This post is a month old already, but I was quite happy to see the progress of @AMD
's support in @PyTorch My prediction is that the future of ML will run on a modern diverse set of hardware Who's experimenting with AMD GPUs here?
AI
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AMD GPU Support in PyTorch Signals Hardware Diversification Future
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IoT and AI Foundation for Smart Factory Future
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Internet of Things (#IoT) devices, combined with broadband connectivity, are the foundation for the “smart factory” of the future. Every part of the process can now be monitored and measured, end-to-end. #ArtificialIntelligence can help manage inventory, keep employees safe and
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Bard’s Training Data Transparency Issues and Speculation
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Bard still seems confused about whether it was or wasn't trained using private data from Gmail (Google says it it wasn't). In reality it probably has zero idea what it was trained since that information was not in the training data, so it's just making guesses.
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Bard Training Data: Google Clarifies Non-Use of Gmail
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I was told "We do not use any Gmail data in Bard […] Bard is currently based on a lightweight and optimized version of LaMDA, which was trained on a variety of data from publicly available sources, similar to most language models available today."
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OpenAI Extends Researcher Access to GPT-4 and Code Models
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we didn’t realize how important code-davinci-002 was to researchers, so we are keeping it going in our researcher access program: https://
openai.com/form/researche
r-access-program
… we are also providing researcher access to the base GPT-4 model! -
NVIDIA AI Foundations Breakthrough Event with Industry Leaders
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Come hear about NVIDIA's latest release of AI Foundations and other recent AI breakthroughs today at 2pm PT – directly from @DrJimFan
, @amasad
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Voice Assistants Balancing Humanlike Personas and Machine Identity
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oh right, interesting point. i guess voice assistants have also tried to thread the line between humanlike personas and machine ones.
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ARC Partnership Advances AI Safety and System Interpretability
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Working with ARC is part of our overall vision for AI safety and evaluation, as we work to build more steerable, predictable, and interpretable systems. You can read more about our approach to safety and the societal impacts of AI systems here:
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ARC Evals Tests Models for Deployment Readiness Assessment
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We’re excited to have ARC Evals test our models to assess their readiness for deployment. We look forward to sharing more about our approach to evaluating our systems in the coming months.