Are you ready to kickstart your Advanced NLP course? Are you ready to deploy your machine learning models in production at AWS? You will learn each and every steps on how to build and deploy your ML model on a robust and secure server at AWS. Prior knowledge of python and Data Science is assumed. If you are AN absolute beginner in Data Science, please do not take this course. This course is made for medium or advanced level of Data Scientist.

Trained on the voices of popular narrators, the AI's can respond in infinite ways to game scenarios Trained on the voices of popular narrators, the AI's can respond in infinite ways to game scenarios Tractable's tech uses cell phone video to estimate damages from accidents and natural disasters Tractable's tech uses cell phone video to estimate damages from accidents and natural disasters When you check out your fresh produce, the AI recognizes the product, even if it's wrapped in layers When you check out your fresh produce, the AI recognizes the product, even if it's wrapped in layers Submit some samples of your voice and AI will be able to speak exactly as you - what could go wrong? Submit some samples of your voice and AI will be able to speak exactly as you - what could go wrong? Open AI's GPT-3 text generator is released into the wild and generates content that is impermissible Open AI's GPT-3 text generator is released into the wild and generates content that is impermissible

Some of the greatest scientists and inventors of the future are sitting in high school classrooms right now, breezing through calculus and eagerly awaiting freshman year at the world's top universities. They may have already won Math Olympiads or invented clever, new internet applications. We know these students are smart, but are they prepared to responsibly guide the future of technology? Developing safe and beneficial technology requires more than technical expertise -- it requires a well-rounded education and the ability to understand other perspectives. But since math and science students must spend so much time doing technical work, they often lack the skills and experience necessary to understand how their inventions will impact society.

The 7th Symposium on Educational Advances in Artificial Intelligence (EAAI'17, co-chaired by Sven Koenig and Eric Eaton) launched the EAAI New and Future AI Educator Program to support the training of early-career university faculty, secondary school faculty, and future educators (PhD candidates or postdocs who intend a career in academia). As part of the program, awardees were asked to address one of the following "blue sky" questions: * How could/should Artificial Intelligence (AI) courses incorporate ethics into the curriculum? * How could we teach AI topics at an early undergraduate or a secondary school level? * AI has the potential for broad impact to numerous disciplines. How could we make AI education more interdisciplinary, specifically to benefit non-engineering fields? This paper is a collection of their responses, intended to help motivate discussion around these issues in AI education.

And because AI students are trained in such a rich multidisciplinary environment, they have excellent career opportunities. To make a thinking machine is one of humanity's oldest dreams. And since Allan Turing?s 1947 lectures on AI, programmable computers seemed to be the best way to go. Expectations were extraordinarily high in the 1950s and '60s, but without major breakthroughs, the whole subject lapsed temporarily into obscurity. Now, advances in the cognitive sciences that are improving our understanding of the nature of intelligence, memory, and perception from the biological perspective, coupled with the ready availability of ever-faster computers, are creating a second spring for AI--and a mecca for multidisciplinary scientists.