are agents just self-orchestrating dags
RESEARCH
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AI-Augmented and Autonomous Everything: Future Vision
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What does the world look like when we have #augmented and #autonomous #AI everything? https://
cognilytica.com/cognilyticas-a
i-enabled-vision-of-the-future-ai-augmented-everything-ai-today-podcast/?utm_source=dlvr.it&utm_medium=twitter
… #AIFuture -
Fine-tuning Index: Benchmarks for Open Source and OpenAI LLMs
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Introducing the Fine-tuning Index! A comprehensive set of benchmarks for 13 fine-tuned #opensource #LLMs and leading models from #OpenAI across 31 diverse tasks. The index reports essential metrics, including: Performance Speed Cost https://
pbase.ai/3wI4S6o -
Microsoft Releases Phi-3 Series: 3.8B to 14B Models
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A new series of Phi-3 mini, small & medium models (MIT license (3.8B – 7B – 14B) Long-context
Phi-3-mini-128k-instruct: https://
huggingface.co/microsoft/Phi-
3-mini-128k-instruct
…
Phi-3 small 128k: https://
huggingface.co/microsoft/Phi-
3-small-128k-instruct
…
Phi-3 medium 128k: https://
huggingface.co/microsoft/Phi-
3-medium-128k-instruct
… Multimodal:
Phi-3-vision-128k-instruct: -
Pritzker Foundation Funds AI Science Research at Caltech and UChicago
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So thankful for the Pritzker foundation for supporting AI+science research at @caltech and @UChicago
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Starting Analysis of Yesterday’s Announcements and Today’s Keynote
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Ya empezamos!!! Primero analizamos alguno de los anuncios de ayer y luego nos metemos a la keynote de hoy 🙂
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Anthropic Interpretability Team Hiring Managers and Researchers
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If this work interests you, our interpretability team is hiring. We’re looking for: • Managers: https://
boards.greenhouse.io/anthropic/jobs
/4009173008
… • Research Scientists: https://
boards.greenhouse.io/anthropic/jobs
/4020159008
… • Research Engineers: -
Dictionary Learning and Sparse Coding Advance AI Interpretability Research
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Our research builds on prior work in sparse coding, compressed sensing, and disentanglement in machine learning, mathematics, and neuroscience. We are also pleased to see work from many other research groups applying dictionary learning and related methods to interpretability.
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Scaling Monosemanticity: Understanding Neural Network Features and Safety
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There’s much more in our paper, including detailed analysis of the breadth and specifics of features, many more safety-relevant case studies, and preliminary work on using features to study computational "circuits" in models. Read the full paper here: https://
transformer-circuits.pub/2024/scaling-m
onosemanticity/index.html
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Safety Features Evaluation Requires Further Practical Validation
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This work is preliminary. Whereas we show that there are many features that seem *plausibly* relevant to safety applications, much more work is needed to establish that our approach is useful in practice.