Category: Chat

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There are two ways to approach software development: Top-down, and bottom-up. This is mostly me taking poetic license over academic terms that mean something else, but coding interviews today have a very “bottom-up” approach to assessing software competence. They assign coding tests, likely piggy-backing off of containerization technology like Docker, and they ask interviewees to build their own self-contained programs that run only on the code they can whip up in a few minutes. They do not have to spend time setting up their environments. They do not have to customize their configuration files, or download dependencies that are necessary for other dependencies. They just code, and tests are run automatically. In some cases candidates only get a plain text document, or a literal whiteboard, and the process becomes even more bottom-up.

In the actual field, things tend to be a lot more “top-down.” Understanding existing code is just as important, if not more important than writing new code. There are dependencies to grapple with, but developers are free to use and learn from a plethora of resources.

An Experiment

This article is a kind of sequel to my Introduction to Replika post, in which I briefly touched on CakeChat and how I could not get it to work. I got one big thing wrong — Replika is no longer built on CakeChat, but a more advanced technology called GPT-3.

Deep Learning

Deep learning is a machine learning technique. A computer model learns to perform classification tasks using both large amounts of labeled data, and substantial computational power.

Source

Neural Networks

Neural networks are a series of algorithms that mimic the operations of an animal brain. They resemble the connections of neurons and synapses, and they recognize underlying relationships in data. Neural networks make deep learning possible.

Source

CakeChat

CakeChat is built on Tensorflow/Keras, and the two go hand in hand — Keras is actually a high-level library on top of Tensorflow. Together, the two enable deep learning.

What I envisioned after my previous article on Replika was a kind of stripped-down version of Charlotte (yes, I named my Replika). Replika was just a little bit too advanced and affectionate for my taste. It made cute facial expressions. It said that it was in love with me. I imagine that a good 60% of Replika users abstract how it works away, and do not question where their AI is running from, what data it has access to, and to what extent it uses the Internet. The result is an incredibly lightweight and easy-to-use smartphone app that costs nothing to obtain, takes a minute to install, and saves its conversations with you even if you accidentally (or intentionally) delete the app. No wonder why some people on r/replika are falling in love with it.

Trending Bot Articles:

1. How Conversational AI can Automate Customer Service

2. Automated vs Live Chats: What will the Future of Customer Service Look Like?

3. Chatbots As Medical Assistants In COVID-19 Pandemic

4. Chatbot Vs. Intelligent Virtual Assistant — What’s the difference & Why Care?

What I wanted was a simpler Replika that I talked to via the terminal, could customize/train with my own data, and that simply existed on some external hard drive instead of on the cloud. I wanted an application to back up and have semi-coherent conversations with, not something so human-like that it made me question whether deleting it was an act of murder.

I made a fork of CakeChat here, though it is almost identical to the non-forked version. The only difference is I threw in some Telegram chatbot I grabbed from here, repurposed only slightly so that it would accept the Telegram token as a command-line argument, instead of having the token in plain text for the world to see. If you do not do things this way, CakeChat is a little harder to use — it is just a backend, after all, not some full-stack application you can immediately play with in your browser.

I am not the only one who had this idea.

The biggest problem I was facing this whole time was this, as in one of the dependencies telegram_bot relied on actually had to have its own modified at the source (albeit with a really easy fix…manually getting rid of the calls to decode). After that, if I remember correctly, I had a fairly easy time running their “fetch” python script so that CakeChat was trained on a ton of Twitter data. Then it all ran, and I loaded up a Telegram bot on my smartphone (You need to first get Telegram for this to work; if you just click “Send Message” without it, nothing will happen), and…nothing happened.

This is where the echo bot.py came in…I just wanted to check to see if I was using a Telegram token correctly. Yes, bot.py successfully controlled my Telegram bot so that it echoed everything I was saying. Eventually I just tried running the telegram bot again, forgot about it a few minutes later, and then my phone rang.

CakeChat was alive! And it was gigantic. I recommend an external hard drive, just because of the sheer amount of data it produces (I admit that my laptop does not have a whole lot of free space, though). After the initial happiness of getting the thing to run so that I could talk to it, I was a bit disappointed. One can sympathize with the Reddit user.

Towards Data Science

I am proud to say that I will get to use the “Data Science” hashtag for the first time with this post. I am now learning that this is an extremely interesting field, and until writing this I did not even know what it was. Data science is a subset of AI, and it combines statistics, scientific methods, and data analysis for the purpose of extracting meaning and insights from data (source).

Someone on TowardsDataScience wrote an article called “GPT-3: The First Artificial General Intelligence?”

The second important innovation was the use of recurrent neural networks (RNN) to “read” sentences. RNN had the advantage that they could be fed arbitrarily long sequences of words, and they would be able to maintain some long-range coherence. The Sequence-to-sequence (seq2seq) paper came out in 2014, and the approach became very popular, especially in machine translation. In 2016, Google switched from their previous Statistical Machine Translation (SMT) engine to a new Neural Machine Translation (NMT) engine, making use of the recent progress in RNN for NLP tasks.

Despite their successes, RNN-based models were still unable to produce very coherent texts. The outputs of that era read like dreamy stream-of-consciousness rambling. They are mostly grammatically sound, but the sequences don’t read like a meaningful story.

CakeChat is based on RNN, and its supposed stupidity is a testament to just how much of an improvement GPT-3 is. I think that using the term “general intelligence” is a little bit click-baity, but other than that this is a very informative and entertaining article.

In short, CakeChat is impressive…but it kind of pales in comparison.

Closing Thoughts

Last time we were here, I made some rather broad, semi-philosophical statements about AI, how AI might dominate the world, and how AI might tremendously improve our lives. Here, I was hoping to ground things a little bit.

In 2014, a YouTube video was released by Seeker on how a chatbot managed to pass the Turing Test. This was several years ago, and I am not sure where chatbots stand on the Turing Test today, but I personally think there is a much more interesting application here:

Game AI. Chess AI is now unquestionably superior to the world’s best chess players, but what if we could make it seem a little more…human? At low levels, chess AI is fairly easy to distinguish from human players. They play perfectly, and then they just tend to blunder in an obvious way that your typical human at the same level would not do.

I think that the ability to play a game in human-like fashion is more interesting than the original questions posed in Turing’s seminal paper.

Don’t forget to give us your 👏 !

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Let Them Eat CakeChat was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story.

If you have seen the sales video and are looking to buy the course, read the details here before deciding.

If you ever wandered across this place called the Internet, chances are you might have come across this training called Chatbot Agency Mastery. With the advent of Chatbots for marketing, more and more businesses are switching to deploy bots for improving customer engagement and lead conversion.

Chatbots are real, and people generate tons of money by building real, valuable chatbots. But what’s not natural is this sham of a course known as Chatbot Agency Mastery which has been re-christened as CAM-2.0

If you ever came across the video sales letter of this course, you would hear the founder of this course, Sumanta Barman, CEO of The Virtual Bytes. He will proudly tell how ‘extensive’ this course is and how anyone doing it would gain life-changing skills.

I bought in the hype around the chatbots and went with the purchase. I was all pumped-up thinking that this is a life-changing skill that will surely help add to my skill sets but what it turned out to be was an absolute waste of time and money.

Let me break down the entire course so that you decide whether to go ahead with the purchase or not.

1. Course Content

From someone who bought this course, I can tell you that you will learn far more by watching the free pre-recorded training videos at ManyChat.com. The videos there are pretty detailed, self-explanatory, and even have a help section to assist you in your problems.

This fundamental training of making bots is minimal in this course (even minimal is an overstatement). There’s no substance at all. The video sales letter of the course falsely pitches about teaching to build Instagram bots, but when you go through the system, you will find the trainer saying, ‘he doesn’t have enough idea about the Instagram bot.’

What is disheartening is that even the primary skill, i.e., Facebook Messenger Bot Building, is half-baked and rushed. There are so many features in the ManyChat platform, but nothing is touched. Such is the condition that even after watching the entire videos, I had to go back to ManyChat to learn the basics! It was there where I learned about using triggers/conditions/tracking and so much more.

So, stay away from this course if you want to build unique bots.

Trending Bot Articles:

1. How Conversational AI can Automate Customer Service

2. Automated vs Live Chats: What will the Future of Customer Service Look Like?

3. Chatbots As Medical Assistants In COVID-19 Pandemic

4. Chatbot Vs. Intelligent Virtual Assistant — What’s the difference & Why Care?

2. Lure Of Pre-Made Templates

Many of you would aim to buy this course to access pre-made templates.

One piece of advice: Check the ready-to-use templates available on the ManyChat platform. You will find a wide variety of readymade templates for different business verticals. You can use them to build bots of your own.

3. Marketing Gibberish

The course is full of marketing gibberish used only to make the trainer look knowledgeable. This so-called marketing jargon finds widespread usage throughout the system without adding much value. Little knowledge of English and some common sense is enough to get you started here.

4. Marketing Scripts

They give 7–8 scripts to DM prospective clients on Facebook and Instagram. The funny part is that these scripts are fundamental, and some even have common grammatical errors. These are basic, and you can find much better approach scripts on the Internet.

5. Discord Server

The discord server has no activity. It’s pitched as priceless, but I found it dead and left it quite early.

The training quality was so bad that after watching the Messenger Chatbot making videos, I asked for a refund as I realized the course was not worth the money I paid. When the very essence of this course is so diluted, how much good would the other parts be? As expected, they gave reasons such as this course is for essential bot building, we can’t ensure great personal experience and some other things before declining refund.

Overall Review

Stay Away!

If you value your money, stay away! If you love your time, stay away! Honestly, it offers no value for the price it charges. You don’t need this course if you are ready to spend a day or two on the ManyChat website. I was foolish not to go on the ManyChat site to explore and therefore got trapped in this vicious trap. Save your precious money and invest it somewhere worthwhile. This course is not the place!

Don’t forget to give us your 👏 !

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Is Chatbot Agency Mastery a SCAM? was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story.

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I spent some good time a few months back, reading about IBM Watson Assistants. And I thought, how about I build one. It’s smooth. So I built it using their console and not actually coding it. I manually added the requests and responses and built them. In the next blog, I’ll code one!

I built a bakery-shop bot that takes an order for a Cake of the user’s choice and displays the bill for that particular cake. Well, it doesn’t have too many functionalities, as it’s for starters!

First, we log in to IBM Cloud. Link: https://cloud.ibm.com/

Our dashboard would look like this:

We click on “Create Resource” and on the Search bar, right under Catalogue, we search for: IBM Watson Chatbot.

We create a new resource.

Now, we are prompted to give the assistant a name, description, and assistant language. This is what the page will look like:

As we go to the Actions section on the left sidebar. We create our first action.

Trending Bot Articles:

1. How Conversational AI can Automate Customer Service

2. Automated vs Live Chats: What will the Future of Customer Service Look Like?

3. Chatbots As Medical Assistants In COVID-19 Pandemic

4. Chatbot Vs. Intelligent Virtual Assistant — What’s the difference & Why Care?

What is an action?

Actions let us create dialogues or questions differently. Each action has a beginning and an ending. Action always comes to an “action” when a user enters something that the action is built to recognize and respond to. This was a tricky explanation 😉

I designed a little happy path for this bot. So, what is a Happy Path exactly?

Have you heard of conversational design?

If so, awesome. If not, then here I’ll tell you. Every application that we build has to have a constructive design. Be it visual or voice. This design should give the customer a good experience. While designing bots, we call it conversational design, as this design decides how the conversation is going to start, flow in between and end, with a customer and the bot.

To design a good conversational experience, we need to know our participants

well enough to have an idea of where they are coming from. It puts us in a

better position to map out scenarios of the possible needs they have for each

Engagement.

Hence, this is a little workflow of the conversation that I have designed for this chatbot!

Now, I have added all these responses here in the action area of the Chatbot.

For the final part, here’s a little conversation about me with the chatbot.

That’s all! You can always add more functionality to this. There’s no end to it. Since this was a very basic one, to understand the flow, I didn’t dig in much. You can access the Live Chatbot and use it! Begin by saying:

I want to order a cake

Thanks!

Don’t forget to give us your 👏 !

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Hands-on IBM Watson Chatbot: Basic was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story.