8 AI chatbots you should use instead of ChatGPT

Meanwhile, Python expanded in scientific computing, which encouraged the creation of a wide range of open-source libraries that have benefited from years of R&D. After this process of information gathering, the chatbot can confidently respond and determine the most appropriate output. Asynchronous programming is a critical component of the backend, allowing the system to handle multiple tasks concurrently without delays or bottlenecks.

Integrating and Managing External Tools

In addition, My AI can now recommend AR filters to use in Snapchat’s camera or places to visit from the app’s map tab. Several companies have announced deep research features in recent weeks and months that excel in areas such as finance, science, marketing, and academics. Research that would have taken a person weeks or months can be achieved in a fraction of the time, with a properly detailed prompt. Similarly, you can create and train a character, giving them a humanlike personality and introduce them to the Character.AI community. Other features allow you to share your conversations publicly within the community and allow the fictional characters to communicate with each other. The chatbot can break down the spoken or written query based on the entity and the intent, which allows it to provide an accurate response even when nuance must be understood in the query.

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Despite the problematic interactions that have already surfaced, Spiegel says the overwhelming majority of interactions with My AI have been positive. “The thing that gave us a lot of confidence is that as we monitored the way that people were using the service, we found that 99.5 percent of My AI replies conformed to our community guidelines,” he says. The OpenAI-powered chatbot is also being added to group chats, gaining the ability to make recommendations for things like AR filters, and will soon be able to even generate photos inside Snapchat.

Apps & Products

The first aforementioned iier allows you to generate conversations anonymously without signing up. Then there is the free sign-up tier, which includes a single-use sign-up option, and a paid Perplexity Pro tier. The free tiers are based on OpenAI’s GPT-3.5 model and also use the natural language processing (NLP) model to train the chatbot. Meanwhile, Perplexity Pro uses a mix of GPT-4, Claude 3, Mistral Large, Llama 3 and an Experimental Perplexity model for different processes.

There are pricing tiers for individuals and freelancers, as well as tiers for professionals and teams. Similar to other brands, Chatsonic is currently based on the GPT-3.5 LLM for its free version, GPT-4 LLM and Claude 3 Opus for its paid tiers, and the DALL-E and Stable Diffusion image generation models. Google now supports several LLM options that are available for different tiers of purpose and expertise, including Gemini Nano, Gemini Pro, Gemini Ultra, and Gemini Advanced. Gemini Pro powers the free Google Gemini chatbot that is the brand’s entry-level,web- and app-based AI product. The company recently released a public preview of the Gemini 1.5 Pro LLM that enables “hearing” capabilities when audio files, from which the chatbot can extract the text information, are uploaded to a system.

Its paid subscription option includes faster response times, early access to new features, and a c.ai+ supporter badge, among other perks. Perplexity AI is a research-focused chatbot with a company CEO who is an OpenAI alumnus. Its simple user interface is reminiscent of ChatGPT, but it doesn’t require an initial login to test. You can simply begin typing your query or click one of the suggested topics available to begin a conversation. Clicking the discover tab also brings up recent news similar to a search engine. The AI chatbot is known for citing its sources with links and being up to date with information pulled from the internet.

But after spending months using them side by side, it’s clear that each has gaps that the other already solves. If Gemini and ChatGPT borrowed the best from each other, they’d be nearly perfect. Put your brand in front of 10,000+ tech and VC leaders across all three days of Disrupt 2025.

There’s experimental voice tech included too, which you can toggle on and off to test — the difference is that apparently, full-duplex speech technology generates audio directly, rather than reading written responses. Selecting your LLM of choice will load its corresponding chatbot and you can begin a conversation. Some of the models included in Poe are Google PaLM and Gemini, Meta Llama, and Anthropic Claude, multiple versions of the GPT LLMs, and lesser-known technologies including Sage, Dragonfly, and NeevaAI. In some versions, users click on buttons with select options and are guided to an answer through the designed flow. When given a text box for the user input, bots look for familiar words within the query and then match the keywords with an available response. Rule-based chatbots only allow the user to input what the chatbot is programmed to handle.

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• When given a text box for the user input, bots look for familiar words within the query and then match the keywords with an available response.
• Rule-based chatbots only allow the user to input what the chatbot is programmed to handle.
• But since then, several companies have developed consumer products with free and paid tiers and a plethora of enterprise and developer options.
• But NLTK is superior thanks to its additional support for other languages, multiple versions and interfaces for other NLP tools and even the capability to install some Stanford NLP packages and third-party Java projects.
• Natural Language Toolkit’s (NLTK) initial release was in 2001 — five years ahead of its Java-based competitor Stanford Library NLP — serving as a wide-ranging resource to help your chatbot utilize the best functions of NLP.

You can ask the bot any question, and it will answer with human-quality responses. Since ChatGPT is a neural network that has been trained on a large amount of data, it can generate a unique response and doesn’t just regurgitate an automated response like a rule-based chatbot would. AI chatbots use machine learning to help the computer learn from the input and feedback received. Over time, the chatbots become more efficient and more accurately address the user’s questions. Powered by the latest Llama 4 model, the app is designed to “get to know you” using the conversations you have and information from your public Meta profiles. It’s designed to work primarily with voice, and Meta says it has improved responses to feel more personal and conversational.

Clarity is also an issue, which is incredibly important when building a chatbot, as even the slightest ambiguity within one of the steps could cause it to fail. On the subject of machine learning, what better approach than to look at some hard data to see which language the experts prefer? In a recent survey of more than 2,000 data scientists and machine learning developers, more than 57 percent of them used Python, while 33 percent prioritized it for development.