client side content metadata delivery.
► Collaborate with Delivery API team to provide necessary endpoints for client needs
► Set up and manage microservices via Docker and Kubernetes
► Write unit tests to ensure service functionality. Measure and report code performance metrics

Software Engineer

Galvanize Inc

Galvanize is a 21st century school for engineers, entrepreneurs and data scientists. On eight campuses across the U.S., the energy, intellect and ambition of Galvanize students, members and alumni are at the heart of a learning community that promotes belonging and celebrates courage and growth. Our faculty and flexible blended-learning platform, combining part-time online education and in-person training, provide the most relevant and in-demand technology skills to anyone with the drive and determination to re-skill, up-skill and define success on their terms. Our members include first-time entrepreneurs, growing startups, and Fortune 1000 companies all looking to level-up.

Professional Highlights:
► Built, revised, and delivered curriculum content, training tutorials, and lectures on scientific Python, SQL, probability, statistics (Bayesian/frequentist), ML, CNN, time series, and data engineering to PhD/Masters' graduates/professionals
► Established alumni/hiring partner relationships. Developed and implemented targeted cultivation campaigns through 1 on 1 meetings, virtual informational sessions, on-campus events, and student focused panels
► Contributed to student preparation at the NYC campus by providing technical support as well individual feedback for capstone presentations, daily coding sprints, and weekly review sessions.
► Lead day-long “sprints,” maintaining a strong presence in the classroom and receiving mentor-ship from other instructional staff
► Contribute to local evangelism, admissions, and nurture activities, such as attendance at meetups, speaking at conferences, leading workshops (daytime and/or evening), etc.

Senior Data Science Resident

RefiBot

Refibot is a company that delivers on promises of a more safe and secure world. The team looks to bring innovation, fairness, and intelligence to communities around the world. The vision of the company is to pioneer safety, security, and peace of mind in the Retail industry through State-of-The-Art AI Surveillance. The goal is to challenge the status quo and bring innovative solutions to empower our schools, stores, respective businesses, and every person impacted. The RefiBot team brings real ingenuity from all around the world and the willingness to give back to our communities by propelling them forward with advanced technologies.

Professional Highlights:
► Using Tensorflow, design and implement ML algorithms for AI security system (RefiCam). Plan, develop, and implement strategies for creating high performance GPU-accelerated applications using CUDA, cuDNN, and TensorRT. Train ML models using data collected (>20GB) from online sources and self created data set of human actions. 
► Curate a list of state of the art pose estimation models, test, and Implement noise reduction/filtering techniques to improve human pose estimation accuracy. 
► Research computer vision algorithms for object detection and action recognition (OpenCV). Investigate Multilayer Perceptron, LSTM, and CNN approaches for improving performance on action recognition tasks. 
► Data acquisition: Acquire multiple sources of video data relating to criminal activity at retail businesses. Aid in creating own data set of videos containing actions being performed by humans such as: standing, waving, punching, kicking, and walking.

Machine Learning Engineer - Computer Vision

ExoDerma

ExoDerma provides applications for human movement analysis. Our company builds on a natural curiosity about how humans move. We are dedicated to developing technologies that allow users to analyze, study, and learn from videos of their movements. We envision a world where information can be leveraged to build data driven training or rehabilitation programs. The company not only provides visual feedback for rehabilitation use cases, but also provides coaching and training for users that are looking to excel in athletic performance.

Professional Highlights:
► Implement human pose estimation algorithms for sports performance analysis
► Develop GUI and functionality to display joint information
► Integrate computer vision, GUI, and webcam for real time movement analysis
► Mathematical modeling of human movement: Develop metrics for movement efficiency
► Run workshops to discuss concepts in physics, biomechanics, mathematics, and programming
► Research methods for improvement of human pose estimation and tracking

Data Scientist/Machine Learning Engineer - Computer Vision

Kurvv

Kurvv is a team of developers and data scientists from leading machine learning companies like Microsoft, Amazon and Google, working behind the scenes to deliver exceptional models and experiences. Kurvv allows customers to apply the power of machine learning into their business processes without data scientists. We believe that the power of AI and machine learning should be accessible to anyone, not just the engineers and data scientists.

Professional Highlights:
► Research of methods to translate complex data science concepts into terms that can be digested by non-technical business users
► Creation and publishing of educational content for target customers

Data Scientist

Collegewise

Collegewise is the nation’s largest college admissions counseling organization. With over 60 admissions experts and 40 testing and curriculum tutors, we’re out to change the way that families approach the college admissions process. We think this should be an exciting time for students and parents, not a stressful, anxiety-ridden rite of passage. We provide counseling, guidance, and tutoring support to students going through their college admissions process.

Professional Highlights:
► Tutor for math, physics, science and Spanish to high school students
► Tutor college level students (undergraduate) in Calculus and physics
► Teach students how to program and utilize graphing calculators (TI series)

Tutor - Mathematics, Physics, Science, Spanish

Rutgers University–New Brunswick

The Department of Biomedical Engineering at Rutgers offers unparalleled access to leaders and innovators in the field as well as to resources, including research funding and internship opportunities. State-of-the-art facilities encourage interdisciplinary collaboration in genomics, tissue engineering, advanced microscopy, biomedical optics, microfabrication, animal study, and more.

Professional Highlights:
► Data acquisition for gum oxygenation prototype
► Prototype testing: Measured Fluorescent Lifetime Imaging Microscope (FLIM) accuracy
► Machine Learning & GUI development for scoliosis detection using ultrasound scans
► Manual image segmentation and data collection for bone surface localization ML model

Research Assistant

University of Rochester

Research in the department covers a broad spectrum, ranging in length scale from molecular to whole animal, and encompassing a wide variety of physiological systems and experimental approaches. Because of the disciplinary nature of biomedical engineering, faculty and students have countless opportunities for collaboration. Identified areas of concentration within the department include: Biomechanics, Biomedical Acoustics, Biomedical Nanotechnology, Biomedical Optics, Cell & Tissue Engineering, Medical Imaging, Neuroengineering

Professional Highlights:
► Data acquisition and analysis for research in salivary gland cancer
► Analyzed effects of neurotrophic factors on cellular regeneration after cell damage
► Utilized real time qPCR analysis to measure DNA concentration and cell viability

No, I will not help you build systems that are *intended* to harm other humans.

Recruiters, please stop sending me opportunities for Defense, Military, or otherwise weapon-related systems.

I am not interested in using my skills, expertise, or talent to build systems that are used to destroy or hurt people - even if it's in the name of "defense" or "national security."

You are what you do and eat
Email: luis.d.riera.m@gmail.com
GitHub: github.com/moonbeam5115

Data scientist with a background in Biomedical and Mechanical Engineering. Passionate about data science/programming, data analysis, and computer vision!

Looking to develop the tools that will help make our lives better. I believe we as humans have unbelievable potential to affect the world and people around us for the better.

Great at analyzing complex problems and effectively communicating ideas to my peers. 
Creative and industrious.
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TECHNICAL SKILLS:
• Machine Learning & Statistics:
Linear regression, logistic regression, decision trees, random forest, gradient boosted descent, exploratory data analysis, hypothesis testing, bayesian statistics, NLP, supervised & unsupervised learning, Deep Learning (Neural Networks, CNN, RNN, LSTM)

• Programming/Software:
Python, Numpy, Pandas, Tensorflow/Keras, C#, C++, OpenCL, Docker, AWS, Flask, git/GitHub, MySQL, Unity3D, Blender, Adobe Premiere, Adobe After Effects

• Computer Vision:
OpenCV, Human Pose Estimation (single person & multi-person), Object Detection & Tracking, YOLO, Image Segmentation, Image Classification, Image Processing

MANAGEMENT SKILLS:
Project and Knowledge-Based Management, Event Planning, Marketing Research, Teaching, Training, and Coaching, Data Analytics, Curriculum Development, Professional Networking

Yann LeCun's Illusion of Consciousness

This idea is not unique to Yann. Many modern AI researchers, neuroscientists, cognitive scientists, computer scientists, philosophers, etc... believe some form of this argument.

To my best summarizing ability, the argument goes as follows:

"Your conscious experience is a side-effect of material neuronal processes. It is illusory in the sense that it has no effect on the body/material - there is no causation from mind to body."

This would imply consciousness has no effect on intelligence or learning. I think Yann would agree with this conclusion.

From Yann's paper, A Path Towards Autonomous Machine Intelligence:

"The hypothesis of a single, configurable world model engine in the human brain may explain why humans can essentially perform a single “conscious” reasoning and planning task at a time. A highly-speculative idea is that the illusion of consciouness may be a side-effect of a configurator-like module in the brain that oversees the function of the rest of brain and configures it for the task at hand. Perhaps if the brain were large enough to contain many independent, non-configurable world models, a configurator would be unnecessary, and the illusion of consciousness would disappear."

So, in Yann's view, if we were able to create a machine powerful enough to contain many independent "non-configurable" world models, there would be no need for a "configurator" - and the "illusion of consciousness" would not be needed.

The paper goes into more detail on the architecture of the proposed system for "autonomous machine intelligence." You can read the paper to learn more about the "configurator" and its role in the system. But it essentially serves as the "orchestrator" of breaking down complex tasks into simpler steps which can then be carried out by other parts of the system. 

How this can be achieved is not specified, and it is left as an exercise for future researchers to figure out. 

The positive thing about this mode of thought is we may not need a "conscious machine" to achieve "AGI" or "Autonomous Machine Intelligence."

That is, if Yann is correct here.

If Yann is correct here, then that can also mean super intelligent machines (way more intelligent than humans) won't be conscious or aware - and thus will not feel or experience the world in the way we do.

If super intelligence is favored in the future over "human intelligence," then the future may be full of highly intelligent "zombies" with no inner life or experience related to the marvelous feats they are accomplishing out there in the "real world." 

Life is le weird.

Paper in the comments.

#ai #philosophy #singularity

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