Businesses are in the midst of a digital transformation. To transform, they must become software companies, they must turn their products and services online, and they must provide more intelligent solutions. This new and connected world has companies turning to the Internet of Things (IoT) to lead them towards new business opportunities.Read the source article at SD Times..
If you’re still unsure of machine learning and it’s benefits, consider these scenarios
In 2016, Google’s net worth was reported to be $336 billion, and this is largely due to the advanced learning algorithms the company employs.
Google was the first company to realize the importance of incorporating machine learning in business processes. And the technology powerhouse doesn't stop at any given point; it keeps modifying its algorithms to better suit the needs of its use..
Artificial intelligence (AI) systems, blending data and advanced algorithms to mimic the cognitive functions of the human mind, have begun to simplify and enhance even the simplest aspects of our everyday experiences — and the automotive industry is no exception. A Tractica market intelligence study forecasts that the demand for automotive AI hardware, software, and services will explode from $404 million in 2016 to $14 billion by 2025.read more »
The key is to find the type of productization that is the best fit. In my framework, the custom kitchen is for companies who are creating their own solutions for wider use either internally or externally. The dinner in a box is for those who want a toolkit built with a set of use cases in mind, again, so a company and/or its consultants can create solutions that can be widely used. The artisanal brew is about a configurable solution for a use case. The value meal is a fully productized use.<..
Machine learning is a very hot topic for many key reasons, and because it provides the ability to automatically obtain deep insights, recognize unknown patterns, and create high performing predictive models from data, all without requiring explicit programming instructions.
Despite the popularity of the subject, machine learning’s true purpose and details are not well understood, except by very technical folks and/or data scientists.
This series is intended to be a comprehensive..
“The next iteration of the internet will be the connection of billions of autonomous devices to the network. These devices will be gathering and transmitting information with no human intervention to platforms and systems that will distill the information in action, again, with no human intervention.”Read the source article at Home - Banking Exchange..
If banking’s compliance fraternity had a coat of arms like those made for the knightly orders of old, it might include the following heraldic devices:
• An hourglass, almost out of sand, to symbolize how compliance officers are nearly always facing some issue with inadequate time.
• A stack of papers depicting the vast body of fine print they must be up on.
• A stack of $100 bills burning to symbolize ongoing and rising costs of compliance.
• A mythical beast..
Aashu Virmani, CMO at Fuzzy Logix here talks to Finance Monthly about the potential impact data analytics can have on fighting money laundering and changing your business for the better.
The numbers speak for themselves:
- 75% reduction in 'False Positives'
- 40% increase in terms of incremental identification of suspicious activity or STRs
- 50% cheaper
So, if y..
"I have found myself in the middle of many a conversation wherein terms like AI, ML, DL, NLP (and other concepts that are clustered around these acronyms such as Neural Networks) are often casually blended into a soup of words where these terms are used interchangeably. Heck…I have done so myself and ought to be classified as a Class A offender by the cognoscenti. If anything, this post is one that I am writing for myself to impart a much needed self-clarity as to what these concepts actuall..
What? AI and machine learning are inextricable to the future of business.
So what? Marketers must learn how to leverage these technologies for insights.
Now what? Make sure your data allow you to scale and automate your insights generation, and don't fall into the trap of finding spurious correlations.