insideBIGDATA AI News Briefs BULLETIN BOARD for Q1 2024

By neub9
4 Min Read

Welcome to the insideBIGDATA AI News Briefs Bulletin Board, our new feature bringing you the latest insights and perspectives in the field of AI, including topics such as deep learning, large language models, generative AI, and transformers. We are committed to providing you with a regular resource to keep you informed and up-to-date on the rapidly advancing field of AI.

Here are the latest updates from the industry:

[1/19/2024] Open Interpreter is an open-source project that allows LLMs to run code such as Python, Javascript, and Shell locally. The latest update introduces the “Computer API” which enables programmatic control over system I/O operations. This tool provides a NL interface to your computer’s general-purpose capabilities, and supports 100 LLMs including Claude and PaLM.

[1/19/2024] Meta CEO Mark Zuckerberg announced plans to develop a massive compute infrastructure including 350,000 NVIDIA H100s. This investment in GPUs is in addition to other compute resources, with a total expenditure potentially nearing $9 billion.

[1/18/2024] A list of the 100 best resources to become a Prompt Engineer was released, highlighting the specialized field within AI and NLP. The field involves crafting effective prompts or inputs to AI language models, enabling them to generate desired outputs accurately.

[1/18/2024] OpenAI’s Sam Altman and Microsoft’s Bill Gates discussed the future of AI, including the development of ChatGPT and the pursuit of superintelligence. They focused on making the upcoming GPT-5 model more accurate and customizable, with potential access to users’ personal data for a tailored experience.

[1/17/2024] A new research paper titled “RAG vs Fine-tuning: Pipelines, Tradeoffs, and a Case Study on Agriculture” was released, discussing the tradeoff between RAG and fine-tuning when using LLMs like Llama 2 and GPT-4.

[1/17/2024] Deci released their new DeciCoder-6B & DeciDiffusion 2.0, offering high-performing language models engineered for cost-efficient performance at scale.

[1/16/2024] A video presentation featuring a recent congressional hearing regarding AI-ready workforce was released, discussing the importance of maintaining the U.S.’s lead in AI technology for national security and economic prosperity.

[1/15/2024] OpenChat released a high-performing open-source 7B LLM, surpassing Grok0, ChatGPT (March), and Grok1. Detailed instructions for independent deployment are available on various platforms.

[1/15/2024] Embedchain is an Open Source RAG Framework that makes it easy to create and deploy AI apps, streamlining the creation of Retrieval-Augmented Generation (RAG) applications.

[1/13/2024] Mixtral is in a position to surpass GPT-4 this year, offering an open-source model at the top in the LLM arena. It is the smallest 7B dense transformer and is open-source for deployment anywhere.

[1/12/2024] NVIDIA GenAI Examples is a GitHub repo providing state-of-the-art, easily deployable GenAI examples optimized for NVIDIA GPUs.”

[1/11/2024] A new research paper titled “Direct Preference Optimization: Your Language Model is Secretly a Reward Model” proposes a simpler alternative to RLHF for aligning language models to human preferences and demonstrates how universities can still do cutting-edge research on large language models.

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