Writer Launches Palmyra X 004: A Next-Gen AI Model Challenging Industry Giants

Next-gen generative AI tool launched Wednesday

Oct. 9 (UPI) -- San Francisco-based artificial intelligence firm Writer launched its new large language model AI tool Wednesday to compete with Anthropic, OpenAI and other providers of generative AI products. The new generative AI tool by Writer is called Palmyra X 004, which cost less to develop than competing large language model AI applications, such as OpenAI's ChatGPT. Writer says it spent $700,000 to develop Palmyra X 004 by using synthetic data while achieving accuracy and a high performance rate. Computer algorithms create synthetic data that replace real-world data used to train AI models at a higher cost than when using synthetic data. "Writer is pioneering a new era of LLM advancement that's being overlooked by big tech as they leverage their resources for sheer training data volume," Writer co-founder and Chief Executive Officer May Habib said in a news release Wednesday. "Larger data sets are hitting their ceiling," Habib added. "The future belongs to precision training and architectural innovation - areas that we have prioritized." Habib said Writer's approach outperforms market competitors while fulfilling the needs of "critical enterprise requirements." It's innovative approach is helping Writer to rise in valuation, which about $1.9 billion, CNBC reported. The valuation is almost four times what it was a year ago when Writer's valuation was $500 million.

Writer releases Palmyra X 004 next-gen generative AI model with tool calling capability - SiliconANGLE

Writer releases Palmyra X 004 next-gen generative AI model with tool calling capability Enterprise-focused generative artificial intelligence startup Writer Inc. today announced the introduction of Palmyra X 004, the company's newest proprietary large language model designed to power AI applications and autonomous agents. To train the new model, the company used synthetic data, which it says allowed it to produce the LLM at a small fraction of the cost reported by its competitors while retaining high accuracy and performance. Synthetic data is artificially created by computer algorithms to augment or supplant data generated by real-world events and it is often used to train AI models when authentic real-world data is too difficult or too expensive to obtain. The company said it curates and manufactures its own structured dataset through a specialized LLM, Instruct-Adapt X, and uses a criterion called the "early stopping mechanism" its team developed to achieve greater proficiency with smaller datasets. "Writer is pioneering a new era of LLM advancement that's being overlooked by big tech, as they leverage their resources for sheer training data volume," said co-founder and Chief Executive May Habib. "Larger datasets are hitting their ceiling; the future belongs to precision training and architectural innovation." Palmyra X 004 includes several new feature capabilities including automatic data integration and built-in retrieval-augmented generation, also known as RAG, which allow enterprise users to complement its training with real-time data to improve accuracy. It also has a large 128,000-token context window, matching rival OpenAI's GPT-4o flagship model. This measures the amount of text that can be read into a model, giving it a significantly larger "memory" by allowing users to input numerous documents or other data for it to work on at once. The new model can also take action in systems external to the LLM with tool calling, meaning that it can extend AI applications to go beyond data analysis and text generation. Palmyra X's tool use capabilities can enable AI assistants and agents to customize them to trigger events, fetch data and carry out work at the behest of users. It can also permit them to perform tasks with minimal human intervention, allowing AI agents to execute complex task chains. For example, an AI agent could analyze a series of end of month reports, create summaries with insights, prepare emails for affected department heads and send them off, all on a specific day each month with minimal employee interaction. Agentic AI, or the use of AI to make informed decisions and execute tasks based on pre-determined goals, is a recent emerging enterprise trend for automating work for both internal employee and customer-facing use. According to a report from the market intelligence firm Emergen Research, the agentic AI market size in 2024 was an estimated $30.9 billion. Diverse industry leaders such as Nvidia Corp., Microsoft Corp., HubSpot Inc. and Salesforce Inc. have introduced AI agents and agent frameworks within the past couple of months. "Unlocking the full potential of generative AI for our powerhouse customers like Intuit, Uber, L'Oreal and Accenture requires the ability to execute complex actions and workflows," said Habib. According to Writer, the new model has achieved excellent results in the latest release of Stanford University's Holistic Evaluation of Language Models or HELM reports. The LLM made it into the world's top 10 models on HELM Lite, which evaluates foundation models, and HELM MMLU, which tests model understanding of 57 subjects, scoring 86.1% and 81.3%, respectively.

Writer's Palmyra X 004 takes the lead in AI function calling, surpassing tech giants

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Writer, the full-stack generative AI platform, unveiled its latest large language model (LLM) Palmyra X 004 today, marking a significant advancement in enterprise artificial intelligence. This new frontier model excels in function calling and workflow execution, key capabilities for building practical AI agents and assistants for businesses. The release of Palmyra X 004 arrives at a crucial juncture in the AI industry. Companies are racing to integrate generative AI into their operations, creating a growing demand for models that can not only process and generate text but also take actions and execute complex workflows. "We're enabling AI to execute multiple functions and actions simultaneously, which is crucial for automating complex enterprise workflows," said Waseem Alshikh, co-founder and CTO of Writer, in an interview with VentureBeat. "With Palmyra X 004, we're moving from AI assistants that simply provide information to systems that can actually do work." Outperforming tech giants: How Palmyra X 004 is raising the bar for AI function calling Palmyra X 004 distinguishes itself with its exceptional performance on function calling tasks. The model achieved a score of 78.76% on Berkeley's Tool Calling Leaderboard, surpassing offerings from tech giants like OpenAI, Anthropic, Google, and Meta by nearly 20%. This benchmark evaluates a model's ability to select appropriate tools, determine which APIs to call, and successfully execute tasks based on natural language inputs. The model's capabilities extend beyond function calling. Palmyra X 004 also ranked in the top 10 on Stanford University's Holistic Evaluation of Language Models (HELM) benchmark, scoring 86.1% on HELM Lite and 81.3% on HELM MMLU. These scores indicate strong general language understanding and reasoning abilities across a wide range of subjects. Writer claims to have achieved these results with a model containing only around 150 billion parameters -- significantly smaller than some other frontier models rumored to have trillions of parameters. The company attributes this efficiency to its innovative use of synthetic data and a proprietary early stopping mechanism during training. Alshikh explained, "We've found a way to build highly capable models without relying on massive parameter counts or exorbitant training costs. Our model training costs were below a million dollars in GPU time for something above 100 billion parameters. We're proving that you don't need hundreds of billions of dollars to compete in the AI race." This focus on efficiency could have major implications for the AI industry. As companies grapple with the high costs of deploying and running large language models, Writer's approach suggests a path to more affordable and accessible enterprise AI solutions. Breaking barriers: Palmyra X 004's multilingual and multimodal capabilities Palmyra X 004 boasts impressive technical specifications. It features a 128,000 token context window, allowing it to process and reason over very long documents or conversations. The model supports multilingual capabilities across 30+ languages and can handle multimodal inputs including text, images, and audio (though image and audio capabilities are still in beta). Writer offers multiple deployment options for Palmyra X 004, addressing a key concern for many enterprises: data privacy and control. Companies can access the model through Writer's API, deploy it via cloud providers like AWS SageMaker and Nvidia AI Enterprise, or even host the model on-premises within their own infrastructure. The release of Palmyra X 004 reflects a broader shift in the AI landscape. While public attention has focused on consumer-facing chatbots and image generators, the real transformative potential of AI lies in its application to complex business processes. "We're seeing a transition from using AI for simple tasks like summarizing emails to building complex, multi-step workflows," Alshikh noted. "Our enterprise customers are looking to create AI agents that can interact with multiple internal systems, access varied data sources, and execute sophisticated business logic." This vision of AI as a workflow automation tool aligns with broader industry trends. Gartner predicts that by 2025, 50% of enterprise applications will embed some form of AI functionality. Writer's focus on function calling and agentic capabilities positions them well to capitalize on this trend. The future of AI: Writer's vision for deeper, smarter, and more efficient models However, challenges remain. As AI systems become more deeply integrated into business processes, issues of reliability, explainability, and governance become paramount. Writer has attempted to address some of these concerns with built-in features like automatic data integration with retrieval augmented generation (RAG) and source transparency. The company emphasizes the importance of AI safety and control. Palmyra X 004 integrates with Writer's existing suite of AI guardrails and governance tools, allowing enterprises to set content policies and control the model's outputs. Looking ahead, Alshikh hinted at Writer's future research directions. The company is exploring ways to build even deeper transformer models, potentially with 500-2000 layers, which they believe could lead to significant improvements in reasoning capabilities. "We're at an inflection point in AI development," Alshikh said. "The next frontier isn't just about making models bigger, but making them smarter and more efficient. We're focusing on architectural innovations that can deliver better reasoning at lower inference costs." As the AI arms race intensifies, Writer's release of Palmyra X 004 serves as a reminder that innovation isn't just about raw scale. By focusing on efficiency, ease of deployment, and real-world business applications, the company is charting a distinctive path in the enterprise AI market. The true test will be in how enterprises adopt and apply this technology. As businesses continue to explore the potential of generative AI, models like Palmyra X 004 could play a crucial role in turning the promise of AI-driven workflow automation into reality.