A2. Spot on! No matter the cloud destination, you're plugged in and ready to generate insights! #ai #datascience #cloud #saschat #Analytics #ExploreSAS
MACHINE LEARNING
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Democratizing Data Science Through Collaborative Team Analytics
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Absolutely! It's like turning a solo marathon into a relay race. Everyone gets to run a leg and contribute to the finish line. Democratisation of data takes the load off data scientists, fostering a team spirit in analytics! #ai #datascience #cloud #saschat #AnalyticsValue
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Accelerating Feature Engineering with RAPIDS cuDF on GPU
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Using RAPIDS cuDF to Leverage GPU in Feature Engineering: Improving Performance by Replacing Pandas with cuDF in Creating Data Frames and Engineering Features and Integrating with Google Colab. https://
kdnuggets.com/2023/06/rapids
-cudf-leverage-gpu-feature-engineering.html?utm_source=dlvr.it&utm_medium=twitter&utm_campaign=using-rapids-cudf-to-leverage-gpu-in-feature-engineering
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Top 15 Tech Trends in 2023 Transforming Industries and Lives
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The top 15 #techtrends in 2023 will transform industries and our lives. #AI, automation, and #quantumcomputing are just a few of the technologies that will have a major impact.
Learn more https://
mck.co/3Dor0lQ via @ingliguori #innovation -

FLASK: Fine-grained Language Model Evaluation Based on Alignment Skills
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FLASK: Fine-grained Language Model Evaluation based on Alignment Skill Sets paper page: https://
huggingface.co/papers/2307.10
928
… Evaluation of Large Language Models (LLMs) is challenging because aligning to human values requires the composition of multiple skills and the required set of skills -

SciBench: Evaluating College-Level Scientific Problem-Solving in LLMs
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SciBench: Evaluating College-Level Scientific Problem-Solving Abilities of Large Language Models paper page: https://
huggingface.co/papers/2307.10
635
… Recent advances in large language models (LLMs) have demonstrated notable progress on many mathematical benchmarks. However, most of these -

Entropy and Reconstruction in Multi-View Self-Supervised Learning
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The Role of Entropy and Reconstruction in Multi-View Self-Supervised Learning paper page: https://
huggingface.co/papers/2307.10
907
… The mechanisms behind the success of multi-view self-supervised learning (MVSSL) are not yet fully understood. Contrastive MVSSL methods have been studied through -

Improving Multimodal Datasets with Image Captioning Techniques
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Improving Multimodal Datasets with Image Captioning paper page: https://
huggingface.co/papers/2307.10
350
… Massive web datasets play a key role in the success of large vision-language models like CLIP and Flamingo. However, the raw web data is noisy, and existing filtering methods to reduce noise -
HuggingFace Raises $200M Funding at $4B Valuation
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HuggingFace reported to be reviewing competing term sheets for a funding round that could raise at least $200M at a valuation of $4B. Happy to see @HuggingFace build a highly impactful business by positioning themselves at the center of open-source ML. https://
forbes.com/sites/alexkonr
ad/2023/07/13/ai-startup-hugging-face-raising-funds-4-billion-valuation/
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Puffin v1.3 Llama2 Fine-tuned on GPT4 Conversations
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Puffin v1.3 — Llama2 fine-tuned on GPT4 conversations https://
reddit.com/r/LocalLLaMA/c
omments/154nxwh/puffin_v13_a_llama_2_model_finetuned_on_curated/
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