AI SERVICES, ARTIFICIAL INTELLIGENCE SOLUTION PROVIDER

We are Artificial Intelligence specialists, we create powerful and intelligent solutions which leverage the most up to date AI technology.

We provide solutions across a range of different services (Alexa, Facebook Messenger, Google Home, Slack, Website Integration).

We look at your business and advise where artificial intelligence can be of value, whether it be marketing, e-commerce, business support or other applications.

Google give an amazing demo of their google assistant making a phone call

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ONSTAGE AT I/O 2018 Showcasing Google Assistant

GOOGLE HAS STARTED OFF ITS ANNUAL 3 DAY I/O DEVELOPER CONFERENCE AT SHORELINE AMPHITHEATER IN MOUNTAIN VIEW, CALIFORNIA. 

In the first day, they have shown some of the amazing new capabilities of Google Assistant. One of them is being able to make phone calls on your behalf. You ask Google Assistant to make an appointment and it makes the call in the background. The demo has to be seen to be believed.

CEO Sundar Pichai played back a phone call recording that he said was placed by the Assistant to a hair salon to book an appointment.

With a voice which sounded totally natural; the person at the salon had no idea they were talking to an automated AI assistant. The Assistant even managed some small talk; dropping “mmhmmm” into the conversation.

Pichai reiterated that this was a real call using Assistant and not some staged demo. “The amazing thing is that Assistant can actually understand the nuances of conversation,” he said. “We’ve been working on this technology for many years. It’s called Google Duplex.” Pichai also made the point that Duplex was still under development and that Google plans to conduct early testing of Duplex inside Assistant this summer. Their aim is “The technology is directed towards completing specific tasks, such as scheduling certain types of appointments”

Google has a blog post with more Duplex information here which has a lot more examples of Duplex in action using different voices, for example, a really interesting one making a call to a restaurant to book a table.

Google again states that these are real-world examples.:

“While sounding natural, these and other examples are conversations between a fully automatic computer system and real businesses.”

This post also does a good job of highlighting some of the real complexities of having a conversation successfully. With many sentences having different meanings depending on the current context. In the same conversation early on the assistant also handles misinterpretation when the person called mentions a table number taken from what she has misheard. Google Assistant seems to handle this perfectly.

This looks set to be groundbreaking technology:

For users, Google Duplex is making supported tasks easier. Instead of making a phone call, the user simply interacts with the Google Assistant, and the call happens completely in the background without any user involvement.

We are looking forward to seeing more of it in summer and using the technology in our projects.

With Google also announcing their rebranding of its Google Research division to Google AI. The move shows how Google has increasingly focused R&D on natural language processing and neural networks.

It looks like Google are setting their sights on being the world’s biggest artificial intelligence (AI) company. 

Facebook has removed its pause on the app review process

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In the wake of the Cambridge Analytica scandal Facebook announced late in March that it was pausing its app review process, which meant developers were no longer able to launch new apps or chatbots on the Facebook ecosystem.
It was an abrupt halt and although temporary was not ideal for any developers planning to unleash a shiny new Facebook Messenger chatbot into the wild. We were lucky ourselves that we had got one of our own bots The Fred Whitton Challenge Chatbot live a few days earlier

True to their word the pause has only been a few weeks so its great news to hear that Facebook has re-enabled the app review process so that new chatbots can now be connected to pages and set live.

App Review is Back

Today we are re-opening our app review process. The process has changed a bit as we now require business verification for apps that need access to specialized APIs or extended Login permissions. Apps that ask for basic public profile or additional permissions, such as birthday or user friends, are not subject to business verification.

 

You can read Facebook’s official statement here.

The point has to be made however that this is a helpful reminder to not be reliant on a single platform. Particularly as Facebook has a habit of changing things. Facebook executives Campbell Brown and Adam Mosseri have also stressed the idea that publishers, at least, should not be too tied to Facebook while speaking at Recode’s Code Media conference. If users find the whole experience too unsettling then Facebooks answer is “If anyone feels that this isn’t the right platform for them, then they should not be on Facebook,” Brown told Recode.

Here at The Bot Forge its good news and we are pleased to be able to get cracking building some fantastic new bots.

The Non-Technical Guide to Popular AI Terminology

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AI Terminology Cheatsheet

Artificial Intelligence is talked about everywhere these days. In the news, media and extensively in science. We mention it a lot on our website and blog after all this technology is at the core of what we do at The Bot Forge.
You may well have encountered some of the different terminology used. But what do developers and technologists really mean when they use these terms? Having a simple understanding of some of the more frequently used terms can be useful when thinking and talking about your chatbot strategy. This AI terminology cheatsheet aims to help you understand; no technical knowledge required!

  1. Algorithm

    An algorithm is a formula for completing a task. Wikipedia states that an algorithm “is a step-by-step procedure for calculations. Algorithms are used for calculating, automated processing and data processing and provide the foundations for artificial intelligence technology.

  2. Artificial Neural Network

    Artificial Neural Networks or ANN are artificial replicas of the biological networks in our brain and are a type of machine learning. Although nowhere near as powerful as our own brains they can still perform complex tasks such as playing chess, for example AlphaZero, the game playing AI created by Google.

  3. Artificial Intelligence

    AI research and development aims to enable computers to make decisions and solve problems. The term is actually a field of computer science and is used to describe any part of AI technology of which there are 3 main distinctions (1)

  4. Autonomous

    Autonomy is the ability to act independently so software which can complete tasks on its own is autonomous for example systems which manage self-driving cars.

  5. Big Data

    Big data describes the large volume of data – both structured and unstructured – that floods through a business and its processes on a day-to-day basis. In the context of AI big data is the fuel which is processed to provide inputs for surfacing patterns and making predictions.

  6. Chatbots

    I think we have mentioned these once or twice! A chatbot is a conversational interface powered by AI and specifically NLP. They can be text-based, living in apps such as Facebook Messenger or their interface can use voice-enabled technology such as Amazon Alexa.

  7. Cognitive

    Cognitive computing mimics the way the human brain thinks by making use of machine learning techniques. As researchers move closer towards transformative artificial intelligence, cognitive will become increasingly relevant.

  8. Deep Learning

    Also known as a deep neural network, deep learning uses algorithms to understand data and datasets. Deep Learning is a subfield of machine learning concerned with algorithms inspired by the structure and function of the brain called artificial neural networks. Deep Learning techniques have become popular in solving traditional Natural Language Processing problems like Sentiment Analysis.

  9. Entity and Entity Extraction

    Entities are also sometimes referred to as slots. An entity is used for extracting parameter values from natural language inputs. Any important data you want to get from a user’s request will have a corresponding entity.  Entity extraction techniques are used to identify and extract different entities: Regex extraction, Dictionary extraction, complex pattern-based extraction or statistical extraction. For example, if asked for your favourite colour you would reply “my favourite colour is red”. Dictionary extraction would be used to extract the red for the colour entity.

  10. Intelligent Personal Assistants

    This term is often used to describe voice-activated assistants which perform tasks for us such as Amazon Alexa, Google Assistant, Siri etc instead of text-based chatbots.

  11. Intent

    An intent represents a mapping between what a user says and what action should be taken by your chatbot. A good rule of thumb is to have An intent is often named after the action completed for example UserProvidedColor.

  12. Machine Learning

    Probably used by you every day in Google search for example or Facebooks image recognition. Machine learning allows software packages to be more accurate in predicting an outcome without being explicitly programmed. Machine learning algorithms take input data and use statistical analysis to predict an outcome within a given range. Machine learning methods include pattern recognition, natural language processing and data mining.

  13. Natural Language Processing

    Natural language processing (NLP) enables machines to understand human language. Machine learning is used to find patterns within large sets of language data sets in order to recognise natural language and aid machines in understanding sentiment so that they can respond correctly.

  14. Sentiment Analysis.

    Sentiment Analysis is the process of determining whether a piece of writing is positive, negative or neutral or more advanced analysis would look at emotional states such as “angry”, “sad”, and “happy”.

  15. Utterance

    An utterance is anything the user says via text or speech. For example, if a user types “what is my favourite colour”, the entire sentence is the utterance.

We hope you have found this AI Terminology Cheatsheet helpful. If you want to talk about your chatbot project contact us at The Bot Forge

Comment if you think I’ve missed any terms out which should be on the cheatsheet