Alternatives to PaLM

Multilingualize your content and apps with machine translation that is available in thousands of languages. The Translation API Basic Edition instantly translates your website or application texts into more than 100 different languages. The Advanced Edition offers dynamic results as quickly as Basic edition but also includes customization features. This is important when you are using phrases or terms that are unique to certain areas and contexts. The Translation API's pre-trained model supports over 100 languages, from Afrikaans through to Zulu. AutoML Translation allows you to create custom models for more than fifty languages. The Translation API glossary ensures that the content you translate is true to your brand. You only need to specify which vocabulary you would like to give priority to, and save the glossary in your translation project.

Dolly is an inexpensive LLM that demonstrates a surprising amount of the capabilities of ChatGPT. Whereas the work from the Alpaca team showed that state-of-the-art models could be coaxed into high quality instruction-following behavior, we find that even years-old open source models with much earlier architectures exhibit striking behaviors when fine tuned on a small corpus of instruction training data. Dolly uses an open source model with 6 billion parameters from EleutherAI, which is modified to include new capabilities like brainstorming and text creation that were not present in the original.

Gemini was designed from the ground-up to be multimodal. It is highly efficient in tool and API integrations, and it is built to support future innovations like memory and planning. We're seeing multimodal capabilities that were not present in previous models. Gemini is our most flexible model to date -- it can run on anything from data centers to smartphones. Its cutting-edge capabilities will improve the way developers and enterprises build and scale AI. We've optimized Gemini 1.0 for three different sizes. Gemini Ultra - Our largest and most capable model, designed for highly complex tasks. Gemini Pro is our best model to scale across a variety of tasks. Gemini Nano -- our most efficient model for on-device tasks.

Multilingual T5 is a massively pretrained text-totext transformer model that has been trained using a similar recipe to T5. This repo can used to reproduce the experiments described in the mT5 article. The mC4 corpus covers 101 languages. Afrikaans, Albanian, Amharic, Arabic, Armenian, Azerbaijani, Basque, Belarusian, Bengali, Bulgarian, Burmese, Catalan, Cebuano, Chichewa, Chinese, Corsican, Czech, Danish, Dutch, English, Esperanto, Estonian, Filipino, Finnish, French, Galician, Georgian, German, Greek, Gujarati, Haitian Creole, Hausa, Hawaiian, Hebrew, Hindi, Hmong, Hungarian, Icelandic, Igbo, Indonesian, Irish, Italian, Japanese, Javanese, Kannada, Kazakh, Khmer, Korean, Kurdish, Kyrgyz, Lao, Latin, Latvian, Lithuanian, Luxembourgish, Macedonian, Malagasy, Malay, Malayalam, Maltese, Maori, Marathi, Mongolian, Nepali, Norwegian, Pashto, Persian, Polish, Portuguese, Punjabi, Romanian, Russian, Samoan, Scottish Gaelic, Serbian, Shona, Sindhi, and more.

PaLM 2 is Google's next-generation large language model, which builds on Google’s research and development in machine learning. It excels in advanced reasoning tasks including code and mathematics, classification and question-answering, translation and multilingual competency, and natural-language generation better than previous state-of the-art LLMs including PaLM. It is able to accomplish these tasks due to the way it has been built - combining compute-optimal scale, an improved dataset mix, and model architecture improvement. PaLM 2 is based on Google's approach for building and deploying AI responsibly. It was rigorously evaluated for its potential biases and harms, as well as its capabilities and downstream applications in research and product applications. It is being used to power generative AI tools and features at Google like Bard, the PaLM API, and other state-ofthe-art models like Sec-PaLM and Med-PaLM 2.

Integrate our Python SDK and Rest API within minutes to ship faster. No data formatting or setup required. As soon as your first customer and data are in, you can start using the system. We have developed and fine-tuned our custom language models in order to recognize entities, crawl the web in real time and select the best match. We can also assign labels with superhuman precision in a fraction the time. Everyone has a data-enrichment model that tries to excel at one thing - whether it's for the US or Europe, or business or consumers. These models are not able to generalize and cannot produce output at the level of a human. You can embed the largest and most efficient models in your products at a fractional cost and time.

StableLM: Stability AI language models StableLM builds upon our experience with open-sourcing previous language models in collaboration with EleutherAI. This nonprofit research hub. These models include GPTJ, GPTNeoX and the Pythia Suite, which were all trained on The Pile dataset. Cerebras GPT and Dolly-2 are two recent open-source models that continue to build upon these efforts. StableLM was trained on a new dataset that is three times bigger than The Pile and contains 1.5 trillion tokens. We will provide more details about the dataset at a later date. StableLM's richness allows it to perform well in conversational and coding challenges, despite the small size of its dataset (3-7 billion parameters, compared to GPT-3's 175 billion). The development of Stable LM 3B broadens the range of applications that are viable on the edge or on home PCs. This means that individuals and companies can now develop cutting-edge technologies with strong conversational capabilities – like creative writing assistance – while keeping costs low and performance high.

With just a few lines, you can integrate natural language understanding and generation into the product. The Cohere API allows you to access models that can read billions upon billions of pages and learn the meaning, sentiment, intent, and intent of every word we use. You can use the Cohere API for human-like text. Simply fill in a prompt or complete blanks. You can create code, write copy, summarize text, and much more. Calculate the likelihood of text, and retrieve representations from your model. You can filter text using the likelihood API based on selected criteria or categories. You can create your own downstream models for a variety of domain-specific natural languages tasks by using representations. The Cohere API is able to compute the similarity of pieces of text and make categorical predictions based on the likelihood of different text options. The model can see ideas through multiple lenses so it can identify abstract similarities between concepts as distinct from DNA and computers.

ChatGPT is an OpenAI language model. It can generate human-like responses to a variety prompts, and has been trained on a wide range of internet texts. ChatGPT can be used to perform natural language processing tasks such as conversation, question answering, and text generation. ChatGPT is a pretrained language model that uses deep-learning algorithms to generate text. It was trained using large amounts of text data. This allows it to respond to a wide variety of prompts with human-like ease. It has a transformer architecture that has been proven to be efficient in many NLP tasks. ChatGPT can generate text in addition to answering questions, text classification and language translation. This allows developers to create powerful NLP applications that can do specific tasks more accurately. ChatGPT can also process code and generate it.

GPT-4, a large multimodal (accepting text and image inputs) model that can solve complex problems with greater accuracy thanks to its advanced reasoning abilities and broader general knowledge than any of our other models. GPT-4 can be found in the OpenAI API for paying customers. GPT-4, like gpt 3.5-turbo is optimized for chat, but also works well with traditional completion tasks using the Chat Completions API. Our GPT guide will teach you how to use GPT-4. GPT-4 is a newer GPT-4 model that features improved instruction following, JSON Mode, reproducible outputs and parallel function calls. Returns up to 4,096 tokens. This preview model has not yet been adapted for production traffic.

AI21 Studio provides API access to Jurassic-1 large-language-models. Our models are used to generate text and provide comprehension features in thousands upon thousands of applications. You can tackle any language task. Our Jurassic-1 models can follow natural language instructions and only need a few examples to adapt for new tasks. Our APIs are perfect for common tasks such as paraphrasing, summarization, and more. Superior results at a lower price without having to reinvent the wheel Do you need to fine-tune your custom model? Just 3 clicks away. Training is quick, affordable, and models can be deployed immediately. Embed an AI co-writer into your app to give your users superpowers. Features like paraphrasing, long-form draft generation, repurposing, and custom auto-complete can increase user engagement and help you to achieve success.

GPT-3.5 is the next evolution to GPT 3 large language model, OpenAI. GPT-3.5 models are able to understand and generate natural languages. There are four main models available with different power levels that can be used for different tasks. The main GPT-3.5 models can be used with the text completion endpoint. There are models that can be used with other endpoints. Davinci is the most versatile model family. It can perform all tasks that other models can do, often with less instruction. Davinci is the best choice for applications that require a deep understanding of the content. This includes summarizations for specific audiences and creative content generation. These higher capabilities mean that Davinci is more expensive per API call and takes longer to process than other models.

Fine-tuning is when you take a dataset, and create a model to use AI. This is not always possible without programming so we created a solution in RIku that handles everything in a very easy format. Fine-tuning unlocks an entirely new level of power for artificial intelligence and we are excited to help you explore this. Public Share Links are landing pages you can create for any of the prompts. These can be designed with your brand in mind, including colors and adding your logo. These links can be shared with anyone, and if they have access to the password to unlock it they will be able make generations. No-code assistant builder for your audience. We found that projects using multiple large languages models have a lot of problems. They all return their outputs in a slightly different way.

ChatGPT Enterprise is the most powerful version yet, with enterprise-grade security and privacy. 1. Training models do not use customer prompts or data 2. Data encryption in transit and at rest (TLS 1.2+). 3. SOC 2 compliant 4. Easy bulk member management and dedicated admin console 5. SSO and Domain Verification 6. Use the analytics dashboard to understand usage 7. Access to GPT-4 Advanced Data Analysis and GPT-4 at high speed is unlimited 8. 32k token context window for 4X longer inputs, memory and inputs 9. Shareable chat templates to help your company collaborate

GPT-3 models are capable of understanding and generating natural language. There are four main models available, each with a different level of power and suitable for different tasks. Ada is the fastest and most capable model while Davinci is our most powerful. GPT-3 models are designed to be used in conjunction with the text completion endpoint. There are models that can be used with other endpoints. Davinci is the most versatile model family. It can perform all tasks that other models can do, often with less instruction. Davinci is the best choice for applications that require a deep understanding of the content. This includes summarizations for specific audiences and creative content generation. These higher capabilities mean that Davinci is more expensive per API call and takes longer to process than other models.

GPT-4o (o for "omni") is an important step towards a more natural interaction between humans and computers. It accepts any combination as input, including text, audio and image, and can generate any combination of outputs, including text, audio and image. It can respond to audio in as little as 228 milliseconds with an average of 325 milliseconds. This is similar to the human response time in a conversation (opens in new window). It is as fast and cheaper than GPT-4 Turbo on text in English or code. However, it has a significant improvement in text in non-English language. GPT-4o performs better than existing models at audio and vision understanding.

GPT-4 (Generative Pretrained Transformer 4) a large-scale, unsupervised language model that is yet to be released. GPT-4, which is the successor of GPT-3, is part of the GPT -n series of natural-language processing models. It was trained using a dataset of 45TB text to produce text generation and understanding abilities that are human-like. GPT-4 is not dependent on additional training data, unlike other NLP models. It can generate text and answer questions using its own context. GPT-4 has been demonstrated to be capable of performing a wide range of tasks without any task-specific training data, such as translation, summarization and sentiment analysis.

OpenAI's mission, which is to ensure artificial general intelligence (AGI), benefits all people. This refers to highly autonomous systems that outperform humans in most economically valuable work. While we will try to build safe and useful AGI, we will also consider our mission accomplished if others are able to do the same. Our API can be used to perform any language task, including summarization, sentiment analysis and content generation. You can specify your task in English or use a few examples. Our constantly improving AI technology is available to you with a simple integration. These sample completions will show you how to integrate with the API.

Use generative language models for improving and optimizing your web services and applications. Get a consolidated result of textual data, whether it is information from chats at work, user reviews or other types. YandexGPT can help summarize and interpret information. Improve the quality and style of your text to speed up the creation process. Create templates for newsletters, product description for online stores, and other applications. Create a chatbot to help your customer service. Teach the bot how to answer common and complex questions. Use the API to automate processes and integrate the service into your applications.

Gemma is the family of lightweight open models that are built using the same research and technology as the Gemini models. Gemma was developed by Google DeepMind, along with other teams within Google. The name is derived from the Latin gemma meaning "precious stones". We're also releasing new tools to encourage developer innovation, encourage collaboration, and guide responsible use of Gemma model. Gemma models are based on the same infrastructure and technical components as Gemini, Google's largest and most powerful AI model. Gemma 2B, 7B and other open models can achieve the best performance possible for their size. Gemma models can run directly on a desktop or laptop computer for developers. Gemma is able to surpass much larger models in key benchmarks, while adhering our rigorous standards of safe and responsible outputs.

Code Llama, a large-language model (LLM), can generate code using text prompts. Code Llama, the most advanced publicly available LLM for code tasks, has the potential to improve workflows for developers and reduce the barrier for those learning to code. Code Llama can be used to improve productivity and educate programmers to create more robust, well documented software. Code Llama, a state-of the-art LLM, is capable of generating both code, and natural languages about code, based on both code and natural-language prompts. Code Llama can be used for free in research and commercial purposes. Code Llama is a new model that is built on Llama 2. It is available in 3 models: Code Llama is the foundational model of code; Codel Llama is a Python-specific language. Code Llama-Instruct is a finely tuned natural language instruction interpreter.

Phi-2 is a 2.7-billion-parameter language-model that shows outstanding reasoning and language-understanding capabilities. It represents the state-of-the art performance among language-base models with less than thirteen billion parameters. Phi-2 can match or even outperform models 25x larger on complex benchmarks, thanks to innovations in model scaling. Phi-2's compact size makes it an ideal playground for researchers. It can be used for exploring mechanistic interpretationability, safety improvements or fine-tuning experiments on a variety tasks. We have included Phi-2 in the Azure AI Studio catalog to encourage research and development of language models.

Our models are deployed all over the world for the best possible response time. Integrate our OpenAI compatible API seamlessly into your application. Start in minutes and scale seamlessly to serve millions of users. Our API is 4 times cheaper than OpenAI GPT-3.5 API due to our extensive performance and scale optimizations. Our AI model can generate text and chat at ChatGPT performance levels for a fraction of what it costs. Our OpenAI-compatible API makes it easy to get started. Use one of the most powerful AI image models in order to create stunning images, graphics and illustrations.

You can choose from our library and fine-tune or create your own capabilities to analyze, process, and present text, audio, and video at large scale. Incorporate advanced NLP in your app or workflow. You can choose from the existing library or create your own. With just one API call, you can summarize, tag, and analyze language using stackable, composable NLP blocks. These blocks are built on state of the art models. Our powerful Custom-Skill engine allows you to create and fine-tune custom Language skills from your data. Only 5% of the world’s population can speak English as their first language. One AI's capabilities can be used in multiple languages. You can build a podcast platform, CRM or content publishing tool using One AI's multilingual capabilities.

Aya is an open-source, state-of-the art, massively multilingual large language research model (LLM), which covers 101 different languages. This is more than twice the number of languages that are covered by open-source models. Aya helps researchers unlock LLMs' powerful potential for dozens of cultures and languages that are largely ignored by the most advanced models available today. We open-source both the Aya Model, as well as the most comprehensive multilingual instruction dataset with 513 million words covering 114 different languages. This data collection contains rare annotations by native and fluent speakers from around the world. This ensures that AI technology is able to effectively serve a global audience who have had limited access up until now.

AssemblyAI's speech to text APIs allow you to convert audio and video files, and live audio streams into text. You can do more with audio intelligence, topic detection, summarization and content moderation. High-tech AI models powered by AssemblyAI. AssemblyAI provides developers with a great experience, from in-depth tutorials to detailed changeslogs to comprehensive documentation. Our simple API provides a complete suite of solutions for all your business speech to text needs, including core speech-to–text conversion and sentiment analysis. We offer cost-effective speech-to-text solutions to startups of all sizes, including scale-ups and early-stage startups. We are built for scale. We process millions of audio files daily for hundreds of customers, many of which are Fortune 500 companies. Developers can get comprehensive support through our detailed documentation, tutorials, and changelog.

Claude is an artificial intelligence language model that can generate text with human-like processing. Anthropic is an AI safety company and research firm that focuses on building reliable, interpretable and steerable AI systems. While large, general systems can provide significant benefits, they can also be unpredictable, unreliable and opaque. Our goal is to make progress in these areas. We are currently focusing on research to achieve these goals. However, we see many opportunities for our work in the future to create value both commercially and for the public good.

Designing and implementing solutions that use collective intelligence and augmented tech. Stability AI is a company that creates open AI tools that will allow us to reach our full potential. We are a team of builders who care deeply for real-world applications and implications. Collaboration across multiple teams is a key factor in many of our greatest achievements. We don't mind challenging established norms and exploring creativity. Our primary goal is to create breakthrough ideas and turn them into solutions. We value innovation more than tradition. We believe that our differences make us stronger, so we seek reason in every perspective.

Databricks has created an open, general purpose LLM called DBRX. DBRX is the new benchmark for open LLMs. It also provides open communities and enterprises that are building their own LLMs capabilities that were previously only available through closed model APIs. According to our measurements, DBRX surpasses GPT 3.5 and is competitive with Gemini 1.0 Pro. It is a code model that is more capable than specialized models such as CodeLLaMA 70B, and it also has the strength of a general-purpose LLM. This state-of the-art quality is accompanied by marked improvements in both training and inference performances. DBRX is the most efficient open model thanks to its finely-grained architecture of mixtures of experts (MoE). Inference is 2x faster than LLaMA2-70B and DBRX has about 40% less parameters in total and active count compared to Grok-1.

Stability AI, in collaboration with its CarperAI Lab, is proud to announce FreeWilly1 (and its successor FreeWilly2), two powerful, new Large Language Models. Both models show exceptional reasoning abilities across a variety of benchmarks. FreeWilly1 leverages the original LLaMA 65B foundation model and was carefully fine-tuned with a new synthetically-generated dataset using Supervised Fine-Tune (SFT) in standard Alpaca format. FreeWilly2 uses the LLaMA 70B foundation model in order to achieve a performance that is comparable with GPT-3.5 on some tasks. The FreeWilly models were inspired by Microsoft's "Orca: Progressive Learning from Complex Explanation traces of GPT-4" paper. While our data generation processes are similar, our data sources differ.

Through scientific rigor and human insight, healthcare breakthroughs can change the world, bringing hope to humanity. We believe that AI can help in this area, through collaboration between researchers, healthcare organisations, and the wider ecosystem. Today, we are sharing exciting progress in these initiatives with the announcement that Google's large language model (LLM) for medical applications, called Med PaLM 2, will be available to a limited number of customers. In the coming weeks, it will be available to a small group of Google Cloud users for limited testing. We will explore use cases, share feedback, and investigate safe, responsible and meaningful ways to utilize this technology. Med-PaLM 2, which harnesses Google's LLMs aligned with the medical domain, is able to answer medical questions more accurately and safely. Med-PaLM 2 is the first LLM that has performed at an "expert" level on the MedQA dataset consisting of US Medical Licensing Examination-style questions.

Information overload is a major barrier to scientific progress. The explosion of scientific literature and data makes it harder to find useful insights among a vast amount of information. Search engines are used to access scientific knowledge today, but they cannot organize it. Galactica is an extensive language model which can store, combine, and reason about scientific information. We train using a large corpus of scientific papers, reference material and knowledge bases, among other sources. We outperform other models in a variety of scientific tasks. Galactica performs better than the latest GPT-3 on technical knowledge probes like LaTeX Equations by 68.2% to 49.0%. Galactica is also good at reasoning. It outperforms Chinchilla in mathematical MMLU with a score between 41.3% and 35.7%. And PaLM 540B in MATH, with a score between 20.4% and 8.8%.

We are proud to announce we have completed the training on Inflection-2. It is the best model for its compute class in the entire world and the second most powerful LLM. Inflection's mission is to create an AI that is personal for everyone. Inflection-2 is a new model that is significantly more capable than Inflection-1. It has better factual knowledge, better style control, and dramatically enhanced reasoning. Inflection-2 has been trained on 5,000 NVIDIA GPUs at fp8 mixed accuracy for 1025 FLOPs. This puts Inflection-2 in the same training compute category as Google's flagship PaLM 2 Large Model. Inflection-2 also outperforms the majority of standard AI performance benchmarks including the well-known MMLU, TriviaQA, HellaSwag & GSM8k. Inflection-2, designed with efficiency in mind, will soon power Pi. We were able to reduce costs by switching from A100 to the H100 GPUs and optimizing our inference implementation.

This repository contains a research preview of LongLLaMA. It is a large language-model capable of handling contexts up to 256k tokens. LongLLaMA was built on the foundation of OpenLLaMA, and fine-tuned with the Focused Transformer method. LongLLaMA code was built on the foundation of Code Llama. We release a smaller base variant of the LongLLaMA (not instruction-tuned) on a permissive licence (Apache 2.0), and inference code that supports longer contexts for hugging face. Our model weights are a drop-in replacement for LLaMA (for short contexts up to 2048 tokens) in existing implementations. We also provide evaluation results, and comparisons with the original OpenLLaMA model.

The next generation of the large language model. This release includes modelweights and starting code to pretrained and fine tuned Llama languages models, ranging from 7B-70B parameters. Llama 1 models have a context length of 2 trillion tokens. Llama 2 models have a context length double that of Llama 1. The fine-tuned Llama 2 models have been trained using over 1,000,000 human annotations. Llama 2, a new open-source language model, outperforms many other open-source language models in external benchmarks. These include tests of reasoning, coding and proficiency, as well as knowledge tests. Llama 2 has been pre-trained using publicly available online data sources. Llama-2 chat, a fine-tuned version of the model, is based on publicly available instruction datasets, and more than 1 million human annotations. We have a wide range of supporters in the world who are committed to our open approach for today's AI. These companies have provided early feedback and have expressed excitement to build with Llama 2

Production-ready AI models that are fast and accurate. High-availability inference API that leverages the most advanced NVIDIA GPUs. We have selected the most popular open-source natural language processing models (NLP) and deployed them for the community. You can fine-tune your models (including GPT-J) or upload your custom models. Then, deploy them to production. Upload your AI models, including GPT-J, to your dashboard and immediately use them in production.

We've developed a model, called ChatGPT, that interacts in a conversational manner. ChatGPT can use the dialogue format to answer questions, admit mistakes, challenge incorrect premises and reject inappropriate requests. ChatGPT is the sibling model of InstructGPT. InstructGPT is trained to follow a prompt, and then provide a detailed answer. ChatGPT Plus, a subscription plan to ChatGPT, a conversational AI. ChatGPT Plus is $20/month and subscribers receive a variety of benefits. - ChatGPT is available to all users, even at peak times - Faster response time Access to GPT-4 ChatGPT plugins Chat with Web-browsingGPT - Priority access for new features and improvements ChatGPT Plus will be available to all customers in the United States. We will begin inviting people on our waitlist within the next few weeks. We plan to extend access and support to other countries and regions in the near future.

LLaMA (Large Language Model meta AI) is a state of the art foundational large language model that was created to aid researchers in this subfield. LLaMA allows researchers to use smaller, more efficient models to study these models. This furtherdemocratizes access to this rapidly-changing field. Because it takes far less computing power and resources than large language models, such as LLaMA, to test new approaches, validate other's work, and explore new uses, training smaller foundation models like LLaMA can be a desirable option. Foundation models are trained on large amounts of unlabeled data. This makes them perfect for fine-tuning for many tasks. We make LLaMA available in several sizes (7B-13B, 33B and 65B parameters), and also share a LLaMA card that explains how the model was built in line with our Responsible AI practices.

StarCoderBase and StarCoder are Large Language Models (Code LLMs), trained on permissively-licensed data from GitHub. This includes data from 80+ programming language, Git commits and issues, Jupyter Notebooks, and Git commits. We trained a 15B-parameter model for 1 trillion tokens, similar to LLaMA. We refined the StarCoderBase for 35B Python tokens. The result is a new model we call StarCoder. StarCoderBase is a model that outperforms other open Code LLMs in popular programming benchmarks. It also matches or exceeds closed models like code-cushman001 from OpenAI, the original Codex model which powered early versions GitHub Copilot. StarCoder models are able to process more input with a context length over 8,000 tokens than any other open LLM. This allows for a variety of interesting applications. By prompting the StarCoder model with a series dialogues, we allowed them to act like a technical assistant.

NVIDIA NeMoLLM is a service that allows you to quickly customize and use large language models that have been trained on multiple frameworks. Developers can use NeMo LLM to deploy enterprise AI applications on both public and private clouds. They can also experiment with Megatron 530B, one of the most powerful language models, via the cloud API or the LLM service. You can choose from a variety of NVIDIA models or community-developed models to best suit your AI applications. You can get better answers in minutes to hours by using prompt learning techniques and providing context for specific use cases. Use the NeMo LLM Service and the cloud API to harness the power of NVIDIA megatron 530B, the largest language model, or NVIDIA Megatron 535B. Use models for drug discovery in the NVIDIA BioNeMo framework and the cloud API.

PygmalionAI, a community of open-source projects based upon EleutherAI’s GPT-J 6B models and Meta’s LLaMA model, was founded in 2009. Pygmalion AI is designed for roleplaying and chatting. The 7B variant of the Pygmalion AI is currently actively supported. It is based on Meta AI’s LLaMA AI model. Pygmalion's chat capabilities are superior to larger language models that require much more resources. Our curated datasets of high-quality data on roleplaying ensure that your bot is the best RP partner. The model weights as well as the code used to train the model are both open-source. You can modify/re-distribute them for any purpose you like. Pygmalion and other language models run on GPUs because they require fast memory and massive processing to produce coherent text at a reasonable speed.

Hippocratic AI, the new SOTA model, is outperforming GPT-4 in 105 of 114 healthcare certifications and exams. Hippocratic AI outperformed GPT-4 in 105 of 114 tests, outperforming by a margin greater than five percent on 74 certifications and by a larger margin on 43 certifications. Most language models are pre-trained on the common crawling of the Internet. This may include incorrect or misleading information. Hippocratic AI, unlike these LLMs is heavily investing in legally acquiring evidenced-based healthcare content. We use healthcare professionals to train the model and validate its readiness for deployment. This is called RLHF-HP. Hippocratic AI won't release the model until many of these licensed professionals have deemed it safe.

Jurassic-1 comes in two sizes. The Jumbo version is the most advanced language model, with 178B parameters. It was released to developers for general use. AI21 Studio, currently in open beta allows anyone to sign up for the service and immediately begin querying Jurassic-1 with our API and interactive website environment. AI21 Labs' mission is to fundamentally change the way humans read and compose by introducing machines as partners in thought. We can only achieve this if we work together. Since the Mesozoic Era, or 2017, we have been researching language models. Jurassic-1 is based on this research and is the first generation we are making available to wide use.

Choose a model from our open-source collection, run it and access the model API within your product. No matter what model you are using for Image Recognition or Language Processing, all models come pre-trained and packaged with an easy-to use API. There are many models to choose from, and the list is growing. We curate and fine-tune only the best models from HuggingFace or Github. You can either host the model yourself or get your API-Key and endpoint with just one click. Cargoship keeps up with the advancement of AI so you don’t have to. The Cargoship Model Store has a collection that can be used for any ML use case. You can test them in demos and receive detailed guidance on how to implement the model. No matter your level of expertise, our team will pick you up and provide you with detailed instructions.

Language and its role as a means of demonstrating and facilitating understanding - or intelligence, as it is sometimes called - are fundamental to being human. It allows people to express themselves, build memories, and communicate ideas. These are the foundational components of social intelligence. Our teams at DeepMind are interested in the language processing and communication aspects, both for artificial agents and humans. As part of an broader portfolio of AI Research, we believe that the development and study more powerful language models, systems that predict and create text, have tremendous potential to build advanced AI systems. These systems can be used safely and effectively to summarise and provide expert advice, and follow instructions using natural language. Research is needed to determine the potential risks and benefits of language models before they can be developed.

Create AI applications that are market-ready and cutting-edge with customizable APIs and models. Studio, SDKs and APIs can be used to quickly integrate generative AI into production workloads. Build AI apps that are powered by foundation models from OpenAI Meta and Microsoft to gain a competitive advantage. With Azure Security, responsible AI tools, and built-in AI, you can detect and mitigate harmful usage. Create your own copilot applications and generative AI with the latest language and vision models. Search for the most relevant information using hybrid, vector and keyword search. Monitor images and text to detect offensive content. Translate documents and text in more than 100 different languages.

Jurassic-2 is the latest generation AI21 Studio foundation models. It's a game changer in the field AI, with new capabilities and top-tier quality. We're also releasing task-specific APIs with superior reading and writing capabilities. AI21 Studio's focus is to help businesses and developers leverage reading and writing AI in order to build real-world, tangible products. The release of Task-Specific and Jurassic-2 APIs marks two significant milestones. They will enable you to bring generative AI into production. Jurassic-2 (or J2, as we like to call it) is the next generation of our foundation models with significant improvements in quality and new capabilities including zero-shot instruction-following, reduced latency, and multi-language support. Task-specific APIs offer developers industry-leading APIs for performing specialized reading and/or writing tasks.

Use NeuralSpace's enterprise-grade APIs for speech & text AI in 100+ languages. Intelligent Document Processing can reduce manual tasks by 50%. Data can be extracted, understood, and categorised from any document, regardless of its quality, layout, file type, or format. Free your team from manual work so they can focus on what's important. Advanced speech and text AI can make your products accessible to all users. NeuralSpace allows you to train and deploy large language models. Our low-code, user-friendly APIs make integration easy. We provide the tools, you bring your vision to reality.

Google's AI technology allows you to convert text into natural-sounding voice using an API. Google's AI technologies can be used to generate speech that has a human-like intonation. The API is based on DeepMind’s speech synthesis expertise and delivers voices with human-like intonation. Choose from 220+ voices in 40+ languages, including Mandarin, Hindi Spanish, Arabic, Russian and more. Choose the voice that best suits your user and application. Create a voice that is unique to your brand and use it across all customer touchpoints. Don't use a voice that is shared by other organizations. You can create a more natural-sounding voice by training a custom model with your own audio recordings. You can choose and define the voice profile for your organization, and quickly adapt to changes in voice requirements without having to record new phrases.

Ernie Bot (Wenxin Yiyan), a Baidu conversational AI chatbot, is a new chatbot that can answer any type of question a user may have.