Media, AI/Machine Learning Architect

We invite you to join Intel’s Next Generation & Standards (NGS) Group and the 5G revolution! We are a global team of passionate engineers and technologists from diverse industry backgrounds, working together to realize a world of connected computing.

Intel’s NGS team is chartered with developing advanced prototypes of various technologies to deliver innovative and state of the art wireless experiences into the market within the Internet of Things, 5G Next Generation Wearable and IoT solutions and other world-class wireless connectivity technologies and products

In this position, you will be working on advanced algorithm design, development and innovation towards the future emerging technologies in the Next Generation and Standards (NGS) group within Intel.

Roles and Responsibilities:

Research new technologies and analyze competition technologies to solve applied problems in various disciplines, including immersive media (e.g. 3DoF+, 6DoF, Point Cloud, AR and VR, etc.), Computer Vision, Data Analytics, AI/Machine learning
Design new algorithms, review professional literature and specify solution options for emerging technologies, e.g. immersive media, machine learning/AI, etc.
Research and development of new proprietary and standardization technical solutions for next-generation video technology (H.266/VVC, MPEG-I, H.265/HEVC, AV1, etc.)
Support Proof-of-Concept development of emerging technologies. Implement algorithm designs in software C/C++, Python, TensorFlow and Matlab
Software development and enhancement of MPEG reference software (HEVC/H.265, AV1, VVC, etc.) for proof-of-concept and standardization contributions

https://ai-jobs.net/job/media-ai-machine-learning-architect/

Initializing neural networks
"Initialization can have a significant impact on convergence in training deep neural networks."
By Katanforoosh & Kunin, "Initializing neural networks", deeplearning.ai, 2018: https://www.deeplearning.ai/ai-notes/initialization/
#artificialintelligence #deeplearning #neuralnetworks

AI Portraits of You

"AI Portraits Ars is able to paint portraits in real time at 4k resolution. You will find yourself in front of a mirror and feel thousands Rembrandt, Caravaggio, Titian portraying you moment after moment."

By MIT-IBM Watson AI Lab: https://aiportraits.com/#

#DeepLearning #GenerativeAdversarialNetwork #GAN

Microsoft is investing $1 billion in and partnering with OpenAI to support us building beneficial AGI: https://openai.com/blog/microsoft/

Automatic vocal tract landmark localization from midsagittal MRI data.
https://arxiv.org/abs/1907.07951

Deep Learning in Healthcare and Computational Biology
Tangible and Practical Deep Learning Projects Repository for Healthcare such as Cancer, Drug Discovery, Genomic and More

https://github.com/TarrySingh/Deep-Neural-Networks-HealthCare

An outstanding Nature Medicine
guide to deep learning in healthcare, including computer vision, natural language processing, reinforcement learning, and generalized methods in genomic medicine and beyond. https://www.nature.com/articles/s41591-018-0316-z

Uber’s EvoGrad is a dev library for evolutionary algorithms
Blog by Kyle Wiggers: https://venturebeat.com/2019/07/22/ubers-evograd-is-a-dev-library-for-evolutionary-algorithms/
#EvolutionaryAlgorithms #NaturalEvolutionStrategies #Python

Dynamical Distance Learning for Unsupervised and Semi-Supervised Skill Discovery

Hartikainen et al.: https://arxiv.org/abs/1907.08225

#ArtificialIntelligence #Robotics #MachineLearning

COMET: Commonsense Transformers for Automatic Knowledge Graph Construction

Bosselut et al.: https://arxiv.org/abs/1906.05317

#ArtificialIntelligence #DeepLearning #MachineLearning

"Predicting planets from orbital perturbations using deep learning"
Blog post by Kyle A. Pearson: https://medium.com/tensorflow/predicting-planets-from-orbital-perturbations-using-deep-learning-cb58fb9996c5
#Astronomy #TensorFlow #DeepLearning

"The Surprising Creativity of Digital Evolution: A Collection of Anecdotes from the Evolutionary Computation and Artificial Life Research Communities"
By Lehman, Clune, Misevic et al.: https://arxiv.org/pdf/1803.03453.pdf
#ArtificialLife #DigitalEvolution #EvolutionStrategy

"Visualizing and Measuring the Geometry of BERT"
Coenen et al.: https://arxiv.org/abs/1906.02715
Blog post : https://pair-code.github.io/interpretability/bert-tree/
#ArtificialIntelligence #DeepLearning #MachineLearning

"Learning to Traverse Latent Spaces for Musical Score Inpainting"
Pati et al.: https://arxiv.org/abs/1907.01164
GitHub: https://github.com/ashispati/InpaintNet
Demo: https://ashispati.github.io/inpaintnet/
#ArtificialIntelligence #MachineLearning #Music

Everything You Need to Know About Autoencoders in TensorFlow


https://towardsdatascience.com/everything-you-need-to-know-about-autoencoders-in-tensorflow-b6a63e8255f0

"Behind the Selection of the NeurIPS 2019 Workshops"

By Neural Information Processing Systems Conference: https://medium.com/@NeurIPSConf/2019workshops-ec820e4d558e

#MachineLearning #Neurips2019 #DeepLearning #ReinforcementLearning #Neurips

Let’s code a Neural Network in plain NumPy
Blog by Piotr Skalski: https://towardsdatascience.com/lets-code-a-neural-network-in-plain-numpy-ae7e74410795
#artificialintelligence #neuralnetwork #numpy

@ArtificialIntelligenceArticles