In a meeting with engineering leadership, I was told, "We'll tack on the AI later."
While doing ethnographic testing with a β customer, I was asked if the AI would just learn and then do everything perfectly.
Most of the big organizations are struggling with AI transformation. Data science projects are either taking too long to complete or would never get into production.
Among various reasons, the most common is the lack of a stable data science team. Due to high demand, the turnover rate is very high in data science, unfortunately. Data science managers or leaders typically go around this problem by focusing on the following:
Added by Nasir Mahmood on May 5, 2020 at 1:30am — No Comments
Such technology as AI existed for years yet experienced a significant popularity boost just a few years ago. Today, it’s far from being a futuristic thing used by the evil geniuses to conquer the planet. Instead, Artificial Intelligence became a cutting-edge tool to improve the lives of millions by assisting us with our job, studies, home duties, and even relationships. There’s no need to mention that AI start-ups are the ones to run the IT industry: $37.5 billion was spent on the start-ups…Continue
Added by Debra White on March 26, 2020 at 6:40am — No Comments
IRIS ML Toolkit adds the power of IntegratedML to further extend convergent scenario coverage into the area of automated feature and model type/parameter selection. The previous "manual" pipelines now collaborate within the same analytic process with "auto" pipelines that are based on automation frameworks, such as H2O.…Continue
Added by Sergey Lukyanchikov on February 14, 2020 at 1:00pm — No Comments
Mastering Machine Learning Algorithms, Second Edition helps you harness the real power of machine learning algorithms in order to implement smarter ways of meeting today's overwhelming data needs. This newly updated and revised guide will help you master algorithms used widely in semi-supervised learning, reinforcement learning, supervised learning, and…Continue
Added by Giuseppe Bonaccorso on February 9, 2020 at 3:01am — No Comments
Added by Mark Cramer on January 23, 2020 at 12:30pm — No Comments
Summary: Just how much should you trust your AI systems? Best practice points to constant review, strong governance, and the willingness to override results that seem illogical.
Added by William Vorhies on January 20, 2020 at 8:26am — No Comments
Choose your format to work on the same analytical process among graphical composer (IRIS BPL), notebook (Jupyter) or IDE (IRIS Studio/Atelier):
This platform-centric approach to developing analytical tools and solutions aiming to maximize the advantages of combining multiple analytic toolsets (AI/ML, BI, SQL, Quantum, IoT, MapReduce, NLP,…Continue
Added by Sergey Lukyanchikov on January 19, 2020 at 9:30pm — No Comments
AI Robotization with IRIS Data Platform
Author: Sergey Lukyanchikov
Fixing the terminology
A robot is not expected to be either huge or humanoid, or even material (in disagreement with Wikipedia, although the latter softens the initial…Continue
Added by Sergey Lukyanchikov on December 15, 2019 at 8:00am — No Comments
Machine learning is not a new tech development, but the ethical issues artificial intelligence presents are at their most historically pressing moment. There are multiple ethical questions to confront, including the four most prevalent below.
1. Privacy Is The End Of An…Continue
Human and artificial intelligence compares just as well as oranges and apples do. Nonetheless, the broader public does precisely that, including a vast portion of businesses and organizations. Hence, let's do a thought experiment: If we were to compare human and artificial intelligence, how would we go about it? And what would be the possible conclusions from that comparison?…Continue
Added by Rafael Knuth on October 14, 2019 at 9:30am — No Comments
There are a lot of on-going controversies on the impact of Artificial Intelligence on designing and development. While, designing is a bit of a complex process; as the humans only have the capability to set the context and create what the user’s really are looking for. But researchers and designers are constantly working on the technology in an attempt to find out how AI will affect the future of designing industry. …Continue
Added by Ashok Sharma on September 29, 2019 at 7:30pm — No Comments
If you’re just starting out in Intelligent Automation (IA) or Robotic Process Automation (RPA), it won’t be long before you start hearing a certain acronym banded around again and again and again.
Indeed, the RPA Centre of Excellence (CoE) retains a…
Added by Harrison Goode on September 16, 2019 at 8:00am — No Comments
The most frequent question I get about AI from colleagues, product managers and others, is,
"What do I need to know about AI and what's the best way to learn it?"
I've invested a considerable amount of time taking…Continue
Added by Mark Cramer on June 19, 2019 at 12:47pm — No Comments
The energy industry is undergoing a rapid transformation in recent past owing to the enhanced role of renewables and enhanced data-driven models making the value chain smarter. In the context of the primary constituents of this sector comprising of coal, power, renewables, solar energy, oil, and gas, there is a huge role AI can play.
We illustrate some key use cases below:
1. Smart Grid
The biggest disruption in power in recent times is in the smart grid…Continue
Added by Mahesh Kumar CV on May 30, 2019 at 5:02am — No Comments
Added by Max Ved on May 27, 2019 at 11:02pm — No Comments
Larry Page's "PageRank" Graph Algorithm as applied to Google search changed the digital world forever. Learn more in this Free eBook: Graph Algorithms: Practical Examples in Apache Spark and Neo4j, By Mark Needham & Amy E. Hodler, Published by O'Reilly Media https://neo4j.com/graph-algorithms-book/
Watch: Improve ML Predictions using Graph Analytics…Continue
Added by David Vessie on May 16, 2019 at 2:52pm — No Comments
"AI will be the most defining technology for the banking industry."
-Ravi Narayanan, HDFC Bank
Such a comment, coming from an organization (HDFC) which has taken a gigantic leap in adopting conversational banking in the form Eva, India’s first AI bank agent, isn’t surprising. However, make no mistake, AI is being accepted globally as the new UI for banks to interact with their customers. Industry thought leaders increasingly agree that…Continue
Added by Mahesh Kumar CV on May 4, 2019 at 10:00am — No Comments
Global trends like fuel price fluctuations, geopolitical events and government regulations have a huge impact on the airline industry. In an industry at the mercy of unpredictable trends, it is all the more important for companies to gather, analyze and apply data intelligently to all business processes.
Some key use cases where AI will provide tons of value in the aviation industry are as follows:
1. Optimizing MRO via Preventive Maintenance
Added by Mahesh Kumar CV on May 4, 2019 at 10:00am — No Comments
Agriculture is a major segment powering the Asian economy. A small transformation in agricultural outcomes can have a huge impact on 2 dimensions – economic and human. Keeping this in mind CANOPY ONE brings to you our pick of the top 3 use cases which would have a massive impact. So here they come
1. Determining Optimal Fertilizer Mixes
One of the fertilizer manufacturer and leading producer and distributor of specialty…Continue
Added by Mahesh Kumar CV on April 6, 2019 at 10:30pm — No Comments
Artificial intelligence has been fascinating to the human imagination since the term was first used by the first science fiction writers.
The roots of the concept of "artificial intelligence" must be sought deep in the ancient world, where folklore, legends and myths in almost every culture spoke of artificially created creatures endowed with supernatural intelligence, consciousness or other human qualities. The only factor uniting the myths of the whole world is that artificial…Continue
Added by Melissa Crooks on February 27, 2019 at 12:42am — No Comments