One goal of AI work in natural language is to enable communication between people and computers without resorting to memorization of complex commands and procedures. Automatic translation – enabling scientists, business people and just plain folks to interact easily with people around the world – is another goal. Both are just part of the broad field of AI and natural language, along with the cognitive science aspect of using computers to study how humans understand language.
Retrieving information from documents and forms has long been a challenge, and even now at the time of writing, organisations are still handling significant amounts of paper forms that need to be scanned, classified and mined for specific information to enable downstream automation and efficiencies. Automating this extraction and applying intelligence is in fact a fundamental step toward digital transformation that organisations are still struggling to solve in an efficient and scalable manner. An example could be a bank that receives hundreds of kilograms of very diverse remittance forms a day that need to be processed manually by people in order to extract a few key fields. Or medicinal prescriptions need to be automated to extract the prescribed medication and quantity. Typically organisations will have built text mining and search solutions which are often tailored for a scenario, with baked in application logic, resulting in an often brittle solution that is difficult and expensive to maintain.
The future of work is remote-- at this point, this assertion could easily double as the proverbial war cry of tech's most prolific armchair experts. Undoubtedly, there's ample evidence to support their claims. Over the past decade, growth in remote work careers has ballooned to the tune of 91 percent, with nearly 5 million Americans engaging in business from the comfort of their couches. Even still, there are numerous barriers preventing this lifestyle from becoming the norm, with geographically-dispersed workforces facing seemingly insurmountable challenges of fragmentation, isolation, and miscommunication. But fear not, office dwellers-- artificial intelligence, the most buzzworthy technology trend of modern computing, offers a number of capabilities that may soon serve as the most critical infrastructure in the remote work revolution.
Word embeddings are dense vector representations of words trained from document corpora. They have become a core component of natural language processing (NLP) downstream systems because of their ability to efficiently capture semantic and syntactic relationships between words. A widely reported shortcoming of word embeddings is that they are prone to inherit stereotypical social biases exhibited in the corpora on which they are trained. The problem of how to quantify the mentioned biases is currently an active area of research, and several different fairness metrics have been proposed in the literature in the past few years. Although all metrics have a similar objective, the relationship between them is by no means clear.
Microsoft has now offered an explanation for the bug that caused Chromium-based Edge to crash when Google was set as the default search engine – but didn't crash if Microsoft's much less popular Bing was set instead. The crashes were happening when users typed in the address bar. The conditions for the crash made it appear to some that there was a skirmish playing out between Google and Microsoft on the new Edge, which ships with Bing as the default search engine and strips out many Google features that are in Chrome. At the time, Microsoft didn't explain the cause of the crashes and why it only impacted Edge with Google as the default. However, after fixing the bug it did advise users to "revert your browser settings that you may have changed" to avoid the crashes.
Amazon is working on a new feature for its Alexa voice assistant that will let the software launch Android and iOS apps using voice commands, a first for Amazon's assistant and a bold expansion of its strategy to position Alexa as a platform-agnostic alternative to Apple's Siri and Google Assistant. Called Alexa for Apps, the new feature is launching today in preview form, meaning Amazon is working with select developers on how they'd like to make use of it. For instance, Amazon imagines users on either an iPhone or an Android device asking Alexa to open Twitter and search for a hashtag, and the app would then let the companion Alexa skill do the work of launching the app and inputting the search term. The results would then show up on the phone instead of being read aloud. Another example Amazon gives is using a voice request to launch TikTok and start a hands-free video recording (in the event you're filming yourself). It's a new type of interaction Amazon is hoping could catch on and help better position Alexa as a viable competitor to digital assistants from Apple and Google, both of which are deeply baked into their respective operating systems and have richer access to apps and system-level features as a result.
A chatbot can benefit the biggest or the smallest eCommerce company. Whether you're selling clothes, shoes, makeup, electronics, art & crafts, or furniture, having a chatbot is a great investment for your store. Big brands benefit from chatbots because it allows them to engage with numerous customers in a timely and efficient manner. At the same time, small stores that cannot hire several employees can compete with bigger businesses by providing immediate service. Having a chatbot can help increase your revenue because it solves different customer problems that often lead to cart abandonment.
Take for example, the loan origination and loan servicing process in a financial institution. There are 5 key activities amongst several that if changed can fuel better productivity. So, if an AI engine is in place at activity 2, it can process customer data regarding financial history and propensity to pay etc. and flag potential defaulters or fraudsters. Similarly, AI-based chat bots can help improve customer service (activity 4) by either automating the transaction completely or offering sentiment-analysis based insights to agents for better customer experience(see Figure 1). Bringing technology in these areas will improve productivity and reduce cost and effort, validating investment.
At a time like this, the banking sector is trying its hand, leg and even head to give a head-start to the AI developments. The financial services industry is appealing to enter AI market to avail the luxury of accurate data and investment. The development assists banks with better customer service, fraud detection, reduction of managing cost and easy decision-making through AI analysis. Customers have expectations that can't be turned down. Expectations to get work done faster and with zero error. The only by-standing solution is the utilisation of AI in the everyday banking sector.
Anchor texts are hyperlinked, clickable words in the content. Working on anchor text optimization for both internal and external content can help your site get a better ranking on search engines. In 2011 and earlier, companies gained good rankings by using keyword-rich links as anchor texts. In 2012, Google released the Penguin update, which caused businesses that had exact matching keywords to suffer major slides in Google rankings. Businesses started considering the use of anchor text optimization strategies to recover the lost ground.