-
Microsoft Azure AI Widens Model Selection with Llama 2 and GPT-4 Turbo with Vision
Microsoft’s Azure AI has expanded by introducing Llama 2 and GPT-4 Turbo with Vision, marking a significant growth in AI capabilities. Llama 2, developed by Meta, and GPT-4 Turbo with Vision offer advanced AI services, accessible through simplified API endpoints. This strategic expansion aims to provide a versatile range of tools and solutions for users.
-
Leveraging language to understand machines
Irene Terpstra ’23 and Rujul Gandhi ’22, two MIT engineering students, are leveraging natural language for AI systems. Terpstra’s team is using language models to assist in chip design, while Gandhi is developing a system to convert natural language instructions for robots. Gandhi is also working on speech models for low-resource languages, seeing potential in…
-
Mixtral-8x7B is now available in Amazon SageMaker JumpStart
The Mixtral-8x7B large language model, developed by Mistral AI, is now available for customers through Amazon SageMaker JumpStart, allowing for one-click deployment for running inference. The model provides significant performance improvements for natural language processing tasks and supports multiple languages, making it suitable for various NLP applications.
-
Meet VistaLLM: Revolutionizing Vision-Language Processing with Advanced Segmentation and Multi-Image Integration
VistaLLM, a new general-purpose vision model, excels in handling coarse- and fine-grained reasoning and grounding tasks for single or multiple-input images. It employs sequence-to-sequence conversion, an instruction-guided image tokenizer, and a gradient-aware adaptive contour sampling scheme. The model consistently outperforms others across diverse vision and vision-language tasks, marking a significant advancement in vision-language processing. Read…
-
Deploy foundation models with Amazon SageMaker, iterate and monitor with TruEra
The blog describes TruEra’s collaboration in co-writing with Josh Reini, Shayak Sen, and Anupam Datta from TruEra. It highlights Amazon SageMaker JumpStart’s provision of pretrained foundation models, outlines the need for adapting foundation models to new tasks or domains, and mentions TruLens’ framework for extensible, automated evaluations. Additionally, it details the processes of deploying and…
-
Build generative AI agents with Amazon Bedrock, Amazon DynamoDB, Amazon Kendra, Amazon Lex, and LangChain
Summary: This post details the development and deployment of a generative AI financial services agent powered by Amazon Bedrock. The agent can assist with account information, loan applications, and natural language queries, and is designed as a launchpad for developers creating conversational agents. The post also discusses deployment automation, testing, cleanup, and considerations for production…
-
Chatbots Caught in the (Legal) Crossfire
The article discusses the challenges of implementing chatbots within the European regulatory framework, covering aspects such as bot selection, finetuning, disclaimers, outputs, and prioritizing quality over speed. It highlights considerations such as data protection, legal obligations, and the need for transparency. The piece aims to guide individuals seeking to implement chatbots in a legally compliant…
-
Can LLMs Replace Data Analysts? Getting Answers Using SQL
The given text mentions about the process of building an LLM-powered analyst and trying different agent types for data analysis tasks. It covers creating agents to interact with an SQL database and using LangChain tools to achieve this. The text explains the process of communicating with, reasoning, and planning for data tasks along with results…
-
You Cannot Patent Your AI Inventions UK Supreme Court Rules
The UK Supreme Court ruled that artificial intelligence cannot be recognized as inventors. Dr. Thaler’s AI creation, DABUS, was denied inventor status for two patents. The court emphasized that inventors must be human, and owning an AI does not grant patent rights. This decision sparks debate on AI’s role in innovation and upholds the law’s…
-
Researchers find that Gemini can’t even beat GPT-3.5 Turbo
Google’s Gemini models generated excitement, aiming to rival OpenAI’s offerings. Gemini Ultra claims superiority over GPT-4, yet unreleased. Gemini Pro competes with GPT-3.5 but lags in impartial tests. Despite struggles in certain tasks, Gemini Pro excels in translation but underperforms in other aspects. Disputed by Google, Gemini’s performance compared to GPT-3.5 remains in question.