Temptations - Artificial Intelligence Technology And The Price Of Admission

If your work puts you in regular contact with technology vendors, you'll have heard terms such as artificial intelligence (AI), machine learning (ML), natural language processing and computer vision before.

You'll have heard that AI/ML is the future, that the boundaries of these technologies are constantly being pushed and broadened, and that AI/ML will play an integral role in shaping this tech-forward era's most successful business models.

As a technology leader, I've heard all these claims and more. To say that AI/ML will play an increasingly impactful role in business is no overstatement. According to a recent Forbes article, the machine learning market is poised to more than quadruple in the coming years.

Many industry watchers agree that AI/ML solutions, when used to good effect, can equip your organization with a significant competitive advantage. And that makes it tempting to dive right in and start implementing these technologies without first gaining a comprehensive understanding of how they work. Accessibility to myriad options is not a barrier; almost every technology vendor now offers AI/ML services.

If anything, we are often inundated with choices in this domain. But how do we know we're making the right choices and using these services to good effect? This is where a genuine, comprehensive understanding of technology becomes critically important. For many of us, the world of AI/ML is a relatively uncharted terrain.

The answers to these fundamental questions are the keys to unlocking the true potential of AI/ML as business solutions. Current machine learning is a statistical process that employs a model/algorithm to explain a set of data and predict future outcomes. Many of these are "big data" algorithms that analyze huge quantities of data to generate predictions that are as accurate as possible.

Once we understand this, we start to see what is required to effectively use ML as a business solution. We need a lot of it, and we need it to be high quality.

Poor data quality is the biggest impediment to successfully adopting and deploying AI/ML solutions, and insufficient quantities of data can be a major hindrance as well.

Take IBM's Watson for oncology as a cautionary tale. After being trained on a small number of synthetic cancer cases, the Watson supercomputer was discovered to generate "erroneous cancer treatment advice" which ranged from incorrect to outright unsafe.

The data management process, which covers everything from data creation or acquisition to transmission and storage, is therefore intrinsically linked to AI initiatives.

When considering the cost of implementing any AI/ML solution, it's vital to also consider the cost of obtaining a robust amount of high-quality data with which to feed that solution.

Considering AI/ML Solutions In The Context Of Your Needs

Now, with a better idea of what goes into deploying AI/ML solutions, we have to consider each of our options in the context of our vision.

What do we hope to achieve by implementing AI/ML strategies?

Any AI/ML technology we implement will function within a web of our existing applications, interfaces and platforms.

So, when crafting our vision, we need to take our organization's existing technology ecosystem into consideration.

Precise goals will help us ground our vision in reality, while a more ambiguous approach may lead to equally muddled (and unsatisfactory) results.

An effective machine learning model or algorithm must, of course, continuously learn.

We won't see much success with a "set it and forget it" mentality when it comes to machine learning algorithms.

If our algorithms don't rapidly adapt to changing requirements, they quickly become irrelevant and unproductive.

It's just as imperative for an algorithm to be unbiased. Cathy O'Neil, the author of Weapons of Math Destruction, spoke to NPR about the dangers of placing blind faith in the objectiveness of ML algorithms when "we really have no idea what's happening to most algorithms under the hood."

Many of the models used today across the public and private sectors certainly suffer from the prejudices and misconceptions of their designers. In 2011, a Massachusetts man was informed his driver's license had been revoked because a facial-recognition algorithm mistook him for another Massachusetts driver who was involved in criminal activity. In a similar vein, Google's hate speech detector was reported to be racially biased.

To make the most of our AI/ML solutions, we have to invest the time and attention to governing them fairly and rigorously.

You might be excited, and reasonably so, about the seemingly boundless potential of AI/ML technology. Or maybe you subscribe to Stephen Hawking's view that the development of AI could be "the worst event in the history of our civilization." In either case, there’s no question that AI/ML technology is here to stay.

Politics and history of Nepal’s Kalapani claim

The Nepali media also backed the country's historic claim to the region, but the coverage of governments in Kathmandu without much emphasis on Nepal's rightful claim to the region has been measured with much blame.

Former Director General of Nepal Topographic Survey, Punya Prasad Oli said there was a "gentleman's agreement" between Nepal and Indian authorities to publish maps after the joint issue of border / delimitation operations and strip maps of their joint border. . After India released its map in November, Nepal was no help, but released its edition.

It was only in 1981 that the two countries formed the Nepal-India Technical Level Joint Boundary Group, which decided to locate the borders, maintain the dilapidated and missing boundary columns and freeze the areas where they were built.

As clearly stated, Nepal's position in relation to Kalapani, Lipu Lekh and Limpiyadhura is based on a map of British East India, published after the Treaty of Sougouli of 1816 - especially the British map of 1857.

Deepak Gurung needs to be educated in Nepal

On the other hand, India's position is based on a map of the British Survey of India 1857–1881 and beyond. It should be remembered that Nepal's Topographic Survey published the first map of Nepal in 1976, but the artist, Lipu Lekh and Limpiyadhura were not shown. On the other hand, Nepal maps published in textbooks during the Panchayat period contain these areas. The new political map has an appendix-like piece from the northwest corner of Nepal.

There is no other treaty that Nepal has entered into with British India, claiming that Nepal has changed its western boundary due to natural causes. Although the flow of rivers has changed in some sections of Terai following the Treaty, the status of the river is taken as a boundary at the time of the Treaty, according to international boundary principles.

An Indian argument is that British cartographers continued to move the Kashi River to the east for strategic reasons, so Nepal should accept it without question.

There are no records in Nepal to suggest that these boundaries were jointly made between the British East India Company and Nepal. There is no water on the international border crossing due to a change in the route of the mountain river. Although these changes along the river route are described in maps published by the Survey of India under British rule, they cannot be used as a reference for determining international boundaries.

Two Nepal-India allies face Alisha Sizapati

Perhaps Indian Army Chief General M.N. Narvana made a very serious statement last week, which suggested that Nepal was influenced by the 'Third Party' in bringing about the issue of artisans. It is not only in Nepal but also in India where the former Indian Ambassador to Nepal is. A-Salah said, creating a ruckus.

According to Biswabandhu Thapa, who was the Home Minister in the reign of King Mahendra in Nepal in 1962, Prime Minister Jawaharlal Nehru wrote a personal letter to King Mahendra. Ask for the Indian War.