Remove AI Development Remove AI Research Remove LLM Remove Responsible AI
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All You Need to Know About Gemma, the Open-Source LLM Powerhouse

Analytics Vidhya

Google has been a frontrunner in AI research, contributing significantly to the open-source community with transformative technologies like TensorFlow, BERT, T5, JAX, AlphaFold, and AlphaCode. What is Gemma LLM?

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Meet Vectorview: An AI Research Startup that Makes It Easy to Evaluate the Capabilities of Foundation Models and LLM Agents

Marktechpost

A great deal of responsibility, however, is associated with this power. Even the most advanced AI models are susceptible to biases, security flaws, and unforeseen outcomes. Meet Vectorview , a cool startup that is standing up for ethical AI development. Subscribe to our AI Research Startup Newsletter Here.

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Elon Musk sues OpenAI over alleged breach of nonprofit agreement

AI News

Founded in 2015 as a nonprofit AI research lab, OpenAI transitioned into a commercial entity in 2020. Musk, who has long voiced concerns about the risks posed by AI, has called for robust government regulation and responsible AI development.

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Hello OLMo: A truly open LLM

Allen AI

The framework features a suite of completely open AI development tools, including: Full pretraining data : The model is built on AI2’s Dolma set which features three trillion token open corpus for language model pretraining, including code that produces the training data.

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8 AI Research Labs Pushing the Boundaries of Artificial Intelligence

ODSC - Open Data Science

If you’re curious, here are eight AI research labs that are leading the way in AI research that you’d want to keep an eye on. From responsible AI to protein discovery and more, The MIT Media Lab aims to drive AI research to create a “transformative future” while working toward the social good.

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This AI Paper Introduces the ‘ForgetFilter’: A Machine Learning Algorithm that Filters Unsafe Data based on How Strong the Model’s Forgetting Signal is for that Data

Marktechpost

This paper (from a team of researchers from the University of Massachusetts Amherst, Columbia University, Google, Stanford University, and New York University) is a significant contribution to the ongoing discourse surrounding LLM safety, as it meticulously explores the intricate dynamics of these models during the finetuning process.

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Learn to Build — Towards AI Community Newsletter #1

Towards AI

In this episode, they discussed the democratization of AI, advancements in AI-assisted coding, and the ethics of innovation. Paige also discussed the need for responsible AI development, the importance of careful product design around LLMs, the role of a product manager within AI research teams, and much more.