The launch of Open AI's ChatGPT ignited a gold rush in the artificial intelligence industry. This groundbreaking development has not only attracted significant investment from both established tech giants and startups alike, but has also enabled widespread adoption by consumers using it to do everything from planning a vacation, generating art, creating a business plan, and much more.
While the masses have embraced this technology with open arms, businesses have exercised caution, with many even banning the use of ChatGPT in their offices due to security concerns.
Samsung accidentally shared top-secret data and internal meeting notes relating to their hardware with Chat GPT, unknowingly giving their company's secrets to Open AI which now owns the data. A flurry of similar incidents followed sending businesses into a frenzy to create policies and restrictions around the use of Gen AI platforms. In response, Open AI released its own private enterprise version that offers more privacy and security to businesses as well as data sovereignty.
But Open AI is not the end all be all of the industry as competition is heating up among the big tech giants like Google and Meta as well as startups that are raising billions to build even better and more powerful models while offering enhanced security, transparency, and safety specifically tailored for enterprise use.
Let’s take a look at five remarkable alternatives to Open AI and ChatGPT that are making waves among consumers and businesses.
First, Let’s Cover the Basics of Large Language Models
LLMs for short, are advanced natural language processing (NLP) algorithms, trained on massive datasets. These LLMs have the unique capability to understand context, generate human-like conversation, and perform a wide range of tasks. Beyond just generating text, LLMs have evolved quickly to execute complex actions, enhancing their potential to transform business operations, enhance customer experiences, and derive insights from massive amounts of unstructured data.
Why are we talking about LLMs?
If you’ve used ChatGPT, Bard, or Bing, you’ve interacted with an LLM. These are the proprietary models that form the foundation of gen AI conversational chatbots. Tech companies are clamoring to build the best, fastest, and most powerful LLM which has enabled space to evolve at lightning speed in just a year.
When looking at alternatives to Open AI and Chat GPT, the competitive landscape is primarily composed of AI companies that are building their own LLMs and then creating new products, features, and interfaces on top of it. The introduction of APIs, collaborative communities, and open-source models has brought a new world of opportunities for the enterprise to leverage the power of LLMs for both internal applications as well as to create new breakthrough experiences for their customers.
Meet The Players
More than $12 billion in VC funding has gone into about 6 LLM providers in the past year, according to The Information's Generative AI Database. For context, about $10 billion of that was invested in OpenAI, but the other investments should not be ignored. New players are bringing distinct strengths and features to the market; enhanced user experience, heightened security, industry specialization, integration capabilities, or transparent decision-making processes. Let’s have a closer look at them!
1. Anthropic & Claude 2
Anthropic is an AI safety and research company, co-founded by OpenAI veterans. They are working towards creating helpful, honest, and harmless AI systems using approaches like Constitutional AI and responsible AI.
The company has raised $750 million in two funding this year and is already valued at $4.1 billion.
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Image source: Anthropic
Their next-gen AI assistant is called Claude which is designed to reduce brand risk. Use cases involving Claude include knowledge management, market research, fraud detection, demand forecasting, report generation, business analysis, and more. It has the best-in-class data retention, with no additional training on your data. It can handle complex multi-step instructions over large amounts of content.
Businesses can personalize Claude to excel at their use cases and speak in their voice. The company’s AI models have been tested by businesses such as Slack, Notion, BCG, and Quora, and Claude 2 has accumulated a waitlist of more than 350,000 people requesting access to its programming interface and consumer offering.
- Zoom recently announced a partnership with Anthropic to “build customer-facing AI products focused on reliability, productivity and safety”.
- Quora is offering Claude to users through their own AI Chat app. “Poe”:
“Users describe Claude’s answers as detailed and easily understood, and they like that exchanges feel like natural conversation,” said Autumn Besselman, Head of People and Comms from Quora.
2. Inflection AI & Pi
Inflection AI is another new player that has burst onto the scene this year. Supported by some of the biggest names in tech and venture capital (like Microsoft, Nvidia, and billionaires Reid Hoffman, Bill Gates, and Eric Schmidt) the startup is valued at an impressive $4 billion.
Inflection is an AI studio that creates a personal AI for everyone. In just over a year, they have developed one of the most sophisticated large language models on the market. Their solution is called Pi, your Personal AI, and enables interaction in a simple, natural way to receive fast, relevant, and helpful information and advice. You can talk to Pi on multiple platforms including SMS, WhatsApp, and Facebook Messenger. It aims to be a supportive and empathetic conversational AI tool, that acts as your personal companion available all the time.
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Image source: InflectionAI
While the company has been primarily focused on creating a personal assistant for every individual, businesses are on the radar. They recently made their foundational large language model called Inflection-1, as an API for use by other businesses.
Inflection AI is positioning its LLM as a rival to those built by Open AI, Meta, and Google and ran tests claiming to prove that Inflection-1 generally outperforms those other models.
3. Adept & Act-1
Adept is a startup building AI that “enables humans and computers to work together creatively to solve problems.” Rather than creating an AI that can generate images or gather answers to questions like Chat-GPT or Dall-E, Adept is working to use AI to advance how people use computers — specifically how they browse the web and navigate software — to train an AI model that can turn text instructions into digital actions.
“We believe that AI systems should be built with users at the center - where machines work together with people in the driver's seat: discovering new solutions, enabling more informed decisions, and giving us more time for the work we love.''
Their model is called ACT-1, and so far has been trained to use a web browser and is integrated using a Chrome extension. The Redfin example shows how a user can input instructions into a chat pop-up and Act-1 will perform the task of finding available property options that would normally take multiple clicks and searching within the website.
Think of this new frontier as “text-to-action” where you can delegate tasks to your computer simply by asking it in natural language. Adept’s vision is that most interaction with computers will be done using natural language in the future. We’ll tell our computer what to do, and it’ll do it for us, making today’s user interfaces soon seem archaic.
4. Meta & LLaMa 2
Meta has also thrown its hat in the AI ring and introduced LLaMA (Large Language Model Meta AI), showcasing the company's vision for the future of AI-driven communication. Llama is a collection of state-of-the-art foundational language models ranging from 7B to 65B parameters, leveraging Meta's extensive data networks and research in AI.
While competitors like Google and Microsoft have fiercely guarded their proprietary LLMs, Meta decided to go open-source with Llama 2, making it a game changer for the industry. The company recognizes the value of attracting users and developers to its platform, leveraging the collaborative power of an open-source community.
The new LLaMA 2 is open for commercial use and is free for businesses to adopt, customize, and monetize as they please.
Its expanded training data enables it to comprehend and generate human-like text with very high accuracy. Businesses can harness this capability to build chatbots, virtual assistants, and customer support systems that engage users in natural conversations.
Llama 2's performance is so far comparable to Open AI’s GPT-4 and Anthropic’s Claude-2 and can solve a lot of the data security problems that businesses often encounter when entrusting sensitive information to third-party AI models.
The shift towards open-source models like Llama that allow for private hosting is expected to increase, driven by these security, privacy, and risk management requirements.
''We believe an open approach is the right one for the development of today’s AI models. (...) Giving businesses, access to tools developed at a scale that would be challenging to build themselves, backed by computing power they might not otherwise access, will open up a world of opportunities (...)'' Meta says.
Image source: Meta
Meta's LLaMA challenges the belief that bigger AI models are always superior, by outperforming larger models (like GPT-3) despite its smaller size.
Businesses can use it for various tasks, such as analyzing consumer sentiment, spotting trends, and creating chatbots. In essence, LLaMA signifies an advancement in AI, striking a balance between size, performance, and fairness.
5. Google's PaLM 2
Google has been at the forefront of AI, creating a multitude of tools used by billions of people on a daily basis. PaLM 2 is their next-generation language model with improved multilingual, reasoning, and coding capabilities. It is fueling over 25 new products from Google that are bringing the power of generative AI to consumers, developers, and enterprises.
One of those products is Bard, Google’s answer to Chat-GPT. The Bard chatbot has a simple interface and returns concise, human-like answers to complex questions while writing with more straightforward and simplistic language than ChatGPT.
Image source: Google
But Google is looking well beyond next-gen AI assistants. PaLM 2 is also powering new use cases for healthcare. Med-PaLM 2 is trained in medical knowledge and can answer questions and provide insights from a variety of large medical texts. It was the first large language model to perform at the “expert” level in the US.
Business customers can also use the model in Vertex AI that provides enterprise-grade privacy, security, and governance. PaLM 2 is also powering Duet AI for Google Cloud, a generative AI collaborator designed to help users learn, build and operate faster than ever before.
The list of new products and features will continue to evolve as Google battles it out with Meta and Microsoft.
Getting Started with Large Language Models
One thing is certain - LLMs are going to revolutionize the user experience and businesses need to act now. But, to harness the potential of LLMs, it is critical to create a comprehensive, forward-thinking strategy before jumping in.
Key steps to include:
- Prioritize and define your use cases.
Identifying your strategic use cases and where LLMs can add the most value is critical before selecting an LLM partner or deciding to build your own. Are you looking to vastly improve internal processes and productivity like content creation or knowledge sharing? Or are you more concerned with creating new personalized experiences for your customers? Or both?
- Get hands-on keyboard experience.
Most gen AI assistants like Chat GPT and Bard are free to use. Getting familiar with what they do and how to prompt them is an easy way to get experience and can also be used for on-demand research, content creation, and other time-consuming tasks. - Experiment with plug-ins.
OpenAI and Microsoft among others offer a framework for building plugins for ChatGPT and Bing AI. Plug-ins are small tools that enable the model to perform tasks that are specific to your business or use case and can be a great way to experiment. For example, Instacart used a Chat-GPT plug-in to create a chat-based personalized shopper for its website and app.
Need help figuring out your next move with LLMs?
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