If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
Create a new Text Classifier Model Project in Create ML and add the training folder. You can choose any of the techniques to train your model and go have a cup of coffee while the training and validation happens. It took me 4 hours to get a Transfer learning model trained. Here's an illustration that compares the model metrics across the two techniques in Text Classification: The transfer learning based model extrapolates better. Though you can try achieving better accuracy by increasing the dataset size(TL model training took four hours on a dataset of 15000 texts for me).
Data Science is considered as one of the most modern and fascinating jobs of our time. It can be funny and can give you satisfaction, but is it really as it's described? At the beginning of their career, Data Scientists think that Data Science is a wonderful, magical world full of algorithms, Python functions that performs every possible spell with a line of code and statistical models able to detect the most useful correlations among data that could make you an invincible superhero in your company. You start dreaming about your CEO congratulating with you and shaking your hand, you begin to see decision trees and clusters everywhere and, of course, the most terrifying neural network architectures your mind can dream. But since the very first day of your first Data Science project, you start to realize what reality is.
The 2019 China New Generation Artificial Intelligence Development Report was officially released on 24 May 2019 during the Pujiang Innovation Forum. According to analysts, the biggest challenge that China's AI development is facing relates to very weak links between universities and universities/research institutes. For instance, although China ranks first in the world for number of papers published, these mainly originate from universities and research institutes. There still are no strong and effective mechanisms to the supply and demand of AI results, which largely remain not market-oriented. The number of industry actors participating in government-funded AI research is still very low.
When it comes to hyped technologies that could aid in the corporate fight against climate change, the blockchain and artificial intelligence are probably neck-in-neck. For those who view both with skepticism, I would suggest there's one big difference in the adoption cycle of the two. I can cite numerous pilot projects involving blockchain, but I think it's reasonable to doubt how it will scale. AI, on the other hand, is already driving some very real-world corporate progress toward stated sustainability goals, particularly energy efficiency. Exhibit A is the warehouse operation I wrote about in October, Lineage Logistics, which is using machine learning combined with sensors and data about weather and other parameters to reduce the amount of electricity it uses to keep food frozen.
Thank you so much for joining me so early today. I am very excited to be here. And thank you to the organizers at my con and especially Paul for having me. We are not easing into this morning, we are crashing straight in to a 30 minute crash course on what is the state of the current field of artificial intelligence. So thank you for being on this journey with me.
Over the weekend, a viral twitter thread exposed several issues in the credit lending decisioning process for Apple's new payment card, underwritten by Goldman Sachs. For some context, Apple and Goldman Sachs were involved in alleged gender discrimination in credit card limits caused by biased algorithms powering Apple Card's credit lending decisioning process. There was widespread social media instances confirming this discrimination, including Apple's very own co-founder, Steve Wozniak and his spouse. The primary issue here is with the Black Box algorithm that generated Apple's credit lending decisions. As laid out in the Twitter thread, Apple Card's customer service reps were rendered powerless to the algorithm's decision.
Cisco recently announced how its three most recent acquisitions will add value to its Cisco Contact Center help desk solution that's currently used by more than three million agents in over 30,000 enterprises. The announcement was made at the 10th annual Cisco Contact Center Summit on September 19, 2019, in Hollywood, Florida, which was attended by 1,100 Cisco salespersons, partners, and customers. Cisco's Contact Center is an integrated communications application suite that delivers intelligent call routing, network-to-desktop computer telephony integration (CTI), and multi-channel contact management to contact center agents over an Internet Protocol (IP) network. Cisco has been enhancing the capabilities of its contact center offerings by acquiring various products over the past year or so, and integrating those offerings' features and functionalities to its feature stack. Beginning in May 2018, Cisco finished its acquisition of business intelligence (BI) specialist Accompany.
What does a fully autonomous, electric, high-performance race car have to do with the United Nations Sustainable Development Goals (SDGs)? For starters, the vehicle, developed by Roborace, is providing a testing ground for new efforts to build public trust in how next-generation vehicles could improve road safety and reduce the 1.35 million annual road deaths worldwide (SDG 3.6). Increased use of autonomous, electric, connected vehicles could also reduce emissions, improve traffic flows -- and provide affordable, safe and sustainable transport systems to underdeveloped nations (SDG 11.2). But how do we go from race track to the road? A panel of experts – Bryn Balcombe, CSO at Roborace and Founder of the Autonomous Drivers Alliance; Lucas di Grassi, Formula-E World Champion and CEO at Roborace; and Fred Werner, Head of Strategic Engagement at ITU's Standardization Bureau – met at Web Summit 2019 to discuss how AI will make our roads safer, and how ITU is helping lead the charge.
REUTERS: Alphabet Inc's Google signed its biggest cloud computing customer in healthcare yet, according to an announcement on Monday (Nov 11), gaining with the deal datasets that could help it tune potentially lucrative artificial intelligence tools. The Wall Street Journal earlier reported Google teaming up with Ascension to collect personal health-related information of millions of Americans across 21 states. The partnership will also explore artificial intelligence and machine learning applications to help improve clinical effectiveness as well as patient safety, Ascension said in a statement. Google Cloud Chief Executive Officer Thomas Kurian has made it a priority in his first year on the job to aggressively chase business from leaders in six industries, including healthcare. The company previously had touted smaller healthcare clients, such as the Colorado Center for Personalized Medicine.