Codestral Mamba Unveiled
Mistral AI has unveiled Codestral Mamba 7B, a groundbreaking language model specialized in code generation. Based on the innovative Mamba2 architecture, this model offers linear time inference and the ability to handle sequences of theoretically infinite length, making it particularly efficient for coding applications 1. Codestral Mamba 7B achieves an impressive 75% score on HumanEval for Python coding, outperforming other open-source models in comparative evaluations 1 3. Released under the Apache 2.0 license, the model is freely available for use, modification, and distribution, with deployment options including the mistral-inference SDK and TensorRT-LLM 1. Alongside Codestral Mamba 7B, Mistral AI also introduced Mathstral 7B, a model designed for mathematical reasoning and scientific discovery, further expanding their suite of specialized AI tools 2 3.
Fujitsu Cohere AI Partnership
Fujitsu has announced a strategic partnership with Cohere Inc., a Toronto-based AI company, to develop and provide large language models (LLMs) with advanced Japanese language capabilities. 1 2 As part of this collaboration, Fujitsu has made a significant investment in Cohere and will become the exclusive provider of jointly developed services globally. 3 The partnership will focus on creating Takane, an advanced Japanese language model based on Cohere's Command R+ LLM, which features enhanced retrieval-augmented generation capabilities to mitigate hallucinations. 2 4 Fujitsu plans to offer Takane through its Kozuchi AI services starting in September 2024, targeting private cloud environments for enterprises in highly regulated industries. 3 5 This partnership aims to accelerate the adoption of generative AI globally while addressing specific industry needs and security requirements. 4 5
DeepL's Translation Breakthrough
DeepL, a leading Language AI company, has launched a next-generation language model specifically built for translation and editing. This new large language model (LLM) outperforms competitors like Google Translate, ChatGPT-4, and Microsoft in translation quality and fluency, according to blind tests conducted with professional linguists 1 3. The model leverages DeepL's proprietary data accumulated over seven years, focusing on content creation and translation rather than relying on public internet data 3. It also incorporates "human model tutoring," where thousands of language experts were involved in training the AI to achieve superior translation results 3. The new LLM is currently available for DeepL Pro users in English, German, Japanese, and Simplified Chinese, with more languages planned for the future 1 3.
AI-Powered Spreadsheet Analysis
Microsoft has unveiled SpreadsheetLLM, an innovative large language model designed to revolutionize spreadsheet analysis and interaction. This AI system addresses the longstanding challenge of applying LLMs to complex spreadsheet structures by introducing a novel encoding method called SheetCompressor. The framework compresses spreadsheets by up to 96%, allowing LLMs to handle large datasets within processing limits while preserving data integrity 1 2. SpreadsheetLLM employs a "Chain of Spreadsheet" (CoS) approach, breaking down spreadsheet reasoning into steps like table detection, matching, and reasoning 2. In tests, the model significantly outperformed existing methods for spreadsheet table detection and enhanced the capabilities of established LLMs like GPT-3.5 and GPT-4 in understanding spreadsheets 2. This breakthrough has the potential to transform data management and analysis across various industries, particularly in finance, accounting, and business analytics 3 4.
European LLM Leaderboard Launch
The OpenGPT-X team has published a European LLM Leaderboard, addressing the need for broader language accessibility and robust evaluation metrics in multilingual language models 1 2. This initiative, part of the BMWK project OpenGPT-X, aims to advance the development and assessment of large language models (LLMs) across 21 of the 24 supported European languages 4. The leaderboard compares several publicly available state-of-the-art language models, each comprising around 7 billion parameters, on tasks such as logical reasoning, commonsense understanding, multi-task learning, truthfulness, and translation 4. To ensure comparability, common benchmarks like ARC, HellaSwag, TruthfulQA, GSM8K, and MMLU were machine-translated using DeepL, with additional multilingual benchmarks incorporated 4. This effort promotes more versatile approaches in language technology and supports the development of AI models that can effectively serve a wider European audience 4.
AI Search Showdown
Perplexity AI has emerged as a formidable challenger to Google's long-standing dominance in web search, leveraging advanced AI technologies to provide a more intuitive and efficient search experience 2. Unlike Google's traditional list of links, Perplexity uses generative AI to deliver direct answers to user queries, offering a clean, minimalist interface that aims to reduce cognitive overload 2. The startup, valued at $1 billion, has gained significant traction, handling about 500 million queries in 2023 2. However, Google is not standing idle, integrating AI features into its search results and leveraging its vast resources to improve its generative AI capabilities 3. While Perplexity's innovative approach has garnered attention, experts note that unseating Google will require more than just a chatbot, as search encompasses a wide range of functions beyond information retrieval 3.
Mockingbird LLM Launch
Vectara, a pioneer in Retrieval-Augmented Generation (RAG) technology, has secured $25 million in Series A funding, bringing its total funding to $53.5 million. 5 Alongside this investment, the company unveiled Mockingbird LLM, a purpose-built large language model designed specifically for enterprise RAG applications. 5 Mockingbird aims to provide more transparent conclusions and adhere closely to factual information, addressing key challenges in enterprise AI such as hallucination risks and citation accuracy. 5 The model is optimized for structured outputs like JSON, crucial for agent-driven AI workflows, and integrates with Vectara's existing RAG pipeline, which includes advanced features like hallucination detection and security measures against prompt attacks. 5