Meet the rivals of ChatGPT

These competitors are no folly either, with heavy-hitting tech giants such as Google, Microsoft, Meta, and Baidu all having their own endeavours with the generative AI revolution.

Google Bard

Google Bard is an AI-powered chatbot being developed by Google to compete with ChatGPT and other similar chatbots. The chatbot is designed to engage in conversations with users in a far more natural way than both its early predecessors and rivals. Bard uses a combination of machine learning algorithms and natural language processing (NLP) techniques to understand and interpret user inquiries and respond accordingly. The chatbot is trained on a vast database of human-to-human interactions on top of human-to-machine interactions enabling it to provide not only relevant and accurate responses, but ones with a far more ‘human tone’ to them.

Bard is an interesting addition to the world of AI-powered chatbots, offering a more unique experience than its competitors. The hope is that Google’s Bard can offer a more engaging and interactive experience for users who are looking for more personalised and human-like interactions with technology.

Microsoft Bing AI

Microsoft, despite being a $10bn investor in ChatGPT, has been developing its own rival of the service, named Bing AI. Microsoft’s Bing AI is one of the more notable rivals of ChatGPT in regards to the AI powering it. Bing AI is a powerful system that uses a combination of machine learning, NLP, and computer vision to provide its users with intelligent search results, personalised recommendations, a chat service, and more.

For the most part, Bing AI is designed to help users find the information they need in an efficient and effective manner. Through utilising its machine learning alongside text and even image analysis, Bing AI can deliver highly relevant search results that are specifically tailored to user preferences.

Bing AI also has the capacity to learn from user behaviour. As users interact with the system, it gathers data on their preferences and behaviours, which it can use to improve its recommendations and search results over time. This means that Bing AI becomes more effective the more it is used, providing a highly personalised experience for each user.

Baidu’s Ernie Bot

Ernie Bot is another NLP model that is in the works by Chinese tech giant Baidu, which maintain the largest Chinese search engine. Ernie stands for ‘Enhanced Representation through kNowledge IntEgration,’ and is similar in features to those seen in Google’s Bard and OpenAI’s ChatGPT.

Ernie is based on a pre-training method that allows the model to learn from large amounts of data before being fine-tuned for specific tasks. This approach enables Ernie to perform well on a wide range of NLP tasks, including text classification, sentiment analysis, and machine translation.

One of the more standout features of Ernie is its ability to integrate knowledge graphs into its understanding of language. Knowledge graphs are databases of structured information that can be used to enhance NLP models’ understanding of language by providing the AI with further context and background knowledge.

Like ChatGPT, Ernie is gaining significant traction amongst the NLP community and is almost seeing successful deployments in various applications such as virtual assistants, the Baidu search engine, and chatbots.

Overall, Baidu’s Ernie represents a strong rival to ChatGPT and demonstrates the growing capabilities and popularity of AI-powered language models. However, Baidu is somewhat hindered from being a true universal rival of ChatGPT, given its current availability being limited to Chinese users as well as being politicised and censored to a much greater extent than its competitors.

Meta Blenderbot

Meta’s swing at the NLP model comes in the form of Blenderbot, developed by Facebook AI Research (FAIR). Blenderbot has a much greater focus on conversational skills, attempting to converse with humans in a natural and engaging manner which makes the model an ideal tool for areas such as customer service, educational purposes, or entertainment.

One of the key features that set Blenderbot apart from the competition is its ability to understand and respond far better to contextual cues. This means that it can take into account previous conversations and tailor its responses accordingly, leading to considerably more personalised interactions. This impressive memory system is an invaluable tool for tasks such as customer support or long-term conversations with a company or organisation over time. Additionally, Blenderbot can also generate its own responses based on the tone and sentiment of the conversation, if a professional tone is more suitable, then that is what it shall use, if a joking tone is detected then Blenderbot will follow along.

Meta’s NLP model also comes with one of the better capabilities for multilinguistic uses, being able to utilise Meta AI’s NLLB-200 model that can translate across 200 languages to a high degree.

Meta’s Blenderbot could well have the potential to be the next step in human-to-machine interactions and it will be interesting to see how this technology develops in the years to come.