Artificial Intelligence and Influencer Marketing — Rise of the Virtual Influencers
Today, data, analytics, and algorithms are the cornerstone of modern marketing. Within the marketing industry, influencer marketing has become a glamorous yet effective way to improve brand awareness and increase revenue.
According to statista.com, “The popularity of influencer marketing worldwide is growing at such a high speed that the global market size is expected to reach 22.2 billion U.S. dollars by 2025”
Influencer marketing is the process through which a company works with an online influencer to promote one of its goods or services.
Artificial Intelligence (AI) has changed the game for influencer marketing.
Artificial intelligence tools can assist you in avoiding influencer fraud by thoroughly examining an influencer’s profile and identifying any red flags.
Marketers can assess whether the followers of an influencer fit the profile of their target audience using AI and machine learning.
AI can search through millions of topics each day to discover which ones are being discussed by actual people
Chatbots as Influencers — Virtual Influencers
Bot Libre chatbots, through its diverse and dynamic features , are able to respond to a large group of people, in a small amount of time and in a more human way. This makes them an incredible asset to business marketing.
The idea of an influencer chatbot is not new, as 2021 reports shared that an influencer chatbot created for the US brand CoverGirl, which was hosted on the messenger app was able to bring in 14 times better conversion rates. Other influencer bots developed include Lil Miquela an AI-generated influencer who counts Prada as one of her clients, and Knox Frost, who was a major influencer bot for the World Health Organisation (WHO) during the height of the pandemic.
Bot Libre is a free, open-source platform where especially small and medium-sized companies can create their own chatbots and AI solutions suitable for the web, mobile apps, social media, gaming, and the metaverse.
Here are some benefits of building your own bot influencer with Bot Libre:
Chatbots are active 24/7 and unaffected by time zone
Boost customer service quality
Able to reach multiple users
Chatbots can effectively collect, analyze and properly use customer data
Chatbots can be easily customized to fit the audience
Bots can quickly and comprehensively customize content based on online engagement.
The data speaks for itself, influencer marketing is one of the top contributors to a business ROI, and with chatbots and AI, influencer marketing can become more targeted, scalable, and affordable.
If you are interested in building your own influencer marketing solution with the use of AI, send an email to sales@botlibre.com.
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Artificial Intelligence & The Retail Industry — Dynamic and Inclusive
Consumers are constantly seeking a more diverse and dynamic shopping experience that offers personalized products and services, and while the internet has already made this more possible, there is still much to be accomplished and enjoyed.
This is where artificial intelligence (AI) comes in. Global AI revenue is expected to increase from $643.7 million in 2016 to more than $36.8 billion in 2025, according to marketing research firm Tractica. Therefore making AI solutions part of your business retail strategy promises to be advantageous to client and revenue growth.
Bot Libre, through its open source and business platform, offers expert and personalized artificial intelligence solutions to various small and medium-sized companies in the retail industry.
Some interesting Bot Libre AI features include:
Easy 10-Click Building Process (little to no programming involved)
Speech / 3D / Metaverse Avatars
Multilingual
Social Media Integration
Consultation
Personalized Development Services
Benefits
Improved Efficiency
AI can be a gamechanger in optimizing the operations of a retail business as the software can act as a sales assistant, shorten cashier lines for customers by accepting money pay, refill inventory through real-time stock monitoring, and create digital storefronts and personalized virtual spaces to shop and try items.
Informed Customer Targeting
Retail artificial intelligence technologies can provide customers with a tailored shopping experience. Technologies like fingerprint and face recognition can recognize returning clients and keep track of their preferences. They can therefore suggest products and create campaigns for them.
Inclusivity
AI solutions, particularly through the metaverse, will provide increased accessibility to persons with a disability, allowing them to have a safer and more enjoyable shopping experience. It might also make accessibility features (such as sound direction and level, contrast, caption size, and menu navigation) customizable.
With AI, the possibilities are endless. If you are an AI, chatbot and metaverse enthusiast looking to build your business in the retail industry. Then send us an email for a free discovery call and an explainer on our development services.
Email: sales@botlibre.com
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From writing amazing job descriptions to scheduling interviews, personalized communications, and many more to add, today’s hiring software is brimming with unique features to streamline and simplify the recruitment process.
Though, with an untold number of solutions available in the market, picking up the right hiring software that caters to your business needs can be a real challenge.
Especially finding and hiring the best talent nowadays without ATS can make the entire recruitment process forlorn. But, purchasing an ATS (Applicant Tracking System) is one big step in the right direction to hiring the best employees for your organization.
After all, these solutions offer advantages, most of which are beneficial for hiring and crafting an excellent candidate’s experience. A handful of the advantages are listed here:
Minimized time and cost-to-hire
Maximized efficiencies
Streamlined communication
Improved quality of hire
Therefore, it’s rightly said, “The right ATS can exceptionally improve your hiring process”.
But how do you choose a recruiting solution that fits your business needs and also consider the candidate’s and hiring manager’s experience?
I understand that many ATS share the same functionalities and features, so it’s important for you to pick an ATS that goes beyond just storing candidate information.
Ready to learn more? Let’s look at the 8 features your applicant tracking system should have.
8 Must-have technical features to look for in a hiring software
Centralisation — All at one place
Swapping between endless spreadsheets, career sites, job portals, job descriptions, and outreach, managing candidates is a labor-oriented task — the leg work to be done before the interview stage.
This is one of the reasons why recruiters and HRs are opting for applicant tracking systems — to centralize their efforts.
Centralization allows you to keep everything related to the candidate in one place — making it a lot easier to create precise workflows which consist of everything from candidate profiles, interviews, profiles, communication, feedback, and all other essential details as organized.
Analytics, reporting, and dashboard
When almost everything about recruiting is fast-paced, staying proactive when sourcing and hiring the right talent is a must.
But, without the important insights needed to make informed decisions, you could bear high costs with minimum ROI.
This is where data comes in the big picture.
ATS reporting and analytics features help hire teams better understand their talent pipeline while focusing on diversity recruiting and tracking hiring progress — all in one place. Besides, you can access a dashboard to collect, store, and present data when strategizing recruitment or making any amendments to your hiring process.
Candidate sourcing
It’s never enough to post job openings on job portals or solely depend on LinkedIn to manage applications. There are numerous online places to source candidates from.
All you need to do is use an applicant tracking system (ATS) to help you enrich the candidate pipeline so applicants from different sources flow into one place. Also, a prospective ATS should allow you to store applicant information, quickly search for reference candidates, create applicant profiles, and automate outreach.
Video recording
Video recording is an unskippable element in recruiting nowadays.
So, be sure that your potential ATS can add another layer to your hiring strategy with the ability to record short videos. This feature will allow you to expedite communications with your candidates by having them reply to your screening questions. Also, it will enable them to connect more directly with the hiring team, eventually saving time.
CRM (Candidate Relationship Management)
The probability of coming across a candidate you want to handhold is high, but you don’t have a relevant job opening at the moment. In these kinds of scenarios, having a candidate relationship management (CRM) solution lets you leverage the candidate down the road when the right time comes.
Furthermore, a CRM helps you nurture meaningful relationships with potential candidates through your ATS, which could add to your culture.
A handful of features you must consider is the ability to tag, vet, and search your candidate database. In addition, check if you can create workflows that allow you to view past outreach and help you stay connected with active candidates.
Automation and customization
To make sure workflows ease the hiring burden on your talent team, customization, and automation are quick fixes. For instance, automated interview scheduling, collecting candidate feedback, personalizing outreach, setting up meetings, and much more stuff with merely a few clicks.
DEI (Diversity, Equity, and Inclusion) reporting
There’s no doubt organizations across the globe are getting more concerned about diversity recruiting; this eventually outlines the fact that hiring teams need access to deeper data that helps them nurture progress with DEI.
So, ensure your applicant tracking system can deliver these insights.
Recruitment marketing
Often, there is a big myth about recruitment marketing that it only consists of what your company does on social media. But the reality is totally different.
The real hiring landscape is that recruitment marketing should sheath every candidate’s touchpoint with your company. Every recruitment process stage should align with your recruitment marketing, including career pages, job portals, nurture relationships, and job descriptions.
Finally…
If you are taking one thing away from here, remember that the easiest way to choose the best ATS is not to have a strategy. Instead, consider the abovementioned features, which will help you stay ahead of the curve and head towards success.
If you are perplexed, experts are here to address your needs thoroughly.
I want a chatbot like character.ai, but whenever anything nsfw comes up, it breaks. I would like something like that except it doesn’t break when anything nsfw happens.
ChatGPT, Bard, and other AI showcases: how Conversational AI platforms have adopted new technologies.
On November 30, 2022, OpenAI, a San Francisco-based AI research and deployment firm, introduced ChatGPT as a research preview. Within just five days of its launch, ChatGPT achieved the remarkable feat of attracting 1 million users, which was confirmed by OpenAI’s founder, Sam Altman, via Twitter. OpenAI’s success and increasing value can be partly attributed to its partnership with Microsoft. The tech giant invested $1 billion in the company in 2019, and has plans to invest another $10 billion in the nearest future.
The technology behind ChatGPT isn`t new and is called Generative AI, but with the success of the chatbot, it has attracted even more attention. Generative AI is a branch of AI that generates various types of data such as audio, images, text, code, and more, using existing data as inspiration and creating new outputs.
ChatGPT, the latest language model from the GPT-3 series, has set new standards in the AI industry. Using only 570 GB of textual data from the web, it has trained a large comprehensive language model that represents a significant advancement in the field. ChatGPT is considered to be the largest language model ever created, with 175 billion ML parameters.
OpenAI made the API of GPT-3 available to the public on November 18, 2021, so every business has had an opportunity to use this technology and integrate this Generative AI model. However, it was only after the launch of the ChatGPT showcase and everyone’s testing and trying their own use cases within it, that the world started to hear about OpenAI`s technology.
Benefits of integrating ChatGPT technologies with Conversational AI platforms or service providers
What does ChatGPT and this Generative AI technology mean for Conversational AI platforms or service providers? Is it a new market competitor, substitutor, or maybe assistant? We decided to ask ChatGPT what its own thoughts on that are.
How GPT-3 technology can help Conversational AI platforms?
To summarize, GPT-3 technology can enhance the functionality of Conversational AI platforms and provide:
Automation of simple support tasks, freeing up customer service agents to focus on more complex issues.
The integration of ChatGPT itself into a conversational AI platform can significantly improve its accuracy, fluency, versatility, and user experience. To enable all the range of benefits of ChatGPT for Conversational AI platforms, providers need to integrate the technology via API, which is not available as an open source solution, but companies could submit a request using OpenAI API Waitlist, yet API for GPT-3 technology itself is available via the link.
What Conversational AI platform has already adopted ChatGPT-inspired technology?
According to ChatGPT’s answer, OpenAI’s GPT (Generative Pretrained Transformer) technology, of which ChatGPT is a variant, has been adopted by several conversational AI platforms. Some notable examples include:
Replika AI: A personal AI companion that learns to communicate with its user.
Haptik: A conversational AI platform for customer service and engagement.
Virtual Personnel: A virtual customer service agent powered by AI.
BotStar: A conversational AI platform for businesses to build and deploy AI-powered chatbots.
Botpress: An open-source conversational AI platform for building and deploying bots.
These are just a few examples of using the technology that stands behind ChatGPT, and it`s popularity in the Conversational AI market is growing rapidly as more companies recognize the benefits it can bring to their platforms.
Intercom, an Irish customer service platform, has integrated OpenAI’s GPT-3.5 technology (which was the basis for ChatGPT) into its Inbox and Articles products. Currently, 100 customers are testing the new features within the limited Beta versions. The new features include ‘Composer AI’ which helps support agents write customer responses, ‘Conversation summarization’ which summarizes customer conversations for efficient handover between agents, and ‘Article generator AI’ that generates a full article version from a summary provided by the authors. The company plans to make these features more widely available this year.
Kore.AI, a leading Conversational AI platform for optimized customer and employee experiences, has provided a comprehensive answer on how technology utilized in the ChatGPT bot Compliment Conversational AI Platforms. Features such as automatic intent recognition, and slot and entity identification are integrated with models like Open AI to provide advanced capabilities such as automatic answers to FAQs, improved human-bot interactions, and faster dialog development. In addition, large language models (LLMs) can be used by Conversational AI Platforms to generate initial prompts, messages, and sample conversations, saving a significant amount of time and providing an excellent starting point for conversation designers to refine responses.
LivePerson also adds ChatGPT’s Generative AI model to the customer service bot platform. LivePerson plans to integrate LLMs into its Conversational Cloud platform. The generative AI will also be incorporated into the company’s Conversation Assist feature to keep the chatbots up-to-date. In addition, LivePerson will use generative AI in its behind-the-scenes tools to provide businesses with conversation summaries, form filling, and customer information updates during and after conversations with the chatbots. The collected data will help improve future AI systems.
Cognigy, a global leader in Conversational AI, went through all the stages of grief and evolved from denial to acceptance in a month, when in December they highlighted Showstoppers for a pureplay ChatGPT bot in Customer Service, and then in January presented a product Demo: with LLM-assisted bot building. Basically, the ideas behind Cognigy’s release is to assess the drawbacks of both Conversational AI and ChatGPT, and combine the most advantageous facets of the two.
That is why businesses are looking for ChatGPT alternatives, and here is the list of the most popular ones.
ChatGPT Conversational AI Alternatives businesses can elect
There exist several alternatives to ChatGPT Generative AI model in the Conversational AI industry that businesses can choose from. Some of the prominent ones include:
Google’s LaMDA (Language Model for Dialogue Applications), a large language model trained on a diverse range of internet text and capable of generating human-like responses to various types of questions and prompts.
Facebook’s Blender, a large-scale, multi-turn, multi-domain conversational AI model, pre-trained on a diverse range of internet text.
IBM Watson Assistant, a conversational AI platform that enables businesses to build conversational experiences for customers across any channel or device.
On February 6, 2023, Google unveiled the ChatGPT rival Bard — an experimental conversational AI service powered by LaMDA (Language Model for Dialogue Applications). What’s unique about this technology? Its approach is a bit different from the OpenAI since it is trained in dialogue data and focuses on three key parameters — Safety, Quality, and Groundedness. ChatGpt, however, is based on three models — code-DaVinci-002, text-DaVinci-002 (it was trained by humans who were checking if the answer was correct), and an additional base model to understand codes. With a large number of parameters, LaMDA excels in generating responses based on freely accessible conversation data. It can handle various customer service and marketing automation tasks, and its future looks promising with the support of platforms like Amazon.
As of now, Google is concentrating on tuning its solution to provide secure service, and it has announced to start the first real business testing in a month, so only after that may we have the opportunity to see the real feedback from the enterprises.
Gleb Dobzhanskiy, VP of Engineering at Master of Code: “We are already working on adding ChatGPT-like functionality to the existing bots of our clients. So, we do not need to throw away old flow-based bots and replace them with a new generating-AI base one. We can augment existing bots with the GPT-3 based flows on a custom fine-tuned GPT-3 model. This model can keep the focus on business-case-specific knowledge and not try to answer every question as generic ChatGPT does.”
Master of Code, as a Conversational AI solution provider and certified delivery partner of LivePerson, has extensive expertise Conversational AI platforms integration with third-party systems to collect information about customers in order to provide a personalized omnichannel experience. OpenAI`s solution could be one of the systems integrated into the conversational flow, starting with questions from the customer’s standpoint and ending with replies derived from Conversational AI. And here at Master of Code, we can share our expertise in Conversational AI development, building conversational solutions, both voice and text, within Conversation Design best practices, and integrating new technologies into ready-made systems.
While working on each project, we collaborate with stakeholders to assess the feasibility of deploying Conversational AI solutions. This involves selecting the appropriate technology, and determining the data sources and the necessary integrations, with the goal being delivering the best user experience. Undoubtedly, OpenAI or Google may be one of the technologies in this stack since, at the end of the day, our main objective is to improve efficiency and address customer issues promptly and accurately.
Want to learn more? Master of Code designs, builds and launches exceptional mobile, web, and conversational experiences. Contact Us
Recently, the GF and I have been having fun each doing some fantasy-world RP chats with ChatGPT and sharing what we’ve gotten. With the recent update(March 14th), ChatGPT Version 4 no longer allows the sort of content (NSFW specifically) that we’ve been managing so far. It will still do our family-friendly stories just fine, but completely refuses to even consider any type of euphemism or innuendo anymore, instead of just politely warning you “Hey, I think this might be a violation, but here ya go!” like it used to.
So, does anyone have a recommendation for a free (or at least a one-time purchase) bot similar to ChatGPT that can either be tricked into NSFW content, or just allows it in general?
I’m not talking ChatGPT or Bing. I mean the most entertaining and persuasive chatbots created by independent chatbot creators (ICCs). I’ve been writing chatbots on top of GPT-3 and GPT 3.5 for a while with some pretty good results. Been looking for people doing the same.
Can someone explain to me how it is that ChatGPT can accurately answer a question like “how far is it from Sacramento to LA”, but can’t answer “What city is as far from Paris as Sacramento is from LA”? For the latter question I get absurd results like ‘Paris is as far from Algiers as Sacramento is from LA’. When I point out the absurd difference in distances, I get ‘sorry’ with a recalculation says Tbilisi is the same distance! And yet it can tell me the straightforward distance from Paris to anywhere.
Does the phrasing of the comparison exceed ChatGPT’s logical capabilities? And yet, it can answer ostensibly much more complex questions to do with technical topics in philosophy. ‘What does Kant’s conception of time share with Heidegger’s?’ What’s the difference here? ChatGPT does a respectable job with philosophical questons, but it can’t do a simple distance comparison! How is this possible?
