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Virtual Assistants - Alexa, Siri, Google Assistant

Artificial intelligence is a term we’ve begun to end up being particularly familiar with. At the point when secured inside your most adored sci-fi film, AI is at present a real, living, powerhouse of its own. Conversational AI is responsible for the basis behind the bots you fabricate. It’s the cerebrum and soul of the chatbot. It’s what empowers the bot to convey your customers to a specific goal. Without conversational AI, your bot is just a ton of requests and replies.

Virtual Assistant

A virtual assistant is an application program that comprehends common language voice directions and finishes assignments for the client.
Such undertakings are generally performed by an individual aide or secretary, incorporate taking transcription, understanding the content or email messages so anyone might hear, looking into telephone numbers, booking, putting telephone calls and reminding the end client about arrangements. Prevalent virtual assistants right now incorporate Amazon Alexa, Apple’s Siri, etc.

Virtual Assistants

Virtual assistant capacities

Virtual assistants regularly perform straightforward occupations for end clients, for example, adding undertakings to a schedule; giving data that would typically be looked in an internet browser; or controlling and checking the status of brilliant home gadgets, including lights, cameras, and indoor regulators.

Clients additionally task virtual assistants to make and get telephone calls, make instant messages, get headings, hear news and climate forecasts, discover inns or eateries, check flight reservations, hear music, or mess around.

AMAZON ALEXA

Amazon Alexa is fit for voice collaboration, music playback, making arrangements for the afternoon, setting alerts, spilling web accounts, playing book chronicles, and giving atmosphere, traffic, sports, and other progressing information, for instance, news. Alexa can in like manner control a couple of splendid contraptions using itself as a home computerization system. Customers can widen the Alexa limits by presenting “aptitudes” (additional value made by outcast dealers, in various settings even more normally called applications, for instance, atmosphere ventures and sound features).

Most devices with Alexa empower customers to start the device using a wake-word, (for instance, Alexa); various contraptions, (for instance, the Amazon adaptable application on iOS or Android and Amazon Dash Wand) require the customer to push a catch to activate Alexa’s listening mode. Starting at now, association and correspondence with Alexa are open just in English, German, French, Italian, Spanish[4], Portuguese, Japanese, and Hindi. In Canada, Alexa is open in English and French (with the Québec complement.

Alexa

SIRI

Siri is a virtual assistant that is a piece of Apple Inc’s. iOS, iPadOS, watchOS, macOS, tvOS and audioOS working systems. The associate uses voice inquiries and a characteristic language UI to respond to questions, make suggestions, and perform activities by assigning solicitations to a lot of Internet administrations. The product adjusts to clients’ individual language uses, searches, and inclinations, with proceeding with use. Returned results are individualized.

GOOGLE ASSISTANT

Google Assistant is a man-made thinking fueled remote helper made by Google that is available on adaptable and splendid home devices. Rather than the association’s past remote helper, Google Now, the Google Assistant can participate in two-way dialogs.

Teammate from the outset showed up in May 2016 as a significant part of Google’s advising application Allo, and its voice-started speaker Google Home. After a period of particularity on the Pixel and Pixel XL PDAs, it began to be passed on other Android devices in February 2017, including outcast mobile phones and Android Wear (by and by Wear OS), and was released as an autonomous application on the iOS working system in May 2017. Close by the announcement of an item improvement unit in April 2017, the Assistant has been and is when in doubt, further connected with assistance a gigantic variety of contraptions, including vehicles and pariah quick home machines. The helpfulness of the Assistant can in like manner be improved by outcast planners.

Comparision

Amazon Alexa, Apple Siri, and Google Assistant are for the most part showing signs of improvement at understanding and responding to questions, thanks to a limited extent to each tech mammoth utilizing people to help improve their AI. Given that voice is intended to be the following outskirts of PC interfaces, financial specialist investigators like Loup Ventures are quick to comprehend which organization has the best interface for voice input.

Straightforward ordinary undertakings

Every one of the three collaborators handle fundamental errands like setting updates and cautions, processing maths issues, and furnishing climate figures without any difficulty. While Google Assistant and Siri can call and send instant messages to anybody in your contact list, Alexa can just contact individuals who have pursued Alexa calling/informing. Siri can place calls just as send instant messages through WhatsApp. Google Assistant can send instant messages and voice messages using WhatsApp yet just when utilized on an Android cell phone. Alexa in correlation can’t incorporate with WhatsApp in any capacity

With regard to changing gadget settings, Google Assistant and Siri are in front of Alexa. On the two iOS and Android, Google Assistant effectively turned on the electric lamp yet neglected to turn on portable information. Siri figured out how to do the accurate inverse and Alexa in correlation expressed “You don’t have any savvy home gadgets to begin” in the two cases.

Incidental data questions

Google Assistant has Google’s incredible inquiry innovation available to its, it was not amazing to see it answer the most questions precisely. Regardless of which stage we utilized it on, Assistant gave the most exact and inside and out data. It gave extra connections just as a source site for the data given.

We were truly intrigued to see Google Assistant effectively answer specialty addresses like “What sort of fish is Dory in Finding Dory?” Siri, in correlation, just kicked us to a Web search in the two cases. Alexa essentially expressed she doesn’t have the foggiest idea about the appropriate response in the last mentioned and chose to give us insights concerning Pixar’s vivified film in the previous.

Complex errands

Every one of the three colleagues is fit for recommending eateries dependent on cooking just like area. While every one of the three was effectively ready to recommend great Chinese cafés around our office, just Google Assistant figured out how to discover spots serving lasagna close by. Google Assistant additionally offers to book a table at a close-by eatery when you disclose to it that you’re’ eager. It even gives a choice to put in a request utilizing Swiggy and view bearings through Google Maps.

Both Siri and Alexa use Zomato’s database to grandstand an eatery’s location, operational hours, and client audits. Every one of the three collaborators likewise enables you to call eateries from inside the query item. Google’s Assistants’ usefulness can likewise be broadened through ‘Activities’.

Setting mindfulness

Google Assistant is unmistakably more conversational and setting mindful than the other two. You would then be able to take things up a score and ask “How tall is he” or “Where is he from”, and Google Assistant comprehends that you’re alluding to a similar individual and reacts as needs are. Alexa in correlation expressed the name of the mentor effectively yet battled to respond to any further questions. Siri bombed after only one inquiry, getting the name of the lead trainer of the University of Iowa Hawkeyes men’s ball group rather than Manchester City’s mentor.

Analytical conclusion

Google Assistant is without a doubt the most balanced virtual assistant. It may have less style than the other two (It can’t sing tunes like Alexa, for instance) yet it is the most helpful right now, particularly in the India setting. Not exclusively does Google Assistant answer the most questions accurately, it is additionally increasingly conversational and setting mindful. With Alexa and Siri, it is critical to get the direction without flaws to summon the necessary reaction. Google Assistant in the examination, is truly adept at understanding regular language.

Alexa is the most customizable associate of the bundle. Aptitudes enable outsider applications to add a great deal of usefulness to Alexa. While Google Virtual Assistant offers comparable component development using activities, the quality and amount of aptitudes offered by Alexa are prevalent. All things considered, Alexa’s center capacities need spit and clean right now and it can’t be activated by voice when setting as the default colleague, something Microsoft’s Cortana can do regardless of not being local to Google’s versatile stage.

Siri has unquestionably improved throughout the years yet at the same time falls behind Alexa and Google Assistant as far as capacities. In our testing, Siri battled with café proposals, area explicit inquiries, and popular culture questions. It additionally neglected to get set. So, Siri’s interface is anything but difficult to utilize and it works admirably with everyday undertakings.

Development of artificial intelligence - a brief history | Blog | Bridged.co

The Three Laws of Robotics — Handbook of Robotics, 56th Edition, 2058 A.D.
1. First Law — A robot may not injure a human being or, through inaction, allow a human being to come to harm.
2. Second Law — A robot must obey the orders given it by human beings except where such orders would conflict with the First Law.
3. Third Law — A robot must protect its own existence as long as such protection does not conflict with the First or Second Laws.

Ever since Isaac Asimov penned down these fictional rules governing the behavior of intelligent robots — in 1942 — humanity has become fixated with the idea of making intelligent machines. After British mathematician Alan Turing devised the Turing Test as a benchmark for machines to be considered sufficiently smart, the term artificial intelligence was coined in 1956 at a summer conference in Dartmouth University, USA for the first time. Prominent scientists and researchers debated the best approaches to creating AI, favoring one that begins by teaching a computer the rules governing human behavior — using reason and logic to process available information.

There was plenty of hype and excitement about AI and several countries started funding research as well. Two decades in, the progress made did not deliver on the initial enthusiasm or have a major real-world implementation. Millions had been spent with nothing to show for it, and the promise of AI failed to become anything more substantial than programs learning to play chess and checkers. Funding for AI research was cut down heavily, and we had what was called an AI Winter which stalled further breakthroughs for several years.

Gary Kasparov vs IBM Deep blue | Blog | Bridged.co

Programmers then focused on smaller specialized tasks for AI to learn to solve. The reduced scale of ambition brought success back to the field. Researchers stopped trying to build artificial general intelligence that would implement human learning techniques and focused on solving particular problems. In 1997, for example, IBM supercomputer Deep Blue played and won against the then world chess champion Gary Kasparov. The achievement was still met with caution, as it showcased success only in a highly specialized problem with clear rules using more or less just a smart search algorithm.

The turn of the century changed the AI status quo for the better. A fundamental shift in approach was brought in that moved away from pre-programming a computer with rules of intelligent behavior, to training a computer to recognize patterns and relationships in data — machine learning. Taking inspiration from the latest research in human cognition and functioning of the brain, neural network algorithms were developed which used several ‘nodes’ that process information similar to how neurons do. These networks have multiple layers of nodes (deep nodes and surface nodes) for different complexities, hence the term deep learning.

Representation of neural networks | Blog | Bridged.co

Different types of machine learning approaches were developed at this time:

Supervised Learning uses training data which is correctly labeled to teach relationships between given input variables and the preferred output.

Unsupervised Learning doesn’t have a training data set but can be used to detect repetitive patterns and styles.

Reinforcement Learning encourages trial-and-error learning by rewarding and punishing respectively for preferred and undesired results.

Along with better-written algorithms, several other factors helped accelerate progress:

Exponential improvements in computing capability with the development of Graphical Processing Units (GPUs) and Tensor Processing Units have reduced training times and enabled implementation of more complex algorithms.

Data repositories for AI systems | Blog | Bridged.co

The availability of massive amounts of data today has also contributed to sharpening machine learning algorithms. The first significant phase of data creation happened with the spread of the internet, with large scale creation of documents and transactions. The next big leap was with the universal adoption of smartphones generating tons of disorganized data — images, music, videos, and docs. We have another phase of data explosion today with cloud networks and smart devices constantly collecting and storing digital information. With so much data available to train neural networks on potential scores of use-cases, significant milestones can be surpassed, and we are now witnessing the result of decades of optimistic strides.

  • Google has built autonomous cars.
  • Microsoft used machine learning to capture human movement in the development of Kinect for Xbox 360.
  • IBM’s Watson defeated previous winners on the television show Jeopardy! where contestants need to come up with general knowledge questions based on given clues.
  • Apple’s Siri, Amazon’s Alexa, Google Voice Assistant, Microsoft’s Cortana, etc. are well-equipped conversational AI assistants that process language and perform tasks based on voice commands.
Developments in AI | Blog | Bridged.co
  • AI is becoming capable of learning from scratch the best strategies and gameplay to defeat human players in multiple games — Chinese board game Go by Google DeepMind’s AlphaGo, computer game DotA 2 by OpenAI are two prolific instances.
  • Alibaba language processing AI outscored top contestants in a reading and comprehension test conducted by Stanford University.
  • And most recently, Google Duplex has learned to use human-sounding speech almost flawlessly to make appointments over the phone for the user.
  • We have even created a Chatbot (called Eugene Goostman) that passed the Turing Test, 64 years after it was first proposed.

All the above examples are path-breaking in each field, but they also show the kind of specialized results that we have managed to attain. In addition, such achievements were realized only by organizations which have access to the best resources — finance, talent, hardware, and data. Building a humanoid bot which can be taught any task using a general artificial intelligence algorithm is still some distance away, but we are taking the right steps in that direction.

Bridged's service offerings | Blog | Bridged.co

Bridged is helping companies realize their dream of developing AI bots and apps by taking care of their training data requirements. We create curated data sets to train machine learning algorithms for various purposes — Self-driving Cars, Facial Recognition, Agri-tech, Chatbots, Customer Service bots, Virtual Assistants, NLP and more.


NLP in AI and the realization of futuristic robots

How a well-trained conversational AI can empower your business

When the most valuable asset in the world is data, the most powerful tool you can have is the ability to process exabytes of information that data has to offer, and productively so. As we begin to produce gigabytes of digital data every day, De Toekomst — The Future — is with those that can effectively utilize this space, or more appropriately, the cloud. And it is precisely here that Artificial Intelligence is making its mark.

While we have only recently begun making meaningful strides in AI, its application has encompassed a wide spread of areas and impressive use-cases. And the sphere where AI is making its presence felt like a real and tangible entity is when it has a voice of its own. Natural Language Processing (NLP) and its variants Natural Language Understanding (NLU) and Natural Language Generation (NLG) are processes which teach human language to computers. They can then use their understanding of our language to interact with us without the need for a machine language intermediary.

AI has grown to become our personal assistant helping us with tasks at our behest, literally. Apple’s Siri, Amazon’s Alexa, Microsoft’s Cortana and Google Voice Assistant are only a few examples of AI systems integrating themselves seamlessly into our daily lives and routine. They help us plan our schedules, carry out functions without us having to push a single button, inform us of the latest developments, all the while learning more about our preferences and customizing themselves for us just by listening. With our permission, AI can become our best help.

Leading voice assistants | Blog | Bridged.co

How businesses are leveraging the AI assistant

Equipped with the knowledge of human communication, AI bots can potentially be used in any field that involves language to derive fast, intelligent, and useful insights which can then be transformed into follow-up actions tailored for each customer. Companies have realized the benefits of this incredibly powerful service and have begun utilizing them to gain significant market advantages. We will now talk about a few major applications of the conversational AI, and how we at Bridged are helping companies realize their ambitions for the AI-driven future.

Voice Control and Assistance

Voice control and assistance | Blog | Bridged.co

Performing basic tasks — reading messages, checking notifications, news updates, changing settings, operating connected devices, speech-to-text services.

Planning and Scheduling — setting up meetings, calendar events, automated replies, navigation, online assistance, payments.

Personalization and Security — compiling playlists, product suggestions, mood-based ambiance control, surveillance, and security.

Bridged.co Services: Voice Recognition, Speech Synthesis, Search Relevance.

Chat-bots

Chatbots training | Blog | Bridged.co

An ever-present agent ready to listen to your needs complaints and thoughts, and respond appropriately and automatically in a timely fashion is an asset that finds application in many places — virtual agents, friendly therapists, automated agents for companies, and more.

Bridged.co Services: Chat-bot Training, Virtual Assistant Training, NLP.

Sentiment Analysis

Sentiment analysis | Blog | Bridged.co

The ability to monitor end-user opinions of a brand or product and gain an understanding of the same on a large scale is clutch in any competitive scenario. Customer retention has become a zero-sum game and sentiment analysis stands at the center of this marketing field. Armed with NLP and machine learning, AI can listen to the scores of available user opinions across multiple platforms be it social media or community forums or even personal blogs. Accurate analyses of brand value at scale provided by accurate AI are invaluable to businesses.

Bridged.co Services: Brand Sentiment Analysis, E-commerce Recommendations, User Content Support.

Customer Service

Customer service | Blog | Bridged.co

AI is revolutionizing customer service, catering to customers by providing tailored individual resolutions as well as enhancing the human service agent capability through profiling and suggesting proven solutions. AI can be put up to a) responding to common queries, b) as a first layer of gathering service request info and routine troubleshooting, c) integrating with the resolution system, learning from successful cases, and suggesting or implementing final calls. AI makes the whole system faster and more efficient.

Bridged.co Services: Chat-bot Training, Sentiment Analysis, User Content Support.

Translate languages as you speak

The need for a multi-language translation book or for a local guide to communicating your need in a tongue you don’t speak is reduced with the advent of live translation by conversation bots that speak your message out loud, as and when you call on them right from your phones and smart devices.

Bridged.co Services: NLP, Voice Recognition, Speech Analysis.

Real-time Transcription

You can count on AI to take down notes for when you are in meetings or need to parse audio or video clips, or just want to pen down your thoughts. Transcription of speech to text is a very common application and finds use in several business tasks.

Bridged.co Services: Audio/Video Transcription, NLP, Voice Recognition.

We are at a very exciting juncture in the development of AI technology. New machine learning techniques including deep learning applied to NLP processes have made it possible to stretch the boundaries of what can be built using AI bots.